diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/LICENSE b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..2f1b8e15e5627d92f0521605c9870bc8e5505cb4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/LICENSE
@@ -0,0 +1,20 @@
+Copyright (c) 2017-2021 Ingy döt Net
+Copyright (c) 2006-2016 Kirill Simonov
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..db029b770cd87a12086e70b1be9900c93d255f0b
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/METADATA
@@ -0,0 +1,46 @@
+Metadata-Version: 2.1
+Name: PyYAML
+Version: 6.0.2
+Summary: YAML parser and emitter for Python
+Home-page: https://pyyaml.org/
+Download-URL: https://pypi.org/project/PyYAML/
+Author: Kirill Simonov
+Author-email: xi@resolvent.net
+License: MIT
+Project-URL: Bug Tracker, https://github.com/yaml/pyyaml/issues
+Project-URL: CI, https://github.com/yaml/pyyaml/actions
+Project-URL: Documentation, https://pyyaml.org/wiki/PyYAMLDocumentation
+Project-URL: Mailing lists, http://lists.sourceforge.net/lists/listinfo/yaml-core
+Project-URL: Source Code, https://github.com/yaml/pyyaml
+Platform: Any
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Cython
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Text Processing :: Markup
+Requires-Python: >=3.8
+License-File: LICENSE
+
+YAML is a data serialization format designed for human readability
+and interaction with scripting languages. PyYAML is a YAML parser
+and emitter for Python.
+
+PyYAML features a complete YAML 1.1 parser, Unicode support, pickle
+support, capable extension API, and sensible error messages. PyYAML
+supports standard YAML tags and provides Python-specific tags that
+allow to represent an arbitrary Python object.
+
+PyYAML is applicable for a broad range of tasks from complex
+configuration files to object serialization and persistence.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/RECORD
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/RECORD
@@ -0,0 +1,43 @@
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+PyYAML-6.0.2.dist-info/RECORD,,
+PyYAML-6.0.2.dist-info/WHEEL,sha256=1pP4yhrbipRtdbm4Rbg3aoTjzc7pDhpHKO0CEY24CNM,152
+PyYAML-6.0.2.dist-info/top_level.txt,sha256=rpj0IVMTisAjh_1vG3Ccf9v5jpCQwAz6cD1IVU5ZdhQ,11
+_yaml/__init__.py,sha256=04Ae_5osxahpJHa3XBZUAf4wi6XX32gR8D6X6p64GEA,1402
+_yaml/__pycache__/__init__.cpython-312.pyc,,
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+yaml/serializer.py,sha256=ChuFgmhU01hj4xgI8GaKv6vfM2Bujwa9i7d2FAHj7cA,4165
+yaml/tokens.py,sha256=lTQIzSVw8Mg9wv459-TjiOQe6wVziqaRlqX2_89rp54,2573
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..56616a86d52ed931647827a07ddc48d04e1cc9ba
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/WHEEL
@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.44.0)
+Root-Is-Purelib: false
+Tag: cp312-cp312-manylinux_2_17_x86_64
+Tag: cp312-cp312-manylinux2014_x86_64
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e6475e911f628412049bc4090d86f23ac403adde
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/PyYAML-6.0.2.dist-info/top_level.txt
@@ -0,0 +1,2 @@
+_yaml
+yaml
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/_yaml/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/_yaml/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7baa8c4b68127d5cdf0be9a799429e61347c2694
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/_yaml/__init__.py
@@ -0,0 +1,33 @@
+# This is a stub package designed to roughly emulate the _yaml
+# extension module, which previously existed as a standalone module
+# and has been moved into the `yaml` package namespace.
+# It does not perfectly mimic its old counterpart, but should get
+# close enough for anyone who's relying on it even when they shouldn't.
+import yaml
+
+# in some circumstances, the yaml module we imoprted may be from a different version, so we need
+# to tread carefully when poking at it here (it may not have the attributes we expect)
+if not getattr(yaml, '__with_libyaml__', False):
+ from sys import version_info
+
+ exc = ModuleNotFoundError if version_info >= (3, 6) else ImportError
+ raise exc("No module named '_yaml'")
+else:
+ from yaml._yaml import *
+ import warnings
+ warnings.warn(
+ 'The _yaml extension module is now located at yaml._yaml'
+ ' and its location is subject to change. To use the'
+ ' LibYAML-based parser and emitter, import from `yaml`:'
+ ' `from yaml import CLoader as Loader, CDumper as Dumper`.',
+ DeprecationWarning
+ )
+ del warnings
+ # Don't `del yaml` here because yaml is actually an existing
+ # namespace member of _yaml.
+
+__name__ = '_yaml'
+# If the module is top-level (i.e. not a part of any specific package)
+# then the attribute should be set to ''.
+# https://docs.python.org/3.8/library/types.html
+__package__ = ''
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/LICENSE b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..f26bcf4d2de6eb136e31006ca3ab447d5e488adf
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/LICENSE
@@ -0,0 +1,279 @@
+A. HISTORY OF THE SOFTWARE
+==========================
+
+Python was created in the early 1990s by Guido van Rossum at Stichting
+Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands
+as a successor of a language called ABC. Guido remains Python's
+principal author, although it includes many contributions from others.
+
+In 1995, Guido continued his work on Python at the Corporation for
+National Research Initiatives (CNRI, see https://www.cnri.reston.va.us)
+in Reston, Virginia where he released several versions of the
+software.
+
+In May 2000, Guido and the Python core development team moved to
+BeOpen.com to form the BeOpen PythonLabs team. In October of the same
+year, the PythonLabs team moved to Digital Creations, which became
+Zope Corporation. In 2001, the Python Software Foundation (PSF, see
+https://www.python.org/psf/) was formed, a non-profit organization
+created specifically to own Python-related Intellectual Property.
+Zope Corporation was a sponsoring member of the PSF.
+
+All Python releases are Open Source (see https://opensource.org for
+the Open Source Definition). Historically, most, but not all, Python
+releases have also been GPL-compatible; the table below summarizes
+the various releases.
+
+ Release Derived Year Owner GPL-
+ from compatible? (1)
+
+ 0.9.0 thru 1.2 1991-1995 CWI yes
+ 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes
+ 1.6 1.5.2 2000 CNRI no
+ 2.0 1.6 2000 BeOpen.com no
+ 1.6.1 1.6 2001 CNRI yes (2)
+ 2.1 2.0+1.6.1 2001 PSF no
+ 2.0.1 2.0+1.6.1 2001 PSF yes
+ 2.1.1 2.1+2.0.1 2001 PSF yes
+ 2.1.2 2.1.1 2002 PSF yes
+ 2.1.3 2.1.2 2002 PSF yes
+ 2.2 and above 2.1.1 2001-now PSF yes
+
+Footnotes:
+
+(1) GPL-compatible doesn't mean that we're distributing Python under
+ the GPL. All Python licenses, unlike the GPL, let you distribute
+ a modified version without making your changes open source. The
+ GPL-compatible licenses make it possible to combine Python with
+ other software that is released under the GPL; the others don't.
+
+(2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
+ because its license has a choice of law clause. According to
+ CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
+ is "not incompatible" with the GPL.
+
+Thanks to the many outside volunteers who have worked under Guido's
+direction to make these releases possible.
+
+
+B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON
+===============================================================
+
+Python software and documentation are licensed under the
+Python Software Foundation License Version 2.
+
+Starting with Python 3.8.6, examples, recipes, and other code in
+the documentation are dual licensed under the PSF License Version 2
+and the Zero-Clause BSD license.
+
+Some software incorporated into Python is under different licenses.
+The licenses are listed with code falling under that license.
+
+
+PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
+--------------------------------------------
+
+1. This LICENSE AGREEMENT is between the Python Software Foundation
+("PSF"), and the Individual or Organization ("Licensee") accessing and
+otherwise using this software ("Python") in source or binary form and
+its associated documentation.
+
+2. Subject to the terms and conditions of this License Agreement, PSF hereby
+grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
+analyze, test, perform and/or display publicly, prepare derivative works,
+distribute, and otherwise use Python alone or in any derivative version,
+provided, however, that PSF's License Agreement and PSF's notice of copyright,
+i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
+2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation;
+All Rights Reserved" are retained in Python alone or in any derivative version
+prepared by Licensee.
+
+3. In the event Licensee prepares a derivative work that is based on
+or incorporates Python or any part thereof, and wants to make
+the derivative work available to others as provided herein, then
+Licensee hereby agrees to include in any such work a brief summary of
+the changes made to Python.
+
+4. PSF is making Python available to Licensee on an "AS IS"
+basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
+DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
+INFRINGE ANY THIRD PARTY RIGHTS.
+
+5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
+FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
+A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
+OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+
+6. This License Agreement will automatically terminate upon a material
+breach of its terms and conditions.
+
+7. Nothing in this License Agreement shall be deemed to create any
+relationship of agency, partnership, or joint venture between PSF and
+Licensee. This License Agreement does not grant permission to use PSF
+trademarks or trade name in a trademark sense to endorse or promote
+products or services of Licensee, or any third party.
+
+8. By copying, installing or otherwise using Python, Licensee
+agrees to be bound by the terms and conditions of this License
+Agreement.
+
+
+BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0
+-------------------------------------------
+
+BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1
+
+1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an
+office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the
+Individual or Organization ("Licensee") accessing and otherwise using
+this software in source or binary form and its associated
+documentation ("the Software").
+
+2. Subject to the terms and conditions of this BeOpen Python License
+Agreement, BeOpen hereby grants Licensee a non-exclusive,
+royalty-free, world-wide license to reproduce, analyze, test, perform
+and/or display publicly, prepare derivative works, distribute, and
+otherwise use the Software alone or in any derivative version,
+provided, however, that the BeOpen Python License is retained in the
+Software, alone or in any derivative version prepared by Licensee.
+
+3. BeOpen is making the Software available to Licensee on an "AS IS"
+basis. BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, BEOPEN MAKES NO AND
+DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE SOFTWARE WILL NOT
+INFRINGE ANY THIRD PARTY RIGHTS.
+
+4. BEOPEN SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF THE
+SOFTWARE FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS
+AS A RESULT OF USING, MODIFYING OR DISTRIBUTING THE SOFTWARE, OR ANY
+DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+
+5. This License Agreement will automatically terminate upon a material
+breach of its terms and conditions.
+
+6. This License Agreement shall be governed by and interpreted in all
+respects by the law of the State of California, excluding conflict of
+law provisions. Nothing in this License Agreement shall be deemed to
+create any relationship of agency, partnership, or joint venture
+between BeOpen and Licensee. This License Agreement does not grant
+permission to use BeOpen trademarks or trade names in a trademark
+sense to endorse or promote products or services of Licensee, or any
+third party. As an exception, the "BeOpen Python" logos available at
+http://www.pythonlabs.com/logos.html may be used according to the
+permissions granted on that web page.
+
+7. By copying, installing or otherwise using the software, Licensee
+agrees to be bound by the terms and conditions of this License
+Agreement.
+
+
+CNRI LICENSE AGREEMENT FOR PYTHON 1.6.1
+---------------------------------------
+
+1. This LICENSE AGREEMENT is between the Corporation for National
+Research Initiatives, having an office at 1895 Preston White Drive,
+Reston, VA 20191 ("CNRI"), and the Individual or Organization
+("Licensee") accessing and otherwise using Python 1.6.1 software in
+source or binary form and its associated documentation.
+
+2. Subject to the terms and conditions of this License Agreement, CNRI
+hereby grants Licensee a nonexclusive, royalty-free, world-wide
+license to reproduce, analyze, test, perform and/or display publicly,
+prepare derivative works, distribute, and otherwise use Python 1.6.1
+alone or in any derivative version, provided, however, that CNRI's
+License Agreement and CNRI's notice of copyright, i.e., "Copyright (c)
+1995-2001 Corporation for National Research Initiatives; All Rights
+Reserved" are retained in Python 1.6.1 alone or in any derivative
+version prepared by Licensee. Alternately, in lieu of CNRI's License
+Agreement, Licensee may substitute the following text (omitting the
+quotes): "Python 1.6.1 is made available subject to the terms and
+conditions in CNRI's License Agreement. This Agreement together with
+Python 1.6.1 may be located on the internet using the following
+unique, persistent identifier (known as a handle): 1895.22/1013. This
+Agreement may also be obtained from a proxy server on the internet
+using the following URL: http://hdl.handle.net/1895.22/1013".
+
+3. In the event Licensee prepares a derivative work that is based on
+or incorporates Python 1.6.1 or any part thereof, and wants to make
+the derivative work available to others as provided herein, then
+Licensee hereby agrees to include in any such work a brief summary of
+the changes made to Python 1.6.1.
+
+4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS"
+basis. CNRI MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, CNRI MAKES NO AND
+DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON 1.6.1 WILL NOT
+INFRINGE ANY THIRD PARTY RIGHTS.
+
+5. CNRI SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
+1.6.1 FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
+A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON 1.6.1,
+OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+
+6. This License Agreement will automatically terminate upon a material
+breach of its terms and conditions.
+
+7. This License Agreement shall be governed by the federal
+intellectual property law of the United States, including without
+limitation the federal copyright law, and, to the extent such
+U.S. federal law does not apply, by the law of the Commonwealth of
+Virginia, excluding Virginia's conflict of law provisions.
+Notwithstanding the foregoing, with regard to derivative works based
+on Python 1.6.1 that incorporate non-separable material that was
+previously distributed under the GNU General Public License (GPL), the
+law of the Commonwealth of Virginia shall govern this License
+Agreement only as to issues arising under or with respect to
+Paragraphs 4, 5, and 7 of this License Agreement. Nothing in this
+License Agreement shall be deemed to create any relationship of
+agency, partnership, or joint venture between CNRI and Licensee. This
+License Agreement does not grant permission to use CNRI trademarks or
+trade name in a trademark sense to endorse or promote products or
+services of Licensee, or any third party.
+
+8. By clicking on the "ACCEPT" button where indicated, or by copying,
+installing or otherwise using Python 1.6.1, Licensee agrees to be
+bound by the terms and conditions of this License Agreement.
+
+ ACCEPT
+
+
+CWI LICENSE AGREEMENT FOR PYTHON 0.9.0 THROUGH 1.2
+--------------------------------------------------
+
+Copyright (c) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam,
+The Netherlands. All rights reserved.
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for any purpose and without fee is hereby granted,
+provided that the above copyright notice appear in all copies and that
+both that copyright notice and this permission notice appear in
+supporting documentation, and that the name of Stichting Mathematisch
+Centrum or CWI not be used in advertising or publicity pertaining to
+distribution of the software without specific, written prior
+permission.
+
+STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO
+THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
+FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE
+FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
+WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
+ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
+OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
+
+ZERO-CLAUSE BSD LICENSE FOR CODE IN THE PYTHON DOCUMENTATION
+----------------------------------------------------------------------
+
+Permission to use, copy, modify, and/or distribute this software for any
+purpose with or without fee is hereby granted.
+
+THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
+INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
+OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
+PERFORMANCE OF THIS SOFTWARE.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..c574749f3c9c1a4a422b2ae3d57aa78e90b53703
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/METADATA
@@ -0,0 +1,123 @@
+Metadata-Version: 2.3
+Name: aiohappyeyeballs
+Version: 2.5.0
+Summary: Happy Eyeballs for asyncio
+License: PSF-2.0
+Author: J. Nick Koston
+Author-email: nick@koston.org
+Requires-Python: >=3.9
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Natural Language :: English
+Classifier: Operating System :: OS Independent
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: License :: OSI Approved :: Python Software Foundation License
+Project-URL: Bug Tracker, https://github.com/aio-libs/aiohappyeyeballs/issues
+Project-URL: Changelog, https://github.com/aio-libs/aiohappyeyeballs/blob/main/CHANGELOG.md
+Project-URL: Documentation, https://aiohappyeyeballs.readthedocs.io
+Project-URL: Repository, https://github.com/aio-libs/aiohappyeyeballs
+Description-Content-Type: text/markdown
+
+# aiohappyeyeballs
+
+
+
+---
+
+**Documentation**: https://aiohappyeyeballs.readthedocs.io
+
+**Source Code**: https://github.com/aio-libs/aiohappyeyeballs
+
+---
+
+[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)
+([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))
+
+## Use case
+
+This library exists to allow connecting with
+[Happy Eyeballs](https://en.wikipedia.org/wiki/Happy_Eyeballs)
+([RFC 8305](https://www.rfc-editor.org/rfc/rfc8305.html))
+when you
+already have a list of addrinfo and not a DNS name.
+
+The stdlib version of `loop.create_connection()`
+will only work when you pass in an unresolved name which
+is not a good fit when using DNS caching or resolving
+names via another method such as `zeroconf`.
+
+## Installation
+
+Install this via pip (or your favourite package manager):
+
+`pip install aiohappyeyeballs`
+
+## License
+
+[aiohappyeyeballs is licensed under the same terms as cpython itself.](https://github.com/python/cpython/blob/main/LICENSE)
+
+## Example usage
+
+```python
+
+addr_infos = await loop.getaddrinfo("example.org", 80)
+
+socket = await start_connection(addr_infos)
+socket = await start_connection(addr_infos, local_addr_infos=local_addr_infos, happy_eyeballs_delay=0.2)
+
+transport, protocol = await loop.create_connection(
+ MyProtocol, sock=socket, ...)
+
+# Remove the first address for each family from addr_info
+pop_addr_infos_interleave(addr_info, 1)
+
+# Remove all matching address from addr_info
+remove_addr_infos(addr_info, "dead::beef::")
+
+# Convert a local_addr to local_addr_infos
+local_addr_infos = addr_to_addr_infos(("127.0.0.1",0))
+```
+
+## Credits
+
+This package contains code from cpython and is licensed under the same terms as cpython itself.
+
+This package was created with
+[Copier](https://copier.readthedocs.io/) and the
+[browniebroke/pypackage-template](https://github.com/browniebroke/pypackage-template)
+project template.
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..f7b76e839307e34ac7533b6f64de7e436d033f01
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/RECORD
@@ -0,0 +1,16 @@
+aiohappyeyeballs-2.5.0.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+aiohappyeyeballs-2.5.0.dist-info/LICENSE,sha256=Oy-B_iHRgcSZxZolbI4ZaEVdZonSaaqFNzv7avQdo78,13936
+aiohappyeyeballs-2.5.0.dist-info/METADATA,sha256=y_3HGOJoNi2P5UbXNeHZm6QbcCqTvTTZJPRWEZrlqFk,5915
+aiohappyeyeballs-2.5.0.dist-info/RECORD,,
+aiohappyeyeballs-2.5.0.dist-info/WHEEL,sha256=XbeZDeTWKc1w7CSIyre5aMDU_-PohRwTQceYnisIYYY,88
+aiohappyeyeballs/__init__.py,sha256=KEVHr8NrkKXCb69d55dQRT3ENUsu5GlET4Q_l_Gl-t8,361
+aiohappyeyeballs/__pycache__/__init__.cpython-312.pyc,,
+aiohappyeyeballs/__pycache__/_staggered.cpython-312.pyc,,
+aiohappyeyeballs/__pycache__/impl.cpython-312.pyc,,
+aiohappyeyeballs/__pycache__/types.cpython-312.pyc,,
+aiohappyeyeballs/__pycache__/utils.cpython-312.pyc,,
+aiohappyeyeballs/_staggered.py,sha256=pY7aQPYPT0OZAYpPePutVem5ikpNPewl50XXW6dQP98,6780
+aiohappyeyeballs/impl.py,sha256=Dlcm2mTJ28ucrGnxkb_fo9CZzLAkOOBizOt7dreBbXE,9681
+aiohappyeyeballs/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+aiohappyeyeballs/types.py,sha256=jyuonLGf3b01snRXgpZd2wywwS-gfhMcRnXgE6ro22Q,332
+aiohappyeyeballs/utils.py,sha256=on9GxIR0LhEfZu8P6Twi9hepX9zDanuZM20MWsb3xlQ,3028
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..0582547b15f02d3a51659106262832565d5dc5ea
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiohappyeyeballs-2.5.0.dist-info/WHEEL
@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: poetry-core 2.1.1
+Root-Is-Purelib: true
+Tag: py3-none-any
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiosignal/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiosignal/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ad0278993a986cecabf966d7b6ffd0c58f060e4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiosignal/__init__.py
@@ -0,0 +1,36 @@
+from frozenlist import FrozenList
+
+__version__ = "1.3.2"
+
+__all__ = ("Signal",)
+
+
+class Signal(FrozenList):
+ """Coroutine-based signal implementation.
+
+ To connect a callback to a signal, use any list method.
+
+ Signals are fired using the send() coroutine, which takes named
+ arguments.
+ """
+
+ __slots__ = ("_owner",)
+
+ def __init__(self, owner):
+ super().__init__()
+ self._owner = owner
+
+ def __repr__(self):
+ return "".format(
+ self._owner, self.frozen, list(self)
+ )
+
+ async def send(self, *args, **kwargs):
+ """
+ Sends data to all registered receivers.
+ """
+ if not self.frozen:
+ raise RuntimeError("Cannot send non-frozen signal.")
+
+ for receiver in self:
+ await receiver(*args, **kwargs) # type: ignore
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiosignal/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/aiosignal/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..a1b5c57543005b310ac2efb02243a6b6ab6d8932
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/METADATA
@@ -0,0 +1,441 @@
+Metadata-Version: 2.1
+Name: colorama
+Version: 0.4.6
+Summary: Cross-platform colored terminal text.
+Project-URL: Homepage, https://github.com/tartley/colorama
+Author-email: Jonathan Hartley
+License-File: LICENSE.txt
+Keywords: ansi,color,colour,crossplatform,terminal,text,windows,xplatform
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 2
+Classifier: Programming Language :: Python :: 2.7
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Terminals
+Requires-Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7
+Description-Content-Type: text/x-rst
+
+.. image:: https://img.shields.io/pypi/v/colorama.svg
+ :target: https://pypi.org/project/colorama/
+ :alt: Latest Version
+
+.. image:: https://img.shields.io/pypi/pyversions/colorama.svg
+ :target: https://pypi.org/project/colorama/
+ :alt: Supported Python versions
+
+.. image:: https://github.com/tartley/colorama/actions/workflows/test.yml/badge.svg
+ :target: https://github.com/tartley/colorama/actions/workflows/test.yml
+ :alt: Build Status
+
+Colorama
+========
+
+Makes ANSI escape character sequences (for producing colored terminal text and
+cursor positioning) work under MS Windows.
+
+.. |donate| image:: https://www.paypalobjects.com/en_US/i/btn/btn_donate_SM.gif
+ :target: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=2MZ9D2GMLYCUJ&item_name=Colorama¤cy_code=USD
+ :alt: Donate with Paypal
+
+`PyPI for releases `_ |
+`Github for source `_ |
+`Colorama for enterprise on Tidelift `_
+
+If you find Colorama useful, please |donate| to the authors. Thank you!
+
+Installation
+------------
+
+Tested on CPython 2.7, 3.7, 3.8, 3.9 and 3.10 and Pypy 2.7 and 3.8.
+
+No requirements other than the standard library.
+
+.. code-block:: bash
+
+ pip install colorama
+ # or
+ conda install -c anaconda colorama
+
+Description
+-----------
+
+ANSI escape character sequences have long been used to produce colored terminal
+text and cursor positioning on Unix and Macs. Colorama makes this work on
+Windows, too, by wrapping ``stdout``, stripping ANSI sequences it finds (which
+would appear as gobbledygook in the output), and converting them into the
+appropriate win32 calls to modify the state of the terminal. On other platforms,
+Colorama does nothing.
+
+This has the upshot of providing a simple cross-platform API for printing
+colored terminal text from Python, and has the happy side-effect that existing
+applications or libraries which use ANSI sequences to produce colored output on
+Linux or Macs can now also work on Windows, simply by calling
+``colorama.just_fix_windows_console()`` (since v0.4.6) or ``colorama.init()``
+(all versions, but may have other side-effects – see below).
+
+An alternative approach is to install ``ansi.sys`` on Windows machines, which
+provides the same behaviour for all applications running in terminals. Colorama
+is intended for situations where that isn't easy (e.g., maybe your app doesn't
+have an installer.)
+
+Demo scripts in the source code repository print some colored text using
+ANSI sequences. Compare their output under Gnome-terminal's built in ANSI
+handling, versus on Windows Command-Prompt using Colorama:
+
+.. image:: https://github.com/tartley/colorama/raw/master/screenshots/ubuntu-demo.png
+ :width: 661
+ :height: 357
+ :alt: ANSI sequences on Ubuntu under gnome-terminal.
+
+.. image:: https://github.com/tartley/colorama/raw/master/screenshots/windows-demo.png
+ :width: 668
+ :height: 325
+ :alt: Same ANSI sequences on Windows, using Colorama.
+
+These screenshots show that, on Windows, Colorama does not support ANSI 'dim
+text'; it looks the same as 'normal text'.
+
+Usage
+-----
+
+Initialisation
+..............
+
+If the only thing you want from Colorama is to get ANSI escapes to work on
+Windows, then run:
+
+.. code-block:: python
+
+ from colorama import just_fix_windows_console
+ just_fix_windows_console()
+
+If you're on a recent version of Windows 10 or better, and your stdout/stderr
+are pointing to a Windows console, then this will flip the magic configuration
+switch to enable Windows' built-in ANSI support.
+
+If you're on an older version of Windows, and your stdout/stderr are pointing to
+a Windows console, then this will wrap ``sys.stdout`` and/or ``sys.stderr`` in a
+magic file object that intercepts ANSI escape sequences and issues the
+appropriate Win32 calls to emulate them.
+
+In all other circumstances, it does nothing whatsoever. Basically the idea is
+that this makes Windows act like Unix with respect to ANSI escape handling.
+
+It's safe to call this function multiple times. It's safe to call this function
+on non-Windows platforms, but it won't do anything. It's safe to call this
+function when one or both of your stdout/stderr are redirected to a file – it
+won't do anything to those streams.
+
+Alternatively, you can use the older interface with more features (but also more
+potential footguns):
+
+.. code-block:: python
+
+ from colorama import init
+ init()
+
+This does the same thing as ``just_fix_windows_console``, except for the
+following differences:
+
+- It's not safe to call ``init`` multiple times; you can end up with multiple
+ layers of wrapping and broken ANSI support.
+
+- Colorama will apply a heuristic to guess whether stdout/stderr support ANSI,
+ and if it thinks they don't, then it will wrap ``sys.stdout`` and
+ ``sys.stderr`` in a magic file object that strips out ANSI escape sequences
+ before printing them. This happens on all platforms, and can be convenient if
+ you want to write your code to emit ANSI escape sequences unconditionally, and
+ let Colorama decide whether they should actually be output. But note that
+ Colorama's heuristic is not particularly clever.
+
+- ``init`` also accepts explicit keyword args to enable/disable various
+ functionality – see below.
+
+To stop using Colorama before your program exits, simply call ``deinit()``.
+This will restore ``stdout`` and ``stderr`` to their original values, so that
+Colorama is disabled. To resume using Colorama again, call ``reinit()``; it is
+cheaper than calling ``init()`` again (but does the same thing).
+
+Most users should depend on ``colorama >= 0.4.6``, and use
+``just_fix_windows_console``. The old ``init`` interface will be supported
+indefinitely for backwards compatibility, but we don't plan to fix any issues
+with it, also for backwards compatibility.
+
+Colored Output
+..............
+
+Cross-platform printing of colored text can then be done using Colorama's
+constant shorthand for ANSI escape sequences. These are deliberately
+rudimentary, see below.
+
+.. code-block:: python
+
+ from colorama import Fore, Back, Style
+ print(Fore.RED + 'some red text')
+ print(Back.GREEN + 'and with a green background')
+ print(Style.DIM + 'and in dim text')
+ print(Style.RESET_ALL)
+ print('back to normal now')
+
+...or simply by manually printing ANSI sequences from your own code:
+
+.. code-block:: python
+
+ print('\033[31m' + 'some red text')
+ print('\033[39m') # and reset to default color
+
+...or, Colorama can be used in conjunction with existing ANSI libraries
+such as the venerable `Termcolor `_
+the fabulous `Blessings `_,
+or the incredible `_Rich `_.
+
+If you wish Colorama's Fore, Back and Style constants were more capable,
+then consider using one of the above highly capable libraries to generate
+colors, etc, and use Colorama just for its primary purpose: to convert
+those ANSI sequences to also work on Windows:
+
+SIMILARLY, do not send PRs adding the generation of new ANSI types to Colorama.
+We are only interested in converting ANSI codes to win32 API calls, not
+shortcuts like the above to generate ANSI characters.
+
+.. code-block:: python
+
+ from colorama import just_fix_windows_console
+ from termcolor import colored
+
+ # use Colorama to make Termcolor work on Windows too
+ just_fix_windows_console()
+
+ # then use Termcolor for all colored text output
+ print(colored('Hello, World!', 'green', 'on_red'))
+
+Available formatting constants are::
+
+ Fore: BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE, RESET.
+ Back: BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE, RESET.
+ Style: DIM, NORMAL, BRIGHT, RESET_ALL
+
+``Style.RESET_ALL`` resets foreground, background, and brightness. Colorama will
+perform this reset automatically on program exit.
+
+These are fairly well supported, but not part of the standard::
+
+ Fore: LIGHTBLACK_EX, LIGHTRED_EX, LIGHTGREEN_EX, LIGHTYELLOW_EX, LIGHTBLUE_EX, LIGHTMAGENTA_EX, LIGHTCYAN_EX, LIGHTWHITE_EX
+ Back: LIGHTBLACK_EX, LIGHTRED_EX, LIGHTGREEN_EX, LIGHTYELLOW_EX, LIGHTBLUE_EX, LIGHTMAGENTA_EX, LIGHTCYAN_EX, LIGHTWHITE_EX
+
+Cursor Positioning
+..................
+
+ANSI codes to reposition the cursor are supported. See ``demos/demo06.py`` for
+an example of how to generate them.
+
+Init Keyword Args
+.................
+
+``init()`` accepts some ``**kwargs`` to override default behaviour.
+
+init(autoreset=False):
+ If you find yourself repeatedly sending reset sequences to turn off color
+ changes at the end of every print, then ``init(autoreset=True)`` will
+ automate that:
+
+ .. code-block:: python
+
+ from colorama import init
+ init(autoreset=True)
+ print(Fore.RED + 'some red text')
+ print('automatically back to default color again')
+
+init(strip=None):
+ Pass ``True`` or ``False`` to override whether ANSI codes should be
+ stripped from the output. The default behaviour is to strip if on Windows
+ or if output is redirected (not a tty).
+
+init(convert=None):
+ Pass ``True`` or ``False`` to override whether to convert ANSI codes in the
+ output into win32 calls. The default behaviour is to convert if on Windows
+ and output is to a tty (terminal).
+
+init(wrap=True):
+ On Windows, Colorama works by replacing ``sys.stdout`` and ``sys.stderr``
+ with proxy objects, which override the ``.write()`` method to do their work.
+ If this wrapping causes you problems, then this can be disabled by passing
+ ``init(wrap=False)``. The default behaviour is to wrap if ``autoreset`` or
+ ``strip`` or ``convert`` are True.
+
+ When wrapping is disabled, colored printing on non-Windows platforms will
+ continue to work as normal. To do cross-platform colored output, you can
+ use Colorama's ``AnsiToWin32`` proxy directly:
+
+ .. code-block:: python
+
+ import sys
+ from colorama import init, AnsiToWin32
+ init(wrap=False)
+ stream = AnsiToWin32(sys.stderr).stream
+
+ # Python 2
+ print >>stream, Fore.BLUE + 'blue text on stderr'
+
+ # Python 3
+ print(Fore.BLUE + 'blue text on stderr', file=stream)
+
+Recognised ANSI Sequences
+.........................
+
+ANSI sequences generally take the form::
+
+ ESC [ ; ...
+
+Where ```` is an integer, and ```` is a single letter. Zero or
+more params are passed to a ````. If no params are passed, it is
+generally synonymous with passing a single zero. No spaces exist in the
+sequence; they have been inserted here simply to read more easily.
+
+The only ANSI sequences that Colorama converts into win32 calls are::
+
+ ESC [ 0 m # reset all (colors and brightness)
+ ESC [ 1 m # bright
+ ESC [ 2 m # dim (looks same as normal brightness)
+ ESC [ 22 m # normal brightness
+
+ # FOREGROUND:
+ ESC [ 30 m # black
+ ESC [ 31 m # red
+ ESC [ 32 m # green
+ ESC [ 33 m # yellow
+ ESC [ 34 m # blue
+ ESC [ 35 m # magenta
+ ESC [ 36 m # cyan
+ ESC [ 37 m # white
+ ESC [ 39 m # reset
+
+ # BACKGROUND
+ ESC [ 40 m # black
+ ESC [ 41 m # red
+ ESC [ 42 m # green
+ ESC [ 43 m # yellow
+ ESC [ 44 m # blue
+ ESC [ 45 m # magenta
+ ESC [ 46 m # cyan
+ ESC [ 47 m # white
+ ESC [ 49 m # reset
+
+ # cursor positioning
+ ESC [ y;x H # position cursor at x across, y down
+ ESC [ y;x f # position cursor at x across, y down
+ ESC [ n A # move cursor n lines up
+ ESC [ n B # move cursor n lines down
+ ESC [ n C # move cursor n characters forward
+ ESC [ n D # move cursor n characters backward
+
+ # clear the screen
+ ESC [ mode J # clear the screen
+
+ # clear the line
+ ESC [ mode K # clear the line
+
+Multiple numeric params to the ``'m'`` command can be combined into a single
+sequence::
+
+ ESC [ 36 ; 45 ; 1 m # bright cyan text on magenta background
+
+All other ANSI sequences of the form ``ESC [ ; ... ``
+are silently stripped from the output on Windows.
+
+Any other form of ANSI sequence, such as single-character codes or alternative
+initial characters, are not recognised or stripped. It would be cool to add
+them though. Let me know if it would be useful for you, via the Issues on
+GitHub.
+
+Status & Known Problems
+-----------------------
+
+I've personally only tested it on Windows XP (CMD, Console2), Ubuntu
+(gnome-terminal, xterm), and OS X.
+
+Some valid ANSI sequences aren't recognised.
+
+If you're hacking on the code, see `README-hacking.md`_. ESPECIALLY, see the
+explanation there of why we do not want PRs that allow Colorama to generate new
+types of ANSI codes.
+
+See outstanding issues and wish-list:
+https://github.com/tartley/colorama/issues
+
+If anything doesn't work for you, or doesn't do what you expected or hoped for,
+I'd love to hear about it on that issues list, would be delighted by patches,
+and would be happy to grant commit access to anyone who submits a working patch
+or two.
+
+.. _README-hacking.md: README-hacking.md
+
+License
+-------
+
+Copyright Jonathan Hartley & Arnon Yaari, 2013-2020. BSD 3-Clause license; see
+LICENSE file.
+
+Professional support
+--------------------
+
+.. |tideliftlogo| image:: https://cdn2.hubspot.net/hubfs/4008838/website/logos/logos_for_download/Tidelift_primary-shorthand-logo.png
+ :alt: Tidelift
+ :target: https://tidelift.com/subscription/pkg/pypi-colorama?utm_source=pypi-colorama&utm_medium=referral&utm_campaign=readme
+
+.. list-table::
+ :widths: 10 100
+
+ * - |tideliftlogo|
+ - Professional support for colorama is available as part of the
+ `Tidelift Subscription`_.
+ Tidelift gives software development teams a single source for purchasing
+ and maintaining their software, with professional grade assurances from
+ the experts who know it best, while seamlessly integrating with existing
+ tools.
+
+.. _Tidelift Subscription: https://tidelift.com/subscription/pkg/pypi-colorama?utm_source=pypi-colorama&utm_medium=referral&utm_campaign=readme
+
+Thanks
+------
+
+See the CHANGELOG for more thanks!
+
+* Marc Schlaich (schlamar) for a ``setup.py`` fix for Python2.5.
+* Marc Abramowitz, reported & fixed a crash on exit with closed ``stdout``,
+ providing a solution to issue #7's setuptools/distutils debate,
+ and other fixes.
+* User 'eryksun', for guidance on correctly instantiating ``ctypes.windll``.
+* Matthew McCormick for politely pointing out a longstanding crash on non-Win.
+* Ben Hoyt, for a magnificent fix under 64-bit Windows.
+* Jesse at Empty Square for submitting a fix for examples in the README.
+* User 'jamessp', an observant documentation fix for cursor positioning.
+* User 'vaal1239', Dave Mckee & Lackner Kristof for a tiny but much-needed Win7
+ fix.
+* Julien Stuyck, for wisely suggesting Python3 compatible updates to README.
+* Daniel Griffith for multiple fabulous patches.
+* Oscar Lesta for a valuable fix to stop ANSI chars being sent to non-tty
+ output.
+* Roger Binns, for many suggestions, valuable feedback, & bug reports.
+* Tim Golden for thought and much appreciated feedback on the initial idea.
+* User 'Zearin' for updates to the README file.
+* John Szakmeister for adding support for light colors
+* Charles Merriam for adding documentation to demos
+* Jurko for a fix on 64-bit Windows CPython2.5 w/o ctypes
+* Florian Bruhin for a fix when stdout or stderr are None
+* Thomas Weininger for fixing ValueError on Windows
+* Remi Rampin for better Github integration and fixes to the README file
+* Simeon Visser for closing a file handle using 'with' and updating classifiers
+ to include Python 3.3 and 3.4
+* Andy Neff for fixing RESET of LIGHT_EX colors.
+* Jonathan Hartley for the initial idea and implementation.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..496de2727d15000bdd9199c585cb2a8df9562ad5
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/RECORD
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+colorama-0.4.6.dist-info/licenses/LICENSE.txt,sha256=ysNcAmhuXQSlpxQL-zs25zrtSWZW6JEQLkKIhteTAxg,1491
+colorama/__init__.py,sha256=wePQA4U20tKgYARySLEC047ucNX-g8pRLpYBuiHlLb8,266
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+colorama/ansitowin32.py,sha256=vPNYa3OZbxjbuFyaVo0Tmhmy1FZ1lKMWCnT7odXpItk,11128
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+colorama/tests/__pycache__/initialise_test.cpython-312.pyc,,
+colorama/tests/__pycache__/isatty_test.cpython-312.pyc,,
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+colorama/tests/__pycache__/winterm_test.cpython-312.pyc,,
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+colorama/tests/winterm_test.py,sha256=qoWFPEjym5gm2RuMwpf3pOis3a5r_PJZFCzK254JL8A,3709
+colorama/win32.py,sha256=YQOKwMTwtGBbsY4dL5HYTvwTeP9wIQra5MvPNddpxZs,6181
+colorama/winterm.py,sha256=XCQFDHjPi6AHYNdZwy0tA02H-Jh48Jp-HvCjeLeLp3U,7134
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..d79189fda3251187de18c3998f23ae6fec11b20f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/colorama-0.4.6.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: hatchling 1.11.1
+Root-Is-Purelib: true
+Tag: py2-none-any
+Tag: py3-none-any
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..1d84b668beada9912dd28d777b9b053c93f390ad
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/METADATA
@@ -0,0 +1,50 @@
+Metadata-Version: 2.4
+Name: cuda-bindings
+Version: 12.9.4
+Summary: Python bindings for CUDA
+Author-email: NVIDIA Corporation
+License-Expression: LicenseRef-NVIDIA-SOFTWARE-LICENSE
+Project-URL: Repository, https://github.com/NVIDIA/cuda-python
+Project-URL: Documentation, https://nvidia.github.io/cuda-python/
+Classifier: Intended Audience :: Developers
+Classifier: Topic :: Database
+Classifier: Topic :: Scientific/Engineering
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Environment :: GPU :: NVIDIA CUDA
+Description-Content-Type: text/x-rst
+License-File: LICENSE
+Requires-Dist: cuda-pathfinder~=1.1
+Provides-Extra: all
+Requires-Dist: nvidia-cuda-nvcc-cu12; extra == "all"
+Requires-Dist: nvidia-cuda-nvrtc-cu12; extra == "all"
+Requires-Dist: nvidia-nvjitlink-cu12>=12.3; extra == "all"
+Requires-Dist: nvidia-cufile-cu12; sys_platform == "linux" and extra == "all"
+Provides-Extra: test
+Requires-Dist: cython<3.2,>=3.1; extra == "test"
+Requires-Dist: setuptools>=77.0.0; extra == "test"
+Requires-Dist: numpy>=1.21.1; extra == "test"
+Requires-Dist: pytest>=6.2.4; extra == "test"
+Requires-Dist: pytest-benchmark>=3.4.1; extra == "test"
+Requires-Dist: pyglet>=2.1.9; extra == "test"
+Dynamic: license-file
+
+.. SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE
+
+****************************************
+cuda-bindings: Low-level CUDA interfaces
+****************************************
+
+`cuda.bindings `_ is a standard set of low-level interfaces, providing full coverage of and 1:1 access to the CUDA host APIs from Python. Checkout the `Overview `_ for the workflow and performance results.
+
+* `Repository `_
+* `Documentation `_
+* `Examples `_
+* `Issue tracker `_
+
+For the installation instruction, please refer to the `Installation `_ page.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/RECORD
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/cuda_bindings-12.9.4.dist-info/top_level.txt
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+cuda
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/AUTHORS b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/AUTHORS
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index 0000000000000000000000000000000000000000..7092efd949bb407beb485f25d6c1847804a79170
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/AUTHORS
@@ -0,0 +1,8 @@
+# This is the list of HuggingFace Datasets authors for copyright purposes.
+#
+# This does not necessarily list everyone who has contributed code, since in
+# some cases, their employer may be the copyright holder. To see the full list
+# of contributors, see the revision history in source control.
+
+Google Inc.
+HuggingFace Inc.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/INSTALLER
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+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/LICENSE b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/LICENSE
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+
+ Apache License
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..4f35e2d18d41399b04b09923ce7984d8dce2e621
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/METADATA
@@ -0,0 +1,368 @@
+Metadata-Version: 2.1
+Name: datasets
+Version: 2.20.0
+Summary: HuggingFace community-driven open-source library of datasets
+Home-page: https://github.com/huggingface/datasets
+Author: HuggingFace Inc.
+Author-email: thomas@huggingface.co
+License: Apache 2.0
+Download-URL: https://github.com/huggingface/datasets/tags
+Keywords: datasets machine learning datasets metrics
+Platform: UNKNOWN
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Requires-Python: >=3.8.0
+Description-Content-Type: text/markdown
+License-File: LICENSE
+License-File: AUTHORS
+Requires-Dist: filelock
+Requires-Dist: numpy (>=1.17)
+Requires-Dist: pyarrow (>=15.0.0)
+Requires-Dist: pyarrow-hotfix
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+Provides-Extra: apache-beam
+Requires-Dist: apache-beam (>=2.26.0) ; extra == 'apache-beam'
+Provides-Extra: audio
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+Requires-Dist: librosa ; extra == 'audio'
+Provides-Extra: benchmarks
+Requires-Dist: tensorflow (==2.12.0) ; extra == 'benchmarks'
+Requires-Dist: torch (==2.0.1) ; extra == 'benchmarks'
+Requires-Dist: transformers (==4.30.1) ; extra == 'benchmarks'
+Provides-Extra: dev
+Requires-Dist: absl-py ; extra == 'dev'
+Requires-Dist: joblib (<1.3.0) ; extra == 'dev'
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+Requires-Dist: jax (>=0.3.14) ; (sys_platform != "win32") and extra == 'dev'
+Requires-Dist: jaxlib (>=0.3.14) ; (sys_platform != "win32") and extra == 'dev'
+Provides-Extra: docs
+Requires-Dist: s3fs ; extra == 'docs'
+Requires-Dist: transformers ; extra == 'docs'
+Requires-Dist: torch ; extra == 'docs'
+Requires-Dist: tensorflow (>=2.6.0) ; extra == 'docs'
+Provides-Extra: jax
+Requires-Dist: jax (>=0.3.14) ; extra == 'jax'
+Requires-Dist: jaxlib (>=0.3.14) ; extra == 'jax'
+Provides-Extra: metrics-tests
+Requires-Dist: accelerate ; extra == 'metrics-tests'
+Requires-Dist: bert-score (>=0.3.6) ; extra == 'metrics-tests'
+Requires-Dist: jiwer ; extra == 'metrics-tests'
+Requires-Dist: langdetect ; extra == 'metrics-tests'
+Requires-Dist: mauve-text ; extra == 'metrics-tests'
+Requires-Dist: nltk ; extra == 'metrics-tests'
+Requires-Dist: rouge-score ; extra == 'metrics-tests'
+Requires-Dist: sacrebleu ; extra == 'metrics-tests'
+Requires-Dist: sacremoses ; extra == 'metrics-tests'
+Requires-Dist: scikit-learn ; extra == 'metrics-tests'
+Requires-Dist: scipy ; extra == 'metrics-tests'
+Requires-Dist: sentencepiece ; extra == 'metrics-tests'
+Requires-Dist: seqeval ; extra == 'metrics-tests'
+Requires-Dist: spacy (>=3.0.0) ; extra == 'metrics-tests'
+Requires-Dist: tldextract ; extra == 'metrics-tests'
+Requires-Dist: toml (>=0.10.1) ; extra == 'metrics-tests'
+Requires-Dist: typer (<0.5.0) ; extra == 'metrics-tests'
+Requires-Dist: requests-file (>=1.5.1) ; extra == 'metrics-tests'
+Requires-Dist: tldextract (>=3.1.0) ; extra == 'metrics-tests'
+Requires-Dist: texttable (>=1.6.3) ; extra == 'metrics-tests'
+Requires-Dist: Werkzeug (>=1.0.1) ; extra == 'metrics-tests'
+Requires-Dist: six (~=1.15.0) ; extra == 'metrics-tests'
+Provides-Extra: quality
+Requires-Dist: ruff (>=0.3.0) ; extra == 'quality'
+Provides-Extra: s3
+Requires-Dist: s3fs ; extra == 's3'
+Provides-Extra: streaming
+Provides-Extra: tensorflow
+Requires-Dist: tensorflow (>=2.6.0) ; extra == 'tensorflow'
+Provides-Extra: tensorflow_gpu
+Requires-Dist: tensorflow (>=2.6.0) ; extra == 'tensorflow_gpu'
+Provides-Extra: tests
+Requires-Dist: absl-py ; extra == 'tests'
+Requires-Dist: joblib (<1.3.0) ; extra == 'tests'
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+Requires-Dist: pytest ; extra == 'tests'
+Requires-Dist: pytest-datadir ; extra == 'tests'
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+Requires-Dist: elasticsearch (<8.0.0) ; extra == 'tests'
+Requires-Dist: faiss-cpu (>=1.6.4) ; extra == 'tests'
+Requires-Dist: lz4 ; extra == 'tests'
+Requires-Dist: pyspark (>=3.4) ; extra == 'tests'
+Requires-Dist: py7zr ; extra == 'tests'
+Requires-Dist: rarfile (>=4.0) ; extra == 'tests'
+Requires-Dist: sqlalchemy ; extra == 'tests'
+Requires-Dist: s3fs (>=2021.11.1) ; extra == 'tests'
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+Requires-Dist: tensorflow (>=2.6.0) ; extra == 'tests'
+Requires-Dist: tiktoken ; extra == 'tests'
+Requires-Dist: torch (>=2.0.0) ; extra == 'tests'
+Requires-Dist: soundfile (>=0.12.1) ; extra == 'tests'
+Requires-Dist: transformers ; extra == 'tests'
+Requires-Dist: typing-extensions (>=4.6.1) ; extra == 'tests'
+Requires-Dist: zstandard ; extra == 'tests'
+Requires-Dist: polars[timezone] (>=0.20.0) ; extra == 'tests'
+Requires-Dist: Pillow (>=9.4.0) ; extra == 'tests'
+Requires-Dist: librosa ; extra == 'tests'
+Requires-Dist: jax (>=0.3.14) ; (sys_platform != "win32") and extra == 'tests'
+Requires-Dist: jaxlib (>=0.3.14) ; (sys_platform != "win32") and extra == 'tests'
+Provides-Extra: torch
+Requires-Dist: torch ; extra == 'torch'
+Provides-Extra: vision
+Requires-Dist: Pillow (>=9.4.0) ; extra == 'vision'
+
+
+
+🤗 Datasets is a lightweight library providing **two** main features:
+
+- **one-line dataloaders for many public datasets**: one-liners to download and pre-process any of the  major public datasets (image datasets, audio datasets, text datasets in 467 languages and dialects, etc.) provided on the [HuggingFace Datasets Hub](https://huggingface.co/datasets). With a simple command like `squad_dataset = load_dataset("squad")`, get any of these datasets ready to use in a dataloader for training/evaluating a ML model (Numpy/Pandas/PyTorch/TensorFlow/JAX),
+- **efficient data pre-processing**: simple, fast and reproducible data pre-processing for the public datasets as well as your own local datasets in CSV, JSON, text, PNG, JPEG, WAV, MP3, Parquet, etc. With simple commands like `processed_dataset = dataset.map(process_example)`, efficiently prepare the dataset for inspection and ML model evaluation and training.
+
+[🎓 **Documentation**](https://huggingface.co/docs/datasets/) [🔎 **Find a dataset in the Hub**](https://huggingface.co/datasets) [🌟 **Share a dataset on the Hub**](https://huggingface.co/docs/datasets/share)
+
+
+
+
+
+🤗 Datasets is designed to let the community easily add and share new datasets.
+
+🤗 Datasets has many additional interesting features:
+
+- Thrive on large datasets: 🤗 Datasets naturally frees the user from RAM memory limitation, all datasets are memory-mapped using an efficient zero-serialization cost backend (Apache Arrow).
+- Smart caching: never wait for your data to process several times.
+- Lightweight and fast with a transparent and pythonic API (multi-processing/caching/memory-mapping).
+- Built-in interoperability with NumPy, pandas, PyTorch, TensorFlow 2 and JAX.
+- Native support for audio and image data.
+- Enable streaming mode to save disk space and start iterating over the dataset immediately.
+
+🤗 Datasets originated from a fork of the awesome [TensorFlow Datasets](https://github.com/tensorflow/datasets) and the HuggingFace team want to deeply thank the TensorFlow Datasets team for building this amazing library. More details on the differences between 🤗 Datasets and `tfds` can be found in the section [Main differences between 🤗 Datasets and `tfds`](#main-differences-between--datasets-and-tfds).
+
+# Installation
+
+## With pip
+
+🤗 Datasets can be installed from PyPi and has to be installed in a virtual environment (venv or conda for instance)
+
+```bash
+pip install datasets
+```
+
+## With conda
+
+🤗 Datasets can be installed using conda as follows:
+
+```bash
+conda install -c huggingface -c conda-forge datasets
+```
+
+Follow the installation pages of TensorFlow and PyTorch to see how to install them with conda.
+
+For more details on installation, check the installation page in the documentation: https://huggingface.co/docs/datasets/installation
+
+## Installation to use with PyTorch/TensorFlow/pandas
+
+If you plan to use 🤗 Datasets with PyTorch (1.0+), TensorFlow (2.2+) or pandas, you should also install PyTorch, TensorFlow or pandas.
+
+For more details on using the library with NumPy, pandas, PyTorch or TensorFlow, check the quick start page in the documentation: https://huggingface.co/docs/datasets/quickstart
+
+# Usage
+
+🤗 Datasets is made to be very simple to use - the API is centered around a single function, `datasets.load_dataset(dataset_name, **kwargs)`, that instantiates a dataset.
+
+This library can be used for text/image/audio/etc. datasets. Here is an example to load a text dataset:
+
+Here is a quick example:
+
+```python
+from datasets import load_dataset
+
+# Print all the available datasets
+from huggingface_hub import list_datasets
+print([dataset.id for dataset in list_datasets()])
+
+# Load a dataset and print the first example in the training set
+squad_dataset = load_dataset('squad')
+print(squad_dataset['train'][0])
+
+# Process the dataset - add a column with the length of the context texts
+dataset_with_length = squad_dataset.map(lambda x: {"length": len(x["context"])})
+
+# Process the dataset - tokenize the context texts (using a tokenizer from the 🤗 Transformers library)
+from transformers import AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained('bert-base-cased')
+
+tokenized_dataset = squad_dataset.map(lambda x: tokenizer(x['context']), batched=True)
+```
+
+If your dataset is bigger than your disk or if you don't want to wait to download the data, you can use streaming:
+
+```python
+# If you want to use the dataset immediately and efficiently stream the data as you iterate over the dataset
+image_dataset = load_dataset('cifar100', streaming=True)
+for example in image_dataset["train"]:
+ break
+```
+
+For more details on using the library, check the quick start page in the documentation: https://huggingface.co/docs/datasets/quickstart and the specific pages on:
+
+- Loading a dataset: https://huggingface.co/docs/datasets/loading
+- What's in a Dataset: https://huggingface.co/docs/datasets/access
+- Processing data with 🤗 Datasets: https://huggingface.co/docs/datasets/process
+ - Processing audio data: https://huggingface.co/docs/datasets/audio_process
+ - Processing image data: https://huggingface.co/docs/datasets/image_process
+ - Processing text data: https://huggingface.co/docs/datasets/nlp_process
+- Streaming a dataset: https://huggingface.co/docs/datasets/stream
+- Writing your own dataset loading script: https://huggingface.co/docs/datasets/dataset_script
+- etc.
+
+# Add a new dataset to the Hub
+
+We have a very detailed step-by-step guide to add a new dataset to the  datasets already provided on the [HuggingFace Datasets Hub](https://huggingface.co/datasets).
+
+You can find:
+- [how to upload a dataset to the Hub using your web browser or Python](https://huggingface.co/docs/datasets/upload_dataset) and also
+- [how to upload it using Git](https://huggingface.co/docs/datasets/share).
+
+# Main differences between 🤗 Datasets and `tfds`
+
+If you are familiar with the great TensorFlow Datasets, here are the main differences between 🤗 Datasets and `tfds`:
+
+- the scripts in 🤗 Datasets are not provided within the library but are queried, downloaded/cached and dynamically loaded upon request
+- the backend serialization of 🤗 Datasets is based on [Apache Arrow](https://arrow.apache.org/) instead of TF Records and leverage python dataclasses for info and features with some diverging features (we mostly don't do encoding and store the raw data as much as possible in the backend serialization cache).
+- the user-facing dataset object of 🤗 Datasets is not a `tf.data.Dataset` but a built-in framework-agnostic dataset class with methods inspired by what we like in `tf.data` (like a `map()` method). It basically wraps a memory-mapped Arrow table cache.
+
+# Disclaimers
+
+🤗 Datasets may run Python code defined by the dataset authors to parse certain data formats or structures. For security reasons, we ask users to:
+- check the dataset scripts they're going to run beforehand and
+- pin the `revision` of the repositories they use.
+
+If you're a dataset owner and wish to update any part of it (description, citation, license, etc.), or do not want your dataset to be included in the Hugging Face Hub, please get in touch by opening a discussion or a pull request in the Community tab of the dataset page. Thanks for your contribution to the ML community!
+
+## BibTeX
+
+If you want to cite our 🤗 Datasets library, you can use our [paper](https://arxiv.org/abs/2109.02846):
+
+```bibtex
+@inproceedings{lhoest-etal-2021-datasets,
+ title = "Datasets: A Community Library for Natural Language Processing",
+ author = "Lhoest, Quentin and
+ Villanova del Moral, Albert and
+ Jernite, Yacine and
+ Thakur, Abhishek and
+ von Platen, Patrick and
+ Patil, Suraj and
+ Chaumond, Julien and
+ Drame, Mariama and
+ Plu, Julien and
+ Tunstall, Lewis and
+ Davison, Joe and
+ {\v{S}}a{\v{s}}ko, Mario and
+ Chhablani, Gunjan and
+ Malik, Bhavitvya and
+ Brandeis, Simon and
+ Le Scao, Teven and
+ Sanh, Victor and
+ Xu, Canwen and
+ Patry, Nicolas and
+ McMillan-Major, Angelina and
+ Schmid, Philipp and
+ Gugger, Sylvain and
+ Delangue, Cl{\'e}ment and
+ Matussi{\`e}re, Th{\'e}o and
+ Debut, Lysandre and
+ Bekman, Stas and
+ Cistac, Pierric and
+ Goehringer, Thibault and
+ Mustar, Victor and
+ Lagunas, Fran{\c{c}}ois and
+ Rush, Alexander and
+ Wolf, Thomas",
+ booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
+ month = nov,
+ year = "2021",
+ address = "Online and Punta Cana, Dominican Republic",
+ publisher = "Association for Computational Linguistics",
+ url = "https://aclanthology.org/2021.emnlp-demo.21",
+ pages = "175--184",
+ abstract = "The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, versioning, and documentation, while providing a lightweight front-end that behaves similarly for small datasets as for internet-scale corpora. The design of the library incorporates a distributed, community-driven approach to adding datasets and documenting usage. After a year of development, the library now includes more than 650 unique datasets, has more than 250 contributors, and has helped support a variety of novel cross-dataset research projects and shared tasks. The library is available at https://github.com/huggingface/datasets.",
+ eprint={2109.02846},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+}
+```
+
+If you need to cite a specific version of our 🤗 Datasets library for reproducibility, you can use the corresponding version Zenodo DOI from this [list](https://zenodo.org/search?q=conceptrecid:%224817768%22&sort=-version&all_versions=True).
+
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..fe8610fddff35e2cc2bd6061acde5f0f3f29981f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/RECORD
@@ -0,0 +1,279 @@
+../../../bin/datasets-cli,sha256=XRKMHoTu8RcaLptXEEAyYX_8C4uF3XYeK9zsbtSI_gc,291
+datasets-2.20.0.dist-info/AUTHORS,sha256=L0FBY23tCNHLmvsOKAbumHn8WZZIK98sH53JYxhAchU,327
+datasets-2.20.0.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+datasets-2.20.0.dist-info/LICENSE,sha256=z8d0m5b2O9McPEK1xHG_dWgUBT6EfBDz6wA0F7xSPTA,11358
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/entry_points.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/entry_points.txt
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@@ -0,0 +1,3 @@
+[console_scripts]
+datasets-cli = datasets.commands.datasets_cli:main
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/datasets-2.20.0.dist-info/top_level.txt
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/INSTALLER
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/LICENSE b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/LICENSE
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+
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/METADATA
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+Name: evaluate
+Version: 0.4.6
+Summary: HuggingFace community-driven open-source library of evaluation
+Home-page: https://github.com/huggingface/evaluate
+Author: HuggingFace Inc.
+Author-email: leandro@huggingface.co
+License: Apache 2.0
+Download-URL: https://github.com/huggingface/evaluate/tags
+Keywords: metrics machine learning evaluate evaluation
+Platform: UNKNOWN
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
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+
+
+
+
+> **Tip:** For more recent evaluation approaches, for example for evaluating LLMs, we recommend our newer and more actively maintained library [LightEval](https://github.com/huggingface/lighteval).
+
+
+
+🤗 Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.
+
+It currently contains:
+
+- **implementations of dozens of popular metrics**: the existing metrics cover a variety of tasks spanning from NLP to Computer Vision, and include dataset-specific metrics for datasets. With a simple command like `accuracy = load("accuracy")`, get any of these metrics ready to use for evaluating a ML model in any framework (Numpy/Pandas/PyTorch/TensorFlow/JAX).
+- **comparisons and measurements**: comparisons are used to measure the difference between models and measurements are tools to evaluate datasets.
+- **an easy way of adding new evaluation modules to the 🤗 Hub**: you can create new evaluation modules and push them to a dedicated Space in the 🤗 Hub with `evaluate-cli create [metric name]`, which allows you to see easily compare different metrics and their outputs for the same sets of references and predictions.
+
+[🎓 **Documentation**](https://huggingface.co/docs/evaluate/)
+
+🔎 **Find a [metric](https://huggingface.co/evaluate-metric), [comparison](https://huggingface.co/evaluate-comparison), [measurement](https://huggingface.co/evaluate-measurement) on the Hub**
+
+[🌟 **Add a new evaluation module**](https://huggingface.co/docs/evaluate/)
+
+🤗 Evaluate also has lots of useful features like:
+
+- **Type checking**: the input types are checked to make sure that you are using the right input formats for each metric
+- **Metric cards**: each metrics comes with a card that describes the values, limitations and their ranges, as well as providing examples of their usage and usefulness.
+- **Community metrics:** Metrics live on the Hugging Face Hub and you can easily add your own metrics for your project or to collaborate with others.
+
+
+# Installation
+
+## With pip
+
+🤗 Evaluate can be installed from PyPi and has to be installed in a virtual environment (venv or conda for instance)
+
+```bash
+pip install evaluate
+```
+
+# Usage
+
+🤗 Evaluate's main methods are:
+
+- `evaluate.list_evaluation_modules()` to list the available metrics, comparisons and measurements
+- `evaluate.load(module_name, **kwargs)` to instantiate an evaluation module
+- `results = module.compute(*kwargs)` to compute the result of an evaluation module
+
+# Adding a new evaluation module
+
+First install the necessary dependencies to create a new metric with the following command:
+```bash
+pip install evaluate[template]
+```
+Then you can get started with the following command which will create a new folder for your metric and display the necessary steps:
+```bash
+evaluate-cli create "Awesome Metric"
+```
+See this [step-by-step guide](https://huggingface.co/docs/evaluate/creating_and_sharing) in the documentation for detailed instructions.
+
+## Credits
+
+Thanks to [@marella](https://github.com/marella) for letting us use the `evaluate` namespace on PyPi previously used by his [library](https://github.com/marella/evaluate).
+
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..868669f90efdf12f547bc1199a2495a870340989
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/RECORD
@@ -0,0 +1,65 @@
+../../../bin/evaluate-cli,sha256=eSCz52hrIV0xsNxmcZUi_WMT0JUfXhWqrvJ7lwcMA-Y,291
+evaluate-0.4.6.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+evaluate-0.4.6.dist-info/LICENSE,sha256=z8d0m5b2O9McPEK1xHG_dWgUBT6EfBDz6wA0F7xSPTA,11358
+evaluate-0.4.6.dist-info/METADATA,sha256=bQ7ra6adRqGzuFO3DLg3ogYkIZKuTEgCao3DF1hV3ko,9521
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+evaluate-0.4.6.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+evaluate-0.4.6.dist-info/WHEEL,sha256=tZoeGjtWxWRfdplE7E3d45VPlLNQnvbKiYnx7gwAy8A,92
+evaluate-0.4.6.dist-info/entry_points.txt,sha256=m2P3heof0lsg47nq6tYW_yUtxTfimd3RuD26Yk8KMkM,70
+evaluate-0.4.6.dist-info/top_level.txt,sha256=wBEoxird-u8p4OKDwq5z9rlfH-ybeez8rjaKNLNJ3B0,9
+evaluate/__init__.py,sha256=R9HfU7D_HP339OJEXufHzlZ_zwZBEQ7UQYm_-RC-rXU,1754
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/REQUESTED b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/REQUESTED
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..79d5c89a71989389294854aa34e329701325f8b0
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.45.1)
+Root-Is-Purelib: true
+Tag: py3-none-any
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/entry_points.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/entry_points.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cbb3e69c055695cd6dccee54dec460f319c3fd25
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/entry_points.txt
@@ -0,0 +1,3 @@
+[console_scripts]
+evaluate-cli = evaluate.commands.evaluate_cli:main
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e6adde7833123ecc7f347ea1f5492568989dfd45
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/evaluate-0.4.6.dist-info/top_level.txt
@@ -0,0 +1 @@
+evaluate
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c9d8c5b8ebe565a652b3671b3dfa066f7346af45
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/__init__.py
@@ -0,0 +1,70 @@
+"""
+A platform independent file lock that supports the with-statement.
+
+.. autodata:: filelock.__version__
+ :no-value:
+
+"""
+
+from __future__ import annotations
+
+import sys
+import warnings
+from typing import TYPE_CHECKING
+
+from ._api import AcquireReturnProxy, BaseFileLock
+from ._error import Timeout
+from ._soft import SoftFileLock
+from ._unix import UnixFileLock, has_fcntl
+from ._windows import WindowsFileLock
+from .asyncio import (
+ AsyncAcquireReturnProxy,
+ AsyncSoftFileLock,
+ AsyncUnixFileLock,
+ AsyncWindowsFileLock,
+ BaseAsyncFileLock,
+)
+from .version import version
+
+#: version of the project as a string
+__version__: str = version
+
+
+if sys.platform == "win32": # pragma: win32 cover
+ _FileLock: type[BaseFileLock] = WindowsFileLock
+ _AsyncFileLock: type[BaseAsyncFileLock] = AsyncWindowsFileLock
+else: # pragma: win32 no cover # noqa: PLR5501
+ if has_fcntl:
+ _FileLock: type[BaseFileLock] = UnixFileLock
+ _AsyncFileLock: type[BaseAsyncFileLock] = AsyncUnixFileLock
+ else:
+ _FileLock = SoftFileLock
+ _AsyncFileLock = AsyncSoftFileLock
+ if warnings is not None:
+ warnings.warn("only soft file lock is available", stacklevel=2)
+
+if TYPE_CHECKING:
+ FileLock = SoftFileLock
+ AsyncFileLock = AsyncSoftFileLock
+else:
+ #: Alias for the lock, which should be used for the current platform.
+ FileLock = _FileLock
+ AsyncFileLock = _AsyncFileLock
+
+
+__all__ = [
+ "AcquireReturnProxy",
+ "AsyncAcquireReturnProxy",
+ "AsyncFileLock",
+ "AsyncSoftFileLock",
+ "AsyncUnixFileLock",
+ "AsyncWindowsFileLock",
+ "BaseAsyncFileLock",
+ "BaseFileLock",
+ "FileLock",
+ "SoftFileLock",
+ "Timeout",
+ "UnixFileLock",
+ "WindowsFileLock",
+ "__version__",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fde69a0fef7badcc123d17735cd784a99baed52
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_api.py
@@ -0,0 +1,403 @@
+from __future__ import annotations
+
+import contextlib
+import inspect
+import logging
+import os
+import time
+import warnings
+from abc import ABCMeta, abstractmethod
+from dataclasses import dataclass
+from threading import local
+from typing import TYPE_CHECKING, Any, cast
+from weakref import WeakValueDictionary
+
+from ._error import Timeout
+
+if TYPE_CHECKING:
+ import sys
+ from types import TracebackType
+
+ if sys.version_info >= (3, 11): # pragma: no cover (py311+)
+ from typing import Self
+ else: # pragma: no cover ( None:
+ self.lock = lock
+
+ def __enter__(self) -> BaseFileLock:
+ return self.lock
+
+ def __exit__(
+ self,
+ exc_type: type[BaseException] | None,
+ exc_value: BaseException | None,
+ traceback: TracebackType | None,
+ ) -> None:
+ self.lock.release()
+
+
+@dataclass
+class FileLockContext:
+ """A dataclass which holds the context for a ``BaseFileLock`` object."""
+
+ # The context is held in a separate class to allow optional use of thread local storage via the
+ # ThreadLocalFileContext class.
+
+ #: The path to the lock file.
+ lock_file: str
+
+ #: The default timeout value.
+ timeout: float
+
+ #: The mode for the lock files
+ mode: int
+
+ #: Whether the lock should be blocking or not
+ blocking: bool
+
+ #: The file descriptor for the *_lock_file* as it is returned by the os.open() function, not None when lock held
+ lock_file_fd: int | None = None
+
+ #: The lock counter is used for implementing the nested locking mechanism.
+ lock_counter: int = 0 # When the lock is acquired is increased and the lock is only released, when this value is 0
+
+
+class ThreadLocalFileContext(FileLockContext, local):
+ """A thread local version of the ``FileLockContext`` class."""
+
+
+class FileLockMeta(ABCMeta):
+ def __call__( # noqa: PLR0913
+ cls,
+ lock_file: str | os.PathLike[str],
+ timeout: float = -1,
+ mode: int = 0o644,
+ thread_local: bool = True, # noqa: FBT001, FBT002
+ *,
+ blocking: bool = True,
+ is_singleton: bool = False,
+ **kwargs: Any, # capture remaining kwargs for subclasses # noqa: ANN401
+ ) -> BaseFileLock:
+ if is_singleton:
+ instance = cls._instances.get(str(lock_file)) # type: ignore[attr-defined]
+ if instance:
+ params_to_check = {
+ "thread_local": (thread_local, instance.is_thread_local()),
+ "timeout": (timeout, instance.timeout),
+ "mode": (mode, instance.mode),
+ "blocking": (blocking, instance.blocking),
+ }
+
+ non_matching_params = {
+ name: (passed_param, set_param)
+ for name, (passed_param, set_param) in params_to_check.items()
+ if passed_param != set_param
+ }
+ if not non_matching_params:
+ return cast("BaseFileLock", instance)
+
+ # parameters do not match; raise error
+ msg = "Singleton lock instances cannot be initialized with differing arguments"
+ msg += "\nNon-matching arguments: "
+ for param_name, (passed_param, set_param) in non_matching_params.items():
+ msg += f"\n\t{param_name} (existing lock has {set_param} but {passed_param} was passed)"
+ raise ValueError(msg)
+
+ # Workaround to make `__init__`'s params optional in subclasses
+ # E.g. virtualenv changes the signature of the `__init__` method in the `BaseFileLock` class descendant
+ # (https://github.com/tox-dev/filelock/pull/340)
+
+ all_params = {
+ "timeout": timeout,
+ "mode": mode,
+ "thread_local": thread_local,
+ "blocking": blocking,
+ "is_singleton": is_singleton,
+ **kwargs,
+ }
+
+ present_params = inspect.signature(cls.__init__).parameters # type: ignore[misc]
+ init_params = {key: value for key, value in all_params.items() if key in present_params}
+
+ instance = super().__call__(lock_file, **init_params)
+
+ if is_singleton:
+ cls._instances[str(lock_file)] = instance # type: ignore[attr-defined]
+
+ return cast("BaseFileLock", instance)
+
+
+class BaseFileLock(contextlib.ContextDecorator, metaclass=FileLockMeta):
+ """Abstract base class for a file lock object."""
+
+ _instances: WeakValueDictionary[str, BaseFileLock]
+
+ def __init_subclass__(cls, **kwargs: dict[str, Any]) -> None:
+ """Setup unique state for lock subclasses."""
+ super().__init_subclass__(**kwargs)
+ cls._instances = WeakValueDictionary()
+
+ def __init__( # noqa: PLR0913
+ self,
+ lock_file: str | os.PathLike[str],
+ timeout: float = -1,
+ mode: int = 0o644,
+ thread_local: bool = True, # noqa: FBT001, FBT002
+ *,
+ blocking: bool = True,
+ is_singleton: bool = False,
+ ) -> None:
+ """
+ Create a new lock object.
+
+ :param lock_file: path to the file
+ :param timeout: default timeout when acquiring the lock, in seconds. It will be used as fallback value in \
+ the acquire method, if no timeout value (``None``) is given. If you want to disable the timeout, set it \
+ to a negative value. A timeout of 0 means that there is exactly one attempt to acquire the file lock.
+ :param mode: file permissions for the lockfile
+ :param thread_local: Whether this object's internal context should be thread local or not. If this is set to \
+ ``False`` then the lock will be reentrant across threads.
+ :param blocking: whether the lock should be blocking or not
+ :param is_singleton: If this is set to ``True`` then only one instance of this class will be created \
+ per lock file. This is useful if you want to use the lock object for reentrant locking without needing \
+ to pass the same object around.
+
+ """
+ self._is_thread_local = thread_local
+ self._is_singleton = is_singleton
+
+ # Create the context. Note that external code should not work with the context directly and should instead use
+ # properties of this class.
+ kwargs: dict[str, Any] = {
+ "lock_file": os.fspath(lock_file),
+ "timeout": timeout,
+ "mode": mode,
+ "blocking": blocking,
+ }
+ self._context: FileLockContext = (ThreadLocalFileContext if thread_local else FileLockContext)(**kwargs)
+
+ def is_thread_local(self) -> bool:
+ """:return: a flag indicating if this lock is thread local or not"""
+ return self._is_thread_local
+
+ @property
+ def is_singleton(self) -> bool:
+ """:return: a flag indicating if this lock is singleton or not"""
+ return self._is_singleton
+
+ @property
+ def lock_file(self) -> str:
+ """:return: path to the lock file"""
+ return self._context.lock_file
+
+ @property
+ def timeout(self) -> float:
+ """
+ :return: the default timeout value, in seconds
+
+ .. versionadded:: 2.0.0
+ """
+ return self._context.timeout
+
+ @timeout.setter
+ def timeout(self, value: float | str) -> None:
+ """
+ Change the default timeout value.
+
+ :param value: the new value, in seconds
+
+ """
+ self._context.timeout = float(value)
+
+ @property
+ def blocking(self) -> bool:
+ """:return: whether the locking is blocking or not"""
+ return self._context.blocking
+
+ @blocking.setter
+ def blocking(self, value: bool) -> None:
+ """
+ Change the default blocking value.
+
+ :param value: the new value as bool
+
+ """
+ self._context.blocking = value
+
+ @property
+ def mode(self) -> int:
+ """:return: the file permissions for the lockfile"""
+ return self._context.mode
+
+ @abstractmethod
+ def _acquire(self) -> None:
+ """If the file lock could be acquired, self._context.lock_file_fd holds the file descriptor of the lock file."""
+ raise NotImplementedError
+
+ @abstractmethod
+ def _release(self) -> None:
+ """Releases the lock and sets self._context.lock_file_fd to None."""
+ raise NotImplementedError
+
+ @property
+ def is_locked(self) -> bool:
+ """
+
+ :return: A boolean indicating if the lock file is holding the lock currently.
+
+ .. versionchanged:: 2.0.0
+
+ This was previously a method and is now a property.
+ """
+ return self._context.lock_file_fd is not None
+
+ @property
+ def lock_counter(self) -> int:
+ """:return: The number of times this lock has been acquired (but not yet released)."""
+ return self._context.lock_counter
+
+ def acquire(
+ self,
+ timeout: float | None = None,
+ poll_interval: float = 0.05,
+ *,
+ poll_intervall: float | None = None,
+ blocking: bool | None = None,
+ ) -> AcquireReturnProxy:
+ """
+ Try to acquire the file lock.
+
+ :param timeout: maximum wait time for acquiring the lock, ``None`` means use the default :attr:`~timeout` is and
+ if ``timeout < 0``, there is no timeout and this method will block until the lock could be acquired
+ :param poll_interval: interval of trying to acquire the lock file
+ :param poll_intervall: deprecated, kept for backwards compatibility, use ``poll_interval`` instead
+ :param blocking: defaults to True. If False, function will return immediately if it cannot obtain a lock on the
+ first attempt. Otherwise, this method will block until the timeout expires or the lock is acquired.
+ :raises Timeout: if fails to acquire lock within the timeout period
+ :return: a context object that will unlock the file when the context is exited
+
+ .. code-block:: python
+
+ # You can use this method in the context manager (recommended)
+ with lock.acquire():
+ pass
+
+ # Or use an equivalent try-finally construct:
+ lock.acquire()
+ try:
+ pass
+ finally:
+ lock.release()
+
+ .. versionchanged:: 2.0.0
+
+ This method returns now a *proxy* object instead of *self*,
+ so that it can be used in a with statement without side effects.
+
+ """
+ # Use the default timeout, if no timeout is provided.
+ if timeout is None:
+ timeout = self._context.timeout
+
+ if blocking is None:
+ blocking = self._context.blocking
+
+ if poll_intervall is not None:
+ msg = "use poll_interval instead of poll_intervall"
+ warnings.warn(msg, DeprecationWarning, stacklevel=2)
+ poll_interval = poll_intervall
+
+ # Increment the number right at the beginning. We can still undo it, if something fails.
+ self._context.lock_counter += 1
+
+ lock_id = id(self)
+ lock_filename = self.lock_file
+ start_time = time.perf_counter()
+ try:
+ while True:
+ if not self.is_locked:
+ _LOGGER.debug("Attempting to acquire lock %s on %s", lock_id, lock_filename)
+ self._acquire()
+ if self.is_locked:
+ _LOGGER.debug("Lock %s acquired on %s", lock_id, lock_filename)
+ break
+ if blocking is False:
+ _LOGGER.debug("Failed to immediately acquire lock %s on %s", lock_id, lock_filename)
+ raise Timeout(lock_filename) # noqa: TRY301
+ if 0 <= timeout < time.perf_counter() - start_time:
+ _LOGGER.debug("Timeout on acquiring lock %s on %s", lock_id, lock_filename)
+ raise Timeout(lock_filename) # noqa: TRY301
+ msg = "Lock %s not acquired on %s, waiting %s seconds ..."
+ _LOGGER.debug(msg, lock_id, lock_filename, poll_interval)
+ time.sleep(poll_interval)
+ except BaseException: # Something did go wrong, so decrement the counter.
+ self._context.lock_counter = max(0, self._context.lock_counter - 1)
+ raise
+ return AcquireReturnProxy(lock=self)
+
+ def release(self, force: bool = False) -> None: # noqa: FBT001, FBT002
+ """
+ Releases the file lock. Please note, that the lock is only completely released, if the lock counter is 0.
+ Also note, that the lock file itself is not automatically deleted.
+
+ :param force: If true, the lock counter is ignored and the lock is released in every case/
+
+ """
+ if self.is_locked:
+ self._context.lock_counter -= 1
+
+ if self._context.lock_counter == 0 or force:
+ lock_id, lock_filename = id(self), self.lock_file
+
+ _LOGGER.debug("Attempting to release lock %s on %s", lock_id, lock_filename)
+ self._release()
+ self._context.lock_counter = 0
+ _LOGGER.debug("Lock %s released on %s", lock_id, lock_filename)
+
+ def __enter__(self) -> Self:
+ """
+ Acquire the lock.
+
+ :return: the lock object
+
+ """
+ self.acquire()
+ return self
+
+ def __exit__(
+ self,
+ exc_type: type[BaseException] | None,
+ exc_value: BaseException | None,
+ traceback: TracebackType | None,
+ ) -> None:
+ """
+ Release the lock.
+
+ :param exc_type: the exception type if raised
+ :param exc_value: the exception value if raised
+ :param traceback: the exception traceback if raised
+
+ """
+ self.release()
+
+ def __del__(self) -> None:
+ """Called when the lock object is deleted."""
+ self.release(force=True)
+
+
+__all__ = [
+ "AcquireReturnProxy",
+ "BaseFileLock",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_error.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_error.py
new file mode 100644
index 0000000000000000000000000000000000000000..f7ff08c0f508ad7077eb6ed1990898840c952b3a
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_error.py
@@ -0,0 +1,30 @@
+from __future__ import annotations
+
+from typing import Any
+
+
+class Timeout(TimeoutError): # noqa: N818
+ """Raised when the lock could not be acquired in *timeout* seconds."""
+
+ def __init__(self, lock_file: str) -> None:
+ super().__init__()
+ self._lock_file = lock_file
+
+ def __reduce__(self) -> str | tuple[Any, ...]:
+ return self.__class__, (self._lock_file,) # Properly pickle the exception
+
+ def __str__(self) -> str:
+ return f"The file lock '{self._lock_file}' could not be acquired."
+
+ def __repr__(self) -> str:
+ return f"{self.__class__.__name__}({self.lock_file!r})"
+
+ @property
+ def lock_file(self) -> str:
+ """:return: The path of the file lock."""
+ return self._lock_file
+
+
+__all__ = [
+ "Timeout",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_soft.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_soft.py
new file mode 100644
index 0000000000000000000000000000000000000000..28c67f74cc82b8f55e47afd6a71972cc1fb95eb6
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_soft.py
@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+import os
+import sys
+from contextlib import suppress
+from errno import EACCES, EEXIST
+from pathlib import Path
+
+from ._api import BaseFileLock
+from ._util import ensure_directory_exists, raise_on_not_writable_file
+
+
+class SoftFileLock(BaseFileLock):
+ """Simply watches the existence of the lock file."""
+
+ def _acquire(self) -> None:
+ raise_on_not_writable_file(self.lock_file)
+ ensure_directory_exists(self.lock_file)
+ # first check for exists and read-only mode as the open will mask this case as EEXIST
+ flags = (
+ os.O_WRONLY # open for writing only
+ | os.O_CREAT
+ | os.O_EXCL # together with above raise EEXIST if the file specified by filename exists
+ | os.O_TRUNC # truncate the file to zero byte
+ )
+ try:
+ file_handler = os.open(self.lock_file, flags, self._context.mode)
+ except OSError as exception: # re-raise unless expected exception
+ if not (
+ exception.errno == EEXIST # lock already exist
+ or (exception.errno == EACCES and sys.platform == "win32") # has no access to this lock
+ ): # pragma: win32 no cover
+ raise
+ else:
+ self._context.lock_file_fd = file_handler
+
+ def _release(self) -> None:
+ assert self._context.lock_file_fd is not None # noqa: S101
+ os.close(self._context.lock_file_fd) # the lock file is definitely not None
+ self._context.lock_file_fd = None
+ with suppress(OSError): # the file is already deleted and that's what we want
+ Path(self.lock_file).unlink()
+
+
+__all__ = [
+ "SoftFileLock",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_unix.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_unix.py
new file mode 100644
index 0000000000000000000000000000000000000000..04f590daa99c7c689aa9fc5d7dc064d1ee027485
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_unix.py
@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+import os
+import sys
+from contextlib import suppress
+from errno import ENOSYS
+from pathlib import Path
+from typing import cast
+
+from ._api import BaseFileLock
+from ._util import ensure_directory_exists
+
+#: a flag to indicate if the fcntl API is available
+has_fcntl = False
+if sys.platform == "win32": # pragma: win32 cover
+
+ class UnixFileLock(BaseFileLock):
+ """Uses the :func:`fcntl.flock` to hard lock the lock file on unix systems."""
+
+ def _acquire(self) -> None:
+ raise NotImplementedError
+
+ def _release(self) -> None:
+ raise NotImplementedError
+
+else: # pragma: win32 no cover
+ try:
+ import fcntl
+ except ImportError:
+ pass
+ else:
+ has_fcntl = True
+
+ class UnixFileLock(BaseFileLock):
+ """Uses the :func:`fcntl.flock` to hard lock the lock file on unix systems."""
+
+ def _acquire(self) -> None:
+ ensure_directory_exists(self.lock_file)
+ open_flags = os.O_RDWR | os.O_TRUNC
+ if not Path(self.lock_file).exists():
+ open_flags |= os.O_CREAT
+ fd = os.open(self.lock_file, open_flags, self._context.mode)
+ with suppress(PermissionError): # This locked is not owned by this UID
+ os.fchmod(fd, self._context.mode)
+ try:
+ fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
+ except OSError as exception:
+ os.close(fd)
+ if exception.errno == ENOSYS: # NotImplemented error
+ msg = "FileSystem does not appear to support flock; use SoftFileLock instead"
+ raise NotImplementedError(msg) from exception
+ else:
+ self._context.lock_file_fd = fd
+
+ def _release(self) -> None:
+ # Do not remove the lockfile:
+ # https://github.com/tox-dev/py-filelock/issues/31
+ # https://stackoverflow.com/questions/17708885/flock-removing-locked-file-without-race-condition
+ fd = cast("int", self._context.lock_file_fd)
+ self._context.lock_file_fd = None
+ fcntl.flock(fd, fcntl.LOCK_UN)
+ os.close(fd)
+
+
+__all__ = [
+ "UnixFileLock",
+ "has_fcntl",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_util.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_util.py
new file mode 100644
index 0000000000000000000000000000000000000000..c671e8533873948f0e1b5575ff952c722019f067
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_util.py
@@ -0,0 +1,52 @@
+from __future__ import annotations
+
+import os
+import stat
+import sys
+from errno import EACCES, EISDIR
+from pathlib import Path
+
+
+def raise_on_not_writable_file(filename: str) -> None:
+ """
+ Raise an exception if attempting to open the file for writing would fail.
+
+ This is done so files that will never be writable can be separated from files that are writable but currently
+ locked.
+
+ :param filename: file to check
+ :raises OSError: as if the file was opened for writing.
+
+ """
+ try: # use stat to do exists + can write to check without race condition
+ file_stat = os.stat(filename) # noqa: PTH116
+ except OSError:
+ return # swallow does not exist or other errors
+
+ if file_stat.st_mtime != 0: # if os.stat returns but modification is zero that's an invalid os.stat - ignore it
+ if not (file_stat.st_mode & stat.S_IWUSR):
+ raise PermissionError(EACCES, "Permission denied", filename)
+
+ if stat.S_ISDIR(file_stat.st_mode):
+ if sys.platform == "win32": # pragma: win32 cover
+ # On Windows, this is PermissionError
+ raise PermissionError(EACCES, "Permission denied", filename)
+ else: # pragma: win32 no cover # noqa: RET506
+ # On linux / macOS, this is IsADirectoryError
+ raise IsADirectoryError(EISDIR, "Is a directory", filename)
+
+
+def ensure_directory_exists(filename: Path | str) -> None:
+ """
+ Ensure the directory containing the file exists (create it if necessary).
+
+ :param filename: file.
+
+ """
+ Path(filename).parent.mkdir(parents=True, exist_ok=True)
+
+
+__all__ = [
+ "ensure_directory_exists",
+ "raise_on_not_writable_file",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_windows.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_windows.py
new file mode 100644
index 0000000000000000000000000000000000000000..348251d1067c28c55a6a267f8d11337abfae837f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/_windows.py
@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+import os
+import sys
+from contextlib import suppress
+from errno import EACCES
+from pathlib import Path
+from typing import cast
+
+from ._api import BaseFileLock
+from ._util import ensure_directory_exists, raise_on_not_writable_file
+
+if sys.platform == "win32": # pragma: win32 cover
+ import msvcrt
+
+ class WindowsFileLock(BaseFileLock):
+ """Uses the :func:`msvcrt.locking` function to hard lock the lock file on Windows systems."""
+
+ def _acquire(self) -> None:
+ raise_on_not_writable_file(self.lock_file)
+ ensure_directory_exists(self.lock_file)
+ flags = (
+ os.O_RDWR # open for read and write
+ | os.O_CREAT # create file if not exists
+ | os.O_TRUNC # truncate file if not empty
+ )
+ try:
+ fd = os.open(self.lock_file, flags, self._context.mode)
+ except OSError as exception:
+ if exception.errno != EACCES: # has no access to this lock
+ raise
+ else:
+ try:
+ msvcrt.locking(fd, msvcrt.LK_NBLCK, 1)
+ except OSError as exception:
+ os.close(fd) # close file first
+ if exception.errno != EACCES: # file is already locked
+ raise
+ else:
+ self._context.lock_file_fd = fd
+
+ def _release(self) -> None:
+ fd = cast("int", self._context.lock_file_fd)
+ self._context.lock_file_fd = None
+ msvcrt.locking(fd, msvcrt.LK_UNLCK, 1)
+ os.close(fd)
+
+ with suppress(OSError): # Probably another instance of the application hat acquired the file lock.
+ Path(self.lock_file).unlink()
+
+else: # pragma: win32 no cover
+
+ class WindowsFileLock(BaseFileLock):
+ """Uses the :func:`msvcrt.locking` function to hard lock the lock file on Windows systems."""
+
+ def _acquire(self) -> None:
+ raise NotImplementedError
+
+ def _release(self) -> None:
+ raise NotImplementedError
+
+
+__all__ = [
+ "WindowsFileLock",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/asyncio.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/asyncio.py
new file mode 100644
index 0000000000000000000000000000000000000000..252de203078677c86345c6ad99230317197b9d28
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/asyncio.py
@@ -0,0 +1,342 @@
+"""An asyncio-based implementation of the file lock.""" # noqa: A005
+
+from __future__ import annotations
+
+import asyncio
+import contextlib
+import logging
+import os
+import time
+from dataclasses import dataclass
+from threading import local
+from typing import TYPE_CHECKING, Any, Callable, NoReturn, cast
+
+from ._api import BaseFileLock, FileLockContext, FileLockMeta
+from ._error import Timeout
+from ._soft import SoftFileLock
+from ._unix import UnixFileLock
+from ._windows import WindowsFileLock
+
+if TYPE_CHECKING:
+ import sys
+ from concurrent import futures
+ from types import TracebackType
+
+ if sys.version_info >= (3, 11): # pragma: no cover (py311+)
+ from typing import Self
+ else: # pragma: no cover ( None: # noqa: D107
+ self.lock = lock
+
+ async def __aenter__(self) -> BaseAsyncFileLock: # noqa: D105
+ return self.lock
+
+ async def __aexit__( # noqa: D105
+ self,
+ exc_type: type[BaseException] | None,
+ exc_value: BaseException | None,
+ traceback: TracebackType | None,
+ ) -> None:
+ await self.lock.release()
+
+
+class AsyncFileLockMeta(FileLockMeta):
+ def __call__( # type: ignore[override] # noqa: PLR0913
+ cls, # noqa: N805
+ lock_file: str | os.PathLike[str],
+ timeout: float = -1,
+ mode: int = 0o644,
+ thread_local: bool = False, # noqa: FBT001, FBT002
+ *,
+ blocking: bool = True,
+ is_singleton: bool = False,
+ loop: asyncio.AbstractEventLoop | None = None,
+ run_in_executor: bool = True,
+ executor: futures.Executor | None = None,
+ ) -> BaseAsyncFileLock:
+ if thread_local and run_in_executor:
+ msg = "run_in_executor is not supported when thread_local is True"
+ raise ValueError(msg)
+ instance = super().__call__(
+ lock_file=lock_file,
+ timeout=timeout,
+ mode=mode,
+ thread_local=thread_local,
+ blocking=blocking,
+ is_singleton=is_singleton,
+ loop=loop,
+ run_in_executor=run_in_executor,
+ executor=executor,
+ )
+ return cast("BaseAsyncFileLock", instance)
+
+
+class BaseAsyncFileLock(BaseFileLock, metaclass=AsyncFileLockMeta):
+ """Base class for asynchronous file locks."""
+
+ def __init__( # noqa: PLR0913
+ self,
+ lock_file: str | os.PathLike[str],
+ timeout: float = -1,
+ mode: int = 0o644,
+ thread_local: bool = False, # noqa: FBT001, FBT002
+ *,
+ blocking: bool = True,
+ is_singleton: bool = False,
+ loop: asyncio.AbstractEventLoop | None = None,
+ run_in_executor: bool = True,
+ executor: futures.Executor | None = None,
+ ) -> None:
+ """
+ Create a new lock object.
+
+ :param lock_file: path to the file
+ :param timeout: default timeout when acquiring the lock, in seconds. It will be used as fallback value in \
+ the acquire method, if no timeout value (``None``) is given. If you want to disable the timeout, set it \
+ to a negative value. A timeout of 0 means that there is exactly one attempt to acquire the file lock.
+ :param mode: file permissions for the lockfile
+ :param thread_local: Whether this object's internal context should be thread local or not. If this is set to \
+ ``False`` then the lock will be reentrant across threads.
+ :param blocking: whether the lock should be blocking or not
+ :param is_singleton: If this is set to ``True`` then only one instance of this class will be created \
+ per lock file. This is useful if you want to use the lock object for reentrant locking without needing \
+ to pass the same object around.
+ :param loop: The event loop to use. If not specified, the running event loop will be used.
+ :param run_in_executor: If this is set to ``True`` then the lock will be acquired in an executor.
+ :param executor: The executor to use. If not specified, the default executor will be used.
+
+ """
+ self._is_thread_local = thread_local
+ self._is_singleton = is_singleton
+
+ # Create the context. Note that external code should not work with the context directly and should instead use
+ # properties of this class.
+ kwargs: dict[str, Any] = {
+ "lock_file": os.fspath(lock_file),
+ "timeout": timeout,
+ "mode": mode,
+ "blocking": blocking,
+ "loop": loop,
+ "run_in_executor": run_in_executor,
+ "executor": executor,
+ }
+ self._context: AsyncFileLockContext = (AsyncThreadLocalFileContext if thread_local else AsyncFileLockContext)(
+ **kwargs
+ )
+
+ @property
+ def run_in_executor(self) -> bool:
+ """::return: whether run in executor."""
+ return self._context.run_in_executor
+
+ @property
+ def executor(self) -> futures.Executor | None:
+ """::return: the executor."""
+ return self._context.executor
+
+ @executor.setter
+ def executor(self, value: futures.Executor | None) -> None: # pragma: no cover
+ """
+ Change the executor.
+
+ :param value: the new executor or ``None``
+ :type value: futures.Executor | None
+
+ """
+ self._context.executor = value
+
+ @property
+ def loop(self) -> asyncio.AbstractEventLoop | None:
+ """::return: the event loop."""
+ return self._context.loop
+
+ async def acquire( # type: ignore[override]
+ self,
+ timeout: float | None = None,
+ poll_interval: float = 0.05,
+ *,
+ blocking: bool | None = None,
+ ) -> AsyncAcquireReturnProxy:
+ """
+ Try to acquire the file lock.
+
+ :param timeout: maximum wait time for acquiring the lock, ``None`` means use the default
+ :attr:`~BaseFileLock.timeout` is and if ``timeout < 0``, there is no timeout and
+ this method will block until the lock could be acquired
+ :param poll_interval: interval of trying to acquire the lock file
+ :param blocking: defaults to True. If False, function will return immediately if it cannot obtain a lock on the
+ first attempt. Otherwise, this method will block until the timeout expires or the lock is acquired.
+ :raises Timeout: if fails to acquire lock within the timeout period
+ :return: a context object that will unlock the file when the context is exited
+
+ .. code-block:: python
+
+ # You can use this method in the context manager (recommended)
+ with lock.acquire():
+ pass
+
+ # Or use an equivalent try-finally construct:
+ lock.acquire()
+ try:
+ pass
+ finally:
+ lock.release()
+
+ """
+ # Use the default timeout, if no timeout is provided.
+ if timeout is None:
+ timeout = self._context.timeout
+
+ if blocking is None:
+ blocking = self._context.blocking
+
+ # Increment the number right at the beginning. We can still undo it, if something fails.
+ self._context.lock_counter += 1
+
+ lock_id = id(self)
+ lock_filename = self.lock_file
+ start_time = time.perf_counter()
+ try:
+ while True:
+ if not self.is_locked:
+ _LOGGER.debug("Attempting to acquire lock %s on %s", lock_id, lock_filename)
+ await self._run_internal_method(self._acquire)
+ if self.is_locked:
+ _LOGGER.debug("Lock %s acquired on %s", lock_id, lock_filename)
+ break
+ if blocking is False:
+ _LOGGER.debug("Failed to immediately acquire lock %s on %s", lock_id, lock_filename)
+ raise Timeout(lock_filename) # noqa: TRY301
+ if 0 <= timeout < time.perf_counter() - start_time:
+ _LOGGER.debug("Timeout on acquiring lock %s on %s", lock_id, lock_filename)
+ raise Timeout(lock_filename) # noqa: TRY301
+ msg = "Lock %s not acquired on %s, waiting %s seconds ..."
+ _LOGGER.debug(msg, lock_id, lock_filename, poll_interval)
+ await asyncio.sleep(poll_interval)
+ except BaseException: # Something did go wrong, so decrement the counter.
+ self._context.lock_counter = max(0, self._context.lock_counter - 1)
+ raise
+ return AsyncAcquireReturnProxy(lock=self)
+
+ async def release(self, force: bool = False) -> None: # type: ignore[override] # noqa: FBT001, FBT002
+ """
+ Releases the file lock. Please note, that the lock is only completely released, if the lock counter is 0.
+ Also note, that the lock file itself is not automatically deleted.
+
+ :param force: If true, the lock counter is ignored and the lock is released in every case/
+
+ """
+ if self.is_locked:
+ self._context.lock_counter -= 1
+
+ if self._context.lock_counter == 0 or force:
+ lock_id, lock_filename = id(self), self.lock_file
+
+ _LOGGER.debug("Attempting to release lock %s on %s", lock_id, lock_filename)
+ await self._run_internal_method(self._release)
+ self._context.lock_counter = 0
+ _LOGGER.debug("Lock %s released on %s", lock_id, lock_filename)
+
+ async def _run_internal_method(self, method: Callable[[], Any]) -> None:
+ if asyncio.iscoroutinefunction(method):
+ await method()
+ elif self.run_in_executor:
+ loop = self.loop or asyncio.get_running_loop()
+ await loop.run_in_executor(self.executor, method)
+ else:
+ method()
+
+ def __enter__(self) -> NoReturn:
+ """
+ Replace old __enter__ method to avoid using it.
+
+ NOTE: DO NOT USE `with` FOR ASYNCIO LOCKS, USE `async with` INSTEAD.
+
+ :return: none
+ :rtype: NoReturn
+ """
+ msg = "Do not use `with` for asyncio locks, use `async with` instead."
+ raise NotImplementedError(msg)
+
+ async def __aenter__(self) -> Self:
+ """
+ Acquire the lock.
+
+ :return: the lock object
+
+ """
+ await self.acquire()
+ return self
+
+ async def __aexit__(
+ self,
+ exc_type: type[BaseException] | None,
+ exc_value: BaseException | None,
+ traceback: TracebackType | None,
+ ) -> None:
+ """
+ Release the lock.
+
+ :param exc_type: the exception type if raised
+ :param exc_value: the exception value if raised
+ :param traceback: the exception traceback if raised
+
+ """
+ await self.release()
+
+ def __del__(self) -> None:
+ """Called when the lock object is deleted."""
+ with contextlib.suppress(RuntimeError):
+ loop = self.loop or asyncio.get_running_loop()
+ if not loop.is_running(): # pragma: no cover
+ loop.run_until_complete(self.release(force=True))
+ else:
+ loop.create_task(self.release(force=True))
+
+
+class AsyncSoftFileLock(SoftFileLock, BaseAsyncFileLock):
+ """Simply watches the existence of the lock file."""
+
+
+class AsyncUnixFileLock(UnixFileLock, BaseAsyncFileLock):
+ """Uses the :func:`fcntl.flock` to hard lock the lock file on unix systems."""
+
+
+class AsyncWindowsFileLock(WindowsFileLock, BaseAsyncFileLock):
+ """Uses the :func:`msvcrt.locking` to hard lock the lock file on windows systems."""
+
+
+__all__ = [
+ "AsyncAcquireReturnProxy",
+ "AsyncSoftFileLock",
+ "AsyncUnixFileLock",
+ "AsyncWindowsFileLock",
+ "BaseAsyncFileLock",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/version.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ef14cbdc1fcdd89aa0d799785c9d1285c9b0c23
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/filelock/version.py
@@ -0,0 +1,16 @@
+# file generated by setuptools_scm
+# don't change, don't track in version control
+TYPE_CHECKING = False
+if TYPE_CHECKING:
+ from typing import Tuple, Union
+ VERSION_TUPLE = Tuple[Union[int, str], ...]
+else:
+ VERSION_TUPLE = object
+
+version: str
+__version__: str
+__version_tuple__: VERSION_TUPLE
+version_tuple: VERSION_TUPLE
+
+__version__ = version = '3.17.0'
+__version_tuple__ = version_tuple = (3, 17, 0)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..3dbeed17babded07352b7334fb4b4463b2791956
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/METADATA
@@ -0,0 +1,273 @@
+Metadata-Version: 2.3
+Name: fsspec
+Version: 2024.5.0
+Summary: File-system specification
+Project-URL: Changelog, https://filesystem-spec.readthedocs.io/en/latest/changelog.html
+Project-URL: Documentation, https://filesystem-spec.readthedocs.io/en/latest/
+Project-URL: Homepage, https://github.com/fsspec/filesystem_spec
+Maintainer-email: Martin Durant
+License: BSD 3-Clause License
+
+ Copyright (c) 2018, Martin Durant
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+ list of conditions and the following disclaimer.
+
+ * Redistributions in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * Neither the name of the copyright holder nor the names of its
+ contributors may be used to endorse or promote products derived from
+ this software without specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+ FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+ DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+ CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+ OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+License-File: LICENSE
+Keywords: file
+Classifier: Development Status :: 4 - Beta
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Requires-Python: >=3.8
+Provides-Extra: abfs
+Requires-Dist: adlfs; extra == 'abfs'
+Provides-Extra: adl
+Requires-Dist: adlfs; extra == 'adl'
+Provides-Extra: arrow
+Requires-Dist: pyarrow>=1; extra == 'arrow'
+Provides-Extra: dask
+Requires-Dist: dask; extra == 'dask'
+Requires-Dist: distributed; extra == 'dask'
+Provides-Extra: dev
+Requires-Dist: pre-commit; extra == 'dev'
+Requires-Dist: ruff; extra == 'dev'
+Provides-Extra: dropbox
+Requires-Dist: dropbox; extra == 'dropbox'
+Requires-Dist: dropboxdrivefs; extra == 'dropbox'
+Requires-Dist: requests; extra == 'dropbox'
+Provides-Extra: entrypoints
+Provides-Extra: full
+Requires-Dist: adlfs; extra == 'full'
+Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'full'
+Requires-Dist: dask; extra == 'full'
+Requires-Dist: distributed; extra == 'full'
+Requires-Dist: dropbox; extra == 'full'
+Requires-Dist: dropboxdrivefs; extra == 'full'
+Requires-Dist: fusepy; extra == 'full'
+Requires-Dist: gcsfs; extra == 'full'
+Requires-Dist: libarchive-c; extra == 'full'
+Requires-Dist: ocifs; extra == 'full'
+Requires-Dist: panel; extra == 'full'
+Requires-Dist: paramiko; extra == 'full'
+Requires-Dist: pyarrow>=1; extra == 'full'
+Requires-Dist: pygit2; extra == 'full'
+Requires-Dist: requests; extra == 'full'
+Requires-Dist: s3fs; extra == 'full'
+Requires-Dist: smbprotocol; extra == 'full'
+Requires-Dist: tqdm; extra == 'full'
+Provides-Extra: fuse
+Requires-Dist: fusepy; extra == 'fuse'
+Provides-Extra: gcs
+Requires-Dist: gcsfs; extra == 'gcs'
+Provides-Extra: git
+Requires-Dist: pygit2; extra == 'git'
+Provides-Extra: github
+Requires-Dist: requests; extra == 'github'
+Provides-Extra: gs
+Requires-Dist: gcsfs; extra == 'gs'
+Provides-Extra: gui
+Requires-Dist: panel; extra == 'gui'
+Provides-Extra: hdfs
+Requires-Dist: pyarrow>=1; extra == 'hdfs'
+Provides-Extra: http
+Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'http'
+Provides-Extra: libarchive
+Requires-Dist: libarchive-c; extra == 'libarchive'
+Provides-Extra: oci
+Requires-Dist: ocifs; extra == 'oci'
+Provides-Extra: s3
+Requires-Dist: s3fs; extra == 's3'
+Provides-Extra: sftp
+Requires-Dist: paramiko; extra == 'sftp'
+Provides-Extra: smb
+Requires-Dist: smbprotocol; extra == 'smb'
+Provides-Extra: ssh
+Requires-Dist: paramiko; extra == 'ssh'
+Provides-Extra: test
+Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'test'
+Requires-Dist: numpy; extra == 'test'
+Requires-Dist: pytest; extra == 'test'
+Requires-Dist: pytest-asyncio!=0.22.0; extra == 'test'
+Requires-Dist: pytest-benchmark; extra == 'test'
+Requires-Dist: pytest-cov; extra == 'test'
+Requires-Dist: pytest-mock; extra == 'test'
+Requires-Dist: pytest-recording; extra == 'test'
+Requires-Dist: pytest-rerunfailures; extra == 'test'
+Requires-Dist: requests; extra == 'test'
+Provides-Extra: test-downstream
+Requires-Dist: aiobotocore<3.0.0,>=2.5.4; extra == 'test-downstream'
+Requires-Dist: dask-expr; extra == 'test-downstream'
+Requires-Dist: dask[dataframe,test]; extra == 'test-downstream'
+Requires-Dist: moto[server]<5,>4; extra == 'test-downstream'
+Requires-Dist: pytest-timeout; extra == 'test-downstream'
+Requires-Dist: xarray; extra == 'test-downstream'
+Provides-Extra: test-full
+Requires-Dist: adlfs; extra == 'test-full'
+Requires-Dist: aiohttp!=4.0.0a0,!=4.0.0a1; extra == 'test-full'
+Requires-Dist: cloudpickle; extra == 'test-full'
+Requires-Dist: dask; extra == 'test-full'
+Requires-Dist: distributed; extra == 'test-full'
+Requires-Dist: dropbox; extra == 'test-full'
+Requires-Dist: dropboxdrivefs; extra == 'test-full'
+Requires-Dist: fastparquet; extra == 'test-full'
+Requires-Dist: fusepy; extra == 'test-full'
+Requires-Dist: gcsfs; extra == 'test-full'
+Requires-Dist: jinja2; extra == 'test-full'
+Requires-Dist: kerchunk; extra == 'test-full'
+Requires-Dist: libarchive-c; extra == 'test-full'
+Requires-Dist: lz4; extra == 'test-full'
+Requires-Dist: notebook; extra == 'test-full'
+Requires-Dist: numpy; extra == 'test-full'
+Requires-Dist: ocifs; extra == 'test-full'
+Requires-Dist: pandas; extra == 'test-full'
+Requires-Dist: panel; extra == 'test-full'
+Requires-Dist: paramiko; extra == 'test-full'
+Requires-Dist: pyarrow; extra == 'test-full'
+Requires-Dist: pyarrow>=1; extra == 'test-full'
+Requires-Dist: pyftpdlib; extra == 'test-full'
+Requires-Dist: pygit2; extra == 'test-full'
+Requires-Dist: pytest; extra == 'test-full'
+Requires-Dist: pytest-asyncio!=0.22.0; extra == 'test-full'
+Requires-Dist: pytest-benchmark; extra == 'test-full'
+Requires-Dist: pytest-cov; extra == 'test-full'
+Requires-Dist: pytest-mock; extra == 'test-full'
+Requires-Dist: pytest-recording; extra == 'test-full'
+Requires-Dist: pytest-rerunfailures; extra == 'test-full'
+Requires-Dist: python-snappy; extra == 'test-full'
+Requires-Dist: requests; extra == 'test-full'
+Requires-Dist: smbprotocol; extra == 'test-full'
+Requires-Dist: tqdm; extra == 'test-full'
+Requires-Dist: urllib3; extra == 'test-full'
+Requires-Dist: zarr; extra == 'test-full'
+Requires-Dist: zstandard; extra == 'test-full'
+Provides-Extra: tqdm
+Requires-Dist: tqdm; extra == 'tqdm'
+Description-Content-Type: text/markdown
+
+# filesystem_spec
+
+[](https://pypi.python.org/pypi/fsspec/)
+[](https://anaconda.org/conda-forge/fsspec)
+
+[](https://filesystem-spec.readthedocs.io/en/latest/?badge=latest)
+[](https://pepy.tech/project/fsspec)
+
+A specification for pythonic filesystems.
+
+## Install
+
+```bash
+pip install fsspec
+```
+
+would install the base fsspec. Various optionally supported features might require specification of custom
+extra require, e.g. `pip install fsspec[ssh]` will install dependencies for `ssh` backends support.
+Use `pip install fsspec[full]` for installation of all known extra dependencies.
+
+Up-to-date package also provided through conda-forge distribution:
+
+```bash
+conda install -c conda-forge fsspec
+```
+
+
+## Purpose
+
+To produce a template or specification for a file-system interface, that specific implementations should follow,
+so that applications making use of them can rely on a common behaviour and not have to worry about the specific
+internal implementation decisions with any given backend. Many such implementations are included in this package,
+or in sister projects such as `s3fs` and `gcsfs`.
+
+In addition, if this is well-designed, then additional functionality, such as a key-value store or FUSE
+mounting of the file-system implementation may be available for all implementations "for free".
+
+## Documentation
+
+Please refer to [RTD](https://filesystem-spec.readthedocs.io/en/latest/?badge=latest)
+
+## Develop
+
+fsspec uses GitHub Actions for CI. Environment files can be found
+in the "ci/" directory. Note that the main environment is called "py38",
+but it is expected that the version of python installed be adjustable at
+CI runtime. For local use, pick a version suitable for you.
+
+```bash
+# For a new environment (mamba / conda).
+mamba create -n fsspec -c conda-forge python=3.9 -y
+conda activate fsspec
+
+# Standard dev test install.
+pip install -e ".[dev,test]"
+
+# Full tests except for downstream
+pip install s3fs
+pip uninstall s3fs
+pip install -e .[dev,test_full]
+pip install s3fs --no-deps
+pytest -v
+
+# Downstream tests.
+sh install_s3fs.sh
+# Windows powershell.
+install_s3fs.sh
+```
+
+### Testing
+
+Tests can be run in the dev environment, if activated, via ``pytest fsspec``.
+
+The full fsspec suite requires a system-level docker, docker-compose, and fuse
+installation. If only making changes to one backend implementation, it is
+not generally necessary to run all tests locally.
+
+It is expected that contributors ensure that any change to fsspec does not
+cause issues or regressions for either other fsspec-related packages such
+as gcsfs and s3fs, nor for downstream users of fsspec. The "downstream" CI
+run and corresponding environment file run a set of tests from the dask
+test suite, and very minimal tests against pandas and zarr from the
+test_downstream.py module in this repo.
+
+### Code Formatting
+
+fsspec uses [Black](https://black.readthedocs.io/en/stable) to ensure
+a consistent code format throughout the project.
+Run ``black fsspec`` from the root of the filesystem_spec repository to
+auto-format your code. Additionally, many editors have plugins that will apply
+``black`` as you edit files. ``black`` is included in the ``tox`` environments.
+
+Optionally, you may wish to setup [pre-commit hooks](https://pre-commit.com) to
+automatically run ``black`` when you make a git commit.
+Run ``pre-commit install --install-hooks`` from the root of the
+filesystem_spec repository to setup pre-commit hooks. ``black`` will now be run
+before you commit, reformatting any changed files. You can format without
+committing via ``pre-commit run`` or skip these checks with ``git commit
+--no-verify``.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..b5695e12a08fc881dac7659ce4aa7474369de8ac
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/RECORD
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/REQUESTED b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/REQUESTED
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..516596c76787b10928cbab24f22c0ea00433b15d
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/fsspec-2024.5.0.dist-info/WHEEL
@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: hatchling 1.24.2
+Root-Is-Purelib: true
+Tag: py3-none-any
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..989e92c3458681a6f0be72ae4105ea742750d328
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/__init__.py
@@ -0,0 +1,62 @@
+# A highish-level implementation of the HTTP/1.1 wire protocol (RFC 7230),
+# containing no networking code at all, loosely modelled on hyper-h2's generic
+# implementation of HTTP/2 (and in particular the h2.connection.H2Connection
+# class). There's still a bunch of subtle details you need to get right if you
+# want to make this actually useful, because it doesn't implement all the
+# semantics to check that what you're asking to write to the wire is sensible,
+# but at least it gets you out of dealing with the wire itself.
+
+from h11._connection import Connection, NEED_DATA, PAUSED
+from h11._events import (
+ ConnectionClosed,
+ Data,
+ EndOfMessage,
+ Event,
+ InformationalResponse,
+ Request,
+ Response,
+)
+from h11._state import (
+ CLIENT,
+ CLOSED,
+ DONE,
+ ERROR,
+ IDLE,
+ MIGHT_SWITCH_PROTOCOL,
+ MUST_CLOSE,
+ SEND_BODY,
+ SEND_RESPONSE,
+ SERVER,
+ SWITCHED_PROTOCOL,
+)
+from h11._util import LocalProtocolError, ProtocolError, RemoteProtocolError
+from h11._version import __version__
+
+PRODUCT_ID = "python-h11/" + __version__
+
+
+__all__ = (
+ "Connection",
+ "NEED_DATA",
+ "PAUSED",
+ "ConnectionClosed",
+ "Data",
+ "EndOfMessage",
+ "Event",
+ "InformationalResponse",
+ "Request",
+ "Response",
+ "CLIENT",
+ "CLOSED",
+ "DONE",
+ "ERROR",
+ "IDLE",
+ "MUST_CLOSE",
+ "SEND_BODY",
+ "SEND_RESPONSE",
+ "SERVER",
+ "SWITCHED_PROTOCOL",
+ "ProtocolError",
+ "LocalProtocolError",
+ "RemoteProtocolError",
+)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_abnf.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_abnf.py
new file mode 100644
index 0000000000000000000000000000000000000000..933587fba22290d7eb7df4c88e12f1e61702b8ce
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_abnf.py
@@ -0,0 +1,132 @@
+# We use native strings for all the re patterns, to take advantage of string
+# formatting, and then convert to bytestrings when compiling the final re
+# objects.
+
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#whitespace
+# OWS = *( SP / HTAB )
+# ; optional whitespace
+OWS = r"[ \t]*"
+
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#rule.token.separators
+# token = 1*tchar
+#
+# tchar = "!" / "#" / "$" / "%" / "&" / "'" / "*"
+# / "+" / "-" / "." / "^" / "_" / "`" / "|" / "~"
+# / DIGIT / ALPHA
+# ; any VCHAR, except delimiters
+token = r"[-!#$%&'*+.^_`|~0-9a-zA-Z]+"
+
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#header.fields
+# field-name = token
+field_name = token
+
+# The standard says:
+#
+# field-value = *( field-content / obs-fold )
+# field-content = field-vchar [ 1*( SP / HTAB ) field-vchar ]
+# field-vchar = VCHAR / obs-text
+# obs-fold = CRLF 1*( SP / HTAB )
+# ; obsolete line folding
+# ; see Section 3.2.4
+#
+# https://tools.ietf.org/html/rfc5234#appendix-B.1
+#
+# VCHAR = %x21-7E
+# ; visible (printing) characters
+#
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#rule.quoted-string
+# obs-text = %x80-FF
+#
+# However, the standard definition of field-content is WRONG! It disallows
+# fields containing a single visible character surrounded by whitespace,
+# e.g. "foo a bar".
+#
+# See: https://www.rfc-editor.org/errata_search.php?rfc=7230&eid=4189
+#
+# So our definition of field_content attempts to fix it up...
+#
+# Also, we allow lots of control characters, because apparently people assume
+# that they're legal in practice (e.g., google analytics makes cookies with
+# \x01 in them!):
+# https://github.com/python-hyper/h11/issues/57
+# We still don't allow NUL or whitespace, because those are often treated as
+# meta-characters and letting them through can lead to nasty issues like SSRF.
+vchar = r"[\x21-\x7e]"
+vchar_or_obs_text = r"[^\x00\s]"
+field_vchar = vchar_or_obs_text
+field_content = r"{field_vchar}+(?:[ \t]+{field_vchar}+)*".format(**globals())
+
+# We handle obs-fold at a different level, and our fixed-up field_content
+# already grows to swallow the whole value, so ? instead of *
+field_value = r"({field_content})?".format(**globals())
+
+# header-field = field-name ":" OWS field-value OWS
+header_field = (
+ r"(?P{field_name})"
+ r":"
+ r"{OWS}"
+ r"(?P{field_value})"
+ r"{OWS}".format(**globals())
+)
+
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#request.line
+#
+# request-line = method SP request-target SP HTTP-version CRLF
+# method = token
+# HTTP-version = HTTP-name "/" DIGIT "." DIGIT
+# HTTP-name = %x48.54.54.50 ; "HTTP", case-sensitive
+#
+# request-target is complicated (see RFC 7230 sec 5.3) -- could be path, full
+# URL, host+port (for connect), or even "*", but in any case we are guaranteed
+# that it contists of the visible printing characters.
+method = token
+request_target = r"{vchar}+".format(**globals())
+http_version = r"HTTP/(?P[0-9]\.[0-9])"
+request_line = (
+ r"(?P{method})"
+ r" "
+ r"(?P{request_target})"
+ r" "
+ r"{http_version}".format(**globals())
+)
+
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#status.line
+#
+# status-line = HTTP-version SP status-code SP reason-phrase CRLF
+# status-code = 3DIGIT
+# reason-phrase = *( HTAB / SP / VCHAR / obs-text )
+status_code = r"[0-9]{3}"
+reason_phrase = r"([ \t]|{vchar_or_obs_text})*".format(**globals())
+status_line = (
+ r"{http_version}"
+ r" "
+ r"(?P{status_code})"
+ # However, there are apparently a few too many servers out there that just
+ # leave out the reason phrase:
+ # https://github.com/scrapy/scrapy/issues/345#issuecomment-281756036
+ # https://github.com/seanmonstar/httparse/issues/29
+ # so make it optional. ?: is a non-capturing group.
+ r"(?: (?P{reason_phrase}))?".format(**globals())
+)
+
+HEXDIG = r"[0-9A-Fa-f]"
+# Actually
+#
+# chunk-size = 1*HEXDIG
+#
+# but we impose an upper-limit to avoid ridiculosity. len(str(2**64)) == 20
+chunk_size = r"({HEXDIG}){{1,20}}".format(**globals())
+# Actually
+#
+# chunk-ext = *( ";" chunk-ext-name [ "=" chunk-ext-val ] )
+#
+# but we aren't parsing the things so we don't really care.
+chunk_ext = r";.*"
+chunk_header = (
+ r"(?P{chunk_size})"
+ r"(?P{chunk_ext})?"
+ r"{OWS}\r\n".format(
+ **globals()
+ ) # Even though the specification does not allow for extra whitespaces,
+ # we are lenient with trailing whitespaces because some servers on the wild use it.
+)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_connection.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_connection.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1752707598154d190d69b2c26f3098b74656652
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_connection.py
@@ -0,0 +1,633 @@
+# This contains the main Connection class. Everything in h11 revolves around
+# this.
+from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Type, Union
+
+from ._events import (
+ ConnectionClosed,
+ Data,
+ EndOfMessage,
+ Event,
+ InformationalResponse,
+ Request,
+ Response,
+)
+from ._headers import get_comma_header, has_expect_100_continue, set_comma_header
+from ._readers import READERS, ReadersType
+from ._receivebuffer import ReceiveBuffer
+from ._state import (
+ _SWITCH_CONNECT,
+ _SWITCH_UPGRADE,
+ CLIENT,
+ ConnectionState,
+ DONE,
+ ERROR,
+ MIGHT_SWITCH_PROTOCOL,
+ SEND_BODY,
+ SERVER,
+ SWITCHED_PROTOCOL,
+)
+from ._util import ( # Import the internal things we need
+ LocalProtocolError,
+ RemoteProtocolError,
+ Sentinel,
+)
+from ._writers import WRITERS, WritersType
+
+# Everything in __all__ gets re-exported as part of the h11 public API.
+__all__ = ["Connection", "NEED_DATA", "PAUSED"]
+
+
+class NEED_DATA(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class PAUSED(Sentinel, metaclass=Sentinel):
+ pass
+
+
+# If we ever have this much buffered without it making a complete parseable
+# event, we error out. The only time we really buffer is when reading the
+# request/response line + headers together, so this is effectively the limit on
+# the size of that.
+#
+# Some precedents for defaults:
+# - node.js: 80 * 1024
+# - tomcat: 8 * 1024
+# - IIS: 16 * 1024
+# - Apache: <8 KiB per line>
+DEFAULT_MAX_INCOMPLETE_EVENT_SIZE = 16 * 1024
+
+# RFC 7230's rules for connection lifecycles:
+# - If either side says they want to close the connection, then the connection
+# must close.
+# - HTTP/1.1 defaults to keep-alive unless someone says Connection: close
+# - HTTP/1.0 defaults to close unless both sides say Connection: keep-alive
+# (and even this is a mess -- e.g. if you're implementing a proxy then
+# sending Connection: keep-alive is forbidden).
+#
+# We simplify life by simply not supporting keep-alive with HTTP/1.0 peers. So
+# our rule is:
+# - If someone says Connection: close, we will close
+# - If someone uses HTTP/1.0, we will close.
+def _keep_alive(event: Union[Request, Response]) -> bool:
+ connection = get_comma_header(event.headers, b"connection")
+ if b"close" in connection:
+ return False
+ if getattr(event, "http_version", b"1.1") < b"1.1":
+ return False
+ return True
+
+
+def _body_framing(
+ request_method: bytes, event: Union[Request, Response]
+) -> Tuple[str, Union[Tuple[()], Tuple[int]]]:
+ # Called when we enter SEND_BODY to figure out framing information for
+ # this body.
+ #
+ # These are the only two events that can trigger a SEND_BODY state:
+ assert type(event) in (Request, Response)
+ # Returns one of:
+ #
+ # ("content-length", count)
+ # ("chunked", ())
+ # ("http/1.0", ())
+ #
+ # which are (lookup key, *args) for constructing body reader/writer
+ # objects.
+ #
+ # Reference: https://tools.ietf.org/html/rfc7230#section-3.3.3
+ #
+ # Step 1: some responses always have an empty body, regardless of what the
+ # headers say.
+ if type(event) is Response:
+ if (
+ event.status_code in (204, 304)
+ or request_method == b"HEAD"
+ or (request_method == b"CONNECT" and 200 <= event.status_code < 300)
+ ):
+ return ("content-length", (0,))
+ # Section 3.3.3 also lists another case -- responses with status_code
+ # < 200. For us these are InformationalResponses, not Responses, so
+ # they can't get into this function in the first place.
+ assert event.status_code >= 200
+
+ # Step 2: check for Transfer-Encoding (T-E beats C-L):
+ transfer_encodings = get_comma_header(event.headers, b"transfer-encoding")
+ if transfer_encodings:
+ assert transfer_encodings == [b"chunked"]
+ return ("chunked", ())
+
+ # Step 3: check for Content-Length
+ content_lengths = get_comma_header(event.headers, b"content-length")
+ if content_lengths:
+ return ("content-length", (int(content_lengths[0]),))
+
+ # Step 4: no applicable headers; fallback/default depends on type
+ if type(event) is Request:
+ return ("content-length", (0,))
+ else:
+ return ("http/1.0", ())
+
+
+################################################################
+#
+# The main Connection class
+#
+################################################################
+
+
+class Connection:
+ """An object encapsulating the state of an HTTP connection.
+
+ Args:
+ our_role: If you're implementing a client, pass :data:`h11.CLIENT`. If
+ you're implementing a server, pass :data:`h11.SERVER`.
+
+ max_incomplete_event_size (int):
+ The maximum number of bytes we're willing to buffer of an
+ incomplete event. In practice this mostly sets a limit on the
+ maximum size of the request/response line + headers. If this is
+ exceeded, then :meth:`next_event` will raise
+ :exc:`RemoteProtocolError`.
+
+ """
+
+ def __init__(
+ self,
+ our_role: Type[Sentinel],
+ max_incomplete_event_size: int = DEFAULT_MAX_INCOMPLETE_EVENT_SIZE,
+ ) -> None:
+ self._max_incomplete_event_size = max_incomplete_event_size
+ # State and role tracking
+ if our_role not in (CLIENT, SERVER):
+ raise ValueError("expected CLIENT or SERVER, not {!r}".format(our_role))
+ self.our_role = our_role
+ self.their_role: Type[Sentinel]
+ if our_role is CLIENT:
+ self.their_role = SERVER
+ else:
+ self.their_role = CLIENT
+ self._cstate = ConnectionState()
+
+ # Callables for converting data->events or vice-versa given the
+ # current state
+ self._writer = self._get_io_object(self.our_role, None, WRITERS)
+ self._reader = self._get_io_object(self.their_role, None, READERS)
+
+ # Holds any unprocessed received data
+ self._receive_buffer = ReceiveBuffer()
+ # If this is true, then it indicates that the incoming connection was
+ # closed *after* the end of whatever's in self._receive_buffer:
+ self._receive_buffer_closed = False
+
+ # Extra bits of state that don't fit into the state machine.
+ #
+ # These two are only used to interpret framing headers for figuring
+ # out how to read/write response bodies. their_http_version is also
+ # made available as a convenient public API.
+ self.their_http_version: Optional[bytes] = None
+ self._request_method: Optional[bytes] = None
+ # This is pure flow-control and doesn't at all affect the set of legal
+ # transitions, so no need to bother ConnectionState with it:
+ self.client_is_waiting_for_100_continue = False
+
+ @property
+ def states(self) -> Dict[Type[Sentinel], Type[Sentinel]]:
+ """A dictionary like::
+
+ {CLIENT: , SERVER: }
+
+ See :ref:`state-machine` for details.
+
+ """
+ return dict(self._cstate.states)
+
+ @property
+ def our_state(self) -> Type[Sentinel]:
+ """The current state of whichever role we are playing. See
+ :ref:`state-machine` for details.
+ """
+ return self._cstate.states[self.our_role]
+
+ @property
+ def their_state(self) -> Type[Sentinel]:
+ """The current state of whichever role we are NOT playing. See
+ :ref:`state-machine` for details.
+ """
+ return self._cstate.states[self.their_role]
+
+ @property
+ def they_are_waiting_for_100_continue(self) -> bool:
+ return self.their_role is CLIENT and self.client_is_waiting_for_100_continue
+
+ def start_next_cycle(self) -> None:
+ """Attempt to reset our connection state for a new request/response
+ cycle.
+
+ If both client and server are in :data:`DONE` state, then resets them
+ both to :data:`IDLE` state in preparation for a new request/response
+ cycle on this same connection. Otherwise, raises a
+ :exc:`LocalProtocolError`.
+
+ See :ref:`keepalive-and-pipelining`.
+
+ """
+ old_states = dict(self._cstate.states)
+ self._cstate.start_next_cycle()
+ self._request_method = None
+ # self.their_http_version gets left alone, since it presumably lasts
+ # beyond a single request/response cycle
+ assert not self.client_is_waiting_for_100_continue
+ self._respond_to_state_changes(old_states)
+
+ def _process_error(self, role: Type[Sentinel]) -> None:
+ old_states = dict(self._cstate.states)
+ self._cstate.process_error(role)
+ self._respond_to_state_changes(old_states)
+
+ def _server_switch_event(self, event: Event) -> Optional[Type[Sentinel]]:
+ if type(event) is InformationalResponse and event.status_code == 101:
+ return _SWITCH_UPGRADE
+ if type(event) is Response:
+ if (
+ _SWITCH_CONNECT in self._cstate.pending_switch_proposals
+ and 200 <= event.status_code < 300
+ ):
+ return _SWITCH_CONNECT
+ return None
+
+ # All events go through here
+ def _process_event(self, role: Type[Sentinel], event: Event) -> None:
+ # First, pass the event through the state machine to make sure it
+ # succeeds.
+ old_states = dict(self._cstate.states)
+ if role is CLIENT and type(event) is Request:
+ if event.method == b"CONNECT":
+ self._cstate.process_client_switch_proposal(_SWITCH_CONNECT)
+ if get_comma_header(event.headers, b"upgrade"):
+ self._cstate.process_client_switch_proposal(_SWITCH_UPGRADE)
+ server_switch_event = None
+ if role is SERVER:
+ server_switch_event = self._server_switch_event(event)
+ self._cstate.process_event(role, type(event), server_switch_event)
+
+ # Then perform the updates triggered by it.
+
+ if type(event) is Request:
+ self._request_method = event.method
+
+ if role is self.their_role and type(event) in (
+ Request,
+ Response,
+ InformationalResponse,
+ ):
+ event = cast(Union[Request, Response, InformationalResponse], event)
+ self.their_http_version = event.http_version
+
+ # Keep alive handling
+ #
+ # RFC 7230 doesn't really say what one should do if Connection: close
+ # shows up on a 1xx InformationalResponse. I think the idea is that
+ # this is not supposed to happen. In any case, if it does happen, we
+ # ignore it.
+ if type(event) in (Request, Response) and not _keep_alive(
+ cast(Union[Request, Response], event)
+ ):
+ self._cstate.process_keep_alive_disabled()
+
+ # 100-continue
+ if type(event) is Request and has_expect_100_continue(event):
+ self.client_is_waiting_for_100_continue = True
+ if type(event) in (InformationalResponse, Response):
+ self.client_is_waiting_for_100_continue = False
+ if role is CLIENT and type(event) in (Data, EndOfMessage):
+ self.client_is_waiting_for_100_continue = False
+
+ self._respond_to_state_changes(old_states, event)
+
+ def _get_io_object(
+ self,
+ role: Type[Sentinel],
+ event: Optional[Event],
+ io_dict: Union[ReadersType, WritersType],
+ ) -> Optional[Callable[..., Any]]:
+ # event may be None; it's only used when entering SEND_BODY
+ state = self._cstate.states[role]
+ if state is SEND_BODY:
+ # Special case: the io_dict has a dict of reader/writer factories
+ # that depend on the request/response framing.
+ framing_type, args = _body_framing(
+ cast(bytes, self._request_method), cast(Union[Request, Response], event)
+ )
+ return io_dict[SEND_BODY][framing_type](*args) # type: ignore[index]
+ else:
+ # General case: the io_dict just has the appropriate reader/writer
+ # for this state
+ return io_dict.get((role, state)) # type: ignore[return-value]
+
+ # This must be called after any action that might have caused
+ # self._cstate.states to change.
+ def _respond_to_state_changes(
+ self,
+ old_states: Dict[Type[Sentinel], Type[Sentinel]],
+ event: Optional[Event] = None,
+ ) -> None:
+ # Update reader/writer
+ if self.our_state != old_states[self.our_role]:
+ self._writer = self._get_io_object(self.our_role, event, WRITERS)
+ if self.their_state != old_states[self.their_role]:
+ self._reader = self._get_io_object(self.their_role, event, READERS)
+
+ @property
+ def trailing_data(self) -> Tuple[bytes, bool]:
+ """Data that has been received, but not yet processed, represented as
+ a tuple with two elements, where the first is a byte-string containing
+ the unprocessed data itself, and the second is a bool that is True if
+ the receive connection was closed.
+
+ See :ref:`switching-protocols` for discussion of why you'd want this.
+ """
+ return (bytes(self._receive_buffer), self._receive_buffer_closed)
+
+ def receive_data(self, data: bytes) -> None:
+ """Add data to our internal receive buffer.
+
+ This does not actually do any processing on the data, just stores
+ it. To trigger processing, you have to call :meth:`next_event`.
+
+ Args:
+ data (:term:`bytes-like object`):
+ The new data that was just received.
+
+ Special case: If *data* is an empty byte-string like ``b""``,
+ then this indicates that the remote side has closed the
+ connection (end of file). Normally this is convenient, because
+ standard Python APIs like :meth:`file.read` or
+ :meth:`socket.recv` use ``b""`` to indicate end-of-file, while
+ other failures to read are indicated using other mechanisms
+ like raising :exc:`TimeoutError`. When using such an API you
+ can just blindly pass through whatever you get from ``read``
+ to :meth:`receive_data`, and everything will work.
+
+ But, if you have an API where reading an empty string is a
+ valid non-EOF condition, then you need to be aware of this and
+ make sure to check for such strings and avoid passing them to
+ :meth:`receive_data`.
+
+ Returns:
+ Nothing, but after calling this you should call :meth:`next_event`
+ to parse the newly received data.
+
+ Raises:
+ RuntimeError:
+ Raised if you pass an empty *data*, indicating EOF, and then
+ pass a non-empty *data*, indicating more data that somehow
+ arrived after the EOF.
+
+ (Calling ``receive_data(b"")`` multiple times is fine,
+ and equivalent to calling it once.)
+
+ """
+ if data:
+ if self._receive_buffer_closed:
+ raise RuntimeError("received close, then received more data?")
+ self._receive_buffer += data
+ else:
+ self._receive_buffer_closed = True
+
+ def _extract_next_receive_event(
+ self,
+ ) -> Union[Event, Type[NEED_DATA], Type[PAUSED]]:
+ state = self.their_state
+ # We don't pause immediately when they enter DONE, because even in
+ # DONE state we can still process a ConnectionClosed() event. But
+ # if we have data in our buffer, then we definitely aren't getting
+ # a ConnectionClosed() immediately and we need to pause.
+ if state is DONE and self._receive_buffer:
+ return PAUSED
+ if state is MIGHT_SWITCH_PROTOCOL or state is SWITCHED_PROTOCOL:
+ return PAUSED
+ assert self._reader is not None
+ event = self._reader(self._receive_buffer)
+ if event is None:
+ if not self._receive_buffer and self._receive_buffer_closed:
+ # In some unusual cases (basically just HTTP/1.0 bodies), EOF
+ # triggers an actual protocol event; in that case, we want to
+ # return that event, and then the state will change and we'll
+ # get called again to generate the actual ConnectionClosed().
+ if hasattr(self._reader, "read_eof"):
+ event = self._reader.read_eof() # type: ignore[attr-defined]
+ else:
+ event = ConnectionClosed()
+ if event is None:
+ event = NEED_DATA
+ return event # type: ignore[no-any-return]
+
+ def next_event(self) -> Union[Event, Type[NEED_DATA], Type[PAUSED]]:
+ """Parse the next event out of our receive buffer, update our internal
+ state, and return it.
+
+ This is a mutating operation -- think of it like calling :func:`next`
+ on an iterator.
+
+ Returns:
+ : One of three things:
+
+ 1) An event object -- see :ref:`events`.
+
+ 2) The special constant :data:`NEED_DATA`, which indicates that
+ you need to read more data from your socket and pass it to
+ :meth:`receive_data` before this method will be able to return
+ any more events.
+
+ 3) The special constant :data:`PAUSED`, which indicates that we
+ are not in a state where we can process incoming data (usually
+ because the peer has finished their part of the current
+ request/response cycle, and you have not yet called
+ :meth:`start_next_cycle`). See :ref:`flow-control` for details.
+
+ Raises:
+ RemoteProtocolError:
+ The peer has misbehaved. You should close the connection
+ (possibly after sending some kind of 4xx response).
+
+ Once this method returns :class:`ConnectionClosed` once, then all
+ subsequent calls will also return :class:`ConnectionClosed`.
+
+ If this method raises any exception besides :exc:`RemoteProtocolError`
+ then that's a bug -- if it happens please file a bug report!
+
+ If this method raises any exception then it also sets
+ :attr:`Connection.their_state` to :data:`ERROR` -- see
+ :ref:`error-handling` for discussion.
+
+ """
+
+ if self.their_state is ERROR:
+ raise RemoteProtocolError("Can't receive data when peer state is ERROR")
+ try:
+ event = self._extract_next_receive_event()
+ if event not in [NEED_DATA, PAUSED]:
+ self._process_event(self.their_role, cast(Event, event))
+ if event is NEED_DATA:
+ if len(self._receive_buffer) > self._max_incomplete_event_size:
+ # 431 is "Request header fields too large" which is pretty
+ # much the only situation where we can get here
+ raise RemoteProtocolError(
+ "Receive buffer too long", error_status_hint=431
+ )
+ if self._receive_buffer_closed:
+ # We're still trying to complete some event, but that's
+ # never going to happen because no more data is coming
+ raise RemoteProtocolError("peer unexpectedly closed connection")
+ return event
+ except BaseException as exc:
+ self._process_error(self.their_role)
+ if isinstance(exc, LocalProtocolError):
+ exc._reraise_as_remote_protocol_error()
+ else:
+ raise
+
+ def send(self, event: Event) -> Optional[bytes]:
+ """Convert a high-level event into bytes that can be sent to the peer,
+ while updating our internal state machine.
+
+ Args:
+ event: The :ref:`event ` to send.
+
+ Returns:
+ If ``type(event) is ConnectionClosed``, then returns
+ ``None``. Otherwise, returns a :term:`bytes-like object`.
+
+ Raises:
+ LocalProtocolError:
+ Sending this event at this time would violate our
+ understanding of the HTTP/1.1 protocol.
+
+ If this method raises any exception then it also sets
+ :attr:`Connection.our_state` to :data:`ERROR` -- see
+ :ref:`error-handling` for discussion.
+
+ """
+ data_list = self.send_with_data_passthrough(event)
+ if data_list is None:
+ return None
+ else:
+ return b"".join(data_list)
+
+ def send_with_data_passthrough(self, event: Event) -> Optional[List[bytes]]:
+ """Identical to :meth:`send`, except that in situations where
+ :meth:`send` returns a single :term:`bytes-like object`, this instead
+ returns a list of them -- and when sending a :class:`Data` event, this
+ list is guaranteed to contain the exact object you passed in as
+ :attr:`Data.data`. See :ref:`sendfile` for discussion.
+
+ """
+ if self.our_state is ERROR:
+ raise LocalProtocolError("Can't send data when our state is ERROR")
+ try:
+ if type(event) is Response:
+ event = self._clean_up_response_headers_for_sending(event)
+ # We want to call _process_event before calling the writer,
+ # because if someone tries to do something invalid then this will
+ # give a sensible error message, while our writers all just assume
+ # they will only receive valid events. But, _process_event might
+ # change self._writer. So we have to do a little dance:
+ writer = self._writer
+ self._process_event(self.our_role, event)
+ if type(event) is ConnectionClosed:
+ return None
+ else:
+ # In any situation where writer is None, process_event should
+ # have raised ProtocolError
+ assert writer is not None
+ data_list: List[bytes] = []
+ writer(event, data_list.append)
+ return data_list
+ except:
+ self._process_error(self.our_role)
+ raise
+
+ def send_failed(self) -> None:
+ """Notify the state machine that we failed to send the data it gave
+ us.
+
+ This causes :attr:`Connection.our_state` to immediately become
+ :data:`ERROR` -- see :ref:`error-handling` for discussion.
+
+ """
+ self._process_error(self.our_role)
+
+ # When sending a Response, we take responsibility for a few things:
+ #
+ # - Sometimes you MUST set Connection: close. We take care of those
+ # times. (You can also set it yourself if you want, and if you do then
+ # we'll respect that and close the connection at the right time. But you
+ # don't have to worry about that unless you want to.)
+ #
+ # - The user has to set Content-Length if they want it. Otherwise, for
+ # responses that have bodies (e.g. not HEAD), then we will automatically
+ # select the right mechanism for streaming a body of unknown length,
+ # which depends on depending on the peer's HTTP version.
+ #
+ # This function's *only* responsibility is making sure headers are set up
+ # right -- everything downstream just looks at the headers. There are no
+ # side channels.
+ def _clean_up_response_headers_for_sending(self, response: Response) -> Response:
+ assert type(response) is Response
+
+ headers = response.headers
+ need_close = False
+
+ # HEAD requests need some special handling: they always act like they
+ # have Content-Length: 0, and that's how _body_framing treats
+ # them. But their headers are supposed to match what we would send if
+ # the request was a GET. (Technically there is one deviation allowed:
+ # we're allowed to leave out the framing headers -- see
+ # https://tools.ietf.org/html/rfc7231#section-4.3.2 . But it's just as
+ # easy to get them right.)
+ method_for_choosing_headers = cast(bytes, self._request_method)
+ if method_for_choosing_headers == b"HEAD":
+ method_for_choosing_headers = b"GET"
+ framing_type, _ = _body_framing(method_for_choosing_headers, response)
+ if framing_type in ("chunked", "http/1.0"):
+ # This response has a body of unknown length.
+ # If our peer is HTTP/1.1, we use Transfer-Encoding: chunked
+ # If our peer is HTTP/1.0, we use no framing headers, and close the
+ # connection afterwards.
+ #
+ # Make sure to clear Content-Length (in principle user could have
+ # set both and then we ignored Content-Length b/c
+ # Transfer-Encoding overwrote it -- this would be naughty of them,
+ # but the HTTP spec says that if our peer does this then we have
+ # to fix it instead of erroring out, so we'll accord the user the
+ # same respect).
+ headers = set_comma_header(headers, b"content-length", [])
+ if self.their_http_version is None or self.their_http_version < b"1.1":
+ # Either we never got a valid request and are sending back an
+ # error (their_http_version is None), so we assume the worst;
+ # or else we did get a valid HTTP/1.0 request, so we know that
+ # they don't understand chunked encoding.
+ headers = set_comma_header(headers, b"transfer-encoding", [])
+ # This is actually redundant ATM, since currently we
+ # unconditionally disable keep-alive when talking to HTTP/1.0
+ # peers. But let's be defensive just in case we add
+ # Connection: keep-alive support later:
+ if self._request_method != b"HEAD":
+ need_close = True
+ else:
+ headers = set_comma_header(headers, b"transfer-encoding", [b"chunked"])
+
+ if not self._cstate.keep_alive or need_close:
+ # Make sure Connection: close is set
+ connection = set(get_comma_header(headers, b"connection"))
+ connection.discard(b"keep-alive")
+ connection.add(b"close")
+ headers = set_comma_header(headers, b"connection", sorted(connection))
+
+ return Response(
+ headers=headers,
+ status_code=response.status_code,
+ http_version=response.http_version,
+ reason=response.reason,
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_events.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_events.py
new file mode 100644
index 0000000000000000000000000000000000000000..075bf8a469d44d2388b08ec3d009fe55d44cb6eb
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_events.py
@@ -0,0 +1,369 @@
+# High level events that make up HTTP/1.1 conversations. Loosely inspired by
+# the corresponding events in hyper-h2:
+#
+# http://python-hyper.org/h2/en/stable/api.html#events
+#
+# Don't subclass these. Stuff will break.
+
+import re
+from abc import ABC
+from dataclasses import dataclass, field
+from typing import Any, cast, Dict, List, Tuple, Union
+
+from ._abnf import method, request_target
+from ._headers import Headers, normalize_and_validate
+from ._util import bytesify, LocalProtocolError, validate
+
+# Everything in __all__ gets re-exported as part of the h11 public API.
+__all__ = [
+ "Event",
+ "Request",
+ "InformationalResponse",
+ "Response",
+ "Data",
+ "EndOfMessage",
+ "ConnectionClosed",
+]
+
+method_re = re.compile(method.encode("ascii"))
+request_target_re = re.compile(request_target.encode("ascii"))
+
+
+class Event(ABC):
+ """
+ Base class for h11 events.
+ """
+
+ __slots__ = ()
+
+
+@dataclass(init=False, frozen=True)
+class Request(Event):
+ """The beginning of an HTTP request.
+
+ Fields:
+
+ .. attribute:: method
+
+ An HTTP method, e.g. ``b"GET"`` or ``b"POST"``. Always a byte
+ string. :term:`Bytes-like objects ` and native
+ strings containing only ascii characters will be automatically
+ converted to byte strings.
+
+ .. attribute:: target
+
+ The target of an HTTP request, e.g. ``b"/index.html"``, or one of the
+ more exotic formats described in `RFC 7320, section 5.3
+ `_. Always a byte
+ string. :term:`Bytes-like objects ` and native
+ strings containing only ascii characters will be automatically
+ converted to byte strings.
+
+ .. attribute:: headers
+
+ Request headers, represented as a list of (name, value) pairs. See
+ :ref:`the header normalization rules ` for details.
+
+ .. attribute:: http_version
+
+ The HTTP protocol version, represented as a byte string like
+ ``b"1.1"``. See :ref:`the HTTP version normalization rules
+ ` for details.
+
+ """
+
+ __slots__ = ("method", "headers", "target", "http_version")
+
+ method: bytes
+ headers: Headers
+ target: bytes
+ http_version: bytes
+
+ def __init__(
+ self,
+ *,
+ method: Union[bytes, str],
+ headers: Union[Headers, List[Tuple[bytes, bytes]], List[Tuple[str, str]]],
+ target: Union[bytes, str],
+ http_version: Union[bytes, str] = b"1.1",
+ _parsed: bool = False,
+ ) -> None:
+ super().__init__()
+ if isinstance(headers, Headers):
+ object.__setattr__(self, "headers", headers)
+ else:
+ object.__setattr__(
+ self, "headers", normalize_and_validate(headers, _parsed=_parsed)
+ )
+ if not _parsed:
+ object.__setattr__(self, "method", bytesify(method))
+ object.__setattr__(self, "target", bytesify(target))
+ object.__setattr__(self, "http_version", bytesify(http_version))
+ else:
+ object.__setattr__(self, "method", method)
+ object.__setattr__(self, "target", target)
+ object.__setattr__(self, "http_version", http_version)
+
+ # "A server MUST respond with a 400 (Bad Request) status code to any
+ # HTTP/1.1 request message that lacks a Host header field and to any
+ # request message that contains more than one Host header field or a
+ # Host header field with an invalid field-value."
+ # -- https://tools.ietf.org/html/rfc7230#section-5.4
+ host_count = 0
+ for name, value in self.headers:
+ if name == b"host":
+ host_count += 1
+ if self.http_version == b"1.1" and host_count == 0:
+ raise LocalProtocolError("Missing mandatory Host: header")
+ if host_count > 1:
+ raise LocalProtocolError("Found multiple Host: headers")
+
+ validate(method_re, self.method, "Illegal method characters")
+ validate(request_target_re, self.target, "Illegal target characters")
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+@dataclass(init=False, frozen=True)
+class _ResponseBase(Event):
+ __slots__ = ("headers", "http_version", "reason", "status_code")
+
+ headers: Headers
+ http_version: bytes
+ reason: bytes
+ status_code: int
+
+ def __init__(
+ self,
+ *,
+ headers: Union[Headers, List[Tuple[bytes, bytes]], List[Tuple[str, str]]],
+ status_code: int,
+ http_version: Union[bytes, str] = b"1.1",
+ reason: Union[bytes, str] = b"",
+ _parsed: bool = False,
+ ) -> None:
+ super().__init__()
+ if isinstance(headers, Headers):
+ object.__setattr__(self, "headers", headers)
+ else:
+ object.__setattr__(
+ self, "headers", normalize_and_validate(headers, _parsed=_parsed)
+ )
+ if not _parsed:
+ object.__setattr__(self, "reason", bytesify(reason))
+ object.__setattr__(self, "http_version", bytesify(http_version))
+ if not isinstance(status_code, int):
+ raise LocalProtocolError("status code must be integer")
+ # Because IntEnum objects are instances of int, but aren't
+ # duck-compatible (sigh), see gh-72.
+ object.__setattr__(self, "status_code", int(status_code))
+ else:
+ object.__setattr__(self, "reason", reason)
+ object.__setattr__(self, "http_version", http_version)
+ object.__setattr__(self, "status_code", status_code)
+
+ self.__post_init__()
+
+ def __post_init__(self) -> None:
+ pass
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+@dataclass(init=False, frozen=True)
+class InformationalResponse(_ResponseBase):
+ """An HTTP informational response.
+
+ Fields:
+
+ .. attribute:: status_code
+
+ The status code of this response, as an integer. For an
+ :class:`InformationalResponse`, this is always in the range [100,
+ 200).
+
+ .. attribute:: headers
+
+ Request headers, represented as a list of (name, value) pairs. See
+ :ref:`the header normalization rules ` for
+ details.
+
+ .. attribute:: http_version
+
+ The HTTP protocol version, represented as a byte string like
+ ``b"1.1"``. See :ref:`the HTTP version normalization rules
+ ` for details.
+
+ .. attribute:: reason
+
+ The reason phrase of this response, as a byte string. For example:
+ ``b"OK"``, or ``b"Not Found"``.
+
+ """
+
+ def __post_init__(self) -> None:
+ if not (100 <= self.status_code < 200):
+ raise LocalProtocolError(
+ "InformationalResponse status_code should be in range "
+ "[100, 200), not {}".format(self.status_code)
+ )
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+@dataclass(init=False, frozen=True)
+class Response(_ResponseBase):
+ """The beginning of an HTTP response.
+
+ Fields:
+
+ .. attribute:: status_code
+
+ The status code of this response, as an integer. For an
+ :class:`Response`, this is always in the range [200,
+ 1000).
+
+ .. attribute:: headers
+
+ Request headers, represented as a list of (name, value) pairs. See
+ :ref:`the header normalization rules ` for details.
+
+ .. attribute:: http_version
+
+ The HTTP protocol version, represented as a byte string like
+ ``b"1.1"``. See :ref:`the HTTP version normalization rules
+ ` for details.
+
+ .. attribute:: reason
+
+ The reason phrase of this response, as a byte string. For example:
+ ``b"OK"``, or ``b"Not Found"``.
+
+ """
+
+ def __post_init__(self) -> None:
+ if not (200 <= self.status_code < 1000):
+ raise LocalProtocolError(
+ "Response status_code should be in range [200, 1000), not {}".format(
+ self.status_code
+ )
+ )
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+@dataclass(init=False, frozen=True)
+class Data(Event):
+ """Part of an HTTP message body.
+
+ Fields:
+
+ .. attribute:: data
+
+ A :term:`bytes-like object` containing part of a message body. Or, if
+ using the ``combine=False`` argument to :meth:`Connection.send`, then
+ any object that your socket writing code knows what to do with, and for
+ which calling :func:`len` returns the number of bytes that will be
+ written -- see :ref:`sendfile` for details.
+
+ .. attribute:: chunk_start
+
+ A marker that indicates whether this data object is from the start of a
+ chunked transfer encoding chunk. This field is ignored when when a Data
+ event is provided to :meth:`Connection.send`: it is only valid on
+ events emitted from :meth:`Connection.next_event`. You probably
+ shouldn't use this attribute at all; see
+ :ref:`chunk-delimiters-are-bad` for details.
+
+ .. attribute:: chunk_end
+
+ A marker that indicates whether this data object is the last for a
+ given chunked transfer encoding chunk. This field is ignored when when
+ a Data event is provided to :meth:`Connection.send`: it is only valid
+ on events emitted from :meth:`Connection.next_event`. You probably
+ shouldn't use this attribute at all; see
+ :ref:`chunk-delimiters-are-bad` for details.
+
+ """
+
+ __slots__ = ("data", "chunk_start", "chunk_end")
+
+ data: bytes
+ chunk_start: bool
+ chunk_end: bool
+
+ def __init__(
+ self, data: bytes, chunk_start: bool = False, chunk_end: bool = False
+ ) -> None:
+ object.__setattr__(self, "data", data)
+ object.__setattr__(self, "chunk_start", chunk_start)
+ object.__setattr__(self, "chunk_end", chunk_end)
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+# XX FIXME: "A recipient MUST ignore (or consider as an error) any fields that
+# are forbidden to be sent in a trailer, since processing them as if they were
+# present in the header section might bypass external security filters."
+# https://svn.tools.ietf.org/svn/wg/httpbis/specs/rfc7230.html#chunked.trailer.part
+# Unfortunately, the list of forbidden fields is long and vague :-/
+@dataclass(init=False, frozen=True)
+class EndOfMessage(Event):
+ """The end of an HTTP message.
+
+ Fields:
+
+ .. attribute:: headers
+
+ Default value: ``[]``
+
+ Any trailing headers attached to this message, represented as a list of
+ (name, value) pairs. See :ref:`the header normalization rules
+ ` for details.
+
+ Must be empty unless ``Transfer-Encoding: chunked`` is in use.
+
+ """
+
+ __slots__ = ("headers",)
+
+ headers: Headers
+
+ def __init__(
+ self,
+ *,
+ headers: Union[
+ Headers, List[Tuple[bytes, bytes]], List[Tuple[str, str]], None
+ ] = None,
+ _parsed: bool = False,
+ ) -> None:
+ super().__init__()
+ if headers is None:
+ headers = Headers([])
+ elif not isinstance(headers, Headers):
+ headers = normalize_and_validate(headers, _parsed=_parsed)
+
+ object.__setattr__(self, "headers", headers)
+
+ # This is an unhashable type.
+ __hash__ = None # type: ignore
+
+
+@dataclass(frozen=True)
+class ConnectionClosed(Event):
+ """This event indicates that the sender has closed their outgoing
+ connection.
+
+ Note that this does not necessarily mean that they can't *receive* further
+ data, because TCP connections are composed to two one-way channels which
+ can be closed independently. See :ref:`closing` for details.
+
+ No fields.
+ """
+
+ pass
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_headers.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_headers.py
new file mode 100644
index 0000000000000000000000000000000000000000..b97d020b634a9f47f5ae6aa3b30e2bd13a6c48c4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_headers.py
@@ -0,0 +1,278 @@
+import re
+from typing import AnyStr, cast, List, overload, Sequence, Tuple, TYPE_CHECKING, Union
+
+from ._abnf import field_name, field_value
+from ._util import bytesify, LocalProtocolError, validate
+
+if TYPE_CHECKING:
+ from ._events import Request
+
+try:
+ from typing import Literal
+except ImportError:
+ from typing_extensions import Literal # type: ignore
+
+
+# Facts
+# -----
+#
+# Headers are:
+# keys: case-insensitive ascii
+# values: mixture of ascii and raw bytes
+#
+# "Historically, HTTP has allowed field content with text in the ISO-8859-1
+# charset [ISO-8859-1], supporting other charsets only through use of
+# [RFC2047] encoding. In practice, most HTTP header field values use only a
+# subset of the US-ASCII charset [USASCII]. Newly defined header fields SHOULD
+# limit their field values to US-ASCII octets. A recipient SHOULD treat other
+# octets in field content (obs-text) as opaque data."
+# And it deprecates all non-ascii values
+#
+# Leading/trailing whitespace in header names is forbidden
+#
+# Values get leading/trailing whitespace stripped
+#
+# Content-Disposition actually needs to contain unicode semantically; to
+# accomplish this it has a terrifically weird way of encoding the filename
+# itself as ascii (and even this still has lots of cross-browser
+# incompatibilities)
+#
+# Order is important:
+# "a proxy MUST NOT change the order of these field values when forwarding a
+# message"
+# (and there are several headers where the order indicates a preference)
+#
+# Multiple occurences of the same header:
+# "A sender MUST NOT generate multiple header fields with the same field name
+# in a message unless either the entire field value for that header field is
+# defined as a comma-separated list [or the header is Set-Cookie which gets a
+# special exception]" - RFC 7230. (cookies are in RFC 6265)
+#
+# So every header aside from Set-Cookie can be merged by b", ".join if it
+# occurs repeatedly. But, of course, they can't necessarily be split by
+# .split(b","), because quoting.
+#
+# Given all this mess (case insensitive, duplicates allowed, order is
+# important, ...), there doesn't appear to be any standard way to handle
+# headers in Python -- they're almost like dicts, but... actually just
+# aren't. For now we punt and just use a super simple representation: headers
+# are a list of pairs
+#
+# [(name1, value1), (name2, value2), ...]
+#
+# where all entries are bytestrings, names are lowercase and have no
+# leading/trailing whitespace, and values are bytestrings with no
+# leading/trailing whitespace. Searching and updating are done via naive O(n)
+# methods.
+#
+# Maybe a dict-of-lists would be better?
+
+_content_length_re = re.compile(rb"[0-9]+")
+_field_name_re = re.compile(field_name.encode("ascii"))
+_field_value_re = re.compile(field_value.encode("ascii"))
+
+
+class Headers(Sequence[Tuple[bytes, bytes]]):
+ """
+ A list-like interface that allows iterating over headers as byte-pairs
+ of (lowercased-name, value).
+
+ Internally we actually store the representation as three-tuples,
+ including both the raw original casing, in order to preserve casing
+ over-the-wire, and the lowercased name, for case-insensitive comparisions.
+
+ r = Request(
+ method="GET",
+ target="/",
+ headers=[("Host", "example.org"), ("Connection", "keep-alive")],
+ http_version="1.1",
+ )
+ assert r.headers == [
+ (b"host", b"example.org"),
+ (b"connection", b"keep-alive")
+ ]
+ assert r.headers.raw_items() == [
+ (b"Host", b"example.org"),
+ (b"Connection", b"keep-alive")
+ ]
+ """
+
+ __slots__ = "_full_items"
+
+ def __init__(self, full_items: List[Tuple[bytes, bytes, bytes]]) -> None:
+ self._full_items = full_items
+
+ def __bool__(self) -> bool:
+ return bool(self._full_items)
+
+ def __eq__(self, other: object) -> bool:
+ return list(self) == list(other) # type: ignore
+
+ def __len__(self) -> int:
+ return len(self._full_items)
+
+ def __repr__(self) -> str:
+ return "" % repr(list(self))
+
+ def __getitem__(self, idx: int) -> Tuple[bytes, bytes]: # type: ignore[override]
+ _, name, value = self._full_items[idx]
+ return (name, value)
+
+ def raw_items(self) -> List[Tuple[bytes, bytes]]:
+ return [(raw_name, value) for raw_name, _, value in self._full_items]
+
+
+HeaderTypes = Union[
+ List[Tuple[bytes, bytes]],
+ List[Tuple[bytes, str]],
+ List[Tuple[str, bytes]],
+ List[Tuple[str, str]],
+]
+
+
+@overload
+def normalize_and_validate(headers: Headers, _parsed: Literal[True]) -> Headers:
+ ...
+
+
+@overload
+def normalize_and_validate(headers: HeaderTypes, _parsed: Literal[False]) -> Headers:
+ ...
+
+
+@overload
+def normalize_and_validate(
+ headers: Union[Headers, HeaderTypes], _parsed: bool = False
+) -> Headers:
+ ...
+
+
+def normalize_and_validate(
+ headers: Union[Headers, HeaderTypes], _parsed: bool = False
+) -> Headers:
+ new_headers = []
+ seen_content_length = None
+ saw_transfer_encoding = False
+ for name, value in headers:
+ # For headers coming out of the parser, we can safely skip some steps,
+ # because it always returns bytes and has already run these regexes
+ # over the data:
+ if not _parsed:
+ name = bytesify(name)
+ value = bytesify(value)
+ validate(_field_name_re, name, "Illegal header name {!r}", name)
+ validate(_field_value_re, value, "Illegal header value {!r}", value)
+ assert isinstance(name, bytes)
+ assert isinstance(value, bytes)
+
+ raw_name = name
+ name = name.lower()
+ if name == b"content-length":
+ lengths = {length.strip() for length in value.split(b",")}
+ if len(lengths) != 1:
+ raise LocalProtocolError("conflicting Content-Length headers")
+ value = lengths.pop()
+ validate(_content_length_re, value, "bad Content-Length")
+ if seen_content_length is None:
+ seen_content_length = value
+ new_headers.append((raw_name, name, value))
+ elif seen_content_length != value:
+ raise LocalProtocolError("conflicting Content-Length headers")
+ elif name == b"transfer-encoding":
+ # "A server that receives a request message with a transfer coding
+ # it does not understand SHOULD respond with 501 (Not
+ # Implemented)."
+ # https://tools.ietf.org/html/rfc7230#section-3.3.1
+ if saw_transfer_encoding:
+ raise LocalProtocolError(
+ "multiple Transfer-Encoding headers", error_status_hint=501
+ )
+ # "All transfer-coding names are case-insensitive"
+ # -- https://tools.ietf.org/html/rfc7230#section-4
+ value = value.lower()
+ if value != b"chunked":
+ raise LocalProtocolError(
+ "Only Transfer-Encoding: chunked is supported",
+ error_status_hint=501,
+ )
+ saw_transfer_encoding = True
+ new_headers.append((raw_name, name, value))
+ else:
+ new_headers.append((raw_name, name, value))
+ return Headers(new_headers)
+
+
+def get_comma_header(headers: Headers, name: bytes) -> List[bytes]:
+ # Should only be used for headers whose value is a list of
+ # comma-separated, case-insensitive values.
+ #
+ # The header name `name` is expected to be lower-case bytes.
+ #
+ # Connection: meets these criteria (including cast insensitivity).
+ #
+ # Content-Length: technically is just a single value (1*DIGIT), but the
+ # standard makes reference to implementations that do multiple values, and
+ # using this doesn't hurt. Ditto, case insensitivity doesn't things either
+ # way.
+ #
+ # Transfer-Encoding: is more complex (allows for quoted strings), so
+ # splitting on , is actually wrong. For example, this is legal:
+ #
+ # Transfer-Encoding: foo; options="1,2", chunked
+ #
+ # and should be parsed as
+ #
+ # foo; options="1,2"
+ # chunked
+ #
+ # but this naive function will parse it as
+ #
+ # foo; options="1
+ # 2"
+ # chunked
+ #
+ # However, this is okay because the only thing we are going to do with
+ # any Transfer-Encoding is reject ones that aren't just "chunked", so
+ # both of these will be treated the same anyway.
+ #
+ # Expect: the only legal value is the literal string
+ # "100-continue". Splitting on commas is harmless. Case insensitive.
+ #
+ out: List[bytes] = []
+ for _, found_name, found_raw_value in headers._full_items:
+ if found_name == name:
+ found_raw_value = found_raw_value.lower()
+ for found_split_value in found_raw_value.split(b","):
+ found_split_value = found_split_value.strip()
+ if found_split_value:
+ out.append(found_split_value)
+ return out
+
+
+def set_comma_header(headers: Headers, name: bytes, new_values: List[bytes]) -> Headers:
+ # The header name `name` is expected to be lower-case bytes.
+ #
+ # Note that when we store the header we use title casing for the header
+ # names, in order to match the conventional HTTP header style.
+ #
+ # Simply calling `.title()` is a blunt approach, but it's correct
+ # here given the cases where we're using `set_comma_header`...
+ #
+ # Connection, Content-Length, Transfer-Encoding.
+ new_headers: List[Tuple[bytes, bytes]] = []
+ for found_raw_name, found_name, found_raw_value in headers._full_items:
+ if found_name != name:
+ new_headers.append((found_raw_name, found_raw_value))
+ for new_value in new_values:
+ new_headers.append((name.title(), new_value))
+ return normalize_and_validate(new_headers)
+
+
+def has_expect_100_continue(request: "Request") -> bool:
+ # https://tools.ietf.org/html/rfc7231#section-5.1.1
+ # "A server that receives a 100-continue expectation in an HTTP/1.0 request
+ # MUST ignore that expectation."
+ if request.http_version < b"1.1":
+ return False
+ expect = get_comma_header(request.headers, b"expect")
+ return b"100-continue" in expect
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_readers.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_readers.py
new file mode 100644
index 0000000000000000000000000000000000000000..08a9574da4a89d82dfb71b3087b14c8644102dd6
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_readers.py
@@ -0,0 +1,247 @@
+# Code to read HTTP data
+#
+# Strategy: each reader is a callable which takes a ReceiveBuffer object, and
+# either:
+# 1) consumes some of it and returns an Event
+# 2) raises a LocalProtocolError (for consistency -- e.g. we call validate()
+# and it might raise a LocalProtocolError, so simpler just to always use
+# this)
+# 3) returns None, meaning "I need more data"
+#
+# If they have a .read_eof attribute, then this will be called if an EOF is
+# received -- but this is optional. Either way, the actual ConnectionClosed
+# event will be generated afterwards.
+#
+# READERS is a dict describing how to pick a reader. It maps states to either:
+# - a reader
+# - or, for body readers, a dict of per-framing reader factories
+
+import re
+from typing import Any, Callable, Dict, Iterable, NoReturn, Optional, Tuple, Type, Union
+
+from ._abnf import chunk_header, header_field, request_line, status_line
+from ._events import Data, EndOfMessage, InformationalResponse, Request, Response
+from ._receivebuffer import ReceiveBuffer
+from ._state import (
+ CLIENT,
+ CLOSED,
+ DONE,
+ IDLE,
+ MUST_CLOSE,
+ SEND_BODY,
+ SEND_RESPONSE,
+ SERVER,
+)
+from ._util import LocalProtocolError, RemoteProtocolError, Sentinel, validate
+
+__all__ = ["READERS"]
+
+header_field_re = re.compile(header_field.encode("ascii"))
+obs_fold_re = re.compile(rb"[ \t]+")
+
+
+def _obsolete_line_fold(lines: Iterable[bytes]) -> Iterable[bytes]:
+ it = iter(lines)
+ last: Optional[bytes] = None
+ for line in it:
+ match = obs_fold_re.match(line)
+ if match:
+ if last is None:
+ raise LocalProtocolError("continuation line at start of headers")
+ if not isinstance(last, bytearray):
+ # Cast to a mutable type, avoiding copy on append to ensure O(n) time
+ last = bytearray(last)
+ last += b" "
+ last += line[match.end() :]
+ else:
+ if last is not None:
+ yield last
+ last = line
+ if last is not None:
+ yield last
+
+
+def _decode_header_lines(
+ lines: Iterable[bytes],
+) -> Iterable[Tuple[bytes, bytes]]:
+ for line in _obsolete_line_fold(lines):
+ matches = validate(header_field_re, line, "illegal header line: {!r}", line)
+ yield (matches["field_name"], matches["field_value"])
+
+
+request_line_re = re.compile(request_line.encode("ascii"))
+
+
+def maybe_read_from_IDLE_client(buf: ReceiveBuffer) -> Optional[Request]:
+ lines = buf.maybe_extract_lines()
+ if lines is None:
+ if buf.is_next_line_obviously_invalid_request_line():
+ raise LocalProtocolError("illegal request line")
+ return None
+ if not lines:
+ raise LocalProtocolError("no request line received")
+ matches = validate(
+ request_line_re, lines[0], "illegal request line: {!r}", lines[0]
+ )
+ return Request(
+ headers=list(_decode_header_lines(lines[1:])), _parsed=True, **matches
+ )
+
+
+status_line_re = re.compile(status_line.encode("ascii"))
+
+
+def maybe_read_from_SEND_RESPONSE_server(
+ buf: ReceiveBuffer,
+) -> Union[InformationalResponse, Response, None]:
+ lines = buf.maybe_extract_lines()
+ if lines is None:
+ if buf.is_next_line_obviously_invalid_request_line():
+ raise LocalProtocolError("illegal request line")
+ return None
+ if not lines:
+ raise LocalProtocolError("no response line received")
+ matches = validate(status_line_re, lines[0], "illegal status line: {!r}", lines[0])
+ http_version = (
+ b"1.1" if matches["http_version"] is None else matches["http_version"]
+ )
+ reason = b"" if matches["reason"] is None else matches["reason"]
+ status_code = int(matches["status_code"])
+ class_: Union[Type[InformationalResponse], Type[Response]] = (
+ InformationalResponse if status_code < 200 else Response
+ )
+ return class_(
+ headers=list(_decode_header_lines(lines[1:])),
+ _parsed=True,
+ status_code=status_code,
+ reason=reason,
+ http_version=http_version,
+ )
+
+
+class ContentLengthReader:
+ def __init__(self, length: int) -> None:
+ self._length = length
+ self._remaining = length
+
+ def __call__(self, buf: ReceiveBuffer) -> Union[Data, EndOfMessage, None]:
+ if self._remaining == 0:
+ return EndOfMessage()
+ data = buf.maybe_extract_at_most(self._remaining)
+ if data is None:
+ return None
+ self._remaining -= len(data)
+ return Data(data=data)
+
+ def read_eof(self) -> NoReturn:
+ raise RemoteProtocolError(
+ "peer closed connection without sending complete message body "
+ "(received {} bytes, expected {})".format(
+ self._length - self._remaining, self._length
+ )
+ )
+
+
+chunk_header_re = re.compile(chunk_header.encode("ascii"))
+
+
+class ChunkedReader:
+ def __init__(self) -> None:
+ self._bytes_in_chunk = 0
+ # After reading a chunk, we have to throw away the trailing \r\n; if
+ # this is >0 then we discard that many bytes before resuming regular
+ # de-chunkification.
+ self._bytes_to_discard = 0
+ self._reading_trailer = False
+
+ def __call__(self, buf: ReceiveBuffer) -> Union[Data, EndOfMessage, None]:
+ if self._reading_trailer:
+ lines = buf.maybe_extract_lines()
+ if lines is None:
+ return None
+ return EndOfMessage(headers=list(_decode_header_lines(lines)))
+ if self._bytes_to_discard > 0:
+ data = buf.maybe_extract_at_most(self._bytes_to_discard)
+ if data is None:
+ return None
+ self._bytes_to_discard -= len(data)
+ if self._bytes_to_discard > 0:
+ return None
+ # else, fall through and read some more
+ assert self._bytes_to_discard == 0
+ if self._bytes_in_chunk == 0:
+ # We need to refill our chunk count
+ chunk_header = buf.maybe_extract_next_line()
+ if chunk_header is None:
+ return None
+ matches = validate(
+ chunk_header_re,
+ chunk_header,
+ "illegal chunk header: {!r}",
+ chunk_header,
+ )
+ # XX FIXME: we discard chunk extensions. Does anyone care?
+ self._bytes_in_chunk = int(matches["chunk_size"], base=16)
+ if self._bytes_in_chunk == 0:
+ self._reading_trailer = True
+ return self(buf)
+ chunk_start = True
+ else:
+ chunk_start = False
+ assert self._bytes_in_chunk > 0
+ data = buf.maybe_extract_at_most(self._bytes_in_chunk)
+ if data is None:
+ return None
+ self._bytes_in_chunk -= len(data)
+ if self._bytes_in_chunk == 0:
+ self._bytes_to_discard = 2
+ chunk_end = True
+ else:
+ chunk_end = False
+ return Data(data=data, chunk_start=chunk_start, chunk_end=chunk_end)
+
+ def read_eof(self) -> NoReturn:
+ raise RemoteProtocolError(
+ "peer closed connection without sending complete message body "
+ "(incomplete chunked read)"
+ )
+
+
+class Http10Reader:
+ def __call__(self, buf: ReceiveBuffer) -> Optional[Data]:
+ data = buf.maybe_extract_at_most(999999999)
+ if data is None:
+ return None
+ return Data(data=data)
+
+ def read_eof(self) -> EndOfMessage:
+ return EndOfMessage()
+
+
+def expect_nothing(buf: ReceiveBuffer) -> None:
+ if buf:
+ raise LocalProtocolError("Got data when expecting EOF")
+ return None
+
+
+ReadersType = Dict[
+ Union[Type[Sentinel], Tuple[Type[Sentinel], Type[Sentinel]]],
+ Union[Callable[..., Any], Dict[str, Callable[..., Any]]],
+]
+
+READERS: ReadersType = {
+ (CLIENT, IDLE): maybe_read_from_IDLE_client,
+ (SERVER, IDLE): maybe_read_from_SEND_RESPONSE_server,
+ (SERVER, SEND_RESPONSE): maybe_read_from_SEND_RESPONSE_server,
+ (CLIENT, DONE): expect_nothing,
+ (CLIENT, MUST_CLOSE): expect_nothing,
+ (CLIENT, CLOSED): expect_nothing,
+ (SERVER, DONE): expect_nothing,
+ (SERVER, MUST_CLOSE): expect_nothing,
+ (SERVER, CLOSED): expect_nothing,
+ SEND_BODY: {
+ "chunked": ChunkedReader,
+ "content-length": ContentLengthReader,
+ "http/1.0": Http10Reader,
+ },
+}
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_receivebuffer.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_receivebuffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..e5c4e08a56f5081e87103f38b4add6ce1b730204
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_receivebuffer.py
@@ -0,0 +1,153 @@
+import re
+import sys
+from typing import List, Optional, Union
+
+__all__ = ["ReceiveBuffer"]
+
+
+# Operations we want to support:
+# - find next \r\n or \r\n\r\n (\n or \n\n are also acceptable),
+# or wait until there is one
+# - read at-most-N bytes
+# Goals:
+# - on average, do this fast
+# - worst case, do this in O(n) where n is the number of bytes processed
+# Plan:
+# - store bytearray, offset, how far we've searched for a separator token
+# - use the how-far-we've-searched data to avoid rescanning
+# - while doing a stream of uninterrupted processing, advance offset instead
+# of constantly copying
+# WARNING:
+# - I haven't benchmarked or profiled any of this yet.
+#
+# Note that starting in Python 3.4, deleting the initial n bytes from a
+# bytearray is amortized O(n), thanks to some excellent work by Antoine
+# Martin:
+#
+# https://bugs.python.org/issue19087
+#
+# This means that if we only supported 3.4+, we could get rid of the code here
+# involving self._start and self.compress, because it's doing exactly the same
+# thing that bytearray now does internally.
+#
+# BUT unfortunately, we still support 2.7, and reading short segments out of a
+# long buffer MUST be O(bytes read) to avoid DoS issues, so we can't actually
+# delete this code. Yet:
+#
+# https://pythonclock.org/
+#
+# (Two things to double-check first though: make sure PyPy also has the
+# optimization, and benchmark to make sure it's a win, since we do have a
+# slightly clever thing where we delay calling compress() until we've
+# processed a whole event, which could in theory be slightly more efficient
+# than the internal bytearray support.)
+blank_line_regex = re.compile(b"\n\r?\n", re.MULTILINE)
+
+
+class ReceiveBuffer:
+ def __init__(self) -> None:
+ self._data = bytearray()
+ self._next_line_search = 0
+ self._multiple_lines_search = 0
+
+ def __iadd__(self, byteslike: Union[bytes, bytearray]) -> "ReceiveBuffer":
+ self._data += byteslike
+ return self
+
+ def __bool__(self) -> bool:
+ return bool(len(self))
+
+ def __len__(self) -> int:
+ return len(self._data)
+
+ # for @property unprocessed_data
+ def __bytes__(self) -> bytes:
+ return bytes(self._data)
+
+ def _extract(self, count: int) -> bytearray:
+ # extracting an initial slice of the data buffer and return it
+ out = self._data[:count]
+ del self._data[:count]
+
+ self._next_line_search = 0
+ self._multiple_lines_search = 0
+
+ return out
+
+ def maybe_extract_at_most(self, count: int) -> Optional[bytearray]:
+ """
+ Extract a fixed number of bytes from the buffer.
+ """
+ out = self._data[:count]
+ if not out:
+ return None
+
+ return self._extract(count)
+
+ def maybe_extract_next_line(self) -> Optional[bytearray]:
+ """
+ Extract the first line, if it is completed in the buffer.
+ """
+ # Only search in buffer space that we've not already looked at.
+ search_start_index = max(0, self._next_line_search - 1)
+ partial_idx = self._data.find(b"\r\n", search_start_index)
+
+ if partial_idx == -1:
+ self._next_line_search = len(self._data)
+ return None
+
+ # + 2 is to compensate len(b"\r\n")
+ idx = partial_idx + 2
+
+ return self._extract(idx)
+
+ def maybe_extract_lines(self) -> Optional[List[bytearray]]:
+ """
+ Extract everything up to the first blank line, and return a list of lines.
+ """
+ # Handle the case where we have an immediate empty line.
+ if self._data[:1] == b"\n":
+ self._extract(1)
+ return []
+
+ if self._data[:2] == b"\r\n":
+ self._extract(2)
+ return []
+
+ # Only search in buffer space that we've not already looked at.
+ match = blank_line_regex.search(self._data, self._multiple_lines_search)
+ if match is None:
+ self._multiple_lines_search = max(0, len(self._data) - 2)
+ return None
+
+ # Truncate the buffer and return it.
+ idx = match.span(0)[-1]
+ out = self._extract(idx)
+ lines = out.split(b"\n")
+
+ for line in lines:
+ if line.endswith(b"\r"):
+ del line[-1]
+
+ assert lines[-2] == lines[-1] == b""
+
+ del lines[-2:]
+
+ return lines
+
+ # In theory we should wait until `\r\n` before starting to validate
+ # incoming data. However it's interesting to detect (very) invalid data
+ # early given they might not even contain `\r\n` at all (hence only
+ # timeout will get rid of them).
+ # This is not a 100% effective detection but more of a cheap sanity check
+ # allowing for early abort in some useful cases.
+ # This is especially interesting when peer is messing up with HTTPS and
+ # sent us a TLS stream where we were expecting plain HTTP given all
+ # versions of TLS so far start handshake with a 0x16 message type code.
+ def is_next_line_obviously_invalid_request_line(self) -> bool:
+ try:
+ # HTTP header line must not contain non-printable characters
+ # and should not start with a space
+ return self._data[0] < 0x21
+ except IndexError:
+ return False
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_state.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_state.py
new file mode 100644
index 0000000000000000000000000000000000000000..3593430a74f21f6e0c2faf495e1627551eebfc30
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_state.py
@@ -0,0 +1,367 @@
+################################################################
+# The core state machine
+################################################################
+#
+# Rule 1: everything that affects the state machine and state transitions must
+# live here in this file. As much as possible goes into the table-based
+# representation, but for the bits that don't quite fit, the actual code and
+# state must nonetheless live here.
+#
+# Rule 2: this file does not know about what role we're playing; it only knows
+# about HTTP request/response cycles in the abstract. This ensures that we
+# don't cheat and apply different rules to local and remote parties.
+#
+#
+# Theory of operation
+# ===================
+#
+# Possibly the simplest way to think about this is that we actually have 5
+# different state machines here. Yes, 5. These are:
+#
+# 1) The client state, with its complicated automaton (see the docs)
+# 2) The server state, with its complicated automaton (see the docs)
+# 3) The keep-alive state, with possible states {True, False}
+# 4) The SWITCH_CONNECT state, with possible states {False, True}
+# 5) The SWITCH_UPGRADE state, with possible states {False, True}
+#
+# For (3)-(5), the first state listed is the initial state.
+#
+# (1)-(3) are stored explicitly in member variables. The last
+# two are stored implicitly in the pending_switch_proposals set as:
+# (state of 4) == (_SWITCH_CONNECT in pending_switch_proposals)
+# (state of 5) == (_SWITCH_UPGRADE in pending_switch_proposals)
+#
+# And each of these machines has two different kinds of transitions:
+#
+# a) Event-triggered
+# b) State-triggered
+#
+# Event triggered is the obvious thing that you'd think it is: some event
+# happens, and if it's the right event at the right time then a transition
+# happens. But there are somewhat complicated rules for which machines can
+# "see" which events. (As a rule of thumb, if a machine "sees" an event, this
+# means two things: the event can affect the machine, and if the machine is
+# not in a state where it expects that event then it's an error.) These rules
+# are:
+#
+# 1) The client machine sees all h11.events objects emitted by the client.
+#
+# 2) The server machine sees all h11.events objects emitted by the server.
+#
+# It also sees the client's Request event.
+#
+# And sometimes, server events are annotated with a _SWITCH_* event. For
+# example, we can have a (Response, _SWITCH_CONNECT) event, which is
+# different from a regular Response event.
+#
+# 3) The keep-alive machine sees the process_keep_alive_disabled() event
+# (which is derived from Request/Response events), and this event
+# transitions it from True -> False, or from False -> False. There's no way
+# to transition back.
+#
+# 4&5) The _SWITCH_* machines transition from False->True when we get a
+# Request that proposes the relevant type of switch (via
+# process_client_switch_proposals), and they go from True->False when we
+# get a Response that has no _SWITCH_* annotation.
+#
+# So that's event-triggered transitions.
+#
+# State-triggered transitions are less standard. What they do here is couple
+# the machines together. The way this works is, when certain *joint*
+# configurations of states are achieved, then we automatically transition to a
+# new *joint* state. So, for example, if we're ever in a joint state with
+#
+# client: DONE
+# keep-alive: False
+#
+# then the client state immediately transitions to:
+#
+# client: MUST_CLOSE
+#
+# This is fundamentally different from an event-based transition, because it
+# doesn't matter how we arrived at the {client: DONE, keep-alive: False} state
+# -- maybe the client transitioned SEND_BODY -> DONE, or keep-alive
+# transitioned True -> False. Either way, once this precondition is satisfied,
+# this transition is immediately triggered.
+#
+# What if two conflicting state-based transitions get enabled at the same
+# time? In practice there's only one case where this arises (client DONE ->
+# MIGHT_SWITCH_PROTOCOL versus DONE -> MUST_CLOSE), and we resolve it by
+# explicitly prioritizing the DONE -> MIGHT_SWITCH_PROTOCOL transition.
+#
+# Implementation
+# --------------
+#
+# The event-triggered transitions for the server and client machines are all
+# stored explicitly in a table. Ditto for the state-triggered transitions that
+# involve just the server and client state.
+#
+# The transitions for the other machines, and the state-triggered transitions
+# that involve the other machines, are written out as explicit Python code.
+#
+# It'd be nice if there were some cleaner way to do all this. This isn't
+# *too* terrible, but I feel like it could probably be better.
+#
+# WARNING
+# -------
+#
+# The script that generates the state machine diagrams for the docs knows how
+# to read out the EVENT_TRIGGERED_TRANSITIONS and STATE_TRIGGERED_TRANSITIONS
+# tables. But it can't automatically read the transitions that are written
+# directly in Python code. So if you touch those, you need to also update the
+# script to keep it in sync!
+from typing import cast, Dict, Optional, Set, Tuple, Type, Union
+
+from ._events import *
+from ._util import LocalProtocolError, Sentinel
+
+# Everything in __all__ gets re-exported as part of the h11 public API.
+__all__ = [
+ "CLIENT",
+ "SERVER",
+ "IDLE",
+ "SEND_RESPONSE",
+ "SEND_BODY",
+ "DONE",
+ "MUST_CLOSE",
+ "CLOSED",
+ "MIGHT_SWITCH_PROTOCOL",
+ "SWITCHED_PROTOCOL",
+ "ERROR",
+]
+
+
+class CLIENT(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class SERVER(Sentinel, metaclass=Sentinel):
+ pass
+
+
+# States
+class IDLE(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class SEND_RESPONSE(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class SEND_BODY(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class DONE(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class MUST_CLOSE(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class CLOSED(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class ERROR(Sentinel, metaclass=Sentinel):
+ pass
+
+
+# Switch types
+class MIGHT_SWITCH_PROTOCOL(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class SWITCHED_PROTOCOL(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class _SWITCH_UPGRADE(Sentinel, metaclass=Sentinel):
+ pass
+
+
+class _SWITCH_CONNECT(Sentinel, metaclass=Sentinel):
+ pass
+
+
+EventTransitionType = Dict[
+ Type[Sentinel],
+ Dict[
+ Type[Sentinel],
+ Dict[Union[Type[Event], Tuple[Type[Event], Type[Sentinel]]], Type[Sentinel]],
+ ],
+]
+
+EVENT_TRIGGERED_TRANSITIONS: EventTransitionType = {
+ CLIENT: {
+ IDLE: {Request: SEND_BODY, ConnectionClosed: CLOSED},
+ SEND_BODY: {Data: SEND_BODY, EndOfMessage: DONE},
+ DONE: {ConnectionClosed: CLOSED},
+ MUST_CLOSE: {ConnectionClosed: CLOSED},
+ CLOSED: {ConnectionClosed: CLOSED},
+ MIGHT_SWITCH_PROTOCOL: {},
+ SWITCHED_PROTOCOL: {},
+ ERROR: {},
+ },
+ SERVER: {
+ IDLE: {
+ ConnectionClosed: CLOSED,
+ Response: SEND_BODY,
+ # Special case: server sees client Request events, in this form
+ (Request, CLIENT): SEND_RESPONSE,
+ },
+ SEND_RESPONSE: {
+ InformationalResponse: SEND_RESPONSE,
+ Response: SEND_BODY,
+ (InformationalResponse, _SWITCH_UPGRADE): SWITCHED_PROTOCOL,
+ (Response, _SWITCH_CONNECT): SWITCHED_PROTOCOL,
+ },
+ SEND_BODY: {Data: SEND_BODY, EndOfMessage: DONE},
+ DONE: {ConnectionClosed: CLOSED},
+ MUST_CLOSE: {ConnectionClosed: CLOSED},
+ CLOSED: {ConnectionClosed: CLOSED},
+ SWITCHED_PROTOCOL: {},
+ ERROR: {},
+ },
+}
+
+StateTransitionType = Dict[
+ Tuple[Type[Sentinel], Type[Sentinel]], Dict[Type[Sentinel], Type[Sentinel]]
+]
+
+# NB: there are also some special-case state-triggered transitions hard-coded
+# into _fire_state_triggered_transitions below.
+STATE_TRIGGERED_TRANSITIONS: StateTransitionType = {
+ # (Client state, Server state) -> new states
+ # Protocol negotiation
+ (MIGHT_SWITCH_PROTOCOL, SWITCHED_PROTOCOL): {CLIENT: SWITCHED_PROTOCOL},
+ # Socket shutdown
+ (CLOSED, DONE): {SERVER: MUST_CLOSE},
+ (CLOSED, IDLE): {SERVER: MUST_CLOSE},
+ (ERROR, DONE): {SERVER: MUST_CLOSE},
+ (DONE, CLOSED): {CLIENT: MUST_CLOSE},
+ (IDLE, CLOSED): {CLIENT: MUST_CLOSE},
+ (DONE, ERROR): {CLIENT: MUST_CLOSE},
+}
+
+
+class ConnectionState:
+ def __init__(self) -> None:
+ # Extra bits of state that don't quite fit into the state model.
+
+ # If this is False then it enables the automatic DONE -> MUST_CLOSE
+ # transition. Don't set this directly; call .keep_alive_disabled()
+ self.keep_alive = True
+
+ # This is a subset of {UPGRADE, CONNECT}, containing the proposals
+ # made by the client for switching protocols.
+ self.pending_switch_proposals: Set[Type[Sentinel]] = set()
+
+ self.states: Dict[Type[Sentinel], Type[Sentinel]] = {CLIENT: IDLE, SERVER: IDLE}
+
+ def process_error(self, role: Type[Sentinel]) -> None:
+ self.states[role] = ERROR
+ self._fire_state_triggered_transitions()
+
+ def process_keep_alive_disabled(self) -> None:
+ self.keep_alive = False
+ self._fire_state_triggered_transitions()
+
+ def process_client_switch_proposal(self, switch_event: Type[Sentinel]) -> None:
+ self.pending_switch_proposals.add(switch_event)
+ self._fire_state_triggered_transitions()
+
+ def process_event(
+ self,
+ role: Type[Sentinel],
+ event_type: Type[Event],
+ server_switch_event: Optional[Type[Sentinel]] = None,
+ ) -> None:
+ _event_type: Union[Type[Event], Tuple[Type[Event], Type[Sentinel]]] = event_type
+ if server_switch_event is not None:
+ assert role is SERVER
+ if server_switch_event not in self.pending_switch_proposals:
+ raise LocalProtocolError(
+ "Received server {} event without a pending proposal".format(
+ server_switch_event
+ )
+ )
+ _event_type = (event_type, server_switch_event)
+ if server_switch_event is None and _event_type is Response:
+ self.pending_switch_proposals = set()
+ self._fire_event_triggered_transitions(role, _event_type)
+ # Special case: the server state does get to see Request
+ # events.
+ if _event_type is Request:
+ assert role is CLIENT
+ self._fire_event_triggered_transitions(SERVER, (Request, CLIENT))
+ self._fire_state_triggered_transitions()
+
+ def _fire_event_triggered_transitions(
+ self,
+ role: Type[Sentinel],
+ event_type: Union[Type[Event], Tuple[Type[Event], Type[Sentinel]]],
+ ) -> None:
+ state = self.states[role]
+ try:
+ new_state = EVENT_TRIGGERED_TRANSITIONS[role][state][event_type]
+ except KeyError:
+ event_type = cast(Type[Event], event_type)
+ raise LocalProtocolError(
+ "can't handle event type {} when role={} and state={}".format(
+ event_type.__name__, role, self.states[role]
+ )
+ ) from None
+ self.states[role] = new_state
+
+ def _fire_state_triggered_transitions(self) -> None:
+ # We apply these rules repeatedly until converging on a fixed point
+ while True:
+ start_states = dict(self.states)
+
+ # It could happen that both these special-case transitions are
+ # enabled at the same time:
+ #
+ # DONE -> MIGHT_SWITCH_PROTOCOL
+ # DONE -> MUST_CLOSE
+ #
+ # For example, this will always be true of a HTTP/1.0 client
+ # requesting CONNECT. If this happens, the protocol switch takes
+ # priority. From there the client will either go to
+ # SWITCHED_PROTOCOL, in which case it's none of our business when
+ # they close the connection, or else the server will deny the
+ # request, in which case the client will go back to DONE and then
+ # from there to MUST_CLOSE.
+ if self.pending_switch_proposals:
+ if self.states[CLIENT] is DONE:
+ self.states[CLIENT] = MIGHT_SWITCH_PROTOCOL
+
+ if not self.pending_switch_proposals:
+ if self.states[CLIENT] is MIGHT_SWITCH_PROTOCOL:
+ self.states[CLIENT] = DONE
+
+ if not self.keep_alive:
+ for role in (CLIENT, SERVER):
+ if self.states[role] is DONE:
+ self.states[role] = MUST_CLOSE
+
+ # Tabular state-triggered transitions
+ joint_state = (self.states[CLIENT], self.states[SERVER])
+ changes = STATE_TRIGGERED_TRANSITIONS.get(joint_state, {})
+ self.states.update(changes)
+
+ if self.states == start_states:
+ # Fixed point reached
+ return
+
+ def start_next_cycle(self) -> None:
+ if self.states != {CLIENT: DONE, SERVER: DONE}:
+ raise LocalProtocolError(
+ "not in a reusable state. self.states={}".format(self.states)
+ )
+ # Can't reach DONE/DONE with any of these active, but still, let's be
+ # sure.
+ assert self.keep_alive
+ assert not self.pending_switch_proposals
+ self.states = {CLIENT: IDLE, SERVER: IDLE}
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_util.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_util.py
new file mode 100644
index 0000000000000000000000000000000000000000..6718445290770e028ea2f1f662026c9a0b0991db
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_util.py
@@ -0,0 +1,135 @@
+from typing import Any, Dict, NoReturn, Pattern, Tuple, Type, TypeVar, Union
+
+__all__ = [
+ "ProtocolError",
+ "LocalProtocolError",
+ "RemoteProtocolError",
+ "validate",
+ "bytesify",
+]
+
+
+class ProtocolError(Exception):
+ """Exception indicating a violation of the HTTP/1.1 protocol.
+
+ This as an abstract base class, with two concrete base classes:
+ :exc:`LocalProtocolError`, which indicates that you tried to do something
+ that HTTP/1.1 says is illegal, and :exc:`RemoteProtocolError`, which
+ indicates that the remote peer tried to do something that HTTP/1.1 says is
+ illegal. See :ref:`error-handling` for details.
+
+ In addition to the normal :exc:`Exception` features, it has one attribute:
+
+ .. attribute:: error_status_hint
+
+ This gives a suggestion as to what status code a server might use if
+ this error occurred as part of a request.
+
+ For a :exc:`RemoteProtocolError`, this is useful as a suggestion for
+ how you might want to respond to a misbehaving peer, if you're
+ implementing a server.
+
+ For a :exc:`LocalProtocolError`, this can be taken as a suggestion for
+ how your peer might have responded to *you* if h11 had allowed you to
+ continue.
+
+ The default is 400 Bad Request, a generic catch-all for protocol
+ violations.
+
+ """
+
+ def __init__(self, msg: str, error_status_hint: int = 400) -> None:
+ if type(self) is ProtocolError:
+ raise TypeError("tried to directly instantiate ProtocolError")
+ Exception.__init__(self, msg)
+ self.error_status_hint = error_status_hint
+
+
+# Strategy: there are a number of public APIs where a LocalProtocolError can
+# be raised (send(), all the different event constructors, ...), and only one
+# public API where RemoteProtocolError can be raised
+# (receive_data()). Therefore we always raise LocalProtocolError internally,
+# and then receive_data will translate this into a RemoteProtocolError.
+#
+# Internally:
+# LocalProtocolError is the generic "ProtocolError".
+# Externally:
+# LocalProtocolError is for local errors and RemoteProtocolError is for
+# remote errors.
+class LocalProtocolError(ProtocolError):
+ def _reraise_as_remote_protocol_error(self) -> NoReturn:
+ # After catching a LocalProtocolError, use this method to re-raise it
+ # as a RemoteProtocolError. This method must be called from inside an
+ # except: block.
+ #
+ # An easy way to get an equivalent RemoteProtocolError is just to
+ # modify 'self' in place.
+ self.__class__ = RemoteProtocolError # type: ignore
+ # But the re-raising is somewhat non-trivial -- you might think that
+ # now that we've modified the in-flight exception object, that just
+ # doing 'raise' to re-raise it would be enough. But it turns out that
+ # this doesn't work, because Python tracks the exception type
+ # (exc_info[0]) separately from the exception object (exc_info[1]),
+ # and we only modified the latter. So we really do need to re-raise
+ # the new type explicitly.
+ # On py3, the traceback is part of the exception object, so our
+ # in-place modification preserved it and we can just re-raise:
+ raise self
+
+
+class RemoteProtocolError(ProtocolError):
+ pass
+
+
+def validate(
+ regex: Pattern[bytes], data: bytes, msg: str = "malformed data", *format_args: Any
+) -> Dict[str, bytes]:
+ match = regex.fullmatch(data)
+ if not match:
+ if format_args:
+ msg = msg.format(*format_args)
+ raise LocalProtocolError(msg)
+ return match.groupdict()
+
+
+# Sentinel values
+#
+# - Inherit identity-based comparison and hashing from object
+# - Have a nice repr
+# - Have a *bonus property*: type(sentinel) is sentinel
+#
+# The bonus property is useful if you want to take the return value from
+# next_event() and do some sort of dispatch based on type(event).
+
+_T_Sentinel = TypeVar("_T_Sentinel", bound="Sentinel")
+
+
+class Sentinel(type):
+ def __new__(
+ cls: Type[_T_Sentinel],
+ name: str,
+ bases: Tuple[type, ...],
+ namespace: Dict[str, Any],
+ **kwds: Any
+ ) -> _T_Sentinel:
+ assert bases == (Sentinel,)
+ v = super().__new__(cls, name, bases, namespace, **kwds)
+ v.__class__ = v # type: ignore
+ return v
+
+ def __repr__(self) -> str:
+ return self.__name__
+
+
+# Used for methods, request targets, HTTP versions, header names, and header
+# values. Accepts ascii-strings, or bytes/bytearray/memoryview/..., and always
+# returns bytes.
+def bytesify(s: Union[bytes, bytearray, memoryview, int, str]) -> bytes:
+ # Fast-path:
+ if type(s) is bytes:
+ return s
+ if isinstance(s, str):
+ s = s.encode("ascii")
+ if isinstance(s, int):
+ raise TypeError("expected bytes-like object, not int")
+ return bytes(s)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_version.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_version.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c8911305680c1083b2da9b87ece12bc36f3a9e1
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_version.py
@@ -0,0 +1,16 @@
+# This file must be kept very simple, because it is consumed from several
+# places -- it is imported by h11/__init__.py, execfile'd by setup.py, etc.
+
+# We use a simple scheme:
+# 1.0.0 -> 1.0.0+dev -> 1.1.0 -> 1.1.0+dev
+# where the +dev versions are never released into the wild, they're just what
+# we stick into the VCS in between releases.
+#
+# This is compatible with PEP 440:
+# http://legacy.python.org/dev/peps/pep-0440/
+# via the use of the "local suffix" "+dev", which is disallowed on index
+# servers and causes 1.0.0+dev to sort after plain 1.0.0, which is what we
+# want. (Contrast with the special suffix 1.0.0.dev, which sorts *before*
+# 1.0.0.)
+
+__version__ = "0.14.0"
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_writers.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_writers.py
new file mode 100644
index 0000000000000000000000000000000000000000..939cdb912a9debaea07fbf3a9ac04549c44d077c
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/_writers.py
@@ -0,0 +1,145 @@
+# Code to read HTTP data
+#
+# Strategy: each writer takes an event + a write-some-bytes function, which is
+# calls.
+#
+# WRITERS is a dict describing how to pick a reader. It maps states to either:
+# - a writer
+# - or, for body writers, a dict of framin-dependent writer factories
+
+from typing import Any, Callable, Dict, List, Tuple, Type, Union
+
+from ._events import Data, EndOfMessage, Event, InformationalResponse, Request, Response
+from ._headers import Headers
+from ._state import CLIENT, IDLE, SEND_BODY, SEND_RESPONSE, SERVER
+from ._util import LocalProtocolError, Sentinel
+
+__all__ = ["WRITERS"]
+
+Writer = Callable[[bytes], Any]
+
+
+def write_headers(headers: Headers, write: Writer) -> None:
+ # "Since the Host field-value is critical information for handling a
+ # request, a user agent SHOULD generate Host as the first header field
+ # following the request-line." - RFC 7230
+ raw_items = headers._full_items
+ for raw_name, name, value in raw_items:
+ if name == b"host":
+ write(b"%s: %s\r\n" % (raw_name, value))
+ for raw_name, name, value in raw_items:
+ if name != b"host":
+ write(b"%s: %s\r\n" % (raw_name, value))
+ write(b"\r\n")
+
+
+def write_request(request: Request, write: Writer) -> None:
+ if request.http_version != b"1.1":
+ raise LocalProtocolError("I only send HTTP/1.1")
+ write(b"%s %s HTTP/1.1\r\n" % (request.method, request.target))
+ write_headers(request.headers, write)
+
+
+# Shared between InformationalResponse and Response
+def write_any_response(
+ response: Union[InformationalResponse, Response], write: Writer
+) -> None:
+ if response.http_version != b"1.1":
+ raise LocalProtocolError("I only send HTTP/1.1")
+ status_bytes = str(response.status_code).encode("ascii")
+ # We don't bother sending ascii status messages like "OK"; they're
+ # optional and ignored by the protocol. (But the space after the numeric
+ # status code is mandatory.)
+ #
+ # XX FIXME: could at least make an effort to pull out the status message
+ # from stdlib's http.HTTPStatus table. Or maybe just steal their enums
+ # (either by import or copy/paste). We already accept them as status codes
+ # since they're of type IntEnum < int.
+ write(b"HTTP/1.1 %s %s\r\n" % (status_bytes, response.reason))
+ write_headers(response.headers, write)
+
+
+class BodyWriter:
+ def __call__(self, event: Event, write: Writer) -> None:
+ if type(event) is Data:
+ self.send_data(event.data, write)
+ elif type(event) is EndOfMessage:
+ self.send_eom(event.headers, write)
+ else: # pragma: no cover
+ assert False
+
+ def send_data(self, data: bytes, write: Writer) -> None:
+ pass
+
+ def send_eom(self, headers: Headers, write: Writer) -> None:
+ pass
+
+
+#
+# These are all careful not to do anything to 'data' except call len(data) and
+# write(data). This allows us to transparently pass-through funny objects,
+# like placeholder objects referring to files on disk that will be sent via
+# sendfile(2).
+#
+class ContentLengthWriter(BodyWriter):
+ def __init__(self, length: int) -> None:
+ self._length = length
+
+ def send_data(self, data: bytes, write: Writer) -> None:
+ self._length -= len(data)
+ if self._length < 0:
+ raise LocalProtocolError("Too much data for declared Content-Length")
+ write(data)
+
+ def send_eom(self, headers: Headers, write: Writer) -> None:
+ if self._length != 0:
+ raise LocalProtocolError("Too little data for declared Content-Length")
+ if headers:
+ raise LocalProtocolError("Content-Length and trailers don't mix")
+
+
+class ChunkedWriter(BodyWriter):
+ def send_data(self, data: bytes, write: Writer) -> None:
+ # if we encoded 0-length data in the naive way, it would look like an
+ # end-of-message.
+ if not data:
+ return
+ write(b"%x\r\n" % len(data))
+ write(data)
+ write(b"\r\n")
+
+ def send_eom(self, headers: Headers, write: Writer) -> None:
+ write(b"0\r\n")
+ write_headers(headers, write)
+
+
+class Http10Writer(BodyWriter):
+ def send_data(self, data: bytes, write: Writer) -> None:
+ write(data)
+
+ def send_eom(self, headers: Headers, write: Writer) -> None:
+ if headers:
+ raise LocalProtocolError("can't send trailers to HTTP/1.0 client")
+ # no need to close the socket ourselves, that will be taken care of by
+ # Connection: close machinery
+
+
+WritersType = Dict[
+ Union[Tuple[Type[Sentinel], Type[Sentinel]], Type[Sentinel]],
+ Union[
+ Dict[str, Type[BodyWriter]],
+ Callable[[Union[InformationalResponse, Response], Writer], None],
+ Callable[[Request, Writer], None],
+ ],
+]
+
+WRITERS: WritersType = {
+ (CLIENT, IDLE): write_request,
+ (SERVER, IDLE): write_any_response,
+ (SERVER, SEND_RESPONSE): write_any_response,
+ SEND_BODY: {
+ "chunked": ChunkedWriter,
+ "content-length": ContentLengthWriter,
+ "http/1.0": Http10Writer,
+ },
+}
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..f5642f79f21d872f010979dcf6f0c4a415acc19d
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/h11/py.typed
@@ -0,0 +1 @@
+Marker
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..b0d2b196385e98259971519793447c1fd7a9a643
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/METADATA
@@ -0,0 +1,203 @@
+Metadata-Version: 2.3
+Name: httpx
+Version: 0.28.1
+Summary: The next generation HTTP client.
+Project-URL: Changelog, https://github.com/encode/httpx/blob/master/CHANGELOG.md
+Project-URL: Documentation, https://www.python-httpx.org
+Project-URL: Homepage, https://github.com/encode/httpx
+Project-URL: Source, https://github.com/encode/httpx
+Author-email: Tom Christie
+License: BSD-3-Clause
+Classifier: Development Status :: 4 - Beta
+Classifier: Environment :: Web Environment
+Classifier: Framework :: AsyncIO
+Classifier: Framework :: Trio
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Topic :: Internet :: WWW/HTTP
+Requires-Python: >=3.8
+Requires-Dist: anyio
+Requires-Dist: certifi
+Requires-Dist: httpcore==1.*
+Requires-Dist: idna
+Provides-Extra: brotli
+Requires-Dist: brotli; (platform_python_implementation == 'CPython') and extra == 'brotli'
+Requires-Dist: brotlicffi; (platform_python_implementation != 'CPython') and extra == 'brotli'
+Provides-Extra: cli
+Requires-Dist: click==8.*; extra == 'cli'
+Requires-Dist: pygments==2.*; extra == 'cli'
+Requires-Dist: rich<14,>=10; extra == 'cli'
+Provides-Extra: http2
+Requires-Dist: h2<5,>=3; extra == 'http2'
+Provides-Extra: socks
+Requires-Dist: socksio==1.*; extra == 'socks'
+Provides-Extra: zstd
+Requires-Dist: zstandard>=0.18.0; extra == 'zstd'
+Description-Content-Type: text/markdown
+
+
+
+HTTPX is a fully featured HTTP client library for Python 3. It includes **an integrated command line client**, has support for both **HTTP/1.1 and HTTP/2**, and provides both **sync and async APIs**.
+
+---
+
+Install HTTPX using pip:
+
+```shell
+$ pip install httpx
+```
+
+Now, let's get started:
+
+```pycon
+>>> import httpx
+>>> r = httpx.get('https://www.example.org/')
+>>> r
+
+>>> r.status_code
+200
+>>> r.headers['content-type']
+'text/html; charset=UTF-8'
+>>> r.text
+'\n\n\nExample Domain...'
+```
+
+Or, using the command-line client.
+
+```shell
+$ pip install 'httpx[cli]' # The command line client is an optional dependency.
+```
+
+Which now allows us to use HTTPX directly from the command-line...
+
+
+
+
+
+Sending a request...
+
+
+
+
+
+## Features
+
+HTTPX builds on the well-established usability of `requests`, and gives you:
+
+* A broadly [requests-compatible API](https://www.python-httpx.org/compatibility/).
+* An integrated command-line client.
+* HTTP/1.1 [and HTTP/2 support](https://www.python-httpx.org/http2/).
+* Standard synchronous interface, but with [async support if you need it](https://www.python-httpx.org/async/).
+* Ability to make requests directly to [WSGI applications](https://www.python-httpx.org/advanced/transports/#wsgi-transport) or [ASGI applications](https://www.python-httpx.org/advanced/transports/#asgi-transport).
+* Strict timeouts everywhere.
+* Fully type annotated.
+* 100% test coverage.
+
+Plus all the standard features of `requests`...
+
+* International Domains and URLs
+* Keep-Alive & Connection Pooling
+* Sessions with Cookie Persistence
+* Browser-style SSL Verification
+* Basic/Digest Authentication
+* Elegant Key/Value Cookies
+* Automatic Decompression
+* Automatic Content Decoding
+* Unicode Response Bodies
+* Multipart File Uploads
+* HTTP(S) Proxy Support
+* Connection Timeouts
+* Streaming Downloads
+* .netrc Support
+* Chunked Requests
+
+## Installation
+
+Install with pip:
+
+```shell
+$ pip install httpx
+```
+
+Or, to include the optional HTTP/2 support, use:
+
+```shell
+$ pip install httpx[http2]
+```
+
+HTTPX requires Python 3.8+.
+
+## Documentation
+
+Project documentation is available at [https://www.python-httpx.org/](https://www.python-httpx.org/).
+
+For a run-through of all the basics, head over to the [QuickStart](https://www.python-httpx.org/quickstart/).
+
+For more advanced topics, see the [Advanced Usage](https://www.python-httpx.org/advanced/) section, the [async support](https://www.python-httpx.org/async/) section, or the [HTTP/2](https://www.python-httpx.org/http2/) section.
+
+The [Developer Interface](https://www.python-httpx.org/api/) provides a comprehensive API reference.
+
+To find out about tools that integrate with HTTPX, see [Third Party Packages](https://www.python-httpx.org/third_party_packages/).
+
+## Contribute
+
+If you want to contribute with HTTPX check out the [Contributing Guide](https://www.python-httpx.org/contributing/) to learn how to start.
+
+## Dependencies
+
+The HTTPX project relies on these excellent libraries:
+
+* `httpcore` - The underlying transport implementation for `httpx`.
+ * `h11` - HTTP/1.1 support.
+* `certifi` - SSL certificates.
+* `idna` - Internationalized domain name support.
+* `sniffio` - Async library autodetection.
+
+As well as these optional installs:
+
+* `h2` - HTTP/2 support. *(Optional, with `httpx[http2]`)*
+* `socksio` - SOCKS proxy support. *(Optional, with `httpx[socks]`)*
+* `rich` - Rich terminal support. *(Optional, with `httpx[cli]`)*
+* `click` - Command line client support. *(Optional, with `httpx[cli]`)*
+* `brotli` or `brotlicffi` - Decoding for "brotli" compressed responses. *(Optional, with `httpx[brotli]`)*
+* `zstandard` - Decoding for "zstd" compressed responses. *(Optional, with `httpx[zstd]`)*
+
+A huge amount of credit is due to `requests` for the API layout that
+much of this work follows, as well as to `urllib3` for plenty of design
+inspiration around the lower-level networking details.
+
+---
+
+
HTTPX is BSD licensed code. Designed & crafted with care. — 🦋 —
+
+## Release Information
+
+### Fixed
+
+* Reintroduced supposedly-private `URLTypes` shortcut. (#2673)
+
+
+---
+
+[Full changelog](https://github.com/encode/httpx/blob/master/CHANGELOG.md)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..ed2357ac6a645e13daaa4c3f052b954713456eeb
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/RECORD
@@ -0,0 +1,54 @@
+../../../bin/httpx,sha256=lxjYkAMaJIXutlZ3C2l09JQzBTPkImHPs8HhUnXeV70,266
+httpx-0.28.1.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+httpx-0.28.1.dist-info/METADATA,sha256=_rubD48-gNV8gZnDBPNcQzboWB0dGNeYPJJ2a4J5OyU,7052
+httpx-0.28.1.dist-info/RECORD,,
+httpx-0.28.1.dist-info/WHEEL,sha256=C2FUgwZgiLbznR-k0b_5k3Ai_1aASOXDss3lzCUsUug,87
+httpx-0.28.1.dist-info/entry_points.txt,sha256=2lVkdQmxLA1pNMgSN2eV89o90HCZezhmNwsy6ryKDSA,37
+httpx-0.28.1.dist-info/licenses/LICENSE.md,sha256=TsWdVE8StfU5o6cW_TIaxYzNgDC0ZSIfLIgCAM3yjY0,1508
+httpx/__init__.py,sha256=CsaZe6yZj0rHg6322AWKWHGTMVr9txgEfD5P3_Rrz60,2171
+httpx/__pycache__/__init__.cpython-312.pyc,,
+httpx/__pycache__/__version__.cpython-312.pyc,,
+httpx/__pycache__/_api.cpython-312.pyc,,
+httpx/__pycache__/_auth.cpython-312.pyc,,
+httpx/__pycache__/_client.cpython-312.pyc,,
+httpx/__pycache__/_config.cpython-312.pyc,,
+httpx/__pycache__/_content.cpython-312.pyc,,
+httpx/__pycache__/_decoders.cpython-312.pyc,,
+httpx/__pycache__/_exceptions.cpython-312.pyc,,
+httpx/__pycache__/_main.cpython-312.pyc,,
+httpx/__pycache__/_models.cpython-312.pyc,,
+httpx/__pycache__/_multipart.cpython-312.pyc,,
+httpx/__pycache__/_status_codes.cpython-312.pyc,,
+httpx/__pycache__/_types.cpython-312.pyc,,
+httpx/__pycache__/_urlparse.cpython-312.pyc,,
+httpx/__pycache__/_urls.cpython-312.pyc,,
+httpx/__pycache__/_utils.cpython-312.pyc,,
+httpx/__version__.py,sha256=LoUyYeOXTieGzuP_64UL0wxdtxjuu_QbOvE7NOg-IqU,108
+httpx/_api.py,sha256=r_Zgs4jIpcPJLqK5dbbSayqo_iVMKFaxZCd-oOHxLEs,11743
+httpx/_auth.py,sha256=Yr3QwaUSK17rGYx-7j-FdicFIzz4Y9FFV-1F4-7RXX4,11891
+httpx/_client.py,sha256=xD-UG67-WMkeltAAOeGGj-cZ2RRTAm19sWRxlFY7_40,65714
+httpx/_config.py,sha256=pPp2U-wicfcKsF-KYRE1LYdt3e6ERGeIoXZ8Gjo3LWc,8547
+httpx/_content.py,sha256=LGGzrJTR3OvN4Mb1GVVNLXkXJH-6oKlwAttO9p5w_yg,8161
+httpx/_decoders.py,sha256=p0dX8I0NEHexs3UGp4SsZutiMhsXrrWl6-GnqVb0iKM,12041
+httpx/_exceptions.py,sha256=bxW7fxzgVMAdNTbwT0Vnq04gJDW1_gI_GFiQPuMyjL0,8527
+httpx/_main.py,sha256=Cg9GMabiTT_swaDfUgIRitSwxLRMSwUDOm7LdSGqlA4,15626
+httpx/_models.py,sha256=4__Guyv1gLxuZChwim8kfQNiIOcJ9acreFOSurvZfms,44700
+httpx/_multipart.py,sha256=KOHEZZl6oohg9mPaKyyu345qq1rJLg35TUG3YAzXB3Y,9843
+httpx/_status_codes.py,sha256=DYn-2ufBgMeXy5s8x3_TB7wjAuAAMewTakPrm5rXEsc,5639
+httpx/_transports/__init__.py,sha256=GbUoBSAOp7z-l-9j5YhMhR3DMIcn6FVLhj072O3Nnno,275
+httpx/_transports/__pycache__/__init__.cpython-312.pyc,,
+httpx/_transports/__pycache__/asgi.cpython-312.pyc,,
+httpx/_transports/__pycache__/base.cpython-312.pyc,,
+httpx/_transports/__pycache__/default.cpython-312.pyc,,
+httpx/_transports/__pycache__/mock.cpython-312.pyc,,
+httpx/_transports/__pycache__/wsgi.cpython-312.pyc,,
+httpx/_transports/asgi.py,sha256=HRfiDYMPt4wQH2gFgHZg4c-i3sblo6bL5GTqcET-xz8,5501
+httpx/_transports/base.py,sha256=kZS_VMbViYfF570pogUCJ1bulz-ybfL51Pqs9yktebU,2523
+httpx/_transports/default.py,sha256=AzeaRUyVwCccTyyNJexDf0n1dFfzzydpdIQgvw7PLnk,13983
+httpx/_transports/mock.py,sha256=PTo0d567RITXxGrki6kN7_67wwAxfwiMDcuXJiZCjEo,1232
+httpx/_transports/wsgi.py,sha256=NcPX3Xap_EwCFZWO_OaSyQNuInCYx1QMNbO8GAei6jY,4825
+httpx/_types.py,sha256=Jyh41GQq7AOev8IOWKDAg7zCbvHAfufmW5g_PiTtErY,2965
+httpx/_urlparse.py,sha256=ZAmH47ONfkxrrj-PPYhGeiHjb6AjKCS-ANWIN4OL_KY,18546
+httpx/_urls.py,sha256=dX99VR1DSOHpgo9Aq7PzYO4FKdxqKjwyNp8grf8dHN0,21550
+httpx/_utils.py,sha256=_TVeqAKvxJkKHdz7dFeb4s0LZqQXgeFkXSgfiHBK_1o,8285
+httpx/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..21aaa72961a8af71c17d2cb3b76d5f7f567100e4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/WHEEL
@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: hatchling 1.26.3
+Root-Is-Purelib: true
+Tag: py3-none-any
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/entry_points.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/entry_points.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8ae96007f7d725813fd02dc1d06d3834ee1939e4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/httpx-0.28.1.dist-info/entry_points.txt
@@ -0,0 +1,2 @@
+[console_scripts]
+httpx = httpx:main
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..643ef9ac20f22f22c4d2d383de4840983849ba30
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/__init__.py
@@ -0,0 +1,1554 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# ***********
+# `huggingface_hub` init has 2 modes:
+# - Normal usage:
+# If imported to use it, all modules and functions are lazy-loaded. This means
+# they exist at top level in module but are imported only the first time they are
+# used. This way, `from huggingface_hub import something` will import `something`
+# quickly without the hassle of importing all the features from `huggingface_hub`.
+# - Static check:
+# If statically analyzed, all modules and functions are loaded normally. This way
+# static typing check works properly as well as autocomplete in text editors and
+# IDEs.
+#
+# The static model imports are done inside the `if TYPE_CHECKING:` statement at
+# the bottom of this file. Since module/functions imports are duplicated, it is
+# mandatory to make sure to add them twice when adding one. This is checked in the
+# `make quality` command.
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_static_imports.py --update-file
+#
+# # Or run style on codebase
+# make style
+# ```
+#
+# ***********
+# Lazy loader vendored from https://github.com/scientific-python/lazy_loader
+import importlib
+import os
+import sys
+from typing import TYPE_CHECKING
+
+
+__version__ = "0.36.2"
+
+# Alphabetical order of definitions is ensured in tests
+# WARNING: any comment added in this dictionary definition will be lost when
+# re-generating the file !
+_SUBMOD_ATTRS = {
+ "_commit_scheduler": [
+ "CommitScheduler",
+ ],
+ "_inference_endpoints": [
+ "InferenceEndpoint",
+ "InferenceEndpointError",
+ "InferenceEndpointStatus",
+ "InferenceEndpointTimeoutError",
+ "InferenceEndpointType",
+ ],
+ "_jobs_api": [
+ "JobInfo",
+ "JobOwner",
+ "JobStage",
+ "JobStatus",
+ ],
+ "_login": [
+ "auth_list",
+ "auth_switch",
+ "interpreter_login",
+ "login",
+ "logout",
+ "notebook_login",
+ ],
+ "_oauth": [
+ "OAuthInfo",
+ "OAuthOrgInfo",
+ "OAuthUserInfo",
+ "attach_huggingface_oauth",
+ "parse_huggingface_oauth",
+ ],
+ "_snapshot_download": [
+ "snapshot_download",
+ ],
+ "_space_api": [
+ "SpaceHardware",
+ "SpaceRuntime",
+ "SpaceStage",
+ "SpaceStorage",
+ "SpaceVariable",
+ ],
+ "_tensorboard_logger": [
+ "HFSummaryWriter",
+ ],
+ "_webhooks_payload": [
+ "WebhookPayload",
+ "WebhookPayloadComment",
+ "WebhookPayloadDiscussion",
+ "WebhookPayloadDiscussionChanges",
+ "WebhookPayloadEvent",
+ "WebhookPayloadMovedTo",
+ "WebhookPayloadRepo",
+ "WebhookPayloadUrl",
+ "WebhookPayloadWebhook",
+ ],
+ "_webhooks_server": [
+ "WebhooksServer",
+ "webhook_endpoint",
+ ],
+ "community": [
+ "Discussion",
+ "DiscussionComment",
+ "DiscussionCommit",
+ "DiscussionEvent",
+ "DiscussionStatusChange",
+ "DiscussionTitleChange",
+ "DiscussionWithDetails",
+ ],
+ "constants": [
+ "CONFIG_NAME",
+ "FLAX_WEIGHTS_NAME",
+ "HUGGINGFACE_CO_URL_HOME",
+ "HUGGINGFACE_CO_URL_TEMPLATE",
+ "PYTORCH_WEIGHTS_NAME",
+ "REPO_TYPE_DATASET",
+ "REPO_TYPE_MODEL",
+ "REPO_TYPE_SPACE",
+ "TF2_WEIGHTS_NAME",
+ "TF_WEIGHTS_NAME",
+ ],
+ "fastai_utils": [
+ "_save_pretrained_fastai",
+ "from_pretrained_fastai",
+ "push_to_hub_fastai",
+ ],
+ "file_download": [
+ "HfFileMetadata",
+ "_CACHED_NO_EXIST",
+ "get_hf_file_metadata",
+ "hf_hub_download",
+ "hf_hub_url",
+ "try_to_load_from_cache",
+ ],
+ "hf_api": [
+ "Collection",
+ "CollectionItem",
+ "CommitInfo",
+ "CommitOperation",
+ "CommitOperationAdd",
+ "CommitOperationCopy",
+ "CommitOperationDelete",
+ "DatasetInfo",
+ "GitCommitInfo",
+ "GitRefInfo",
+ "GitRefs",
+ "HfApi",
+ "ModelInfo",
+ "Organization",
+ "RepoUrl",
+ "SpaceInfo",
+ "User",
+ "UserLikes",
+ "WebhookInfo",
+ "WebhookWatchedItem",
+ "accept_access_request",
+ "add_collection_item",
+ "add_space_secret",
+ "add_space_variable",
+ "auth_check",
+ "cancel_access_request",
+ "cancel_job",
+ "change_discussion_status",
+ "comment_discussion",
+ "create_branch",
+ "create_collection",
+ "create_commit",
+ "create_discussion",
+ "create_inference_endpoint",
+ "create_inference_endpoint_from_catalog",
+ "create_pull_request",
+ "create_repo",
+ "create_scheduled_job",
+ "create_scheduled_uv_job",
+ "create_tag",
+ "create_webhook",
+ "dataset_info",
+ "delete_branch",
+ "delete_collection",
+ "delete_collection_item",
+ "delete_file",
+ "delete_folder",
+ "delete_inference_endpoint",
+ "delete_repo",
+ "delete_scheduled_job",
+ "delete_space_secret",
+ "delete_space_storage",
+ "delete_space_variable",
+ "delete_tag",
+ "delete_webhook",
+ "disable_webhook",
+ "duplicate_space",
+ "edit_discussion_comment",
+ "enable_webhook",
+ "fetch_job_logs",
+ "file_exists",
+ "get_collection",
+ "get_dataset_tags",
+ "get_discussion_details",
+ "get_full_repo_name",
+ "get_inference_endpoint",
+ "get_model_tags",
+ "get_organization_overview",
+ "get_paths_info",
+ "get_repo_discussions",
+ "get_safetensors_metadata",
+ "get_space_runtime",
+ "get_space_variables",
+ "get_token_permission",
+ "get_user_overview",
+ "get_webhook",
+ "grant_access",
+ "inspect_job",
+ "inspect_scheduled_job",
+ "list_accepted_access_requests",
+ "list_collections",
+ "list_datasets",
+ "list_inference_catalog",
+ "list_inference_endpoints",
+ "list_jobs",
+ "list_lfs_files",
+ "list_liked_repos",
+ "list_models",
+ "list_organization_members",
+ "list_papers",
+ "list_pending_access_requests",
+ "list_rejected_access_requests",
+ "list_repo_commits",
+ "list_repo_files",
+ "list_repo_likers",
+ "list_repo_refs",
+ "list_repo_tree",
+ "list_spaces",
+ "list_user_followers",
+ "list_user_following",
+ "list_webhooks",
+ "merge_pull_request",
+ "model_info",
+ "move_repo",
+ "paper_info",
+ "parse_safetensors_file_metadata",
+ "pause_inference_endpoint",
+ "pause_space",
+ "permanently_delete_lfs_files",
+ "preupload_lfs_files",
+ "reject_access_request",
+ "rename_discussion",
+ "repo_exists",
+ "repo_info",
+ "repo_type_and_id_from_hf_id",
+ "request_space_hardware",
+ "request_space_storage",
+ "restart_space",
+ "resume_inference_endpoint",
+ "resume_scheduled_job",
+ "revision_exists",
+ "run_as_future",
+ "run_job",
+ "run_uv_job",
+ "scale_to_zero_inference_endpoint",
+ "set_space_sleep_time",
+ "space_info",
+ "super_squash_history",
+ "suspend_scheduled_job",
+ "unlike",
+ "update_collection_item",
+ "update_collection_metadata",
+ "update_inference_endpoint",
+ "update_repo_settings",
+ "update_repo_visibility",
+ "update_webhook",
+ "upload_file",
+ "upload_folder",
+ "upload_large_folder",
+ "whoami",
+ ],
+ "hf_file_system": [
+ "HfFileSystem",
+ "HfFileSystemFile",
+ "HfFileSystemResolvedPath",
+ "HfFileSystemStreamFile",
+ ],
+ "hub_mixin": [
+ "ModelHubMixin",
+ "PyTorchModelHubMixin",
+ ],
+ "inference._client": [
+ "InferenceClient",
+ "InferenceTimeoutError",
+ ],
+ "inference._generated._async_client": [
+ "AsyncInferenceClient",
+ ],
+ "inference._generated.types": [
+ "AudioClassificationInput",
+ "AudioClassificationOutputElement",
+ "AudioClassificationOutputTransform",
+ "AudioClassificationParameters",
+ "AudioToAudioInput",
+ "AudioToAudioOutputElement",
+ "AutomaticSpeechRecognitionEarlyStoppingEnum",
+ "AutomaticSpeechRecognitionGenerationParameters",
+ "AutomaticSpeechRecognitionInput",
+ "AutomaticSpeechRecognitionOutput",
+ "AutomaticSpeechRecognitionOutputChunk",
+ "AutomaticSpeechRecognitionParameters",
+ "ChatCompletionInput",
+ "ChatCompletionInputFunctionDefinition",
+ "ChatCompletionInputFunctionName",
+ "ChatCompletionInputGrammarType",
+ "ChatCompletionInputJSONSchema",
+ "ChatCompletionInputMessage",
+ "ChatCompletionInputMessageChunk",
+ "ChatCompletionInputMessageChunkType",
+ "ChatCompletionInputResponseFormatJSONObject",
+ "ChatCompletionInputResponseFormatJSONSchema",
+ "ChatCompletionInputResponseFormatText",
+ "ChatCompletionInputStreamOptions",
+ "ChatCompletionInputTool",
+ "ChatCompletionInputToolCall",
+ "ChatCompletionInputToolChoiceClass",
+ "ChatCompletionInputToolChoiceEnum",
+ "ChatCompletionInputURL",
+ "ChatCompletionOutput",
+ "ChatCompletionOutputComplete",
+ "ChatCompletionOutputFunctionDefinition",
+ "ChatCompletionOutputLogprob",
+ "ChatCompletionOutputLogprobs",
+ "ChatCompletionOutputMessage",
+ "ChatCompletionOutputToolCall",
+ "ChatCompletionOutputTopLogprob",
+ "ChatCompletionOutputUsage",
+ "ChatCompletionStreamOutput",
+ "ChatCompletionStreamOutputChoice",
+ "ChatCompletionStreamOutputDelta",
+ "ChatCompletionStreamOutputDeltaToolCall",
+ "ChatCompletionStreamOutputFunction",
+ "ChatCompletionStreamOutputLogprob",
+ "ChatCompletionStreamOutputLogprobs",
+ "ChatCompletionStreamOutputTopLogprob",
+ "ChatCompletionStreamOutputUsage",
+ "DepthEstimationInput",
+ "DepthEstimationOutput",
+ "DocumentQuestionAnsweringInput",
+ "DocumentQuestionAnsweringInputData",
+ "DocumentQuestionAnsweringOutputElement",
+ "DocumentQuestionAnsweringParameters",
+ "FeatureExtractionInput",
+ "FeatureExtractionInputTruncationDirection",
+ "FillMaskInput",
+ "FillMaskOutputElement",
+ "FillMaskParameters",
+ "ImageClassificationInput",
+ "ImageClassificationOutputElement",
+ "ImageClassificationOutputTransform",
+ "ImageClassificationParameters",
+ "ImageSegmentationInput",
+ "ImageSegmentationOutputElement",
+ "ImageSegmentationParameters",
+ "ImageSegmentationSubtask",
+ "ImageToImageInput",
+ "ImageToImageOutput",
+ "ImageToImageParameters",
+ "ImageToImageTargetSize",
+ "ImageToTextEarlyStoppingEnum",
+ "ImageToTextGenerationParameters",
+ "ImageToTextInput",
+ "ImageToTextOutput",
+ "ImageToTextParameters",
+ "ImageToVideoInput",
+ "ImageToVideoOutput",
+ "ImageToVideoParameters",
+ "ImageToVideoTargetSize",
+ "ObjectDetectionBoundingBox",
+ "ObjectDetectionInput",
+ "ObjectDetectionOutputElement",
+ "ObjectDetectionParameters",
+ "Padding",
+ "QuestionAnsweringInput",
+ "QuestionAnsweringInputData",
+ "QuestionAnsweringOutputElement",
+ "QuestionAnsweringParameters",
+ "SentenceSimilarityInput",
+ "SentenceSimilarityInputData",
+ "SummarizationInput",
+ "SummarizationOutput",
+ "SummarizationParameters",
+ "SummarizationTruncationStrategy",
+ "TableQuestionAnsweringInput",
+ "TableQuestionAnsweringInputData",
+ "TableQuestionAnsweringOutputElement",
+ "TableQuestionAnsweringParameters",
+ "Text2TextGenerationInput",
+ "Text2TextGenerationOutput",
+ "Text2TextGenerationParameters",
+ "Text2TextGenerationTruncationStrategy",
+ "TextClassificationInput",
+ "TextClassificationOutputElement",
+ "TextClassificationOutputTransform",
+ "TextClassificationParameters",
+ "TextGenerationInput",
+ "TextGenerationInputGenerateParameters",
+ "TextGenerationInputGrammarType",
+ "TextGenerationOutput",
+ "TextGenerationOutputBestOfSequence",
+ "TextGenerationOutputDetails",
+ "TextGenerationOutputFinishReason",
+ "TextGenerationOutputPrefillToken",
+ "TextGenerationOutputToken",
+ "TextGenerationStreamOutput",
+ "TextGenerationStreamOutputStreamDetails",
+ "TextGenerationStreamOutputToken",
+ "TextToAudioEarlyStoppingEnum",
+ "TextToAudioGenerationParameters",
+ "TextToAudioInput",
+ "TextToAudioOutput",
+ "TextToAudioParameters",
+ "TextToImageInput",
+ "TextToImageOutput",
+ "TextToImageParameters",
+ "TextToSpeechEarlyStoppingEnum",
+ "TextToSpeechGenerationParameters",
+ "TextToSpeechInput",
+ "TextToSpeechOutput",
+ "TextToSpeechParameters",
+ "TextToVideoInput",
+ "TextToVideoOutput",
+ "TextToVideoParameters",
+ "TokenClassificationAggregationStrategy",
+ "TokenClassificationInput",
+ "TokenClassificationOutputElement",
+ "TokenClassificationParameters",
+ "TranslationInput",
+ "TranslationOutput",
+ "TranslationParameters",
+ "TranslationTruncationStrategy",
+ "TypeEnum",
+ "VideoClassificationInput",
+ "VideoClassificationOutputElement",
+ "VideoClassificationOutputTransform",
+ "VideoClassificationParameters",
+ "VisualQuestionAnsweringInput",
+ "VisualQuestionAnsweringInputData",
+ "VisualQuestionAnsweringOutputElement",
+ "VisualQuestionAnsweringParameters",
+ "ZeroShotClassificationInput",
+ "ZeroShotClassificationOutputElement",
+ "ZeroShotClassificationParameters",
+ "ZeroShotImageClassificationInput",
+ "ZeroShotImageClassificationOutputElement",
+ "ZeroShotImageClassificationParameters",
+ "ZeroShotObjectDetectionBoundingBox",
+ "ZeroShotObjectDetectionInput",
+ "ZeroShotObjectDetectionOutputElement",
+ "ZeroShotObjectDetectionParameters",
+ ],
+ "inference._mcp.agent": [
+ "Agent",
+ ],
+ "inference._mcp.mcp_client": [
+ "MCPClient",
+ ],
+ "inference_api": [
+ "InferenceApi",
+ ],
+ "keras_mixin": [
+ "KerasModelHubMixin",
+ "from_pretrained_keras",
+ "push_to_hub_keras",
+ "save_pretrained_keras",
+ ],
+ "repocard": [
+ "DatasetCard",
+ "ModelCard",
+ "RepoCard",
+ "SpaceCard",
+ "metadata_eval_result",
+ "metadata_load",
+ "metadata_save",
+ "metadata_update",
+ ],
+ "repocard_data": [
+ "CardData",
+ "DatasetCardData",
+ "EvalResult",
+ "ModelCardData",
+ "SpaceCardData",
+ ],
+ "repository": [
+ "Repository",
+ ],
+ "serialization": [
+ "StateDictSplit",
+ "get_tf_storage_size",
+ "get_torch_storage_id",
+ "get_torch_storage_size",
+ "load_state_dict_from_file",
+ "load_torch_model",
+ "save_torch_model",
+ "save_torch_state_dict",
+ "split_state_dict_into_shards_factory",
+ "split_tf_state_dict_into_shards",
+ "split_torch_state_dict_into_shards",
+ ],
+ "serialization._dduf": [
+ "DDUFEntry",
+ "export_entries_as_dduf",
+ "export_folder_as_dduf",
+ "read_dduf_file",
+ ],
+ "utils": [
+ "CacheNotFound",
+ "CachedFileInfo",
+ "CachedRepoInfo",
+ "CachedRevisionInfo",
+ "CorruptedCacheException",
+ "DeleteCacheStrategy",
+ "HFCacheInfo",
+ "HfFolder",
+ "cached_assets_path",
+ "configure_http_backend",
+ "dump_environment_info",
+ "get_session",
+ "get_token",
+ "logging",
+ "scan_cache_dir",
+ ],
+}
+
+# WARNING: __all__ is generated automatically, Any manual edit will be lost when re-generating this file !
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_all_variable.py --update
+#
+# # Or run style on codebase
+# make style
+# ```
+
+__all__ = [
+ "Agent",
+ "AsyncInferenceClient",
+ "AudioClassificationInput",
+ "AudioClassificationOutputElement",
+ "AudioClassificationOutputTransform",
+ "AudioClassificationParameters",
+ "AudioToAudioInput",
+ "AudioToAudioOutputElement",
+ "AutomaticSpeechRecognitionEarlyStoppingEnum",
+ "AutomaticSpeechRecognitionGenerationParameters",
+ "AutomaticSpeechRecognitionInput",
+ "AutomaticSpeechRecognitionOutput",
+ "AutomaticSpeechRecognitionOutputChunk",
+ "AutomaticSpeechRecognitionParameters",
+ "CONFIG_NAME",
+ "CacheNotFound",
+ "CachedFileInfo",
+ "CachedRepoInfo",
+ "CachedRevisionInfo",
+ "CardData",
+ "ChatCompletionInput",
+ "ChatCompletionInputFunctionDefinition",
+ "ChatCompletionInputFunctionName",
+ "ChatCompletionInputGrammarType",
+ "ChatCompletionInputJSONSchema",
+ "ChatCompletionInputMessage",
+ "ChatCompletionInputMessageChunk",
+ "ChatCompletionInputMessageChunkType",
+ "ChatCompletionInputResponseFormatJSONObject",
+ "ChatCompletionInputResponseFormatJSONSchema",
+ "ChatCompletionInputResponseFormatText",
+ "ChatCompletionInputStreamOptions",
+ "ChatCompletionInputTool",
+ "ChatCompletionInputToolCall",
+ "ChatCompletionInputToolChoiceClass",
+ "ChatCompletionInputToolChoiceEnum",
+ "ChatCompletionInputURL",
+ "ChatCompletionOutput",
+ "ChatCompletionOutputComplete",
+ "ChatCompletionOutputFunctionDefinition",
+ "ChatCompletionOutputLogprob",
+ "ChatCompletionOutputLogprobs",
+ "ChatCompletionOutputMessage",
+ "ChatCompletionOutputToolCall",
+ "ChatCompletionOutputTopLogprob",
+ "ChatCompletionOutputUsage",
+ "ChatCompletionStreamOutput",
+ "ChatCompletionStreamOutputChoice",
+ "ChatCompletionStreamOutputDelta",
+ "ChatCompletionStreamOutputDeltaToolCall",
+ "ChatCompletionStreamOutputFunction",
+ "ChatCompletionStreamOutputLogprob",
+ "ChatCompletionStreamOutputLogprobs",
+ "ChatCompletionStreamOutputTopLogprob",
+ "ChatCompletionStreamOutputUsage",
+ "Collection",
+ "CollectionItem",
+ "CommitInfo",
+ "CommitOperation",
+ "CommitOperationAdd",
+ "CommitOperationCopy",
+ "CommitOperationDelete",
+ "CommitScheduler",
+ "CorruptedCacheException",
+ "DDUFEntry",
+ "DatasetCard",
+ "DatasetCardData",
+ "DatasetInfo",
+ "DeleteCacheStrategy",
+ "DepthEstimationInput",
+ "DepthEstimationOutput",
+ "Discussion",
+ "DiscussionComment",
+ "DiscussionCommit",
+ "DiscussionEvent",
+ "DiscussionStatusChange",
+ "DiscussionTitleChange",
+ "DiscussionWithDetails",
+ "DocumentQuestionAnsweringInput",
+ "DocumentQuestionAnsweringInputData",
+ "DocumentQuestionAnsweringOutputElement",
+ "DocumentQuestionAnsweringParameters",
+ "EvalResult",
+ "FLAX_WEIGHTS_NAME",
+ "FeatureExtractionInput",
+ "FeatureExtractionInputTruncationDirection",
+ "FillMaskInput",
+ "FillMaskOutputElement",
+ "FillMaskParameters",
+ "GitCommitInfo",
+ "GitRefInfo",
+ "GitRefs",
+ "HFCacheInfo",
+ "HFSummaryWriter",
+ "HUGGINGFACE_CO_URL_HOME",
+ "HUGGINGFACE_CO_URL_TEMPLATE",
+ "HfApi",
+ "HfFileMetadata",
+ "HfFileSystem",
+ "HfFileSystemFile",
+ "HfFileSystemResolvedPath",
+ "HfFileSystemStreamFile",
+ "HfFolder",
+ "ImageClassificationInput",
+ "ImageClassificationOutputElement",
+ "ImageClassificationOutputTransform",
+ "ImageClassificationParameters",
+ "ImageSegmentationInput",
+ "ImageSegmentationOutputElement",
+ "ImageSegmentationParameters",
+ "ImageSegmentationSubtask",
+ "ImageToImageInput",
+ "ImageToImageOutput",
+ "ImageToImageParameters",
+ "ImageToImageTargetSize",
+ "ImageToTextEarlyStoppingEnum",
+ "ImageToTextGenerationParameters",
+ "ImageToTextInput",
+ "ImageToTextOutput",
+ "ImageToTextParameters",
+ "ImageToVideoInput",
+ "ImageToVideoOutput",
+ "ImageToVideoParameters",
+ "ImageToVideoTargetSize",
+ "InferenceApi",
+ "InferenceClient",
+ "InferenceEndpoint",
+ "InferenceEndpointError",
+ "InferenceEndpointStatus",
+ "InferenceEndpointTimeoutError",
+ "InferenceEndpointType",
+ "InferenceTimeoutError",
+ "JobInfo",
+ "JobOwner",
+ "JobStage",
+ "JobStatus",
+ "KerasModelHubMixin",
+ "MCPClient",
+ "ModelCard",
+ "ModelCardData",
+ "ModelHubMixin",
+ "ModelInfo",
+ "OAuthInfo",
+ "OAuthOrgInfo",
+ "OAuthUserInfo",
+ "ObjectDetectionBoundingBox",
+ "ObjectDetectionInput",
+ "ObjectDetectionOutputElement",
+ "ObjectDetectionParameters",
+ "Organization",
+ "PYTORCH_WEIGHTS_NAME",
+ "Padding",
+ "PyTorchModelHubMixin",
+ "QuestionAnsweringInput",
+ "QuestionAnsweringInputData",
+ "QuestionAnsweringOutputElement",
+ "QuestionAnsweringParameters",
+ "REPO_TYPE_DATASET",
+ "REPO_TYPE_MODEL",
+ "REPO_TYPE_SPACE",
+ "RepoCard",
+ "RepoUrl",
+ "Repository",
+ "SentenceSimilarityInput",
+ "SentenceSimilarityInputData",
+ "SpaceCard",
+ "SpaceCardData",
+ "SpaceHardware",
+ "SpaceInfo",
+ "SpaceRuntime",
+ "SpaceStage",
+ "SpaceStorage",
+ "SpaceVariable",
+ "StateDictSplit",
+ "SummarizationInput",
+ "SummarizationOutput",
+ "SummarizationParameters",
+ "SummarizationTruncationStrategy",
+ "TF2_WEIGHTS_NAME",
+ "TF_WEIGHTS_NAME",
+ "TableQuestionAnsweringInput",
+ "TableQuestionAnsweringInputData",
+ "TableQuestionAnsweringOutputElement",
+ "TableQuestionAnsweringParameters",
+ "Text2TextGenerationInput",
+ "Text2TextGenerationOutput",
+ "Text2TextGenerationParameters",
+ "Text2TextGenerationTruncationStrategy",
+ "TextClassificationInput",
+ "TextClassificationOutputElement",
+ "TextClassificationOutputTransform",
+ "TextClassificationParameters",
+ "TextGenerationInput",
+ "TextGenerationInputGenerateParameters",
+ "TextGenerationInputGrammarType",
+ "TextGenerationOutput",
+ "TextGenerationOutputBestOfSequence",
+ "TextGenerationOutputDetails",
+ "TextGenerationOutputFinishReason",
+ "TextGenerationOutputPrefillToken",
+ "TextGenerationOutputToken",
+ "TextGenerationStreamOutput",
+ "TextGenerationStreamOutputStreamDetails",
+ "TextGenerationStreamOutputToken",
+ "TextToAudioEarlyStoppingEnum",
+ "TextToAudioGenerationParameters",
+ "TextToAudioInput",
+ "TextToAudioOutput",
+ "TextToAudioParameters",
+ "TextToImageInput",
+ "TextToImageOutput",
+ "TextToImageParameters",
+ "TextToSpeechEarlyStoppingEnum",
+ "TextToSpeechGenerationParameters",
+ "TextToSpeechInput",
+ "TextToSpeechOutput",
+ "TextToSpeechParameters",
+ "TextToVideoInput",
+ "TextToVideoOutput",
+ "TextToVideoParameters",
+ "TokenClassificationAggregationStrategy",
+ "TokenClassificationInput",
+ "TokenClassificationOutputElement",
+ "TokenClassificationParameters",
+ "TranslationInput",
+ "TranslationOutput",
+ "TranslationParameters",
+ "TranslationTruncationStrategy",
+ "TypeEnum",
+ "User",
+ "UserLikes",
+ "VideoClassificationInput",
+ "VideoClassificationOutputElement",
+ "VideoClassificationOutputTransform",
+ "VideoClassificationParameters",
+ "VisualQuestionAnsweringInput",
+ "VisualQuestionAnsweringInputData",
+ "VisualQuestionAnsweringOutputElement",
+ "VisualQuestionAnsweringParameters",
+ "WebhookInfo",
+ "WebhookPayload",
+ "WebhookPayloadComment",
+ "WebhookPayloadDiscussion",
+ "WebhookPayloadDiscussionChanges",
+ "WebhookPayloadEvent",
+ "WebhookPayloadMovedTo",
+ "WebhookPayloadRepo",
+ "WebhookPayloadUrl",
+ "WebhookPayloadWebhook",
+ "WebhookWatchedItem",
+ "WebhooksServer",
+ "ZeroShotClassificationInput",
+ "ZeroShotClassificationOutputElement",
+ "ZeroShotClassificationParameters",
+ "ZeroShotImageClassificationInput",
+ "ZeroShotImageClassificationOutputElement",
+ "ZeroShotImageClassificationParameters",
+ "ZeroShotObjectDetectionBoundingBox",
+ "ZeroShotObjectDetectionInput",
+ "ZeroShotObjectDetectionOutputElement",
+ "ZeroShotObjectDetectionParameters",
+ "_CACHED_NO_EXIST",
+ "_save_pretrained_fastai",
+ "accept_access_request",
+ "add_collection_item",
+ "add_space_secret",
+ "add_space_variable",
+ "attach_huggingface_oauth",
+ "auth_check",
+ "auth_list",
+ "auth_switch",
+ "cached_assets_path",
+ "cancel_access_request",
+ "cancel_job",
+ "change_discussion_status",
+ "comment_discussion",
+ "configure_http_backend",
+ "create_branch",
+ "create_collection",
+ "create_commit",
+ "create_discussion",
+ "create_inference_endpoint",
+ "create_inference_endpoint_from_catalog",
+ "create_pull_request",
+ "create_repo",
+ "create_scheduled_job",
+ "create_scheduled_uv_job",
+ "create_tag",
+ "create_webhook",
+ "dataset_info",
+ "delete_branch",
+ "delete_collection",
+ "delete_collection_item",
+ "delete_file",
+ "delete_folder",
+ "delete_inference_endpoint",
+ "delete_repo",
+ "delete_scheduled_job",
+ "delete_space_secret",
+ "delete_space_storage",
+ "delete_space_variable",
+ "delete_tag",
+ "delete_webhook",
+ "disable_webhook",
+ "dump_environment_info",
+ "duplicate_space",
+ "edit_discussion_comment",
+ "enable_webhook",
+ "export_entries_as_dduf",
+ "export_folder_as_dduf",
+ "fetch_job_logs",
+ "file_exists",
+ "from_pretrained_fastai",
+ "from_pretrained_keras",
+ "get_collection",
+ "get_dataset_tags",
+ "get_discussion_details",
+ "get_full_repo_name",
+ "get_hf_file_metadata",
+ "get_inference_endpoint",
+ "get_model_tags",
+ "get_organization_overview",
+ "get_paths_info",
+ "get_repo_discussions",
+ "get_safetensors_metadata",
+ "get_session",
+ "get_space_runtime",
+ "get_space_variables",
+ "get_tf_storage_size",
+ "get_token",
+ "get_token_permission",
+ "get_torch_storage_id",
+ "get_torch_storage_size",
+ "get_user_overview",
+ "get_webhook",
+ "grant_access",
+ "hf_hub_download",
+ "hf_hub_url",
+ "inspect_job",
+ "inspect_scheduled_job",
+ "interpreter_login",
+ "list_accepted_access_requests",
+ "list_collections",
+ "list_datasets",
+ "list_inference_catalog",
+ "list_inference_endpoints",
+ "list_jobs",
+ "list_lfs_files",
+ "list_liked_repos",
+ "list_models",
+ "list_organization_members",
+ "list_papers",
+ "list_pending_access_requests",
+ "list_rejected_access_requests",
+ "list_repo_commits",
+ "list_repo_files",
+ "list_repo_likers",
+ "list_repo_refs",
+ "list_repo_tree",
+ "list_spaces",
+ "list_user_followers",
+ "list_user_following",
+ "list_webhooks",
+ "load_state_dict_from_file",
+ "load_torch_model",
+ "logging",
+ "login",
+ "logout",
+ "merge_pull_request",
+ "metadata_eval_result",
+ "metadata_load",
+ "metadata_save",
+ "metadata_update",
+ "model_info",
+ "move_repo",
+ "notebook_login",
+ "paper_info",
+ "parse_huggingface_oauth",
+ "parse_safetensors_file_metadata",
+ "pause_inference_endpoint",
+ "pause_space",
+ "permanently_delete_lfs_files",
+ "preupload_lfs_files",
+ "push_to_hub_fastai",
+ "push_to_hub_keras",
+ "read_dduf_file",
+ "reject_access_request",
+ "rename_discussion",
+ "repo_exists",
+ "repo_info",
+ "repo_type_and_id_from_hf_id",
+ "request_space_hardware",
+ "request_space_storage",
+ "restart_space",
+ "resume_inference_endpoint",
+ "resume_scheduled_job",
+ "revision_exists",
+ "run_as_future",
+ "run_job",
+ "run_uv_job",
+ "save_pretrained_keras",
+ "save_torch_model",
+ "save_torch_state_dict",
+ "scale_to_zero_inference_endpoint",
+ "scan_cache_dir",
+ "set_space_sleep_time",
+ "snapshot_download",
+ "space_info",
+ "split_state_dict_into_shards_factory",
+ "split_tf_state_dict_into_shards",
+ "split_torch_state_dict_into_shards",
+ "super_squash_history",
+ "suspend_scheduled_job",
+ "try_to_load_from_cache",
+ "unlike",
+ "update_collection_item",
+ "update_collection_metadata",
+ "update_inference_endpoint",
+ "update_repo_settings",
+ "update_repo_visibility",
+ "update_webhook",
+ "upload_file",
+ "upload_folder",
+ "upload_large_folder",
+ "webhook_endpoint",
+ "whoami",
+]
+
+
+def _attach(package_name, submodules=None, submod_attrs=None):
+ """Attach lazily loaded submodules, functions, or other attributes.
+
+ Typically, modules import submodules and attributes as follows:
+
+ ```py
+ import mysubmodule
+ import anothersubmodule
+
+ from .foo import someattr
+ ```
+
+ The idea is to replace a package's `__getattr__`, `__dir__`, such that all imports
+ work exactly the way they would with normal imports, except that the import occurs
+ upon first use.
+
+ The typical way to call this function, replacing the above imports, is:
+
+ ```python
+ __getattr__, __dir__ = lazy.attach(
+ __name__,
+ ['mysubmodule', 'anothersubmodule'],
+ {'foo': ['someattr']}
+ )
+ ```
+ This functionality requires Python 3.7 or higher.
+
+ Args:
+ package_name (`str`):
+ Typically use `__name__`.
+ submodules (`set`):
+ List of submodules to attach.
+ submod_attrs (`dict`):
+ Dictionary of submodule -> list of attributes / functions.
+ These attributes are imported as they are used.
+
+ Returns:
+ __getattr__, __dir__, __all__
+
+ """
+ if submod_attrs is None:
+ submod_attrs = {}
+
+ if submodules is None:
+ submodules = set()
+ else:
+ submodules = set(submodules)
+
+ attr_to_modules = {attr: mod for mod, attrs in submod_attrs.items() for attr in attrs}
+
+ def __getattr__(name):
+ if name in submodules:
+ try:
+ return importlib.import_module(f"{package_name}.{name}")
+ except Exception as e:
+ print(f"Error importing {package_name}.{name}: {e}")
+ raise
+ elif name in attr_to_modules:
+ submod_path = f"{package_name}.{attr_to_modules[name]}"
+ try:
+ submod = importlib.import_module(submod_path)
+ except Exception as e:
+ print(f"Error importing {submod_path}: {e}")
+ raise
+ attr = getattr(submod, name)
+
+ # If the attribute lives in a file (module) with the same
+ # name as the attribute, ensure that the attribute and *not*
+ # the module is accessible on the package.
+ if name == attr_to_modules[name]:
+ pkg = sys.modules[package_name]
+ pkg.__dict__[name] = attr
+
+ return attr
+ else:
+ raise AttributeError(f"No {package_name} attribute {name}")
+
+ def __dir__():
+ return __all__
+
+ return __getattr__, __dir__
+
+
+__getattr__, __dir__ = _attach(__name__, submodules=[], submod_attrs=_SUBMOD_ATTRS)
+
+if os.environ.get("EAGER_IMPORT", ""):
+ for attr in __all__:
+ __getattr__(attr)
+
+# WARNING: any content below this statement is generated automatically. Any manual edit
+# will be lost when re-generating this file !
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_static_imports.py --update
+#
+# # Or run style on codebase
+# make style
+# ```
+if TYPE_CHECKING: # pragma: no cover
+ from ._commit_scheduler import CommitScheduler # noqa: F401
+ from ._inference_endpoints import (
+ InferenceEndpoint, # noqa: F401
+ InferenceEndpointError, # noqa: F401
+ InferenceEndpointStatus, # noqa: F401
+ InferenceEndpointTimeoutError, # noqa: F401
+ InferenceEndpointType, # noqa: F401
+ )
+ from ._jobs_api import (
+ JobInfo, # noqa: F401
+ JobOwner, # noqa: F401
+ JobStage, # noqa: F401
+ JobStatus, # noqa: F401
+ )
+ from ._login import (
+ auth_list, # noqa: F401
+ auth_switch, # noqa: F401
+ interpreter_login, # noqa: F401
+ login, # noqa: F401
+ logout, # noqa: F401
+ notebook_login, # noqa: F401
+ )
+ from ._oauth import (
+ OAuthInfo, # noqa: F401
+ OAuthOrgInfo, # noqa: F401
+ OAuthUserInfo, # noqa: F401
+ attach_huggingface_oauth, # noqa: F401
+ parse_huggingface_oauth, # noqa: F401
+ )
+ from ._snapshot_download import snapshot_download # noqa: F401
+ from ._space_api import (
+ SpaceHardware, # noqa: F401
+ SpaceRuntime, # noqa: F401
+ SpaceStage, # noqa: F401
+ SpaceStorage, # noqa: F401
+ SpaceVariable, # noqa: F401
+ )
+ from ._tensorboard_logger import HFSummaryWriter # noqa: F401
+ from ._webhooks_payload import (
+ WebhookPayload, # noqa: F401
+ WebhookPayloadComment, # noqa: F401
+ WebhookPayloadDiscussion, # noqa: F401
+ WebhookPayloadDiscussionChanges, # noqa: F401
+ WebhookPayloadEvent, # noqa: F401
+ WebhookPayloadMovedTo, # noqa: F401
+ WebhookPayloadRepo, # noqa: F401
+ WebhookPayloadUrl, # noqa: F401
+ WebhookPayloadWebhook, # noqa: F401
+ )
+ from ._webhooks_server import (
+ WebhooksServer, # noqa: F401
+ webhook_endpoint, # noqa: F401
+ )
+ from .community import (
+ Discussion, # noqa: F401
+ DiscussionComment, # noqa: F401
+ DiscussionCommit, # noqa: F401
+ DiscussionEvent, # noqa: F401
+ DiscussionStatusChange, # noqa: F401
+ DiscussionTitleChange, # noqa: F401
+ DiscussionWithDetails, # noqa: F401
+ )
+ from .constants import (
+ CONFIG_NAME, # noqa: F401
+ FLAX_WEIGHTS_NAME, # noqa: F401
+ HUGGINGFACE_CO_URL_HOME, # noqa: F401
+ HUGGINGFACE_CO_URL_TEMPLATE, # noqa: F401
+ PYTORCH_WEIGHTS_NAME, # noqa: F401
+ REPO_TYPE_DATASET, # noqa: F401
+ REPO_TYPE_MODEL, # noqa: F401
+ REPO_TYPE_SPACE, # noqa: F401
+ TF2_WEIGHTS_NAME, # noqa: F401
+ TF_WEIGHTS_NAME, # noqa: F401
+ )
+ from .fastai_utils import (
+ _save_pretrained_fastai, # noqa: F401
+ from_pretrained_fastai, # noqa: F401
+ push_to_hub_fastai, # noqa: F401
+ )
+ from .file_download import (
+ _CACHED_NO_EXIST, # noqa: F401
+ HfFileMetadata, # noqa: F401
+ get_hf_file_metadata, # noqa: F401
+ hf_hub_download, # noqa: F401
+ hf_hub_url, # noqa: F401
+ try_to_load_from_cache, # noqa: F401
+ )
+ from .hf_api import (
+ Collection, # noqa: F401
+ CollectionItem, # noqa: F401
+ CommitInfo, # noqa: F401
+ CommitOperation, # noqa: F401
+ CommitOperationAdd, # noqa: F401
+ CommitOperationCopy, # noqa: F401
+ CommitOperationDelete, # noqa: F401
+ DatasetInfo, # noqa: F401
+ GitCommitInfo, # noqa: F401
+ GitRefInfo, # noqa: F401
+ GitRefs, # noqa: F401
+ HfApi, # noqa: F401
+ ModelInfo, # noqa: F401
+ Organization, # noqa: F401
+ RepoUrl, # noqa: F401
+ SpaceInfo, # noqa: F401
+ User, # noqa: F401
+ UserLikes, # noqa: F401
+ WebhookInfo, # noqa: F401
+ WebhookWatchedItem, # noqa: F401
+ accept_access_request, # noqa: F401
+ add_collection_item, # noqa: F401
+ add_space_secret, # noqa: F401
+ add_space_variable, # noqa: F401
+ auth_check, # noqa: F401
+ cancel_access_request, # noqa: F401
+ cancel_job, # noqa: F401
+ change_discussion_status, # noqa: F401
+ comment_discussion, # noqa: F401
+ create_branch, # noqa: F401
+ create_collection, # noqa: F401
+ create_commit, # noqa: F401
+ create_discussion, # noqa: F401
+ create_inference_endpoint, # noqa: F401
+ create_inference_endpoint_from_catalog, # noqa: F401
+ create_pull_request, # noqa: F401
+ create_repo, # noqa: F401
+ create_scheduled_job, # noqa: F401
+ create_scheduled_uv_job, # noqa: F401
+ create_tag, # noqa: F401
+ create_webhook, # noqa: F401
+ dataset_info, # noqa: F401
+ delete_branch, # noqa: F401
+ delete_collection, # noqa: F401
+ delete_collection_item, # noqa: F401
+ delete_file, # noqa: F401
+ delete_folder, # noqa: F401
+ delete_inference_endpoint, # noqa: F401
+ delete_repo, # noqa: F401
+ delete_scheduled_job, # noqa: F401
+ delete_space_secret, # noqa: F401
+ delete_space_storage, # noqa: F401
+ delete_space_variable, # noqa: F401
+ delete_tag, # noqa: F401
+ delete_webhook, # noqa: F401
+ disable_webhook, # noqa: F401
+ duplicate_space, # noqa: F401
+ edit_discussion_comment, # noqa: F401
+ enable_webhook, # noqa: F401
+ fetch_job_logs, # noqa: F401
+ file_exists, # noqa: F401
+ get_collection, # noqa: F401
+ get_dataset_tags, # noqa: F401
+ get_discussion_details, # noqa: F401
+ get_full_repo_name, # noqa: F401
+ get_inference_endpoint, # noqa: F401
+ get_model_tags, # noqa: F401
+ get_organization_overview, # noqa: F401
+ get_paths_info, # noqa: F401
+ get_repo_discussions, # noqa: F401
+ get_safetensors_metadata, # noqa: F401
+ get_space_runtime, # noqa: F401
+ get_space_variables, # noqa: F401
+ get_token_permission, # noqa: F401
+ get_user_overview, # noqa: F401
+ get_webhook, # noqa: F401
+ grant_access, # noqa: F401
+ inspect_job, # noqa: F401
+ inspect_scheduled_job, # noqa: F401
+ list_accepted_access_requests, # noqa: F401
+ list_collections, # noqa: F401
+ list_datasets, # noqa: F401
+ list_inference_catalog, # noqa: F401
+ list_inference_endpoints, # noqa: F401
+ list_jobs, # noqa: F401
+ list_lfs_files, # noqa: F401
+ list_liked_repos, # noqa: F401
+ list_models, # noqa: F401
+ list_organization_members, # noqa: F401
+ list_papers, # noqa: F401
+ list_pending_access_requests, # noqa: F401
+ list_rejected_access_requests, # noqa: F401
+ list_repo_commits, # noqa: F401
+ list_repo_files, # noqa: F401
+ list_repo_likers, # noqa: F401
+ list_repo_refs, # noqa: F401
+ list_repo_tree, # noqa: F401
+ list_spaces, # noqa: F401
+ list_user_followers, # noqa: F401
+ list_user_following, # noqa: F401
+ list_webhooks, # noqa: F401
+ merge_pull_request, # noqa: F401
+ model_info, # noqa: F401
+ move_repo, # noqa: F401
+ paper_info, # noqa: F401
+ parse_safetensors_file_metadata, # noqa: F401
+ pause_inference_endpoint, # noqa: F401
+ pause_space, # noqa: F401
+ permanently_delete_lfs_files, # noqa: F401
+ preupload_lfs_files, # noqa: F401
+ reject_access_request, # noqa: F401
+ rename_discussion, # noqa: F401
+ repo_exists, # noqa: F401
+ repo_info, # noqa: F401
+ repo_type_and_id_from_hf_id, # noqa: F401
+ request_space_hardware, # noqa: F401
+ request_space_storage, # noqa: F401
+ restart_space, # noqa: F401
+ resume_inference_endpoint, # noqa: F401
+ resume_scheduled_job, # noqa: F401
+ revision_exists, # noqa: F401
+ run_as_future, # noqa: F401
+ run_job, # noqa: F401
+ run_uv_job, # noqa: F401
+ scale_to_zero_inference_endpoint, # noqa: F401
+ set_space_sleep_time, # noqa: F401
+ space_info, # noqa: F401
+ super_squash_history, # noqa: F401
+ suspend_scheduled_job, # noqa: F401
+ unlike, # noqa: F401
+ update_collection_item, # noqa: F401
+ update_collection_metadata, # noqa: F401
+ update_inference_endpoint, # noqa: F401
+ update_repo_settings, # noqa: F401
+ update_repo_visibility, # noqa: F401
+ update_webhook, # noqa: F401
+ upload_file, # noqa: F401
+ upload_folder, # noqa: F401
+ upload_large_folder, # noqa: F401
+ whoami, # noqa: F401
+ )
+ from .hf_file_system import (
+ HfFileSystem, # noqa: F401
+ HfFileSystemFile, # noqa: F401
+ HfFileSystemResolvedPath, # noqa: F401
+ HfFileSystemStreamFile, # noqa: F401
+ )
+ from .hub_mixin import (
+ ModelHubMixin, # noqa: F401
+ PyTorchModelHubMixin, # noqa: F401
+ )
+ from .inference._client import (
+ InferenceClient, # noqa: F401
+ InferenceTimeoutError, # noqa: F401
+ )
+ from .inference._generated._async_client import AsyncInferenceClient # noqa: F401
+ from .inference._generated.types import (
+ AudioClassificationInput, # noqa: F401
+ AudioClassificationOutputElement, # noqa: F401
+ AudioClassificationOutputTransform, # noqa: F401
+ AudioClassificationParameters, # noqa: F401
+ AudioToAudioInput, # noqa: F401
+ AudioToAudioOutputElement, # noqa: F401
+ AutomaticSpeechRecognitionEarlyStoppingEnum, # noqa: F401
+ AutomaticSpeechRecognitionGenerationParameters, # noqa: F401
+ AutomaticSpeechRecognitionInput, # noqa: F401
+ AutomaticSpeechRecognitionOutput, # noqa: F401
+ AutomaticSpeechRecognitionOutputChunk, # noqa: F401
+ AutomaticSpeechRecognitionParameters, # noqa: F401
+ ChatCompletionInput, # noqa: F401
+ ChatCompletionInputFunctionDefinition, # noqa: F401
+ ChatCompletionInputFunctionName, # noqa: F401
+ ChatCompletionInputGrammarType, # noqa: F401
+ ChatCompletionInputJSONSchema, # noqa: F401
+ ChatCompletionInputMessage, # noqa: F401
+ ChatCompletionInputMessageChunk, # noqa: F401
+ ChatCompletionInputMessageChunkType, # noqa: F401
+ ChatCompletionInputResponseFormatJSONObject, # noqa: F401
+ ChatCompletionInputResponseFormatJSONSchema, # noqa: F401
+ ChatCompletionInputResponseFormatText, # noqa: F401
+ ChatCompletionInputStreamOptions, # noqa: F401
+ ChatCompletionInputTool, # noqa: F401
+ ChatCompletionInputToolCall, # noqa: F401
+ ChatCompletionInputToolChoiceClass, # noqa: F401
+ ChatCompletionInputToolChoiceEnum, # noqa: F401
+ ChatCompletionInputURL, # noqa: F401
+ ChatCompletionOutput, # noqa: F401
+ ChatCompletionOutputComplete, # noqa: F401
+ ChatCompletionOutputFunctionDefinition, # noqa: F401
+ ChatCompletionOutputLogprob, # noqa: F401
+ ChatCompletionOutputLogprobs, # noqa: F401
+ ChatCompletionOutputMessage, # noqa: F401
+ ChatCompletionOutputToolCall, # noqa: F401
+ ChatCompletionOutputTopLogprob, # noqa: F401
+ ChatCompletionOutputUsage, # noqa: F401
+ ChatCompletionStreamOutput, # noqa: F401
+ ChatCompletionStreamOutputChoice, # noqa: F401
+ ChatCompletionStreamOutputDelta, # noqa: F401
+ ChatCompletionStreamOutputDeltaToolCall, # noqa: F401
+ ChatCompletionStreamOutputFunction, # noqa: F401
+ ChatCompletionStreamOutputLogprob, # noqa: F401
+ ChatCompletionStreamOutputLogprobs, # noqa: F401
+ ChatCompletionStreamOutputTopLogprob, # noqa: F401
+ ChatCompletionStreamOutputUsage, # noqa: F401
+ DepthEstimationInput, # noqa: F401
+ DepthEstimationOutput, # noqa: F401
+ DocumentQuestionAnsweringInput, # noqa: F401
+ DocumentQuestionAnsweringInputData, # noqa: F401
+ DocumentQuestionAnsweringOutputElement, # noqa: F401
+ DocumentQuestionAnsweringParameters, # noqa: F401
+ FeatureExtractionInput, # noqa: F401
+ FeatureExtractionInputTruncationDirection, # noqa: F401
+ FillMaskInput, # noqa: F401
+ FillMaskOutputElement, # noqa: F401
+ FillMaskParameters, # noqa: F401
+ ImageClassificationInput, # noqa: F401
+ ImageClassificationOutputElement, # noqa: F401
+ ImageClassificationOutputTransform, # noqa: F401
+ ImageClassificationParameters, # noqa: F401
+ ImageSegmentationInput, # noqa: F401
+ ImageSegmentationOutputElement, # noqa: F401
+ ImageSegmentationParameters, # noqa: F401
+ ImageSegmentationSubtask, # noqa: F401
+ ImageToImageInput, # noqa: F401
+ ImageToImageOutput, # noqa: F401
+ ImageToImageParameters, # noqa: F401
+ ImageToImageTargetSize, # noqa: F401
+ ImageToTextEarlyStoppingEnum, # noqa: F401
+ ImageToTextGenerationParameters, # noqa: F401
+ ImageToTextInput, # noqa: F401
+ ImageToTextOutput, # noqa: F401
+ ImageToTextParameters, # noqa: F401
+ ImageToVideoInput, # noqa: F401
+ ImageToVideoOutput, # noqa: F401
+ ImageToVideoParameters, # noqa: F401
+ ImageToVideoTargetSize, # noqa: F401
+ ObjectDetectionBoundingBox, # noqa: F401
+ ObjectDetectionInput, # noqa: F401
+ ObjectDetectionOutputElement, # noqa: F401
+ ObjectDetectionParameters, # noqa: F401
+ Padding, # noqa: F401
+ QuestionAnsweringInput, # noqa: F401
+ QuestionAnsweringInputData, # noqa: F401
+ QuestionAnsweringOutputElement, # noqa: F401
+ QuestionAnsweringParameters, # noqa: F401
+ SentenceSimilarityInput, # noqa: F401
+ SentenceSimilarityInputData, # noqa: F401
+ SummarizationInput, # noqa: F401
+ SummarizationOutput, # noqa: F401
+ SummarizationParameters, # noqa: F401
+ SummarizationTruncationStrategy, # noqa: F401
+ TableQuestionAnsweringInput, # noqa: F401
+ TableQuestionAnsweringInputData, # noqa: F401
+ TableQuestionAnsweringOutputElement, # noqa: F401
+ TableQuestionAnsweringParameters, # noqa: F401
+ Text2TextGenerationInput, # noqa: F401
+ Text2TextGenerationOutput, # noqa: F401
+ Text2TextGenerationParameters, # noqa: F401
+ Text2TextGenerationTruncationStrategy, # noqa: F401
+ TextClassificationInput, # noqa: F401
+ TextClassificationOutputElement, # noqa: F401
+ TextClassificationOutputTransform, # noqa: F401
+ TextClassificationParameters, # noqa: F401
+ TextGenerationInput, # noqa: F401
+ TextGenerationInputGenerateParameters, # noqa: F401
+ TextGenerationInputGrammarType, # noqa: F401
+ TextGenerationOutput, # noqa: F401
+ TextGenerationOutputBestOfSequence, # noqa: F401
+ TextGenerationOutputDetails, # noqa: F401
+ TextGenerationOutputFinishReason, # noqa: F401
+ TextGenerationOutputPrefillToken, # noqa: F401
+ TextGenerationOutputToken, # noqa: F401
+ TextGenerationStreamOutput, # noqa: F401
+ TextGenerationStreamOutputStreamDetails, # noqa: F401
+ TextGenerationStreamOutputToken, # noqa: F401
+ TextToAudioEarlyStoppingEnum, # noqa: F401
+ TextToAudioGenerationParameters, # noqa: F401
+ TextToAudioInput, # noqa: F401
+ TextToAudioOutput, # noqa: F401
+ TextToAudioParameters, # noqa: F401
+ TextToImageInput, # noqa: F401
+ TextToImageOutput, # noqa: F401
+ TextToImageParameters, # noqa: F401
+ TextToSpeechEarlyStoppingEnum, # noqa: F401
+ TextToSpeechGenerationParameters, # noqa: F401
+ TextToSpeechInput, # noqa: F401
+ TextToSpeechOutput, # noqa: F401
+ TextToSpeechParameters, # noqa: F401
+ TextToVideoInput, # noqa: F401
+ TextToVideoOutput, # noqa: F401
+ TextToVideoParameters, # noqa: F401
+ TokenClassificationAggregationStrategy, # noqa: F401
+ TokenClassificationInput, # noqa: F401
+ TokenClassificationOutputElement, # noqa: F401
+ TokenClassificationParameters, # noqa: F401
+ TranslationInput, # noqa: F401
+ TranslationOutput, # noqa: F401
+ TranslationParameters, # noqa: F401
+ TranslationTruncationStrategy, # noqa: F401
+ TypeEnum, # noqa: F401
+ VideoClassificationInput, # noqa: F401
+ VideoClassificationOutputElement, # noqa: F401
+ VideoClassificationOutputTransform, # noqa: F401
+ VideoClassificationParameters, # noqa: F401
+ VisualQuestionAnsweringInput, # noqa: F401
+ VisualQuestionAnsweringInputData, # noqa: F401
+ VisualQuestionAnsweringOutputElement, # noqa: F401
+ VisualQuestionAnsweringParameters, # noqa: F401
+ ZeroShotClassificationInput, # noqa: F401
+ ZeroShotClassificationOutputElement, # noqa: F401
+ ZeroShotClassificationParameters, # noqa: F401
+ ZeroShotImageClassificationInput, # noqa: F401
+ ZeroShotImageClassificationOutputElement, # noqa: F401
+ ZeroShotImageClassificationParameters, # noqa: F401
+ ZeroShotObjectDetectionBoundingBox, # noqa: F401
+ ZeroShotObjectDetectionInput, # noqa: F401
+ ZeroShotObjectDetectionOutputElement, # noqa: F401
+ ZeroShotObjectDetectionParameters, # noqa: F401
+ )
+ from .inference._mcp.agent import Agent # noqa: F401
+ from .inference._mcp.mcp_client import MCPClient # noqa: F401
+ from .inference_api import InferenceApi # noqa: F401
+ from .keras_mixin import (
+ KerasModelHubMixin, # noqa: F401
+ from_pretrained_keras, # noqa: F401
+ push_to_hub_keras, # noqa: F401
+ save_pretrained_keras, # noqa: F401
+ )
+ from .repocard import (
+ DatasetCard, # noqa: F401
+ ModelCard, # noqa: F401
+ RepoCard, # noqa: F401
+ SpaceCard, # noqa: F401
+ metadata_eval_result, # noqa: F401
+ metadata_load, # noqa: F401
+ metadata_save, # noqa: F401
+ metadata_update, # noqa: F401
+ )
+ from .repocard_data import (
+ CardData, # noqa: F401
+ DatasetCardData, # noqa: F401
+ EvalResult, # noqa: F401
+ ModelCardData, # noqa: F401
+ SpaceCardData, # noqa: F401
+ )
+ from .repository import Repository # noqa: F401
+ from .serialization import (
+ StateDictSplit, # noqa: F401
+ get_tf_storage_size, # noqa: F401
+ get_torch_storage_id, # noqa: F401
+ get_torch_storage_size, # noqa: F401
+ load_state_dict_from_file, # noqa: F401
+ load_torch_model, # noqa: F401
+ save_torch_model, # noqa: F401
+ save_torch_state_dict, # noqa: F401
+ split_state_dict_into_shards_factory, # noqa: F401
+ split_tf_state_dict_into_shards, # noqa: F401
+ split_torch_state_dict_into_shards, # noqa: F401
+ )
+ from .serialization._dduf import (
+ DDUFEntry, # noqa: F401
+ export_entries_as_dduf, # noqa: F401
+ export_folder_as_dduf, # noqa: F401
+ read_dduf_file, # noqa: F401
+ )
+ from .utils import (
+ CachedFileInfo, # noqa: F401
+ CachedRepoInfo, # noqa: F401
+ CachedRevisionInfo, # noqa: F401
+ CacheNotFound, # noqa: F401
+ CorruptedCacheException, # noqa: F401
+ DeleteCacheStrategy, # noqa: F401
+ HFCacheInfo, # noqa: F401
+ HfFolder, # noqa: F401
+ cached_assets_path, # noqa: F401
+ configure_http_backend, # noqa: F401
+ dump_environment_info, # noqa: F401
+ get_session, # noqa: F401
+ get_token, # noqa: F401
+ logging, # noqa: F401
+ scan_cache_dir, # noqa: F401
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ed64b0e5ed550c392f193239a2e00669cc3144a
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_api.py
@@ -0,0 +1,968 @@
+"""
+Type definitions and utilities for the `create_commit` API
+"""
+
+import base64
+import io
+import os
+import warnings
+from collections import defaultdict
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from itertools import groupby
+from pathlib import Path, PurePosixPath
+from typing import TYPE_CHECKING, Any, BinaryIO, Dict, Iterable, Iterator, List, Literal, Optional, Tuple, Union
+
+from tqdm.contrib.concurrent import thread_map
+
+from . import constants
+from .errors import EntryNotFoundError, HfHubHTTPError, XetAuthorizationError, XetRefreshTokenError
+from .file_download import hf_hub_url
+from .lfs import UploadInfo, lfs_upload, post_lfs_batch_info
+from .utils import (
+ FORBIDDEN_FOLDERS,
+ XetTokenType,
+ are_progress_bars_disabled,
+ chunk_iterable,
+ fetch_xet_connection_info_from_repo_info,
+ get_session,
+ hf_raise_for_status,
+ logging,
+ sha,
+ tqdm_stream_file,
+ validate_hf_hub_args,
+)
+from .utils import tqdm as hf_tqdm
+from .utils._runtime import is_xet_available
+
+
+if TYPE_CHECKING:
+ from .hf_api import RepoFile
+
+
+logger = logging.get_logger(__name__)
+
+
+UploadMode = Literal["lfs", "regular"]
+
+# Max is 1,000 per request on the Hub for HfApi.get_paths_info
+# Otherwise we get:
+# HfHubHTTPError: 413 Client Error: Payload Too Large for url: https://huggingface.co/api/datasets/xxx (Request ID: xxx)\n\ntoo many parameters
+# See https://github.com/huggingface/huggingface_hub/issues/1503
+FETCH_LFS_BATCH_SIZE = 500
+
+UPLOAD_BATCH_MAX_NUM_FILES = 256
+
+
+@dataclass
+class CommitOperationDelete:
+ """
+ Data structure holding necessary info to delete a file or a folder from a repository
+ on the Hub.
+
+ Args:
+ path_in_repo (`str`):
+ Relative filepath in the repo, for example: `"checkpoints/1fec34a/weights.bin"`
+ for a file or `"checkpoints/1fec34a/"` for a folder.
+ is_folder (`bool` or `Literal["auto"]`, *optional*)
+ Whether the Delete Operation applies to a folder or not. If "auto", the path
+ type (file or folder) is guessed automatically by looking if path ends with
+ a "/" (folder) or not (file). To explicitly set the path type, you can set
+ `is_folder=True` or `is_folder=False`.
+ """
+
+ path_in_repo: str
+ is_folder: Union[bool, Literal["auto"]] = "auto"
+
+ def __post_init__(self):
+ self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+ if self.is_folder == "auto":
+ self.is_folder = self.path_in_repo.endswith("/")
+ if not isinstance(self.is_folder, bool):
+ raise ValueError(
+ f"Wrong value for `is_folder`. Must be one of [`True`, `False`, `'auto'`]. Got '{self.is_folder}'."
+ )
+
+
+@dataclass
+class CommitOperationCopy:
+ """
+ Data structure holding necessary info to copy a file in a repository on the Hub.
+
+ Limitations:
+ - Only LFS files can be copied. To copy a regular file, you need to download it locally and re-upload it
+ - Cross-repository copies are not supported.
+
+ Note: you can combine a [`CommitOperationCopy`] and a [`CommitOperationDelete`] to rename an LFS file on the Hub.
+
+ Args:
+ src_path_in_repo (`str`):
+ Relative filepath in the repo of the file to be copied, e.g. `"checkpoints/1fec34a/weights.bin"`.
+ path_in_repo (`str`):
+ Relative filepath in the repo where to copy the file, e.g. `"checkpoints/1fec34a/weights_copy.bin"`.
+ src_revision (`str`, *optional*):
+ The git revision of the file to be copied. Can be any valid git revision.
+ Default to the target commit revision.
+ """
+
+ src_path_in_repo: str
+ path_in_repo: str
+ src_revision: Optional[str] = None
+ # set to the OID of the file to be copied if it has already been uploaded
+ # useful to determine if a commit will be empty or not.
+ _src_oid: Optional[str] = None
+ # set to the OID of the file to copy to if it has already been uploaded
+ # useful to determine if a commit will be empty or not.
+ _dest_oid: Optional[str] = None
+
+ def __post_init__(self):
+ self.src_path_in_repo = _validate_path_in_repo(self.src_path_in_repo)
+ self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+
+@dataclass
+class CommitOperationAdd:
+ """
+ Data structure holding necessary info to upload a file to a repository on the Hub.
+
+ Args:
+ path_in_repo (`str`):
+ Relative filepath in the repo, for example: `"checkpoints/1fec34a/weights.bin"`
+ path_or_fileobj (`str`, `Path`, `bytes`, or `BinaryIO`):
+ Either:
+ - a path to a local file (as `str` or `pathlib.Path`) to upload
+ - a buffer of bytes (`bytes`) holding the content of the file to upload
+ - a "file object" (subclass of `io.BufferedIOBase`), typically obtained
+ with `open(path, "rb")`. It must support `seek()` and `tell()` methods.
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `path_or_fileobj` is not one of `str`, `Path`, `bytes` or `io.BufferedIOBase`.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `path_or_fileobj` is a `str` or `Path` but not a path to an existing file.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `path_or_fileobj` is a `io.BufferedIOBase` but it doesn't support both
+ `seek()` and `tell()`.
+ """
+
+ path_in_repo: str
+ path_or_fileobj: Union[str, Path, bytes, BinaryIO]
+ upload_info: UploadInfo = field(init=False, repr=False)
+
+ # Internal attributes
+
+ # set to "lfs" or "regular" once known
+ _upload_mode: Optional[UploadMode] = field(init=False, repr=False, default=None)
+
+ # set to True if .gitignore rules prevent the file from being uploaded as LFS
+ # (server-side check)
+ _should_ignore: Optional[bool] = field(init=False, repr=False, default=None)
+
+ # set to the remote OID of the file if it has already been uploaded
+ # useful to determine if a commit will be empty or not
+ _remote_oid: Optional[str] = field(init=False, repr=False, default=None)
+
+ # set to True once the file has been uploaded as LFS
+ _is_uploaded: bool = field(init=False, repr=False, default=False)
+
+ # set to True once the file has been committed
+ _is_committed: bool = field(init=False, repr=False, default=False)
+
+ def __post_init__(self) -> None:
+ """Validates `path_or_fileobj` and compute `upload_info`."""
+ self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+ # Validate `path_or_fileobj` value
+ if isinstance(self.path_or_fileobj, Path):
+ self.path_or_fileobj = str(self.path_or_fileobj)
+ if isinstance(self.path_or_fileobj, str):
+ path_or_fileobj = os.path.normpath(os.path.expanduser(self.path_or_fileobj))
+ if not os.path.isfile(path_or_fileobj):
+ raise ValueError(f"Provided path: '{path_or_fileobj}' is not a file on the local file system")
+ elif not isinstance(self.path_or_fileobj, (io.BufferedIOBase, bytes)):
+ # ^^ Inspired from: https://stackoverflow.com/questions/44584829/how-to-determine-if-file-is-opened-in-binary-or-text-mode
+ raise ValueError(
+ "path_or_fileobj must be either an instance of str, bytes or"
+ " io.BufferedIOBase. If you passed a file-like object, make sure it is"
+ " in binary mode."
+ )
+ if isinstance(self.path_or_fileobj, io.BufferedIOBase):
+ try:
+ self.path_or_fileobj.tell()
+ self.path_or_fileobj.seek(0, os.SEEK_CUR)
+ except (OSError, AttributeError) as exc:
+ raise ValueError(
+ "path_or_fileobj is a file-like object but does not implement seek() and tell()"
+ ) from exc
+
+ # Compute "upload_info" attribute
+ if isinstance(self.path_or_fileobj, str):
+ self.upload_info = UploadInfo.from_path(self.path_or_fileobj)
+ elif isinstance(self.path_or_fileobj, bytes):
+ self.upload_info = UploadInfo.from_bytes(self.path_or_fileobj)
+ else:
+ self.upload_info = UploadInfo.from_fileobj(self.path_or_fileobj)
+
+ @contextmanager
+ def as_file(self, with_tqdm: bool = False) -> Iterator[BinaryIO]:
+ """
+ A context manager that yields a file-like object allowing to read the underlying
+ data behind `path_or_fileobj`.
+
+ Args:
+ with_tqdm (`bool`, *optional*, defaults to `False`):
+ If True, iterating over the file object will display a progress bar. Only
+ works if the file-like object is a path to a file. Pure bytes and buffers
+ are not supported.
+
+ Example:
+
+ ```python
+ >>> operation = CommitOperationAdd(
+ ... path_in_repo="remote/dir/weights.h5",
+ ... path_or_fileobj="./local/weights.h5",
+ ... )
+ CommitOperationAdd(path_in_repo='remote/dir/weights.h5', path_or_fileobj='./local/weights.h5')
+
+ >>> with operation.as_file() as file:
+ ... content = file.read()
+
+ >>> with operation.as_file(with_tqdm=True) as file:
+ ... while True:
+ ... data = file.read(1024)
+ ... if not data:
+ ... break
+ config.json: 100%|█████████████████████████| 8.19k/8.19k [00:02<00:00, 3.72kB/s]
+
+ >>> with operation.as_file(with_tqdm=True) as file:
+ ... requests.put(..., data=file)
+ config.json: 100%|█████████████████████████| 8.19k/8.19k [00:02<00:00, 3.72kB/s]
+ ```
+ """
+ if isinstance(self.path_or_fileobj, str) or isinstance(self.path_or_fileobj, Path):
+ if with_tqdm:
+ with tqdm_stream_file(self.path_or_fileobj) as file:
+ yield file
+ else:
+ with open(self.path_or_fileobj, "rb") as file:
+ yield file
+ elif isinstance(self.path_or_fileobj, bytes):
+ yield io.BytesIO(self.path_or_fileobj)
+ elif isinstance(self.path_or_fileobj, io.BufferedIOBase):
+ prev_pos = self.path_or_fileobj.tell()
+ yield self.path_or_fileobj
+ self.path_or_fileobj.seek(prev_pos, io.SEEK_SET)
+
+ def b64content(self) -> bytes:
+ """
+ The base64-encoded content of `path_or_fileobj`
+
+ Returns: `bytes`
+ """
+ with self.as_file() as file:
+ return base64.b64encode(file.read())
+
+ @property
+ def _local_oid(self) -> Optional[str]:
+ """Return the OID of the local file.
+
+ This OID is then compared to `self._remote_oid` to check if the file has changed compared to the remote one.
+ If the file did not change, we won't upload it again to prevent empty commits.
+
+ For LFS files, the OID corresponds to the SHA256 of the file content (used a LFS ref).
+ For regular files, the OID corresponds to the SHA1 of the file content.
+ Note: this is slightly different to git OID computation since the oid of an LFS file is usually the git-SHA1 of the
+ pointer file content (not the actual file content). However, using the SHA256 is enough to detect changes
+ and more convenient client-side.
+ """
+ if self._upload_mode is None:
+ return None
+ elif self._upload_mode == "lfs":
+ return self.upload_info.sha256.hex()
+ else:
+ # Regular file => compute sha1
+ # => no need to read by chunk since the file is guaranteed to be <=5MB.
+ with self.as_file() as file:
+ return sha.git_hash(file.read())
+
+
+def _validate_path_in_repo(path_in_repo: str) -> str:
+ # Validate `path_in_repo` value to prevent a server-side issue
+ if path_in_repo.startswith("/"):
+ path_in_repo = path_in_repo[1:]
+ if path_in_repo == "." or path_in_repo == ".." or path_in_repo.startswith("../"):
+ raise ValueError(f"Invalid `path_in_repo` in CommitOperation: '{path_in_repo}'")
+ if path_in_repo.startswith("./"):
+ path_in_repo = path_in_repo[2:]
+ for forbidden in FORBIDDEN_FOLDERS:
+ if any(part == forbidden for part in path_in_repo.split("/")):
+ raise ValueError(
+ f"Invalid `path_in_repo` in CommitOperation: cannot update files under a '{forbidden}/' folder (path:"
+ f" '{path_in_repo}')."
+ )
+ return path_in_repo
+
+
+CommitOperation = Union[CommitOperationAdd, CommitOperationCopy, CommitOperationDelete]
+
+
+def _warn_on_overwriting_operations(operations: List[CommitOperation]) -> None:
+ """
+ Warn user when a list of operations is expected to overwrite itself in a single
+ commit.
+
+ Rules:
+ - If a filepath is updated by multiple `CommitOperationAdd` operations, a warning
+ message is triggered.
+ - If a filepath is updated at least once by a `CommitOperationAdd` and then deleted
+ by a `CommitOperationDelete`, a warning is triggered.
+ - If a `CommitOperationDelete` deletes a filepath that is then updated by a
+ `CommitOperationAdd`, no warning is triggered. This is usually useless (no need to
+ delete before upload) but can happen if a user deletes an entire folder and then
+ add new files to it.
+ """
+ nb_additions_per_path: Dict[str, int] = defaultdict(int)
+ for operation in operations:
+ path_in_repo = operation.path_in_repo
+ if isinstance(operation, CommitOperationAdd):
+ if nb_additions_per_path[path_in_repo] > 0:
+ warnings.warn(
+ "About to update multiple times the same file in the same commit:"
+ f" '{path_in_repo}'. This can cause undesired inconsistencies in"
+ " your repo."
+ )
+ nb_additions_per_path[path_in_repo] += 1
+ for parent in PurePosixPath(path_in_repo).parents:
+ # Also keep track of number of updated files per folder
+ # => warns if deleting a folder overwrite some contained files
+ nb_additions_per_path[str(parent)] += 1
+ if isinstance(operation, CommitOperationDelete):
+ if nb_additions_per_path[str(PurePosixPath(path_in_repo))] > 0:
+ if operation.is_folder:
+ warnings.warn(
+ "About to delete a folder containing files that have just been"
+ f" updated within the same commit: '{path_in_repo}'. This can"
+ " cause undesired inconsistencies in your repo."
+ )
+ else:
+ warnings.warn(
+ "About to delete a file that have just been updated within the"
+ f" same commit: '{path_in_repo}'. This can cause undesired"
+ " inconsistencies in your repo."
+ )
+
+
+@validate_hf_hub_args
+def _upload_files(
+ *,
+ additions: List[CommitOperationAdd],
+ repo_type: str,
+ repo_id: str,
+ headers: Dict[str, str],
+ endpoint: Optional[str] = None,
+ num_threads: int = 5,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+):
+ """
+ Negotiates per-file transfer (LFS vs Xet) and uploads in batches.
+ """
+ xet_additions: List[CommitOperationAdd] = []
+ lfs_actions: List[Dict] = []
+ lfs_oid2addop: Dict[str, CommitOperationAdd] = {}
+
+ for chunk in chunk_iterable(additions, chunk_size=UPLOAD_BATCH_MAX_NUM_FILES):
+ chunk_list = [op for op in chunk]
+
+ transfers: List[str] = ["basic", "multipart"]
+ has_buffered_io_data = any(isinstance(op.path_or_fileobj, io.BufferedIOBase) for op in chunk_list)
+ if is_xet_available():
+ if not has_buffered_io_data:
+ transfers.append("xet")
+ else:
+ logger.warning(
+ "Uploading files as a binary IO buffer is not supported by Xet Storage. "
+ "Falling back to HTTP upload."
+ )
+
+ actions_chunk, errors_chunk, chosen_transfer = post_lfs_batch_info(
+ upload_infos=[op.upload_info for op in chunk_list],
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ endpoint=endpoint,
+ headers=headers,
+ token=None, # already passed in 'headers'
+ transfers=transfers,
+ )
+ if errors_chunk:
+ message = "\n".join(
+ [
+ f"Encountered error for file with OID {err.get('oid')}: `{err.get('error', {}).get('message')}"
+ for err in errors_chunk
+ ]
+ )
+ raise ValueError(f"LFS batch API returned errors:\n{message}")
+
+ # If server returns a transfer we didn't offer (e.g "xet" while uploading from BytesIO),
+ # fall back to LFS for this chunk.
+ if chosen_transfer == "xet" and ("xet" in transfers):
+ xet_additions.extend(chunk_list)
+ else:
+ lfs_actions.extend(actions_chunk)
+ for op in chunk_list:
+ lfs_oid2addop[op.upload_info.sha256.hex()] = op
+
+ if len(lfs_actions) > 0:
+ _upload_lfs_files(
+ actions=lfs_actions,
+ oid2addop=lfs_oid2addop,
+ headers=headers,
+ endpoint=endpoint,
+ num_threads=num_threads,
+ )
+
+ if len(xet_additions) > 0:
+ _upload_xet_files(
+ additions=xet_additions,
+ repo_type=repo_type,
+ repo_id=repo_id,
+ headers=headers,
+ endpoint=endpoint,
+ revision=revision,
+ create_pr=create_pr,
+ )
+
+
+@validate_hf_hub_args
+def _upload_lfs_files(
+ *,
+ actions: List[Dict],
+ oid2addop: Dict[str, CommitOperationAdd],
+ headers: Dict[str, str],
+ endpoint: Optional[str] = None,
+ num_threads: int = 5,
+):
+ """
+ Uploads the content of `additions` to the Hub using the large file storage protocol.
+
+ Relevant external documentation:
+ - LFS Batch API: https://github.com/git-lfs/git-lfs/blob/main/docs/api/batch.md
+
+ Args:
+ actions (`List[Dict]`):
+ LFS batch actions returned by the server.
+ oid2addop (`Dict[str, CommitOperationAdd]`):
+ A dictionary mapping the OID of the file to the corresponding `CommitOperationAdd` object.
+ headers (`Dict[str, str]`):
+ Headers to use for the request, including authorization headers and user agent.
+ endpoint (`str`, *optional*):
+ The endpoint to use for the request. Defaults to `constants.ENDPOINT`.
+ num_threads (`int`, *optional*):
+ The number of concurrent threads to use when uploading. Defaults to 5.
+
+ Raises:
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If an upload failed for any reason
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ headers (`Dict[str, str]`):
+ Headers to use for the request, including authorization headers and user agent.
+ num_threads (`int`, *optional*):
+ The number of concurrent threads to use when uploading. Defaults to 5.
+ revision (`str`, *optional*):
+ The git revision to upload to.
+
+ Raises:
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If an upload failed for any reason
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If the server returns malformed responses
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ If the LFS batch endpoint returned an HTTP error.
+ """
+ # Filter out files already present upstream
+ filtered_actions = []
+ for action in actions:
+ if action.get("actions") is None:
+ logger.debug(
+ f"Content of file {oid2addop[action['oid']].path_in_repo} is already present upstream - skipping upload."
+ )
+ else:
+ filtered_actions.append(action)
+
+ # Upload according to server-provided actions
+ def _wrapped_lfs_upload(batch_action) -> None:
+ try:
+ operation = oid2addop[batch_action["oid"]]
+ lfs_upload(operation=operation, lfs_batch_action=batch_action, headers=headers, endpoint=endpoint)
+ except Exception as exc:
+ raise RuntimeError(f"Error while uploading '{operation.path_in_repo}' to the Hub.") from exc
+
+ if constants.HF_HUB_ENABLE_HF_TRANSFER:
+ logger.debug(f"Uploading {len(filtered_actions)} LFS files to the Hub using `hf_transfer`.")
+ for action in hf_tqdm(filtered_actions, name="huggingface_hub.lfs_upload"):
+ _wrapped_lfs_upload(action)
+ elif len(filtered_actions) == 1:
+ logger.debug("Uploading 1 LFS file to the Hub")
+ _wrapped_lfs_upload(filtered_actions[0])
+ else:
+ logger.debug(
+ f"Uploading {len(filtered_actions)} LFS files to the Hub using up to {num_threads} threads concurrently"
+ )
+ thread_map(
+ _wrapped_lfs_upload,
+ filtered_actions,
+ desc=f"Upload {len(filtered_actions)} LFS files",
+ max_workers=num_threads,
+ tqdm_class=hf_tqdm,
+ )
+
+
+@validate_hf_hub_args
+def _upload_xet_files(
+ *,
+ additions: List[CommitOperationAdd],
+ repo_type: str,
+ repo_id: str,
+ headers: Dict[str, str],
+ endpoint: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+):
+ """
+ Uploads the content of `additions` to the Hub using the xet storage protocol.
+ This chunks the files and deduplicates the chunks before uploading them to xetcas storage.
+
+ Args:
+ additions (`List` of `CommitOperationAdd`):
+ The files to be uploaded.
+ repo_type (`str`):
+ Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ headers (`Dict[str, str]`):
+ Headers to use for the request, including authorization headers and user agent.
+ endpoint: (`str`, *optional*):
+ The endpoint to use for the xetcas service. Defaults to `constants.ENDPOINT`.
+ revision (`str`, *optional*):
+ The git revision to upload to.
+ create_pr (`bool`, *optional*):
+ Whether or not to create a Pull Request with that commit.
+
+ Raises:
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If an upload failed for any reason.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If the server returns malformed responses or if the user is unauthorized to upload to xet storage.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ If the LFS batch endpoint returned an HTTP error.
+
+ **How it works:**
+ The file download system uses Xet storage, which is a content-addressable storage system that breaks files into chunks
+ for efficient storage and transfer.
+
+ `hf_xet.upload_files` manages uploading files by:
+ - Taking a list of file paths to upload
+ - Breaking files into smaller chunks for efficient storage
+ - Avoiding duplicate storage by recognizing identical chunks across files
+ - Connecting to a storage server (CAS server) that manages these chunks
+
+ The upload process works like this:
+ 1. Create a local folder at ~/.cache/huggingface/xet/chunk-cache to store file chunks for reuse.
+ 2. Process files in parallel (up to 8 files at once):
+ 2.1. Read the file content.
+ 2.2. Split the file content into smaller chunks based on content patterns: each chunk gets a unique ID based on what's in it.
+ 2.3. For each chunk:
+ - Check if it already exists in storage.
+ - Skip uploading chunks that already exist.
+ 2.4. Group chunks into larger blocks for efficient transfer.
+ 2.5. Upload these blocks to the storage server.
+ 2.6. Create and upload information about how the file is structured.
+ 3. Return reference files that contain information about the uploaded files, which can be used later to download them.
+ """
+ if len(additions) == 0:
+ return
+
+ # at this point, we know that hf_xet is installed
+ from hf_xet import upload_bytes, upload_files
+
+ from .utils._xet_progress_reporting import XetProgressReporter
+
+ try:
+ xet_connection_info = fetch_xet_connection_info_from_repo_info(
+ token_type=XetTokenType.WRITE,
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ headers=headers,
+ endpoint=endpoint,
+ params={"create_pr": "1"} if create_pr else None,
+ )
+ except HfHubHTTPError as e:
+ if e.response.status_code == 401:
+ raise XetAuthorizationError(
+ f"You are unauthorized to upload to xet storage for {repo_type}/{repo_id}. "
+ f"Please check that you have configured your access token with write access to the repo."
+ ) from e
+ raise
+
+ xet_endpoint = xet_connection_info.endpoint
+ access_token_info = (xet_connection_info.access_token, xet_connection_info.expiration_unix_epoch)
+
+ def token_refresher() -> Tuple[str, int]:
+ new_xet_connection = fetch_xet_connection_info_from_repo_info(
+ token_type=XetTokenType.WRITE,
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ headers=headers,
+ endpoint=endpoint,
+ params={"create_pr": "1"} if create_pr else None,
+ )
+ if new_xet_connection is None:
+ raise XetRefreshTokenError("Failed to refresh xet token")
+ return new_xet_connection.access_token, new_xet_connection.expiration_unix_epoch
+
+ if not are_progress_bars_disabled():
+ progress = XetProgressReporter()
+ progress_callback = progress.update_progress
+ else:
+ progress, progress_callback = None, None
+
+ try:
+ all_bytes_ops = [op for op in additions if isinstance(op.path_or_fileobj, bytes)]
+ all_paths_ops = [op for op in additions if isinstance(op.path_or_fileobj, (str, Path))]
+
+ if len(all_paths_ops) > 0:
+ all_paths = [str(op.path_or_fileobj) for op in all_paths_ops]
+ upload_files(
+ all_paths,
+ xet_endpoint,
+ access_token_info,
+ token_refresher,
+ progress_callback,
+ repo_type,
+ )
+
+ if len(all_bytes_ops) > 0:
+ all_bytes = [op.path_or_fileobj for op in all_bytes_ops]
+ upload_bytes(
+ all_bytes,
+ xet_endpoint,
+ access_token_info,
+ token_refresher,
+ progress_callback,
+ repo_type,
+ )
+
+ finally:
+ if progress is not None:
+ progress.close(False)
+
+ return
+
+
+def _validate_preupload_info(preupload_info: dict):
+ files = preupload_info.get("files")
+ if not isinstance(files, list):
+ raise ValueError("preupload_info is improperly formatted")
+ for file_info in files:
+ if not (
+ isinstance(file_info, dict)
+ and isinstance(file_info.get("path"), str)
+ and isinstance(file_info.get("uploadMode"), str)
+ and (file_info["uploadMode"] in ("lfs", "regular"))
+ ):
+ raise ValueError("preupload_info is improperly formatted:")
+ return preupload_info
+
+
+@validate_hf_hub_args
+def _fetch_upload_modes(
+ additions: Iterable[CommitOperationAdd],
+ repo_type: str,
+ repo_id: str,
+ headers: Dict[str, str],
+ revision: str,
+ endpoint: Optional[str] = None,
+ create_pr: bool = False,
+ gitignore_content: Optional[str] = None,
+) -> None:
+ """
+ Requests the Hub "preupload" endpoint to determine whether each input file should be uploaded as a regular git blob,
+ as a git LFS blob, or as a XET file. Input `additions` are mutated in-place with the upload mode.
+
+ Args:
+ additions (`Iterable` of :class:`CommitOperationAdd`):
+ Iterable of :class:`CommitOperationAdd` describing the files to
+ upload to the Hub.
+ repo_type (`str`):
+ Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ headers (`Dict[str, str]`):
+ Headers to use for the request, including authorization headers and user agent.
+ revision (`str`):
+ The git revision to upload the files to. Can be any valid git revision.
+ gitignore_content (`str`, *optional*):
+ The content of the `.gitignore` file to know which files should be ignored. The order of priority
+ is to first check if `gitignore_content` is passed, then check if the `.gitignore` file is present
+ in the list of files to commit and finally default to the `.gitignore` file already hosted on the Hub
+ (if any).
+ Raises:
+ [`~utils.HfHubHTTPError`]
+ If the Hub API returned an error.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If the Hub API response is improperly formatted.
+ """
+ endpoint = endpoint if endpoint is not None else constants.ENDPOINT
+
+ # Fetch upload mode (LFS or regular) chunk by chunk.
+ upload_modes: Dict[str, UploadMode] = {}
+ should_ignore_info: Dict[str, bool] = {}
+ oid_info: Dict[str, Optional[str]] = {}
+
+ for chunk in chunk_iterable(additions, 256):
+ payload: Dict = {
+ "files": [
+ {
+ "path": op.path_in_repo,
+ "sample": base64.b64encode(op.upload_info.sample).decode("ascii"),
+ "size": op.upload_info.size,
+ }
+ for op in chunk
+ ]
+ }
+ if gitignore_content is not None:
+ payload["gitIgnore"] = gitignore_content
+
+ resp = get_session().post(
+ f"{endpoint}/api/{repo_type}s/{repo_id}/preupload/{revision}",
+ json=payload,
+ headers=headers,
+ params={"create_pr": "1"} if create_pr else None,
+ )
+ hf_raise_for_status(resp)
+ preupload_info = _validate_preupload_info(resp.json())
+ upload_modes.update(**{file["path"]: file["uploadMode"] for file in preupload_info["files"]})
+ should_ignore_info.update(**{file["path"]: file["shouldIgnore"] for file in preupload_info["files"]})
+ oid_info.update(**{file["path"]: file.get("oid") for file in preupload_info["files"]})
+
+ # Set upload mode for each addition operation
+ for addition in additions:
+ addition._upload_mode = upload_modes[addition.path_in_repo]
+ addition._should_ignore = should_ignore_info[addition.path_in_repo]
+ addition._remote_oid = oid_info[addition.path_in_repo]
+
+ # Empty files cannot be uploaded as LFS (S3 would fail with a 501 Not Implemented)
+ # => empty files are uploaded as "regular" to still allow users to commit them.
+ for addition in additions:
+ if addition.upload_info.size == 0:
+ addition._upload_mode = "regular"
+
+
+@validate_hf_hub_args
+def _fetch_files_to_copy(
+ copies: Iterable[CommitOperationCopy],
+ repo_type: str,
+ repo_id: str,
+ headers: Dict[str, str],
+ revision: str,
+ endpoint: Optional[str] = None,
+) -> Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]]:
+ """
+ Fetch information about the files to copy.
+
+ For LFS files, we only need their metadata (file size and sha256) while for regular files
+ we need to download the raw content from the Hub.
+
+ Args:
+ copies (`Iterable` of :class:`CommitOperationCopy`):
+ Iterable of :class:`CommitOperationCopy` describing the files to
+ copy on the Hub.
+ repo_type (`str`):
+ Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ headers (`Dict[str, str]`):
+ Headers to use for the request, including authorization headers and user agent.
+ revision (`str`):
+ The git revision to upload the files to. Can be any valid git revision.
+
+ Returns: `Dict[Tuple[str, Optional[str]], Union[RepoFile, bytes]]]`
+ Key is the file path and revision of the file to copy.
+ Value is the raw content as bytes (for regular files) or the file information as a RepoFile (for LFS files).
+
+ Raises:
+ [`~utils.HfHubHTTPError`]
+ If the Hub API returned an error.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If the Hub API response is improperly formatted.
+ """
+ from .hf_api import HfApi, RepoFolder
+
+ hf_api = HfApi(endpoint=endpoint, headers=headers)
+ files_to_copy: Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]] = {}
+ # Store (path, revision) -> oid mapping
+ oid_info: Dict[Tuple[str, Optional[str]], Optional[str]] = {}
+ # 1. Fetch OIDs for destination paths in batches.
+ dest_paths = [op.path_in_repo for op in copies]
+ for offset in range(0, len(dest_paths), FETCH_LFS_BATCH_SIZE):
+ dest_repo_files = hf_api.get_paths_info(
+ repo_id=repo_id,
+ paths=dest_paths[offset : offset + FETCH_LFS_BATCH_SIZE],
+ revision=revision,
+ repo_type=repo_type,
+ )
+ for file in dest_repo_files:
+ if not isinstance(file, RepoFolder):
+ oid_info[(file.path, revision)] = file.blob_id
+
+ # 2. Group by source revision and fetch source file info in batches.
+ for src_revision, operations in groupby(copies, key=lambda op: op.src_revision):
+ operations = list(operations) # type: ignore
+ src_paths = [op.src_path_in_repo for op in operations]
+ for offset in range(0, len(src_paths), FETCH_LFS_BATCH_SIZE):
+ src_repo_files = hf_api.get_paths_info(
+ repo_id=repo_id,
+ paths=src_paths[offset : offset + FETCH_LFS_BATCH_SIZE],
+ revision=src_revision or revision,
+ repo_type=repo_type,
+ )
+
+ for src_repo_file in src_repo_files:
+ if isinstance(src_repo_file, RepoFolder):
+ raise NotImplementedError("Copying a folder is not implemented.")
+ oid_info[(src_repo_file.path, src_revision)] = src_repo_file.blob_id
+ # If it's an LFS file, store the RepoFile object. Otherwise, download raw bytes.
+ if src_repo_file.lfs:
+ files_to_copy[(src_repo_file.path, src_revision)] = src_repo_file
+ else:
+ # TODO: (optimization) download regular files to copy concurrently
+ url = hf_hub_url(
+ endpoint=endpoint,
+ repo_type=repo_type,
+ repo_id=repo_id,
+ revision=src_revision or revision,
+ filename=src_repo_file.path,
+ )
+ response = get_session().get(url, headers=headers)
+ hf_raise_for_status(response)
+ files_to_copy[(src_repo_file.path, src_revision)] = response.content
+ # 3. Ensure all operations found a corresponding file in the Hub
+ # and track src/dest OIDs for each operation.
+ for operation in operations:
+ if (operation.src_path_in_repo, src_revision) not in files_to_copy:
+ raise EntryNotFoundError(
+ f"Cannot copy {operation.src_path_in_repo} at revision "
+ f"{src_revision or revision}: file is missing on repo."
+ )
+ operation._src_oid = oid_info.get((operation.src_path_in_repo, operation.src_revision))
+ operation._dest_oid = oid_info.get((operation.path_in_repo, revision))
+ return files_to_copy
+
+
+def _prepare_commit_payload(
+ operations: Iterable[CommitOperation],
+ files_to_copy: Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]],
+ commit_message: str,
+ commit_description: Optional[str] = None,
+ parent_commit: Optional[str] = None,
+) -> Iterable[Dict[str, Any]]:
+ """
+ Builds the payload to POST to the `/commit` API of the Hub.
+
+ Payload is returned as an iterator so that it can be streamed as a ndjson in the
+ POST request.
+
+ For more information, see:
+ - https://github.com/huggingface/huggingface_hub/issues/1085#issuecomment-1265208073
+ - http://ndjson.org/
+ """
+ commit_description = commit_description if commit_description is not None else ""
+
+ # 1. Send a header item with the commit metadata
+ header_value = {"summary": commit_message, "description": commit_description}
+ if parent_commit is not None:
+ header_value["parentCommit"] = parent_commit
+ yield {"key": "header", "value": header_value}
+
+ nb_ignored_files = 0
+
+ # 2. Send operations, one per line
+ for operation in operations:
+ # Skip ignored files
+ if isinstance(operation, CommitOperationAdd) and operation._should_ignore:
+ logger.debug(f"Skipping file '{operation.path_in_repo}' in commit (ignored by gitignore file).")
+ nb_ignored_files += 1
+ continue
+
+ # 2.a. Case adding a regular file
+ if isinstance(operation, CommitOperationAdd) and operation._upload_mode == "regular":
+ yield {
+ "key": "file",
+ "value": {
+ "content": operation.b64content().decode(),
+ "path": operation.path_in_repo,
+ "encoding": "base64",
+ },
+ }
+ # 2.b. Case adding an LFS file
+ elif isinstance(operation, CommitOperationAdd) and operation._upload_mode == "lfs":
+ yield {
+ "key": "lfsFile",
+ "value": {
+ "path": operation.path_in_repo,
+ "algo": "sha256",
+ "oid": operation.upload_info.sha256.hex(),
+ "size": operation.upload_info.size,
+ },
+ }
+ # 2.c. Case deleting a file or folder
+ elif isinstance(operation, CommitOperationDelete):
+ yield {
+ "key": "deletedFolder" if operation.is_folder else "deletedFile",
+ "value": {"path": operation.path_in_repo},
+ }
+ # 2.d. Case copying a file or folder
+ elif isinstance(operation, CommitOperationCopy):
+ file_to_copy = files_to_copy[(operation.src_path_in_repo, operation.src_revision)]
+ if isinstance(file_to_copy, bytes):
+ yield {
+ "key": "file",
+ "value": {
+ "content": base64.b64encode(file_to_copy).decode(),
+ "path": operation.path_in_repo,
+ "encoding": "base64",
+ },
+ }
+ elif file_to_copy.lfs:
+ yield {
+ "key": "lfsFile",
+ "value": {
+ "path": operation.path_in_repo,
+ "algo": "sha256",
+ "oid": file_to_copy.lfs.sha256,
+ },
+ }
+ else:
+ raise ValueError(
+ "Malformed files_to_copy (should be raw file content as bytes or RepoFile objects with LFS info."
+ )
+ # 2.e. Never expected to happen
+ else:
+ raise ValueError(
+ f"Unknown operation to commit. Operation: {operation}. Upload mode:"
+ f" {getattr(operation, '_upload_mode', None)}"
+ )
+
+ if nb_ignored_files > 0:
+ logger.info(f"Skipped {nb_ignored_files} file(s) in commit (ignored by gitignore file).")
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_scheduler.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_scheduler.py
new file mode 100644
index 0000000000000000000000000000000000000000..1bc8db6a8ade4d2253dd241a66c86def5dac2733
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_commit_scheduler.py
@@ -0,0 +1,350 @@
+import atexit
+import logging
+import os
+import time
+from concurrent.futures import Future
+from dataclasses import dataclass
+from io import SEEK_END, SEEK_SET, BytesIO
+from pathlib import Path
+from threading import Lock, Thread
+from typing import Dict, List, Optional, Union
+
+from .hf_api import DEFAULT_IGNORE_PATTERNS, CommitInfo, CommitOperationAdd, HfApi
+from .utils import filter_repo_objects
+
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True)
+class _FileToUpload:
+ """Temporary dataclass to store info about files to upload. Not meant to be used directly."""
+
+ local_path: Path
+ path_in_repo: str
+ size_limit: int
+ last_modified: float
+
+
+class CommitScheduler:
+ """
+ Scheduler to upload a local folder to the Hub at regular intervals (e.g. push to hub every 5 minutes).
+
+ The recommended way to use the scheduler is to use it as a context manager. This ensures that the scheduler is
+ properly stopped and the last commit is triggered when the script ends. The scheduler can also be stopped manually
+ with the `stop` method. Checkout the [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#scheduled-uploads)
+ to learn more about how to use it.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to commit to.
+ folder_path (`str` or `Path`):
+ Path to the local folder to upload regularly.
+ every (`int` or `float`, *optional*):
+ The number of minutes between each commit. Defaults to 5 minutes.
+ path_in_repo (`str`, *optional*):
+ Relative path of the directory in the repo, for example: `"checkpoints/"`. Defaults to the root folder
+ of the repository.
+ repo_type (`str`, *optional*):
+ The type of the repo to commit to. Defaults to `model`.
+ revision (`str`, *optional*):
+ The revision of the repo to commit to. Defaults to `main`.
+ private (`bool`, *optional*):
+ Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
+ token (`str`, *optional*):
+ The token to use to commit to the repo. Defaults to the token saved on the machine.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are uploaded.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not uploaded.
+ squash_history (`bool`, *optional*):
+ Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is
+ useful to avoid degraded performances on the repo when it grows too large.
+ hf_api (`HfApi`, *optional*):
+ The [`HfApi`] client to use to commit to the Hub. Can be set with custom settings (user agent, token,...).
+
+ Example:
+ ```py
+ >>> from pathlib import Path
+ >>> from huggingface_hub import CommitScheduler
+
+ # Scheduler uploads every 10 minutes
+ >>> csv_path = Path("watched_folder/data.csv")
+ >>> CommitScheduler(repo_id="test_scheduler", repo_type="dataset", folder_path=csv_path.parent, every=10)
+
+ >>> with csv_path.open("a") as f:
+ ... f.write("first line")
+
+ # Some time later (...)
+ >>> with csv_path.open("a") as f:
+ ... f.write("second line")
+ ```
+
+ Example using a context manager:
+ ```py
+ >>> from pathlib import Path
+ >>> from huggingface_hub import CommitScheduler
+
+ >>> with CommitScheduler(repo_id="test_scheduler", repo_type="dataset", folder_path="watched_folder", every=10) as scheduler:
+ ... csv_path = Path("watched_folder/data.csv")
+ ... with csv_path.open("a") as f:
+ ... f.write("first line")
+ ... (...)
+ ... with csv_path.open("a") as f:
+ ... f.write("second line")
+
+ # Scheduler is now stopped and last commit have been triggered
+ ```
+ """
+
+ def __init__(
+ self,
+ *,
+ repo_id: str,
+ folder_path: Union[str, Path],
+ every: Union[int, float] = 5,
+ path_in_repo: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ private: Optional[bool] = None,
+ token: Optional[str] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ squash_history: bool = False,
+ hf_api: Optional["HfApi"] = None,
+ ) -> None:
+ self.api = hf_api or HfApi(token=token)
+
+ # Folder
+ self.folder_path = Path(folder_path).expanduser().resolve()
+ self.path_in_repo = path_in_repo or ""
+ self.allow_patterns = allow_patterns
+
+ if ignore_patterns is None:
+ ignore_patterns = []
+ elif isinstance(ignore_patterns, str):
+ ignore_patterns = [ignore_patterns]
+ self.ignore_patterns = ignore_patterns + DEFAULT_IGNORE_PATTERNS
+
+ if self.folder_path.is_file():
+ raise ValueError(f"'folder_path' must be a directory, not a file: '{self.folder_path}'.")
+ self.folder_path.mkdir(parents=True, exist_ok=True)
+
+ # Repository
+ repo_url = self.api.create_repo(repo_id=repo_id, private=private, repo_type=repo_type, exist_ok=True)
+ self.repo_id = repo_url.repo_id
+ self.repo_type = repo_type
+ self.revision = revision
+ self.token = token
+
+ # Keep track of already uploaded files
+ self.last_uploaded: Dict[Path, float] = {} # key is local path, value is timestamp
+
+ # Scheduler
+ if not every > 0:
+ raise ValueError(f"'every' must be a positive integer, not '{every}'.")
+ self.lock = Lock()
+ self.every = every
+ self.squash_history = squash_history
+
+ logger.info(f"Scheduled job to push '{self.folder_path}' to '{self.repo_id}' every {self.every} minutes.")
+ self._scheduler_thread = Thread(target=self._run_scheduler, daemon=True)
+ self._scheduler_thread.start()
+ atexit.register(self._push_to_hub)
+
+ self.__stopped = False
+
+ def stop(self) -> None:
+ """Stop the scheduler.
+
+ A stopped scheduler cannot be restarted. Mostly for tests purposes.
+ """
+ self.__stopped = True
+
+ def __enter__(self) -> "CommitScheduler":
+ return self
+
+ def __exit__(self, exc_type, exc_value, traceback) -> None:
+ # Upload last changes before exiting
+ self.trigger().result()
+ self.stop()
+ return
+
+ def _run_scheduler(self) -> None:
+ """Dumb thread waiting between each scheduled push to Hub."""
+ while True:
+ self.last_future = self.trigger()
+ time.sleep(self.every * 60)
+ if self.__stopped:
+ break
+
+ def trigger(self) -> Future:
+ """Trigger a `push_to_hub` and return a future.
+
+ This method is automatically called every `every` minutes. You can also call it manually to trigger a commit
+ immediately, without waiting for the next scheduled commit.
+ """
+ return self.api.run_as_future(self._push_to_hub)
+
+ def _push_to_hub(self) -> Optional[CommitInfo]:
+ if self.__stopped: # If stopped, already scheduled commits are ignored
+ return None
+
+ logger.info("(Background) scheduled commit triggered.")
+ try:
+ value = self.push_to_hub()
+ if self.squash_history:
+ logger.info("(Background) squashing repo history.")
+ self.api.super_squash_history(repo_id=self.repo_id, repo_type=self.repo_type, branch=self.revision)
+ return value
+ except Exception as e:
+ logger.error(f"Error while pushing to Hub: {e}") # Depending on the setup, error might be silenced
+ raise
+
+ def push_to_hub(self) -> Optional[CommitInfo]:
+ """
+ Push folder to the Hub and return the commit info.
+
+ > [!WARNING]
+ > This method is not meant to be called directly. It is run in the background by the scheduler, respecting a
+ > queue mechanism to avoid concurrent commits. Making a direct call to the method might lead to concurrency
+ > issues.
+
+ The default behavior of `push_to_hub` is to assume an append-only folder. It lists all files in the folder and
+ uploads only changed files. If no changes are found, the method returns without committing anything. If you want
+ to change this behavior, you can inherit from [`CommitScheduler`] and override this method. This can be useful
+ for example to compress data together in a single file before committing. For more details and examples, check
+ out our [integration guide](https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#scheduled-uploads).
+ """
+ # Check files to upload (with lock)
+ with self.lock:
+ logger.debug("Listing files to upload for scheduled commit.")
+
+ # List files from folder (taken from `_prepare_upload_folder_additions`)
+ relpath_to_abspath = {
+ path.relative_to(self.folder_path).as_posix(): path
+ for path in sorted(self.folder_path.glob("**/*")) # sorted to be deterministic
+ if path.is_file()
+ }
+ prefix = f"{self.path_in_repo.strip('/')}/" if self.path_in_repo else ""
+
+ # Filter with pattern + filter out unchanged files + retrieve current file size
+ files_to_upload: List[_FileToUpload] = []
+ for relpath in filter_repo_objects(
+ relpath_to_abspath.keys(), allow_patterns=self.allow_patterns, ignore_patterns=self.ignore_patterns
+ ):
+ local_path = relpath_to_abspath[relpath]
+ stat = local_path.stat()
+ if self.last_uploaded.get(local_path) is None or self.last_uploaded[local_path] != stat.st_mtime:
+ files_to_upload.append(
+ _FileToUpload(
+ local_path=local_path,
+ path_in_repo=prefix + relpath,
+ size_limit=stat.st_size,
+ last_modified=stat.st_mtime,
+ )
+ )
+
+ # Return if nothing to upload
+ if len(files_to_upload) == 0:
+ logger.debug("Dropping schedule commit: no changed file to upload.")
+ return None
+
+ # Convert `_FileToUpload` as `CommitOperationAdd` (=> compute file shas + limit to file size)
+ logger.debug("Removing unchanged files since previous scheduled commit.")
+ add_operations = [
+ CommitOperationAdd(
+ # Cap the file to its current size, even if the user append data to it while a scheduled commit is happening
+ path_or_fileobj=PartialFileIO(file_to_upload.local_path, size_limit=file_to_upload.size_limit),
+ path_in_repo=file_to_upload.path_in_repo,
+ )
+ for file_to_upload in files_to_upload
+ ]
+
+ # Upload files (append mode expected - no need for lock)
+ logger.debug("Uploading files for scheduled commit.")
+ commit_info = self.api.create_commit(
+ repo_id=self.repo_id,
+ repo_type=self.repo_type,
+ operations=add_operations,
+ commit_message="Scheduled Commit",
+ revision=self.revision,
+ )
+
+ # Successful commit: keep track of the latest "last_modified" for each file
+ for file in files_to_upload:
+ self.last_uploaded[file.local_path] = file.last_modified
+ return commit_info
+
+
+class PartialFileIO(BytesIO):
+ """A file-like object that reads only the first part of a file.
+
+ Useful to upload a file to the Hub when the user might still be appending data to it. Only the first part of the
+ file is uploaded (i.e. the part that was available when the filesystem was first scanned).
+
+ In practice, only used internally by the CommitScheduler to regularly push a folder to the Hub with minimal
+ disturbance for the user. The object is passed to `CommitOperationAdd`.
+
+ Only supports `read`, `tell` and `seek` methods.
+
+ Args:
+ file_path (`str` or `Path`):
+ Path to the file to read.
+ size_limit (`int`):
+ The maximum number of bytes to read from the file. If the file is larger than this, only the first part
+ will be read (and uploaded).
+ """
+
+ def __init__(self, file_path: Union[str, Path], size_limit: int) -> None:
+ self._file_path = Path(file_path)
+ self._file = self._file_path.open("rb")
+ self._size_limit = min(size_limit, os.fstat(self._file.fileno()).st_size)
+
+ def __del__(self) -> None:
+ self._file.close()
+ return super().__del__()
+
+ def __repr__(self) -> str:
+ return f""
+
+ def __len__(self) -> int:
+ return self._size_limit
+
+ def __getattribute__(self, name: str):
+ if name.startswith("_") or name in ("read", "tell", "seek"): # only 3 public methods supported
+ return super().__getattribute__(name)
+ raise NotImplementedError(f"PartialFileIO does not support '{name}'.")
+
+ def tell(self) -> int:
+ """Return the current file position."""
+ return self._file.tell()
+
+ def seek(self, __offset: int, __whence: int = SEEK_SET) -> int:
+ """Change the stream position to the given offset.
+
+ Behavior is the same as a regular file, except that the position is capped to the size limit.
+ """
+ if __whence == SEEK_END:
+ # SEEK_END => set from the truncated end
+ __offset = len(self) + __offset
+ __whence = SEEK_SET
+
+ pos = self._file.seek(__offset, __whence)
+ if pos > self._size_limit:
+ return self._file.seek(self._size_limit)
+ return pos
+
+ def read(self, __size: Optional[int] = -1) -> bytes:
+ """Read at most `__size` bytes from the file.
+
+ Behavior is the same as a regular file, except that it is capped to the size limit.
+ """
+ current = self._file.tell()
+ if __size is None or __size < 0:
+ # Read until file limit
+ truncated_size = self._size_limit - current
+ else:
+ # Read until file limit or __size
+ truncated_size = min(__size, self._size_limit - current)
+ return self._file.read(truncated_size)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_inference_endpoints.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_inference_endpoints.py
new file mode 100644
index 0000000000000000000000000000000000000000..37f772bfbe28013ff5329d0a19a438706d50a19c
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_inference_endpoints.py
@@ -0,0 +1,413 @@
+import time
+from dataclasses import dataclass, field
+from datetime import datetime
+from enum import Enum
+from typing import TYPE_CHECKING, Dict, Optional, Union
+
+from huggingface_hub.errors import InferenceEndpointError, InferenceEndpointTimeoutError
+
+from .utils import get_session, logging, parse_datetime
+
+
+if TYPE_CHECKING:
+ from .hf_api import HfApi
+ from .inference._client import InferenceClient
+ from .inference._generated._async_client import AsyncInferenceClient
+
+logger = logging.get_logger(__name__)
+
+
+class InferenceEndpointStatus(str, Enum):
+ PENDING = "pending"
+ INITIALIZING = "initializing"
+ UPDATING = "updating"
+ UPDATE_FAILED = "updateFailed"
+ RUNNING = "running"
+ PAUSED = "paused"
+ FAILED = "failed"
+ SCALED_TO_ZERO = "scaledToZero"
+
+
+class InferenceEndpointType(str, Enum):
+ PUBlIC = "public"
+ PROTECTED = "protected"
+ PRIVATE = "private"
+
+
+@dataclass
+class InferenceEndpoint:
+ """
+ Contains information about a deployed Inference Endpoint.
+
+ Args:
+ name (`str`):
+ The unique name of the Inference Endpoint.
+ namespace (`str`):
+ The namespace where the Inference Endpoint is located.
+ repository (`str`):
+ The name of the model repository deployed on this Inference Endpoint.
+ status ([`InferenceEndpointStatus`]):
+ The current status of the Inference Endpoint.
+ url (`str`, *optional*):
+ The URL of the Inference Endpoint, if available. Only a deployed Inference Endpoint will have a URL.
+ framework (`str`):
+ The machine learning framework used for the model.
+ revision (`str`):
+ The specific model revision deployed on the Inference Endpoint.
+ task (`str`):
+ The task associated with the deployed model.
+ created_at (`datetime.datetime`):
+ The timestamp when the Inference Endpoint was created.
+ updated_at (`datetime.datetime`):
+ The timestamp of the last update of the Inference Endpoint.
+ type ([`InferenceEndpointType`]):
+ The type of the Inference Endpoint (public, protected, private).
+ raw (`Dict`):
+ The raw dictionary data returned from the API.
+ token (`str` or `bool`, *optional*):
+ Authentication token for the Inference Endpoint, if set when requesting the API. Will default to the
+ locally saved token if not provided. Pass `token=False` if you don't want to send your token to the server.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import get_inference_endpoint
+ >>> endpoint = get_inference_endpoint("my-text-to-image")
+ >>> endpoint
+ InferenceEndpoint(name='my-text-to-image', ...)
+
+ # Get status
+ >>> endpoint.status
+ 'running'
+ >>> endpoint.url
+ 'https://my-text-to-image.region.vendor.endpoints.huggingface.cloud'
+
+ # Run inference
+ >>> endpoint.client.text_to_image(...)
+
+ # Pause endpoint to save $$$
+ >>> endpoint.pause()
+
+ # ...
+ # Resume and wait for deployment
+ >>> endpoint.resume()
+ >>> endpoint.wait()
+ >>> endpoint.client.text_to_image(...)
+ ```
+ """
+
+ # Field in __repr__
+ name: str = field(init=False)
+ namespace: str
+ repository: str = field(init=False)
+ status: InferenceEndpointStatus = field(init=False)
+ health_route: str = field(init=False)
+ url: Optional[str] = field(init=False)
+
+ # Other fields
+ framework: str = field(repr=False, init=False)
+ revision: str = field(repr=False, init=False)
+ task: str = field(repr=False, init=False)
+ created_at: datetime = field(repr=False, init=False)
+ updated_at: datetime = field(repr=False, init=False)
+ type: InferenceEndpointType = field(repr=False, init=False)
+
+ # Raw dict from the API
+ raw: Dict = field(repr=False)
+
+ # Internal fields
+ _token: Union[str, bool, None] = field(repr=False, compare=False)
+ _api: "HfApi" = field(repr=False, compare=False)
+
+ @classmethod
+ def from_raw(
+ cls, raw: Dict, namespace: str, token: Union[str, bool, None] = None, api: Optional["HfApi"] = None
+ ) -> "InferenceEndpoint":
+ """Initialize object from raw dictionary."""
+ if api is None:
+ from .hf_api import HfApi
+
+ api = HfApi()
+ if token is None:
+ token = api.token
+
+ # All other fields are populated in __post_init__
+ return cls(raw=raw, namespace=namespace, _token=token, _api=api)
+
+ def __post_init__(self) -> None:
+ """Populate fields from raw dictionary."""
+ self._populate_from_raw()
+
+ @property
+ def client(self) -> "InferenceClient":
+ """Returns a client to make predictions on this Inference Endpoint.
+
+ Returns:
+ [`InferenceClient`]: an inference client pointing to the deployed endpoint.
+
+ Raises:
+ [`InferenceEndpointError`]: If the Inference Endpoint is not yet deployed.
+ """
+ if self.url is None:
+ raise InferenceEndpointError(
+ "Cannot create a client for this Inference Endpoint as it is not yet deployed. "
+ "Please wait for the Inference Endpoint to be deployed using `endpoint.wait()` and try again."
+ )
+ from .inference._client import InferenceClient
+
+ return InferenceClient(
+ model=self.url,
+ token=self._token, # type: ignore[arg-type] # boolean token shouldn't be possible. In practice it's ok.
+ )
+
+ @property
+ def async_client(self) -> "AsyncInferenceClient":
+ """Returns a client to make predictions on this Inference Endpoint.
+
+ Returns:
+ [`AsyncInferenceClient`]: an asyncio-compatible inference client pointing to the deployed endpoint.
+
+ Raises:
+ [`InferenceEndpointError`]: If the Inference Endpoint is not yet deployed.
+ """
+ if self.url is None:
+ raise InferenceEndpointError(
+ "Cannot create a client for this Inference Endpoint as it is not yet deployed. "
+ "Please wait for the Inference Endpoint to be deployed using `endpoint.wait()` and try again."
+ )
+ from .inference._generated._async_client import AsyncInferenceClient
+
+ return AsyncInferenceClient(
+ model=self.url,
+ token=self._token, # type: ignore[arg-type] # boolean token shouldn't be possible. In practice it's ok.
+ )
+
+ def wait(self, timeout: Optional[int] = None, refresh_every: int = 5) -> "InferenceEndpoint":
+ """Wait for the Inference Endpoint to be deployed.
+
+ Information from the server will be fetched every 1s. If the Inference Endpoint is not deployed after `timeout`
+ seconds, a [`InferenceEndpointTimeoutError`] will be raised. The [`InferenceEndpoint`] will be mutated in place with the latest
+ data.
+
+ Args:
+ timeout (`int`, *optional*):
+ The maximum time to wait for the Inference Endpoint to be deployed, in seconds. If `None`, will wait
+ indefinitely.
+ refresh_every (`int`, *optional*):
+ The time to wait between each fetch of the Inference Endpoint status, in seconds. Defaults to 5s.
+
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+
+ Raises:
+ [`InferenceEndpointError`]
+ If the Inference Endpoint ended up in a failed state.
+ [`InferenceEndpointTimeoutError`]
+ If the Inference Endpoint is not deployed after `timeout` seconds.
+ """
+ if timeout is not None and timeout < 0:
+ raise ValueError("`timeout` cannot be negative.")
+ if refresh_every <= 0:
+ raise ValueError("`refresh_every` must be positive.")
+
+ start = time.time()
+ while True:
+ if self.status == InferenceEndpointStatus.FAILED:
+ raise InferenceEndpointError(
+ f"Inference Endpoint {self.name} failed to deploy. Please check the logs for more information."
+ )
+ if self.status == InferenceEndpointStatus.UPDATE_FAILED:
+ raise InferenceEndpointError(
+ f"Inference Endpoint {self.name} failed to update. Please check the logs for more information."
+ )
+ if self.status == InferenceEndpointStatus.RUNNING and self.url is not None:
+ # Verify the endpoint is actually reachable
+ _health_url = f"{self.url.rstrip('/')}/{self.health_route.lstrip('/')}"
+ response = get_session().get(_health_url, headers=self._api._build_hf_headers(token=self._token))
+ if response.status_code == 200:
+ logger.info("Inference Endpoint is ready to be used.")
+ return self
+
+ if timeout is not None:
+ if time.time() - start > timeout:
+ raise InferenceEndpointTimeoutError("Timeout while waiting for Inference Endpoint to be deployed.")
+ logger.info(f"Inference Endpoint is not deployed yet ({self.status}). Waiting {refresh_every}s...")
+ time.sleep(refresh_every)
+ self.fetch()
+
+ def fetch(self) -> "InferenceEndpoint":
+ """Fetch latest information about the Inference Endpoint.
+
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+ """
+ obj = self._api.get_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token) # type: ignore [arg-type]
+ self.raw = obj.raw
+ self._populate_from_raw()
+ return self
+
+ def update(
+ self,
+ *,
+ # Compute update
+ accelerator: Optional[str] = None,
+ instance_size: Optional[str] = None,
+ instance_type: Optional[str] = None,
+ min_replica: Optional[int] = None,
+ max_replica: Optional[int] = None,
+ scale_to_zero_timeout: Optional[int] = None,
+ # Model update
+ repository: Optional[str] = None,
+ framework: Optional[str] = None,
+ revision: Optional[str] = None,
+ task: Optional[str] = None,
+ custom_image: Optional[Dict] = None,
+ secrets: Optional[Dict[str, str]] = None,
+ ) -> "InferenceEndpoint":
+ """Update the Inference Endpoint.
+
+ This method allows the update of either the compute configuration, the deployed model, or both. All arguments are
+ optional but at least one must be provided.
+
+ This is an alias for [`HfApi.update_inference_endpoint`]. The current object is mutated in place with the
+ latest data from the server.
+
+ Args:
+ accelerator (`str`, *optional*):
+ The hardware accelerator to be used for inference (e.g. `"cpu"`).
+ instance_size (`str`, *optional*):
+ The size or type of the instance to be used for hosting the model (e.g. `"x4"`).
+ instance_type (`str`, *optional*):
+ The cloud instance type where the Inference Endpoint will be deployed (e.g. `"intel-icl"`).
+ min_replica (`int`, *optional*):
+ The minimum number of replicas (instances) to keep running for the Inference Endpoint.
+ max_replica (`int`, *optional*):
+ The maximum number of replicas (instances) to scale to for the Inference Endpoint.
+ scale_to_zero_timeout (`int`, *optional*):
+ The duration in minutes before an inactive endpoint is scaled to zero.
+
+ repository (`str`, *optional*):
+ The name of the model repository associated with the Inference Endpoint (e.g. `"gpt2"`).
+ framework (`str`, *optional*):
+ The machine learning framework used for the model (e.g. `"custom"`).
+ revision (`str`, *optional*):
+ The specific model revision to deploy on the Inference Endpoint (e.g. `"6c0e6080953db56375760c0471a8c5f2929baf11"`).
+ task (`str`, *optional*):
+ The task on which to deploy the model (e.g. `"text-classification"`).
+ custom_image (`Dict`, *optional*):
+ A custom Docker image to use for the Inference Endpoint. This is useful if you want to deploy an
+ Inference Endpoint running on the `text-generation-inference` (TGI) framework (see examples).
+ secrets (`Dict[str, str]`, *optional*):
+ Secret values to inject in the container environment.
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+ """
+ # Make API call
+ obj = self._api.update_inference_endpoint(
+ name=self.name,
+ namespace=self.namespace,
+ accelerator=accelerator,
+ instance_size=instance_size,
+ instance_type=instance_type,
+ min_replica=min_replica,
+ max_replica=max_replica,
+ scale_to_zero_timeout=scale_to_zero_timeout,
+ repository=repository,
+ framework=framework,
+ revision=revision,
+ task=task,
+ custom_image=custom_image,
+ secrets=secrets,
+ token=self._token, # type: ignore [arg-type]
+ )
+
+ # Mutate current object
+ self.raw = obj.raw
+ self._populate_from_raw()
+ return self
+
+ def pause(self) -> "InferenceEndpoint":
+ """Pause the Inference Endpoint.
+
+ A paused Inference Endpoint will not be charged. It can be resumed at any time using [`InferenceEndpoint.resume`].
+ This is different than scaling the Inference Endpoint to zero with [`InferenceEndpoint.scale_to_zero`], which
+ would be automatically restarted when a request is made to it.
+
+ This is an alias for [`HfApi.pause_inference_endpoint`]. The current object is mutated in place with the
+ latest data from the server.
+
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+ """
+ obj = self._api.pause_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token) # type: ignore [arg-type]
+ self.raw = obj.raw
+ self._populate_from_raw()
+ return self
+
+ def resume(self, running_ok: bool = True) -> "InferenceEndpoint":
+ """Resume the Inference Endpoint.
+
+ This is an alias for [`HfApi.resume_inference_endpoint`]. The current object is mutated in place with the
+ latest data from the server.
+
+ Args:
+ running_ok (`bool`, *optional*):
+ If `True`, the method will not raise an error if the Inference Endpoint is already running. Defaults to
+ `True`.
+
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+ """
+ obj = self._api.resume_inference_endpoint(
+ name=self.name, namespace=self.namespace, running_ok=running_ok, token=self._token
+ ) # type: ignore [arg-type]
+ self.raw = obj.raw
+ self._populate_from_raw()
+ return self
+
+ def scale_to_zero(self) -> "InferenceEndpoint":
+ """Scale Inference Endpoint to zero.
+
+ An Inference Endpoint scaled to zero will not be charged. It will be resume on the next request to it, with a
+ cold start delay. This is different than pausing the Inference Endpoint with [`InferenceEndpoint.pause`], which
+ would require a manual resume with [`InferenceEndpoint.resume`].
+
+ This is an alias for [`HfApi.scale_to_zero_inference_endpoint`]. The current object is mutated in place with the
+ latest data from the server.
+
+ Returns:
+ [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+ """
+ obj = self._api.scale_to_zero_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token) # type: ignore [arg-type]
+ self.raw = obj.raw
+ self._populate_from_raw()
+ return self
+
+ def delete(self) -> None:
+ """Delete the Inference Endpoint.
+
+ This operation is not reversible. If you don't want to be charged for an Inference Endpoint, it is preferable
+ to pause it with [`InferenceEndpoint.pause`] or scale it to zero with [`InferenceEndpoint.scale_to_zero`].
+
+ This is an alias for [`HfApi.delete_inference_endpoint`].
+ """
+ self._api.delete_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token) # type: ignore [arg-type]
+
+ def _populate_from_raw(self) -> None:
+ """Populate fields from raw dictionary.
+
+ Called in __post_init__ + each time the Inference Endpoint is updated.
+ """
+ # Repr fields
+ self.name = self.raw["name"]
+ self.repository = self.raw["model"]["repository"]
+ self.status = self.raw["status"]["state"]
+ self.url = self.raw["status"].get("url")
+ self.health_route = self.raw["healthRoute"]
+
+ # Other fields
+ self.framework = self.raw["model"]["framework"]
+ self.revision = self.raw["model"]["revision"]
+ self.task = self.raw["model"]["task"]
+ self.created_at = parse_datetime(self.raw["status"]["createdAt"])
+ self.updated_at = parse_datetime(self.raw["status"]["updatedAt"])
+ self.type = self.raw["type"]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_jobs_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_jobs_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..00177a008c177d5484fb9069d0684bbf416e9289
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_jobs_api.py
@@ -0,0 +1,301 @@
+# coding=utf-8
+# Copyright 2025-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from dataclasses import dataclass
+from datetime import datetime
+from enum import Enum
+from typing import Any, Dict, List, Optional, Union
+
+from huggingface_hub import constants
+from huggingface_hub._space_api import SpaceHardware
+from huggingface_hub.utils._datetime import parse_datetime
+
+
+class JobStage(str, Enum):
+ """
+ Enumeration of possible stage of a Job on the Hub.
+
+ Value can be compared to a string:
+ ```py
+ assert JobStage.COMPLETED == "COMPLETED"
+ ```
+ Possible values are: `COMPLETED`, `CANCELED`, `ERROR`, `DELETED`, `RUNNING`.
+ Taken from https://github.com/huggingface/moon-landing/blob/main/server/job_types/JobInfo.ts#L61 (private url).
+ """
+
+ # Copied from moon-landing > server > lib > Job.ts
+ COMPLETED = "COMPLETED"
+ CANCELED = "CANCELED"
+ ERROR = "ERROR"
+ DELETED = "DELETED"
+ RUNNING = "RUNNING"
+
+
+@dataclass
+class JobStatus:
+ stage: JobStage
+ message: Optional[str]
+
+
+@dataclass
+class JobOwner:
+ id: str
+ name: str
+ type: str
+
+
+@dataclass
+class JobInfo:
+ """
+ Contains information about a Job.
+
+ Args:
+ id (`str`):
+ Job ID.
+ created_at (`datetime` or `None`):
+ When the Job was created.
+ docker_image (`str` or `None`):
+ The Docker image from Docker Hub used for the Job.
+ Can be None if space_id is present instead.
+ space_id (`str` or `None`):
+ The Docker image from Hugging Face Spaces used for the Job.
+ Can be None if docker_image is present instead.
+ command (`List[str]` or `None`):
+ Command of the Job, e.g. `["python", "-c", "print('hello world')"]`
+ arguments (`List[str]` or `None`):
+ Arguments passed to the command
+ environment (`Dict[str]` or `None`):
+ Environment variables of the Job as a dictionary.
+ secrets (`Dict[str]` or `None`):
+ Secret environment variables of the Job (encrypted).
+ flavor (`str` or `None`):
+ Flavor for the hardware, as in Hugging Face Spaces. See [`SpaceHardware`] for possible values.
+ E.g. `"cpu-basic"`.
+ status: (`JobStatus` or `None`):
+ Status of the Job, e.g. `JobStatus(stage="RUNNING", message=None)`
+ See [`JobStage`] for possible stage values.
+ owner: (`JobOwner` or `None`):
+ Owner of the Job, e.g. `JobOwner(id="5e9ecfc04957053f60648a3e", name="lhoestq", type="user")`
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import run_job
+ >>> job = run_job(
+ ... image="python:3.12",
+ ... command=["python", "-c", "print('Hello from the cloud!')"]
+ ... )
+ >>> job
+ JobInfo(id='687fb701029421ae5549d998', created_at=datetime.datetime(2025, 7, 22, 16, 6, 25, 79000, tzinfo=datetime.timezone.utc), docker_image='python:3.12', space_id=None, command=['python', '-c', "print('Hello from the cloud!')"], arguments=[], environment={}, secrets={}, flavor='cpu-basic', status=JobStatus(stage='RUNNING', message=None), owner=JobOwner(id='5e9ecfc04957053f60648a3e', name='lhoestq', type='user'), endpoint='https://huggingface.co', url='https://huggingface.co/jobs/lhoestq/687fb701029421ae5549d998')
+ >>> job.id
+ '687fb701029421ae5549d998'
+ >>> job.url
+ 'https://huggingface.co/jobs/lhoestq/687fb701029421ae5549d998'
+ >>> job.status.stage
+ 'RUNNING'
+ ```
+ """
+
+ id: str
+ created_at: Optional[datetime]
+ docker_image: Optional[str]
+ space_id: Optional[str]
+ command: Optional[List[str]]
+ arguments: Optional[List[str]]
+ environment: Optional[Dict[str, Any]]
+ secrets: Optional[Dict[str, Any]]
+ flavor: Optional[SpaceHardware]
+ status: JobStatus
+ owner: JobOwner
+
+ # Inferred fields
+ endpoint: str
+ url: str
+
+ def __init__(self, **kwargs) -> None:
+ self.id = kwargs["id"]
+ created_at = kwargs.get("createdAt") or kwargs.get("created_at")
+ self.created_at = parse_datetime(created_at) if created_at else None
+ self.docker_image = kwargs.get("dockerImage") or kwargs.get("docker_image")
+ self.space_id = kwargs.get("spaceId") or kwargs.get("space_id")
+ owner = kwargs.get("owner", {})
+ self.owner = JobOwner(id=owner["id"], name=owner["name"], type=owner["type"])
+ self.command = kwargs.get("command")
+ self.arguments = kwargs.get("arguments")
+ self.environment = kwargs.get("environment")
+ self.secrets = kwargs.get("secrets")
+ self.flavor = kwargs.get("flavor")
+ status = kwargs.get("status", {})
+ self.status = JobStatus(stage=status["stage"], message=status.get("message"))
+
+ # Inferred fields
+ self.endpoint = kwargs.get("endpoint", constants.ENDPOINT)
+ self.url = f"{self.endpoint}/jobs/{self.owner.name}/{self.id}"
+
+
+@dataclass
+class JobSpec:
+ docker_image: Optional[str]
+ space_id: Optional[str]
+ command: Optional[List[str]]
+ arguments: Optional[List[str]]
+ environment: Optional[Dict[str, Any]]
+ secrets: Optional[Dict[str, Any]]
+ flavor: Optional[SpaceHardware]
+ timeout: Optional[int]
+ tags: Optional[List[str]]
+ arch: Optional[str]
+
+ def __init__(self, **kwargs) -> None:
+ self.docker_image = kwargs.get("dockerImage") or kwargs.get("docker_image")
+ self.space_id = kwargs.get("spaceId") or kwargs.get("space_id")
+ self.command = kwargs.get("command")
+ self.arguments = kwargs.get("arguments")
+ self.environment = kwargs.get("environment")
+ self.secrets = kwargs.get("secrets")
+ self.flavor = kwargs.get("flavor")
+ self.timeout = kwargs.get("timeout")
+ self.tags = kwargs.get("tags")
+ self.arch = kwargs.get("arch")
+
+
+@dataclass
+class LastJobInfo:
+ id: str
+ at: datetime
+
+ def __init__(self, **kwargs) -> None:
+ self.id = kwargs["id"]
+ self.at = parse_datetime(kwargs["at"])
+
+
+@dataclass
+class ScheduledJobStatus:
+ last_job: Optional[LastJobInfo]
+ next_job_run_at: Optional[datetime]
+
+ def __init__(self, **kwargs) -> None:
+ last_job = kwargs.get("lastJob") or kwargs.get("last_job")
+ self.last_job = LastJobInfo(**last_job) if last_job else None
+ next_job_run_at = kwargs.get("nextJobRunAt") or kwargs.get("next_job_run_at")
+ self.next_job_run_at = parse_datetime(str(next_job_run_at)) if next_job_run_at else None
+
+
+@dataclass
+class ScheduledJobInfo:
+ """
+ Contains information about a Job.
+
+ Args:
+ id (`str`):
+ Scheduled Job ID.
+ created_at (`datetime` or `None`):
+ When the scheduled Job was created.
+ tags (`List[str]` or `None`):
+ The tags of the scheduled Job.
+ schedule (`str` or `None`):
+ One of "@annually", "@yearly", "@monthly", "@weekly", "@daily", "@hourly", or a
+ CRON schedule expression (e.g., '0 9 * * 1' for 9 AM every Monday).
+ suspend (`bool` or `None`):
+ Whether the scheduled job is suspended (paused).
+ concurrency (`bool` or `None`):
+ Whether multiple instances of this Job can run concurrently.
+ status (`ScheduledJobStatus` or `None`):
+ Status of the scheduled Job.
+ owner: (`JobOwner` or `None`):
+ Owner of the scheduled Job, e.g. `JobOwner(id="5e9ecfc04957053f60648a3e", name="lhoestq", type="user")`
+ job_spec: (`JobSpec` or `None`):
+ Specifications of the Job.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import run_job
+ >>> scheduled_job = create_scheduled_job(
+ ... image="python:3.12",
+ ... command=["python", "-c", "print('Hello from the cloud!')"],
+ ... schedule="@hourly",
+ ... )
+ >>> scheduled_job.id
+ '687fb701029421ae5549d999'
+ >>> scheduled_job.status.next_job_run_at
+ datetime.datetime(2025, 7, 22, 17, 6, 25, 79000, tzinfo=datetime.timezone.utc)
+ ```
+ """
+
+ id: str
+ created_at: Optional[datetime]
+ job_spec: JobSpec
+ schedule: Optional[str]
+ suspend: Optional[bool]
+ concurrency: Optional[bool]
+ status: ScheduledJobStatus
+ owner: JobOwner
+
+ def __init__(self, **kwargs) -> None:
+ self.id = kwargs["id"]
+ created_at = kwargs.get("createdAt") or kwargs.get("created_at")
+ self.created_at = parse_datetime(created_at) if created_at else None
+ self.job_spec = JobSpec(**(kwargs.get("job_spec") or kwargs.get("jobSpec", {})))
+ self.schedule = kwargs.get("schedule")
+ self.suspend = kwargs.get("suspend")
+ self.concurrency = kwargs.get("concurrency")
+ status = kwargs.get("status", {})
+ self.status = ScheduledJobStatus(
+ last_job=status.get("last_job") or status.get("lastJob"),
+ next_job_run_at=status.get("next_job_run_at") or status.get("nextJobRunAt"),
+ )
+ owner = kwargs.get("owner", {})
+ self.owner = JobOwner(id=owner["id"], name=owner["name"], type=owner["type"])
+
+
+def _create_job_spec(
+ *,
+ image: str,
+ command: List[str],
+ env: Optional[Dict[str, Any]],
+ secrets: Optional[Dict[str, Any]],
+ flavor: Optional[SpaceHardware],
+ timeout: Optional[Union[int, float, str]],
+) -> Dict[str, Any]:
+ # prepare job spec to send to HF Jobs API
+ job_spec: Dict[str, Any] = {
+ "command": command,
+ "arguments": [],
+ "environment": env or {},
+ "flavor": flavor or SpaceHardware.CPU_BASIC,
+ }
+ # secrets are optional
+ if secrets:
+ job_spec["secrets"] = secrets
+ # timeout is optional
+ if timeout:
+ time_units_factors = {"s": 1, "m": 60, "h": 3600, "d": 3600 * 24}
+ if isinstance(timeout, str) and timeout[-1] in time_units_factors:
+ job_spec["timeoutSeconds"] = int(float(timeout[:-1]) * time_units_factors[timeout[-1]])
+ else:
+ job_spec["timeoutSeconds"] = int(timeout)
+ # input is either from docker hub or from HF spaces
+ for prefix in (
+ "https://huggingface.co/spaces/",
+ "https://hf.co/spaces/",
+ "huggingface.co/spaces/",
+ "hf.co/spaces/",
+ ):
+ if image.startswith(prefix):
+ job_spec["spaceId"] = image[len(prefix) :]
+ break
+ else:
+ job_spec["dockerImage"] = image
+ return job_spec
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_local_folder.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_local_folder.py
new file mode 100644
index 0000000000000000000000000000000000000000..37f6c32a760ecf03794c129735fe2e15516952d1
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_local_folder.py
@@ -0,0 +1,447 @@
+# coding=utf-8
+# Copyright 2024-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains utilities to handle the `../.cache/huggingface` folder in local directories.
+
+First discussed in https://github.com/huggingface/huggingface_hub/issues/1738 to store
+download metadata when downloading files from the hub to a local directory (without
+using the cache).
+
+./.cache/huggingface folder structure:
+[4.0K] data
+├── [4.0K] .cache
+│ └── [4.0K] huggingface
+│ └── [4.0K] download
+│ ├── [ 16] file.parquet.metadata
+│ ├── [ 16] file.txt.metadata
+│ └── [4.0K] folder
+│ └── [ 16] file.parquet.metadata
+│
+├── [6.5G] file.parquet
+├── [1.5K] file.txt
+└── [4.0K] folder
+ └── [ 16] file.parquet
+
+
+Download metadata file structure:
+```
+# file.txt.metadata
+11c5a3d5811f50298f278a704980280950aedb10
+a16a55fda99d2f2e7b69cce5cf93ff4ad3049930
+1712656091.123
+
+# file.parquet.metadata
+11c5a3d5811f50298f278a704980280950aedb10
+7c5d3f4b8b76583b422fcb9189ad6c89d5d97a094541ce8932dce3ecabde1421
+1712656091.123
+}
+```
+"""
+
+import base64
+import hashlib
+import logging
+import os
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Optional
+
+from .utils import WeakFileLock
+
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class LocalDownloadFilePaths:
+ """
+ Paths to the files related to a download process in a local dir.
+
+ Returned by [`get_local_download_paths`].
+
+ Attributes:
+ file_path (`Path`):
+ Path where the file will be saved.
+ lock_path (`Path`):
+ Path to the lock file used to ensure atomicity when reading/writing metadata.
+ metadata_path (`Path`):
+ Path to the metadata file.
+ """
+
+ file_path: Path
+ lock_path: Path
+ metadata_path: Path
+
+ def incomplete_path(self, etag: str) -> Path:
+ """Return the path where a file will be temporarily downloaded before being moved to `file_path`."""
+ path = self.metadata_path.parent / f"{_short_hash(self.metadata_path.name)}.{etag}.incomplete"
+ resolved_path = str(path.resolve())
+ # Some Windows versions do not allow for paths longer than 255 characters.
+ # In this case, we must specify it as an extended path by using the "\\?\" prefix.
+ if os.name == "nt" and len(resolved_path) > 255 and not resolved_path.startswith("\\\\?\\"):
+ path = Path("\\\\?\\" + resolved_path)
+ return path
+
+
+@dataclass(frozen=True)
+class LocalUploadFilePaths:
+ """
+ Paths to the files related to an upload process in a local dir.
+
+ Returned by [`get_local_upload_paths`].
+
+ Attributes:
+ path_in_repo (`str`):
+ Path of the file in the repo.
+ file_path (`Path`):
+ Path where the file will be saved.
+ lock_path (`Path`):
+ Path to the lock file used to ensure atomicity when reading/writing metadata.
+ metadata_path (`Path`):
+ Path to the metadata file.
+ """
+
+ path_in_repo: str
+ file_path: Path
+ lock_path: Path
+ metadata_path: Path
+
+
+@dataclass
+class LocalDownloadFileMetadata:
+ """
+ Metadata about a file in the local directory related to a download process.
+
+ Attributes:
+ filename (`str`):
+ Path of the file in the repo.
+ commit_hash (`str`):
+ Commit hash of the file in the repo.
+ etag (`str`):
+ ETag of the file in the repo. Used to check if the file has changed.
+ For LFS files, this is the sha256 of the file. For regular files, it corresponds to the git hash.
+ timestamp (`int`):
+ Unix timestamp of when the metadata was saved i.e. when the metadata was accurate.
+ """
+
+ filename: str
+ commit_hash: str
+ etag: str
+ timestamp: float
+
+
+@dataclass
+class LocalUploadFileMetadata:
+ """
+ Metadata about a file in the local directory related to an upload process.
+ """
+
+ size: int
+
+ # Default values correspond to "we don't know yet"
+ timestamp: Optional[float] = None
+ should_ignore: Optional[bool] = None
+ sha256: Optional[str] = None
+ upload_mode: Optional[str] = None
+ remote_oid: Optional[str] = None
+ is_uploaded: bool = False
+ is_committed: bool = False
+
+ def save(self, paths: LocalUploadFilePaths) -> None:
+ """Save the metadata to disk."""
+ with WeakFileLock(paths.lock_path):
+ with paths.metadata_path.open("w") as f:
+ new_timestamp = time.time()
+ f.write(str(new_timestamp) + "\n")
+
+ f.write(str(self.size)) # never None
+ f.write("\n")
+
+ if self.should_ignore is not None:
+ f.write(str(int(self.should_ignore)))
+ f.write("\n")
+
+ if self.sha256 is not None:
+ f.write(self.sha256)
+ f.write("\n")
+
+ if self.upload_mode is not None:
+ f.write(self.upload_mode)
+ f.write("\n")
+
+ if self.remote_oid is not None:
+ f.write(self.remote_oid)
+ f.write("\n")
+
+ f.write(str(int(self.is_uploaded)) + "\n")
+ f.write(str(int(self.is_committed)) + "\n")
+
+ self.timestamp = new_timestamp
+
+
+def get_local_download_paths(local_dir: Path, filename: str) -> LocalDownloadFilePaths:
+ """Compute paths to the files related to a download process.
+
+ Folders containing the paths are all guaranteed to exist.
+
+ Args:
+ local_dir (`Path`):
+ Path to the local directory in which files are downloaded.
+ filename (`str`):
+ Path of the file in the repo.
+
+ Return:
+ [`LocalDownloadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path, incomplete_path).
+ """
+ # filename is the path in the Hub repository (separated by '/')
+ # make sure to have a cross platform transcription
+ sanitized_filename = os.path.join(*filename.split("/"))
+ if os.name == "nt":
+ if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:
+ raise ValueError(
+ f"Invalid filename: cannot handle filename '{sanitized_filename}' on Windows. Please ask the repository"
+ " owner to rename this file."
+ )
+ file_path = local_dir / sanitized_filename
+ metadata_path = _huggingface_dir(local_dir) / "download" / f"{sanitized_filename}.metadata"
+ lock_path = metadata_path.with_suffix(".lock")
+
+ # Some Windows versions do not allow for paths longer than 255 characters.
+ # In this case, we must specify it as an extended path by using the "\\?\" prefix
+ if os.name == "nt":
+ if not str(local_dir).startswith("\\\\?\\") and len(os.path.abspath(lock_path)) > 255:
+ file_path = Path("\\\\?\\" + os.path.abspath(file_path))
+ lock_path = Path("\\\\?\\" + os.path.abspath(lock_path))
+ metadata_path = Path("\\\\?\\" + os.path.abspath(metadata_path))
+
+ file_path.parent.mkdir(parents=True, exist_ok=True)
+ metadata_path.parent.mkdir(parents=True, exist_ok=True)
+ return LocalDownloadFilePaths(file_path=file_path, lock_path=lock_path, metadata_path=metadata_path)
+
+
+def get_local_upload_paths(local_dir: Path, filename: str) -> LocalUploadFilePaths:
+ """Compute paths to the files related to an upload process.
+
+ Folders containing the paths are all guaranteed to exist.
+
+ Args:
+ local_dir (`Path`):
+ Path to the local directory that is uploaded.
+ filename (`str`):
+ Path of the file in the repo.
+
+ Return:
+ [`LocalUploadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path).
+ """
+ # filename is the path in the Hub repository (separated by '/')
+ # make sure to have a cross platform transcription
+ sanitized_filename = os.path.join(*filename.split("/"))
+ if os.name == "nt":
+ if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:
+ raise ValueError(
+ f"Invalid filename: cannot handle filename '{sanitized_filename}' on Windows. Please ask the repository"
+ " owner to rename this file."
+ )
+ file_path = local_dir / sanitized_filename
+ metadata_path = _huggingface_dir(local_dir) / "upload" / f"{sanitized_filename}.metadata"
+ lock_path = metadata_path.with_suffix(".lock")
+
+ # Some Windows versions do not allow for paths longer than 255 characters.
+ # In this case, we must specify it as an extended path by using the "\\?\" prefix
+ if os.name == "nt":
+ if not str(local_dir).startswith("\\\\?\\") and len(os.path.abspath(lock_path)) > 255:
+ file_path = Path("\\\\?\\" + os.path.abspath(file_path))
+ lock_path = Path("\\\\?\\" + os.path.abspath(lock_path))
+ metadata_path = Path("\\\\?\\" + os.path.abspath(metadata_path))
+
+ file_path.parent.mkdir(parents=True, exist_ok=True)
+ metadata_path.parent.mkdir(parents=True, exist_ok=True)
+ return LocalUploadFilePaths(
+ path_in_repo=filename, file_path=file_path, lock_path=lock_path, metadata_path=metadata_path
+ )
+
+
+def read_download_metadata(local_dir: Path, filename: str) -> Optional[LocalDownloadFileMetadata]:
+ """Read metadata about a file in the local directory related to a download process.
+
+ Args:
+ local_dir (`Path`):
+ Path to the local directory in which files are downloaded.
+ filename (`str`):
+ Path of the file in the repo.
+
+ Return:
+ `[LocalDownloadFileMetadata]` or `None`: the metadata if it exists, `None` otherwise.
+ """
+ paths = get_local_download_paths(local_dir, filename)
+ with WeakFileLock(paths.lock_path):
+ if paths.metadata_path.exists():
+ try:
+ with paths.metadata_path.open() as f:
+ commit_hash = f.readline().strip()
+ etag = f.readline().strip()
+ timestamp = float(f.readline().strip())
+ metadata = LocalDownloadFileMetadata(
+ filename=filename,
+ commit_hash=commit_hash,
+ etag=etag,
+ timestamp=timestamp,
+ )
+ except Exception as e:
+ # remove the metadata file if it is corrupted / not the right format
+ logger.warning(
+ f"Invalid metadata file {paths.metadata_path}: {e}. Removing it from disk and continue."
+ )
+ try:
+ paths.metadata_path.unlink()
+ except Exception as e:
+ logger.warning(f"Could not remove corrupted metadata file {paths.metadata_path}: {e}")
+
+ try:
+ # check if the file exists and hasn't been modified since the metadata was saved
+ stat = paths.file_path.stat()
+ if (
+ stat.st_mtime - 1 <= metadata.timestamp
+ ): # allow 1s difference as stat.st_mtime might not be precise
+ return metadata
+ logger.info(f"Ignored metadata for '{filename}' (outdated). Will re-compute hash.")
+ except FileNotFoundError:
+ # file does not exist => metadata is outdated
+ return None
+ return None
+
+
+def read_upload_metadata(local_dir: Path, filename: str) -> LocalUploadFileMetadata:
+ """Read metadata about a file in the local directory related to an upload process.
+
+ TODO: factorize logic with `read_download_metadata`.
+
+ Args:
+ local_dir (`Path`):
+ Path to the local directory in which files are downloaded.
+ filename (`str`):
+ Path of the file in the repo.
+
+ Return:
+ `[LocalUploadFileMetadata]` or `None`: the metadata if it exists, `None` otherwise.
+ """
+ paths = get_local_upload_paths(local_dir, filename)
+ with WeakFileLock(paths.lock_path):
+ if paths.metadata_path.exists():
+ try:
+ with paths.metadata_path.open() as f:
+ timestamp = float(f.readline().strip())
+
+ size = int(f.readline().strip()) # never None
+
+ _should_ignore = f.readline().strip()
+ should_ignore = None if _should_ignore == "" else bool(int(_should_ignore))
+
+ _sha256 = f.readline().strip()
+ sha256 = None if _sha256 == "" else _sha256
+
+ _upload_mode = f.readline().strip()
+ upload_mode = None if _upload_mode == "" else _upload_mode
+ if upload_mode not in (None, "regular", "lfs"):
+ raise ValueError(f"Invalid upload mode in metadata {paths.path_in_repo}: {upload_mode}")
+
+ _remote_oid = f.readline().strip()
+ remote_oid = None if _remote_oid == "" else _remote_oid
+
+ is_uploaded = bool(int(f.readline().strip()))
+ is_committed = bool(int(f.readline().strip()))
+
+ metadata = LocalUploadFileMetadata(
+ timestamp=timestamp,
+ size=size,
+ should_ignore=should_ignore,
+ sha256=sha256,
+ upload_mode=upload_mode,
+ remote_oid=remote_oid,
+ is_uploaded=is_uploaded,
+ is_committed=is_committed,
+ )
+ except Exception as e:
+ # remove the metadata file if it is corrupted / not the right format
+ logger.warning(
+ f"Invalid metadata file {paths.metadata_path}: {e}. Removing it from disk and continue."
+ )
+ try:
+ paths.metadata_path.unlink()
+ except Exception as e:
+ logger.warning(f"Could not remove corrupted metadata file {paths.metadata_path}: {e}")
+
+ # TODO: can we do better?
+ if (
+ metadata.timestamp is not None
+ and metadata.is_uploaded # file was uploaded
+ and not metadata.is_committed # but not committed
+ and time.time() - metadata.timestamp > 20 * 3600 # and it's been more than 20 hours
+ ): # => we consider it as garbage-collected by S3
+ metadata.is_uploaded = False
+
+ # check if the file exists and hasn't been modified since the metadata was saved
+ try:
+ if metadata.timestamp is not None and paths.file_path.stat().st_mtime <= metadata.timestamp:
+ return metadata
+ logger.info(f"Ignored metadata for '{filename}' (outdated). Will re-compute hash.")
+ except FileNotFoundError:
+ # file does not exist => metadata is outdated
+ pass
+
+ # empty metadata => we don't know anything expect its size
+ return LocalUploadFileMetadata(size=paths.file_path.stat().st_size)
+
+
+def write_download_metadata(local_dir: Path, filename: str, commit_hash: str, etag: str) -> None:
+ """Write metadata about a file in the local directory related to a download process.
+
+ Args:
+ local_dir (`Path`):
+ Path to the local directory in which files are downloaded.
+ """
+ paths = get_local_download_paths(local_dir, filename)
+ with WeakFileLock(paths.lock_path):
+ with paths.metadata_path.open("w") as f:
+ f.write(f"{commit_hash}\n{etag}\n{time.time()}\n")
+
+
+def _huggingface_dir(local_dir: Path) -> Path:
+ """Return the path to the `.cache/huggingface` directory in a local directory."""
+ # Wrap in lru_cache to avoid overwriting the .gitignore file if called multiple times
+ path = local_dir / ".cache" / "huggingface"
+ path.mkdir(exist_ok=True, parents=True)
+
+ # Create a .gitignore file in the .cache/huggingface directory if it doesn't exist
+ # Should be thread-safe enough like this.
+ gitignore = path / ".gitignore"
+ gitignore_lock = path / ".gitignore.lock"
+ if not gitignore.exists():
+ try:
+ with WeakFileLock(gitignore_lock, timeout=0.1):
+ gitignore.write_text("*")
+ except IndexError:
+ pass
+ except OSError: # TimeoutError, FileNotFoundError, PermissionError, etc.
+ pass
+ try:
+ gitignore_lock.unlink()
+ except OSError:
+ pass
+ return path
+
+
+def _short_hash(filename: str) -> str:
+ return base64.urlsafe_b64encode(hashlib.sha1(filename.encode()).digest()).decode()
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_login.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_login.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f721b68348fc3abeb2f90b6a756cb125ce19571
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_login.py
@@ -0,0 +1,514 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains methods to log in to the Hub."""
+
+import os
+import subprocess
+from getpass import getpass
+from pathlib import Path
+from typing import Optional
+
+from . import constants
+from .commands._cli_utils import ANSI
+from .utils import (
+ capture_output,
+ get_token,
+ is_google_colab,
+ is_notebook,
+ list_credential_helpers,
+ logging,
+ run_subprocess,
+ set_git_credential,
+ unset_git_credential,
+)
+from .utils._auth import (
+ _get_token_by_name,
+ _get_token_from_environment,
+ _get_token_from_file,
+ _get_token_from_google_colab,
+ _save_stored_tokens,
+ _save_token,
+ get_stored_tokens,
+)
+from .utils._deprecation import _deprecate_arguments, _deprecate_positional_args
+
+
+logger = logging.get_logger(__name__)
+
+_HF_LOGO_ASCII = """
+ _| _| _| _| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _|_|_|_| _|_| _|_|_| _|_|_|_|
+ _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|
+ _|_|_|_| _| _| _| _|_| _| _|_| _| _| _| _| _| _|_| _|_|_| _|_|_|_| _| _|_|_|
+ _| _| _| _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|
+ _| _| _|_| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _| _| _| _|_|_| _|_|_|_|
+"""
+
+
+@_deprecate_arguments(
+ version="1.0",
+ deprecated_args="write_permission",
+ custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def login(
+ token: Optional[str] = None,
+ *,
+ add_to_git_credential: bool = False,
+ new_session: bool = True,
+ write_permission: bool = False,
+) -> None:
+ """Login the machine to access the Hub.
+
+ The `token` is persisted in cache and set as a git credential. Once done, the machine
+ is logged in and the access token will be available across all `huggingface_hub`
+ components. If `token` is not provided, it will be prompted to the user either with
+ a widget (in a notebook) or via the terminal.
+
+ To log in from outside of a script, one can also use `hf auth login` which is
+ a cli command that wraps [`login`].
+
+ > [!TIP]
+ > [`login`] is a drop-in replacement method for [`notebook_login`] as it wraps and
+ > extends its capabilities.
+
+ > [!TIP]
+ > When the token is not passed, [`login`] will automatically detect if the script runs
+ > in a notebook or not. However, this detection might not be accurate due to the
+ > variety of notebooks that exists nowadays. If that is the case, you can always force
+ > the UI by using [`notebook_login`] or [`interpreter_login`].
+
+ Args:
+ token (`str`, *optional*):
+ User access token to generate from https://huggingface.co/settings/token.
+ add_to_git_credential (`bool`, defaults to `False`):
+ If `True`, token will be set as git credential. If no git credential helper
+ is configured, a warning will be displayed to the user. If `token` is `None`,
+ the value of `add_to_git_credential` is ignored and will be prompted again
+ to the end user.
+ new_session (`bool`, defaults to `True`):
+ If `True`, will request a token even if one is already saved on the machine.
+ write_permission (`bool`):
+ Ignored and deprecated argument.
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If an organization token is passed. Only personal account tokens are valid
+ to log in.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If token is invalid.
+ [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+ If running in a notebook but `ipywidgets` is not installed.
+ """
+ if token is not None:
+ if not add_to_git_credential:
+ logger.info(
+ "The token has not been saved to the git credentials helper. Pass "
+ "`add_to_git_credential=True` in this function directly or "
+ "`--add-to-git-credential` if using via `hf`CLI if "
+ "you want to set the git credential as well."
+ )
+ _login(token, add_to_git_credential=add_to_git_credential)
+ elif is_notebook():
+ notebook_login(new_session=new_session)
+ else:
+ interpreter_login(new_session=new_session)
+
+
+def logout(token_name: Optional[str] = None) -> None:
+ """Logout the machine from the Hub.
+
+ Token is deleted from the machine and removed from git credential.
+
+ Args:
+ token_name (`str`, *optional*):
+ Name of the access token to logout from. If `None`, will logout from all saved access tokens.
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+ If the access token name is not found.
+ """
+ if get_token() is None and not get_stored_tokens(): # No active token and no saved access tokens
+ logger.warning("Not logged in!")
+ return
+ if not token_name:
+ # Delete all saved access tokens and token
+ for file_path in (constants.HF_TOKEN_PATH, constants.HF_STORED_TOKENS_PATH):
+ try:
+ Path(file_path).unlink()
+ except FileNotFoundError:
+ pass
+ logger.info("Successfully logged out from all access tokens.")
+ else:
+ _logout_from_token(token_name)
+ logger.info(f"Successfully logged out from access token: {token_name}.")
+
+ unset_git_credential()
+
+ # Check if still logged in
+ if _get_token_from_google_colab() is not None:
+ raise EnvironmentError(
+ "You are automatically logged in using a Google Colab secret.\n"
+ "To log out, you must unset the `HF_TOKEN` secret in your Colab settings."
+ )
+ if _get_token_from_environment() is not None:
+ raise EnvironmentError(
+ "Token has been deleted from your machine but you are still logged in.\n"
+ "To log out, you must clear out both `HF_TOKEN` and `HUGGING_FACE_HUB_TOKEN` environment variables."
+ )
+
+
+def auth_switch(token_name: str, add_to_git_credential: bool = False) -> None:
+ """Switch to a different access token.
+
+ Args:
+ token_name (`str`):
+ Name of the access token to switch to.
+ add_to_git_credential (`bool`, defaults to `False`):
+ If `True`, token will be set as git credential. If no git credential helper
+ is configured, a warning will be displayed to the user. If `token` is `None`,
+ the value of `add_to_git_credential` is ignored and will be prompted again
+ to the end user.
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+ If the access token name is not found.
+ """
+ token = _get_token_by_name(token_name)
+ if not token:
+ raise ValueError(f"Access token {token_name} not found in {constants.HF_STORED_TOKENS_PATH}")
+ # Write token to HF_TOKEN_PATH
+ _set_active_token(token_name, add_to_git_credential)
+ logger.info(f"The current active token is: {token_name}")
+ token_from_environment = _get_token_from_environment()
+ if token_from_environment is not None and token_from_environment != token:
+ logger.warning(
+ "The environment variable `HF_TOKEN` is set and will override the access token you've just switched to."
+ )
+
+
+def auth_list() -> None:
+ """List all stored access tokens."""
+ tokens = get_stored_tokens()
+
+ if not tokens:
+ logger.info("No access tokens found.")
+ return
+ # Find current token
+ current_token = get_token()
+ current_token_name = None
+ for token_name in tokens:
+ if tokens.get(token_name) == current_token:
+ current_token_name = token_name
+ # Print header
+ max_offset = max(len("token"), max(len(token) for token in tokens)) + 2
+ print(f" {{:<{max_offset}}}| {{:<15}}".format("name", "token"))
+ print("-" * (max_offset + 2) + "|" + "-" * 15)
+
+ # Print saved access tokens
+ for token_name in tokens:
+ token = tokens.get(token_name, "")
+ masked_token = f"{token[:3]}****{token[-4:]}" if token != "" else token
+ is_current = "*" if token == current_token else " "
+
+ print(f"{is_current} {{:<{max_offset}}}| {{:<15}}".format(token_name, masked_token))
+
+ if _get_token_from_environment():
+ logger.warning(
+ "\nNote: Environment variable `HF_TOKEN` is set and is the current active token independently from the stored tokens listed above."
+ )
+ elif current_token_name is None:
+ logger.warning(
+ "\nNote: No active token is set and no environment variable `HF_TOKEN` is found. Use `hf auth login` to log in."
+ )
+
+
+###
+# Interpreter-based login (text)
+###
+
+
+@_deprecate_arguments(
+ version="1.0",
+ deprecated_args="write_permission",
+ custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def interpreter_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+ """
+ Displays a prompt to log in to the HF website and store the token.
+
+ This is equivalent to [`login`] without passing a token when not run in a notebook.
+ [`interpreter_login`] is useful if you want to force the use of the terminal prompt
+ instead of a notebook widget.
+
+ For more details, see [`login`].
+
+ Args:
+ new_session (`bool`, defaults to `True`):
+ If `True`, will request a token even if one is already saved on the machine.
+ write_permission (`bool`):
+ Ignored and deprecated argument.
+ """
+ if not new_session and get_token() is not None:
+ logger.info("User is already logged in.")
+ return
+
+ from .commands.delete_cache import _ask_for_confirmation_no_tui
+
+ print(_HF_LOGO_ASCII)
+ if get_token() is not None:
+ logger.info(
+ " A token is already saved on your machine. Run `hf auth whoami`"
+ " to get more information or `hf auth logout` if you want"
+ " to log out."
+ )
+ logger.info(" Setting a new token will erase the existing one.")
+
+ logger.info(
+ " To log in, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens ."
+ )
+ if os.name == "nt":
+ logger.info("Token can be pasted using 'Right-Click'.")
+ token = getpass("Enter your token (input will not be visible): ")
+ add_to_git_credential = _ask_for_confirmation_no_tui("Add token as git credential?")
+
+ _login(token=token, add_to_git_credential=add_to_git_credential)
+
+
+###
+# Notebook-based login (widget)
+###
+
+NOTEBOOK_LOGIN_PASSWORD_HTML = """
Immediately click login after typing your password or
+it might be stored in plain text in this notebook file.
"""
+
+
+NOTEBOOK_LOGIN_TOKEN_HTML_START = """
Copy a token from your Hugging Face
+tokens page and paste it below. Immediately click login after copying
+your token or it might be stored in plain text in this notebook file.
"""
+
+
+NOTEBOOK_LOGIN_TOKEN_HTML_END = """
+Pro Tip: If you don't already have one, you can create a dedicated
+'notebooks' token with 'write' access, that you can then easily reuse for all
+notebooks. """
+
+
+@_deprecate_arguments(
+ version="1.0",
+ deprecated_args="write_permission",
+ custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def notebook_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+ """
+ Displays a widget to log in to the HF website and store the token.
+
+ This is equivalent to [`login`] without passing a token when run in a notebook.
+ [`notebook_login`] is useful if you want to force the use of the notebook widget
+ instead of a prompt in the terminal.
+
+ For more details, see [`login`].
+
+ Args:
+ new_session (`bool`, defaults to `True`):
+ If `True`, will request a token even if one is already saved on the machine.
+ write_permission (`bool`):
+ Ignored and deprecated argument.
+ """
+ try:
+ import ipywidgets.widgets as widgets # type: ignore
+ from IPython.display import display # type: ignore
+ except ImportError:
+ raise ImportError(
+ "The `notebook_login` function can only be used in a notebook (Jupyter or"
+ " Colab) and you need the `ipywidgets` module: `pip install ipywidgets`."
+ )
+ if not new_session and get_token() is not None:
+ logger.info("User is already logged in.")
+ return
+
+ box_layout = widgets.Layout(display="flex", flex_flow="column", align_items="center", width="50%")
+
+ token_widget = widgets.Password(description="Token:")
+ git_checkbox_widget = widgets.Checkbox(value=True, description="Add token as git credential?")
+ token_finish_button = widgets.Button(description="Login")
+
+ login_token_widget = widgets.VBox(
+ [
+ widgets.HTML(NOTEBOOK_LOGIN_TOKEN_HTML_START),
+ token_widget,
+ git_checkbox_widget,
+ token_finish_button,
+ widgets.HTML(NOTEBOOK_LOGIN_TOKEN_HTML_END),
+ ],
+ layout=box_layout,
+ )
+ display(login_token_widget)
+
+ # On click events
+ def login_token_event(t):
+ """Event handler for the login button."""
+ token = token_widget.value
+ add_to_git_credential = git_checkbox_widget.value
+ # Erase token and clear value to make sure it's not saved in the notebook.
+ token_widget.value = ""
+ # Hide inputs
+ login_token_widget.children = [widgets.Label("Connecting...")]
+ try:
+ with capture_output() as captured:
+ _login(token, add_to_git_credential=add_to_git_credential)
+ message = captured.getvalue()
+ except Exception as error:
+ message = str(error)
+ # Print result (success message or error)
+ login_token_widget.children = [widgets.Label(line) for line in message.split("\n") if line.strip()]
+
+ token_finish_button.on_click(login_token_event)
+
+
+###
+# Login private helpers
+###
+
+
+def _login(
+ token: str,
+ add_to_git_credential: bool,
+) -> None:
+ from .hf_api import whoami # avoid circular import
+
+ if token.startswith("api_org"):
+ raise ValueError("You must use your personal account token, not an organization token.")
+
+ token_info = whoami(token)
+ permission = token_info["auth"]["accessToken"]["role"]
+ logger.info(f"Token is valid (permission: {permission}).")
+
+ token_name = token_info["auth"]["accessToken"]["displayName"]
+ # Store token locally
+ _save_token(token=token, token_name=token_name)
+ # Set active token
+ _set_active_token(token_name=token_name, add_to_git_credential=add_to_git_credential)
+ logger.info("Login successful.")
+ if _get_token_from_environment():
+ logger.warning(
+ "Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured."
+ )
+ else:
+ logger.info(f"The current active token is: `{token_name}`")
+
+
+def _logout_from_token(token_name: str) -> None:
+ """Logout from a specific access token.
+
+ Args:
+ token_name (`str`):
+ The name of the access token to logout from.
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+ If the access token name is not found.
+ """
+ stored_tokens = get_stored_tokens()
+ # If there is no access tokens saved or the access token name is not found, do nothing
+ if not stored_tokens or token_name not in stored_tokens:
+ return
+
+ token = stored_tokens.pop(token_name)
+ _save_stored_tokens(stored_tokens)
+
+ if token == _get_token_from_file():
+ logger.warning(f"Active token '{token_name}' has been deleted.")
+ Path(constants.HF_TOKEN_PATH).unlink(missing_ok=True)
+
+
+def _set_active_token(
+ token_name: str,
+ add_to_git_credential: bool,
+) -> None:
+ """Set the active access token.
+
+ Args:
+ token_name (`str`):
+ The name of the token to set as active.
+ """
+ token = _get_token_by_name(token_name)
+ if not token:
+ raise ValueError(f"Token {token_name} not found in {constants.HF_STORED_TOKENS_PATH}")
+ if add_to_git_credential:
+ if _is_git_credential_helper_configured():
+ set_git_credential(token)
+ logger.info(
+ "Your token has been saved in your configured git credential helpers"
+ + f" ({','.join(list_credential_helpers())})."
+ )
+ else:
+ logger.warning("Token has not been saved to git credential helper.")
+ # Write token to HF_TOKEN_PATH
+ path = Path(constants.HF_TOKEN_PATH)
+ path.parent.mkdir(parents=True, exist_ok=True)
+ path.write_text(token)
+ logger.info(f"Your token has been saved to {constants.HF_TOKEN_PATH}")
+
+
+def _is_git_credential_helper_configured() -> bool:
+ """Check if a git credential helper is configured.
+
+ Warns user if not the case (except for Google Colab where "store" is set by default
+ by `huggingface_hub`).
+ """
+ helpers = list_credential_helpers()
+ if len(helpers) > 0:
+ return True # Do not warn: at least 1 helper is set
+
+ # Only in Google Colab to avoid the warning message
+ # See https://github.com/huggingface/huggingface_hub/issues/1043#issuecomment-1247010710
+ if is_google_colab():
+ _set_store_as_git_credential_helper_globally()
+ return True # Do not warn: "store" is used by default in Google Colab
+
+ # Otherwise, warn user
+ print(
+ ANSI.red(
+ "Cannot authenticate through git-credential as no helper is defined on your"
+ " machine.\nYou might have to re-authenticate when pushing to the Hugging"
+ " Face Hub.\nRun the following command in your terminal in case you want to"
+ " set the 'store' credential helper as default.\n\ngit config --global"
+ " credential.helper store\n\nRead"
+ " https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more"
+ " details."
+ )
+ )
+ return False
+
+
+def _set_store_as_git_credential_helper_globally() -> None:
+ """Set globally the credential.helper to `store`.
+
+ To be used only in Google Colab as we assume the user doesn't care about the git
+ credential config. It is the only particular case where we don't want to display the
+ warning message in [`notebook_login()`].
+
+ Related:
+ - https://github.com/huggingface/huggingface_hub/issues/1043
+ - https://github.com/huggingface/huggingface_hub/issues/1051
+ - https://git-scm.com/docs/git-credential-store
+ """
+ try:
+ run_subprocess("git config --global credential.helper store")
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_oauth.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_oauth.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f8eb607962bc18fec348fed18ce269524983e23
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_oauth.py
@@ -0,0 +1,460 @@
+import datetime
+import hashlib
+import logging
+import os
+import time
+import urllib.parse
+import warnings
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Tuple, Union
+
+from . import constants
+from .hf_api import whoami
+from .utils import experimental, get_token
+
+
+logger = logging.getLogger(__name__)
+
+if TYPE_CHECKING:
+ import fastapi
+
+
+@dataclass
+class OAuthOrgInfo:
+ """
+ Information about an organization linked to a user logged in with OAuth.
+
+ Attributes:
+ sub (`str`):
+ Unique identifier for the org. OpenID Connect field.
+ name (`str`):
+ The org's full name. OpenID Connect field.
+ preferred_username (`str`):
+ The org's username. OpenID Connect field.
+ picture (`str`):
+ The org's profile picture URL. OpenID Connect field.
+ is_enterprise (`bool`):
+ Whether the org is an enterprise org. Hugging Face field.
+ can_pay (`Optional[bool]`, *optional*):
+ Whether the org has a payment method set up. Hugging Face field.
+ role_in_org (`Optional[str]`, *optional*):
+ The user's role in the org. Hugging Face field.
+ security_restrictions (`Optional[List[Literal["ip", "token-policy", "mfa", "sso"]]]`, *optional*):
+ Array of security restrictions that the user hasn't completed for this org. Possible values: "ip", "token-policy", "mfa", "sso". Hugging Face field.
+ """
+
+ sub: str
+ name: str
+ preferred_username: str
+ picture: str
+ is_enterprise: bool
+ can_pay: Optional[bool] = None
+ role_in_org: Optional[str] = None
+ security_restrictions: Optional[List[Literal["ip", "token-policy", "mfa", "sso"]]] = None
+
+
+@dataclass
+class OAuthUserInfo:
+ """
+ Information about a user logged in with OAuth.
+
+ Attributes:
+ sub (`str`):
+ Unique identifier for the user, even in case of rename. OpenID Connect field.
+ name (`str`):
+ The user's full name. OpenID Connect field.
+ preferred_username (`str`):
+ The user's username. OpenID Connect field.
+ email_verified (`Optional[bool]`, *optional*):
+ Indicates if the user's email is verified. OpenID Connect field.
+ email (`Optional[str]`, *optional*):
+ The user's email address. OpenID Connect field.
+ picture (`str`):
+ The user's profile picture URL. OpenID Connect field.
+ profile (`str`):
+ The user's profile URL. OpenID Connect field.
+ website (`Optional[str]`, *optional*):
+ The user's website URL. OpenID Connect field.
+ is_pro (`bool`):
+ Whether the user is a pro user. Hugging Face field.
+ can_pay (`Optional[bool]`, *optional*):
+ Whether the user has a payment method set up. Hugging Face field.
+ orgs (`Optional[List[OrgInfo]]`, *optional*):
+ List of organizations the user is part of. Hugging Face field.
+ """
+
+ sub: str
+ name: str
+ preferred_username: str
+ email_verified: Optional[bool]
+ email: Optional[str]
+ picture: str
+ profile: str
+ website: Optional[str]
+ is_pro: bool
+ can_pay: Optional[bool]
+ orgs: Optional[List[OAuthOrgInfo]]
+
+
+@dataclass
+class OAuthInfo:
+ """
+ Information about the OAuth login.
+
+ Attributes:
+ access_token (`str`):
+ The access token.
+ access_token_expires_at (`datetime.datetime`):
+ The expiration date of the access token.
+ user_info ([`OAuthUserInfo`]):
+ The user information.
+ state (`str`, *optional*):
+ State passed to the OAuth provider in the original request to the OAuth provider.
+ scope (`str`):
+ Granted scope.
+ """
+
+ access_token: str
+ access_token_expires_at: datetime.datetime
+ user_info: OAuthUserInfo
+ state: Optional[str]
+ scope: str
+
+
+@experimental
+def attach_huggingface_oauth(app: "fastapi.FastAPI", route_prefix: str = "/"):
+ """
+ Add OAuth endpoints to a FastAPI app to enable OAuth login with Hugging Face.
+
+ How to use:
+ - Call this method on your FastAPI app to add the OAuth endpoints.
+ - Inside your route handlers, call `parse_huggingface_oauth(request)` to retrieve the OAuth info.
+ - If user is logged in, an [`OAuthInfo`] object is returned with the user's info. If not, `None` is returned.
+ - In your app, make sure to add links to `/oauth/huggingface/login` and `/oauth/huggingface/logout` for the user to log in and out.
+
+ Example:
+ ```py
+ from huggingface_hub import attach_huggingface_oauth, parse_huggingface_oauth
+
+ # Create a FastAPI app
+ app = FastAPI()
+
+ # Add OAuth endpoints to the FastAPI app
+ attach_huggingface_oauth(app)
+
+ # Add a route that greets the user if they are logged in
+ @app.get("/")
+ def greet_json(request: Request):
+ # Retrieve the OAuth info from the request
+ oauth_info = parse_huggingface_oauth(request) # e.g. OAuthInfo dataclass
+ if oauth_info is None:
+ return {"msg": "Not logged in!"}
+ return {"msg": f"Hello, {oauth_info.user_info.preferred_username}!"}
+ ```
+ """
+ # TODO: handle generic case (handling OAuth in a non-Space environment with custom dev values) (low priority)
+
+ # Add SessionMiddleware to the FastAPI app to store the OAuth info in the session.
+ # Session Middleware requires a secret key to sign the cookies. Let's use a hash
+ # of the OAuth secret key to make it unique to the Space + updated in case OAuth
+ # config gets updated. When ran locally, we use an empty string as a secret key.
+ try:
+ from starlette.middleware.sessions import SessionMiddleware
+ except ImportError as e:
+ raise ImportError(
+ "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+ "`huggingface_hub[oauth]` to your requirements.txt file in order to install the required dependencies."
+ ) from e
+ session_secret = (constants.OAUTH_CLIENT_SECRET or "") + "-v1"
+ app.add_middleware(
+ SessionMiddleware, # type: ignore[arg-type]
+ secret_key=hashlib.sha256(session_secret.encode()).hexdigest(),
+ same_site="none",
+ https_only=True,
+ ) # type: ignore
+
+ # Add OAuth endpoints to the FastAPI app:
+ # - {route_prefix}/oauth/huggingface/login
+ # - {route_prefix}/oauth/huggingface/callback
+ # - {route_prefix}/oauth/huggingface/logout
+ # If the app is running in a Space, OAuth is enabled normally.
+ # Otherwise, we mock the endpoints to make the user log in with a fake user profile - without any calls to hf.co.
+ route_prefix = route_prefix.strip("/")
+ if os.getenv("SPACE_ID") is not None:
+ logger.info("OAuth is enabled in the Space. Adding OAuth routes.")
+ _add_oauth_routes(app, route_prefix=route_prefix)
+ else:
+ logger.info("App is not running in a Space. Adding mocked OAuth routes.")
+ _add_mocked_oauth_routes(app, route_prefix=route_prefix)
+
+
+def parse_huggingface_oauth(request: "fastapi.Request") -> Optional[OAuthInfo]:
+ """
+ Returns the information from a logged in user as a [`OAuthInfo`] object.
+
+ For flexibility and future-proofing, this method is very lax in its parsing and does not raise errors.
+ Missing fields are set to `None` without a warning.
+
+ Return `None`, if the user is not logged in (no info in session cookie).
+
+ See [`attach_huggingface_oauth`] for an example on how to use this method.
+ """
+ if "oauth_info" not in request.session:
+ logger.debug("No OAuth info in session.")
+ return None
+
+ logger.debug("Parsing OAuth info from session.")
+ oauth_data = request.session["oauth_info"]
+ user_data = oauth_data.get("userinfo", {})
+ orgs_data = user_data.get("orgs", [])
+
+ orgs = (
+ [
+ OAuthOrgInfo(
+ sub=org.get("sub"),
+ name=org.get("name"),
+ preferred_username=org.get("preferred_username"),
+ picture=org.get("picture"),
+ is_enterprise=org.get("isEnterprise"),
+ can_pay=org.get("canPay"),
+ role_in_org=org.get("roleInOrg"),
+ security_restrictions=org.get("securityRestrictions"),
+ )
+ for org in orgs_data
+ ]
+ if orgs_data
+ else None
+ )
+
+ user_info = OAuthUserInfo(
+ sub=user_data.get("sub"),
+ name=user_data.get("name"),
+ preferred_username=user_data.get("preferred_username"),
+ email_verified=user_data.get("email_verified"),
+ email=user_data.get("email"),
+ picture=user_data.get("picture"),
+ profile=user_data.get("profile"),
+ website=user_data.get("website"),
+ is_pro=user_data.get("isPro"),
+ can_pay=user_data.get("canPay"),
+ orgs=orgs,
+ )
+
+ return OAuthInfo(
+ access_token=oauth_data.get("access_token"),
+ access_token_expires_at=datetime.datetime.fromtimestamp(oauth_data.get("expires_at")),
+ user_info=user_info,
+ state=oauth_data.get("state"),
+ scope=oauth_data.get("scope"),
+ )
+
+
+def _add_oauth_routes(app: "fastapi.FastAPI", route_prefix: str) -> None:
+ """Add OAuth routes to the FastAPI app (login, callback handler and logout)."""
+ try:
+ import fastapi
+ from authlib.integrations.base_client.errors import MismatchingStateError
+ from authlib.integrations.starlette_client import OAuth
+ from fastapi.responses import RedirectResponse
+ except ImportError as e:
+ raise ImportError(
+ "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+ "`huggingface_hub[oauth]` to your requirements.txt file."
+ ) from e
+
+ # Check environment variables
+ msg = (
+ "OAuth is required but '{}' environment variable is not set. Make sure you've enabled OAuth in your Space by"
+ " setting `hf_oauth: true` in the Space metadata."
+ )
+ if constants.OAUTH_CLIENT_ID is None:
+ raise ValueError(msg.format("OAUTH_CLIENT_ID"))
+ if constants.OAUTH_CLIENT_SECRET is None:
+ raise ValueError(msg.format("OAUTH_CLIENT_SECRET"))
+ if constants.OAUTH_SCOPES is None:
+ raise ValueError(msg.format("OAUTH_SCOPES"))
+ if constants.OPENID_PROVIDER_URL is None:
+ raise ValueError(msg.format("OPENID_PROVIDER_URL"))
+
+ # Register OAuth server
+ oauth = OAuth()
+ oauth.register(
+ name="huggingface",
+ client_id=constants.OAUTH_CLIENT_ID,
+ client_secret=constants.OAUTH_CLIENT_SECRET,
+ client_kwargs={"scope": constants.OAUTH_SCOPES},
+ server_metadata_url=constants.OPENID_PROVIDER_URL + "/.well-known/openid-configuration",
+ )
+
+ login_uri, callback_uri, logout_uri = _get_oauth_uris(route_prefix)
+
+ # Register OAuth endpoints
+ @app.get(login_uri)
+ async def oauth_login(request: fastapi.Request) -> RedirectResponse:
+ """Endpoint that redirects to HF OAuth page."""
+ redirect_uri = _generate_redirect_uri(request)
+ return await oauth.huggingface.authorize_redirect(request, redirect_uri) # type: ignore
+
+ @app.get(callback_uri)
+ async def oauth_redirect_callback(request: fastapi.Request) -> RedirectResponse:
+ """Endpoint that handles the OAuth callback."""
+ try:
+ oauth_info = await oauth.huggingface.authorize_access_token(request) # type: ignore
+ except MismatchingStateError:
+ # Parse query params
+ nb_redirects = int(request.query_params.get("_nb_redirects", 0))
+ target_url = request.query_params.get("_target_url")
+
+ # Build redirect URI with the same query params as before and bump nb_redirects count
+ query_params: Dict[str, Union[int, str]] = {"_nb_redirects": nb_redirects + 1}
+ if target_url:
+ query_params["_target_url"] = target_url
+
+ redirect_uri = f"{login_uri}?{urllib.parse.urlencode(query_params)}"
+
+ # If the user is redirected more than 3 times, it is very likely that the cookie is not working properly.
+ # (e.g. browser is blocking third-party cookies in iframe). In this case, redirect the user in the
+ # non-iframe view.
+ if nb_redirects > constants.OAUTH_MAX_REDIRECTS:
+ host = os.environ.get("SPACE_HOST")
+ if host is None: # cannot happen in a Space
+ raise RuntimeError(
+ "App is not running in a Space (SPACE_HOST environment variable is not set). Cannot redirect to non-iframe view."
+ ) from None
+ host_url = "https://" + host.rstrip("/")
+ return RedirectResponse(host_url + redirect_uri)
+
+ # Redirect the user to the login page again
+ return RedirectResponse(redirect_uri)
+
+ # OAuth login worked => store the user info in the session and redirect
+ logger.debug("Successfully logged in with OAuth. Storing user info in session.")
+ request.session["oauth_info"] = oauth_info
+ return RedirectResponse(_get_redirect_target(request))
+
+ @app.get(logout_uri)
+ async def oauth_logout(request: fastapi.Request) -> RedirectResponse:
+ """Endpoint that logs out the user (e.g. delete info from cookie session)."""
+ logger.debug("Logged out with OAuth. Removing user info from session.")
+ request.session.pop("oauth_info", None)
+ return RedirectResponse(_get_redirect_target(request))
+
+
+def _add_mocked_oauth_routes(app: "fastapi.FastAPI", route_prefix: str = "/") -> None:
+ """Add fake oauth routes if app is run locally and OAuth is enabled.
+
+ Using OAuth will have the same behavior as in a Space but instead of authenticating with HF, a mocked user profile
+ is added to the session.
+ """
+ try:
+ import fastapi
+ from fastapi.responses import RedirectResponse
+ from starlette.datastructures import URL
+ except ImportError as e:
+ raise ImportError(
+ "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+ "`huggingface_hub[oauth]` to your requirements.txt file."
+ ) from e
+
+ warnings.warn(
+ "OAuth is not supported outside of a Space environment. To help you debug your app locally, the oauth endpoints"
+ " are mocked to return your profile and token. To make it work, your machine must be logged in to Huggingface."
+ )
+ mocked_oauth_info = _get_mocked_oauth_info()
+
+ login_uri, callback_uri, logout_uri = _get_oauth_uris(route_prefix)
+
+ # Define OAuth routes
+ @app.get(login_uri)
+ async def oauth_login(request: fastapi.Request) -> RedirectResponse:
+ """Fake endpoint that redirects to HF OAuth page."""
+ # Define target (where to redirect after login)
+ redirect_uri = _generate_redirect_uri(request)
+ return RedirectResponse(callback_uri + "?" + urllib.parse.urlencode({"_target_url": redirect_uri}))
+
+ @app.get(callback_uri)
+ async def oauth_redirect_callback(request: fastapi.Request) -> RedirectResponse:
+ """Endpoint that handles the OAuth callback."""
+ request.session["oauth_info"] = mocked_oauth_info
+ return RedirectResponse(_get_redirect_target(request))
+
+ @app.get(logout_uri)
+ async def oauth_logout(request: fastapi.Request) -> RedirectResponse:
+ """Endpoint that logs out the user (e.g. delete cookie session)."""
+ request.session.pop("oauth_info", None)
+ logout_url = URL("/").include_query_params(**request.query_params)
+ return RedirectResponse(url=logout_url, status_code=302) # see https://github.com/gradio-app/gradio/pull/9659
+
+
+def _generate_redirect_uri(request: "fastapi.Request") -> str:
+ if "_target_url" in request.query_params:
+ # if `_target_url` already in query params => respect it
+ target = request.query_params["_target_url"]
+ else:
+ # otherwise => keep query params
+ target = "/?" + urllib.parse.urlencode(request.query_params)
+
+ redirect_uri = request.url_for("oauth_redirect_callback").include_query_params(_target_url=target)
+ redirect_uri_as_str = str(redirect_uri)
+ if redirect_uri.netloc.endswith(".hf.space"):
+ # In Space, FastAPI redirect as http but we want https
+ redirect_uri_as_str = redirect_uri_as_str.replace("http://", "https://")
+ return redirect_uri_as_str
+
+
+def _get_redirect_target(request: "fastapi.Request", default_target: str = "/") -> str:
+ return request.query_params.get("_target_url", default_target)
+
+
+def _get_mocked_oauth_info() -> Dict:
+ token = get_token()
+ if token is None:
+ raise ValueError(
+ "Your machine must be logged in to HF to debug an OAuth app locally. Please"
+ " run `hf auth login` or set `HF_TOKEN` as environment variable "
+ "with one of your access token. You can generate a new token in your "
+ "settings page (https://huggingface.co/settings/tokens)."
+ )
+
+ user = whoami()
+ if user["type"] != "user":
+ raise ValueError(
+ "Your machine is not logged in with a personal account. Please use a "
+ "personal access token. You can generate a new token in your settings page"
+ " (https://huggingface.co/settings/tokens)."
+ )
+
+ return {
+ "access_token": token,
+ "token_type": "bearer",
+ "expires_in": 8 * 60 * 60, # 8 hours
+ "id_token": "FOOBAR",
+ "scope": "openid profile",
+ "refresh_token": "hf_oauth__refresh_token",
+ "expires_at": int(time.time()) + 8 * 60 * 60, # 8 hours
+ "userinfo": {
+ "sub": "0123456789",
+ "name": user["fullname"],
+ "preferred_username": user["name"],
+ "profile": f"https://huggingface.co/{user['name']}",
+ "picture": user["avatarUrl"],
+ "website": "",
+ "aud": "00000000-0000-0000-0000-000000000000",
+ "auth_time": 1691672844,
+ "nonce": "aaaaaaaaaaaaaaaaaaa",
+ "iat": 1691672844,
+ "exp": 1691676444,
+ "iss": "https://huggingface.co",
+ },
+ }
+
+
+def _get_oauth_uris(route_prefix: str = "/") -> Tuple[str, str, str]:
+ route_prefix = route_prefix.strip("/")
+ if route_prefix:
+ route_prefix = f"/{route_prefix}"
+ return (
+ f"{route_prefix}/oauth/huggingface/login",
+ f"{route_prefix}/oauth/huggingface/callback",
+ f"{route_prefix}/oauth/huggingface/logout",
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_snapshot_download.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_snapshot_download.py
new file mode 100644
index 0000000000000000000000000000000000000000..0db8a29f7e65a4841590d033f6b7b51d46647bf0
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_snapshot_download.py
@@ -0,0 +1,343 @@
+import os
+from pathlib import Path
+from typing import Dict, Iterable, List, Literal, Optional, Type, Union
+
+import requests
+from tqdm.auto import tqdm as base_tqdm
+from tqdm.contrib.concurrent import thread_map
+
+from . import constants
+from .errors import (
+ GatedRepoError,
+ HfHubHTTPError,
+ LocalEntryNotFoundError,
+ RepositoryNotFoundError,
+ RevisionNotFoundError,
+)
+from .file_download import REGEX_COMMIT_HASH, hf_hub_download, repo_folder_name
+from .hf_api import DatasetInfo, HfApi, ModelInfo, RepoFile, SpaceInfo
+from .utils import OfflineModeIsEnabled, filter_repo_objects, logging, validate_hf_hub_args
+from .utils import tqdm as hf_tqdm
+
+
+logger = logging.get_logger(__name__)
+
+VERY_LARGE_REPO_THRESHOLD = 50000 # After this limit, we don't consider `repo_info.siblings` to be reliable enough
+
+
+@validate_hf_hub_args
+def snapshot_download(
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ cache_dir: Union[str, Path, None] = None,
+ local_dir: Union[str, Path, None] = None,
+ library_name: Optional[str] = None,
+ library_version: Optional[str] = None,
+ user_agent: Optional[Union[Dict, str]] = None,
+ proxies: Optional[Dict] = None,
+ etag_timeout: float = constants.DEFAULT_ETAG_TIMEOUT,
+ force_download: bool = False,
+ token: Optional[Union[bool, str]] = None,
+ local_files_only: bool = False,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ max_workers: int = 8,
+ tqdm_class: Optional[Type[base_tqdm]] = None,
+ headers: Optional[Dict[str, str]] = None,
+ endpoint: Optional[str] = None,
+ # Deprecated args
+ local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
+ resume_download: Optional[bool] = None,
+) -> str:
+ """Download repo files.
+
+ Download a whole snapshot of a repo's files at the specified revision. This is useful when you want all files from
+ a repo, because you don't know which ones you will need a priori. All files are nested inside a folder in order
+ to keep their actual filename relative to that folder. You can also filter which files to download using
+ `allow_patterns` and `ignore_patterns`.
+
+ If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
+ option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
+ to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
+ cache-system, it's optimized for regularly pulling the latest version of a repository.
+
+ An alternative would be to clone the repo but this requires git and git-lfs to be installed and properly
+ configured. It is also not possible to filter which files to download when cloning a repository using git.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+ `None` or `"model"` if downloading from a model. Default is `None`.
+ revision (`str`, *optional*):
+ An optional Git revision id which can be a branch name, a tag, or a
+ commit hash.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_dir (`str` or `Path`, *optional*):
+ If provided, the downloaded files will be placed under this directory.
+ library_name (`str`, *optional*):
+ The name of the library to which the object corresponds.
+ library_version (`str`, *optional*):
+ The version of the library.
+ user_agent (`str`, `dict`, *optional*):
+ The user-agent info in the form of a dictionary or a string.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to
+ `requests.request`.
+ etag_timeout (`float`, *optional*, defaults to `10`):
+ When fetching ETag, how many seconds to wait for the server to send
+ data before giving up which is passed to `requests.request`.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether the file should be downloaded even if it already exists in the local cache.
+ token (`str`, `bool`, *optional*):
+ A token to be used for the download.
+ - If `True`, the token is read from the HuggingFace config
+ folder.
+ - If a string, it's used as the authentication token.
+ headers (`dict`, *optional*):
+ Additional headers to include in the request. Those headers take precedence over the others.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the
+ local cached file if it exists.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are downloaded.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not downloaded.
+ max_workers (`int`, *optional*):
+ Number of concurrent threads to download files (1 thread = 1 file download).
+ Defaults to 8.
+ tqdm_class (`tqdm`, *optional*):
+ If provided, overwrites the default behavior for the progress bar. Passed
+ argument must inherit from `tqdm.auto.tqdm` or at least mimic its behavior.
+ Note that the `tqdm_class` is not passed to each individual download.
+ Defaults to the custom HF progress bar that can be disabled by setting
+ `HF_HUB_DISABLE_PROGRESS_BARS` environment variable.
+
+ Returns:
+ `str`: folder path of the repo snapshot.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to download from cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ [`~utils.RevisionNotFoundError`]
+ If the revision to download from cannot be found.
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If `token=True` and the token cannot be found.
+ [`OSError`](https://docs.python.org/3/library/exceptions.html#OSError) if
+ ETag cannot be determined.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ if some parameter value is invalid.
+ """
+ if cache_dir is None:
+ cache_dir = constants.HF_HUB_CACHE
+ if revision is None:
+ revision = constants.DEFAULT_REVISION
+ if isinstance(cache_dir, Path):
+ cache_dir = str(cache_dir)
+
+ if repo_type is None:
+ repo_type = "model"
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type: {repo_type}. Accepted repo types are: {str(constants.REPO_TYPES)}")
+
+ storage_folder = os.path.join(cache_dir, repo_folder_name(repo_id=repo_id, repo_type=repo_type))
+
+ api = HfApi(
+ library_name=library_name,
+ library_version=library_version,
+ user_agent=user_agent,
+ endpoint=endpoint,
+ headers=headers,
+ token=token,
+ )
+
+ repo_info: Union[ModelInfo, DatasetInfo, SpaceInfo, None] = None
+ api_call_error: Optional[Exception] = None
+ if not local_files_only:
+ # try/except logic to handle different errors => taken from `hf_hub_download`
+ try:
+ # if we have internet connection we want to list files to download
+ repo_info = api.repo_info(repo_id=repo_id, repo_type=repo_type, revision=revision)
+ except (requests.exceptions.SSLError, requests.exceptions.ProxyError):
+ # Actually raise for those subclasses of ConnectionError
+ raise
+ except (
+ requests.exceptions.ConnectionError,
+ requests.exceptions.Timeout,
+ OfflineModeIsEnabled,
+ ) as error:
+ # Internet connection is down
+ # => will try to use local files only
+ api_call_error = error
+ pass
+ except RevisionNotFoundError:
+ # The repo was found but the revision doesn't exist on the Hub (never existed or got deleted)
+ raise
+ except requests.HTTPError as error:
+ # Multiple reasons for an http error:
+ # - Repository is private and invalid/missing token sent
+ # - Repository is gated and invalid/missing token sent
+ # - Hub is down (error 500 or 504)
+ # => let's switch to 'local_files_only=True' to check if the files are already cached.
+ # (if it's not the case, the error will be re-raised)
+ api_call_error = error
+ pass
+
+ # At this stage, if `repo_info` is None it means either:
+ # - internet connection is down
+ # - internet connection is deactivated (local_files_only=True or HF_HUB_OFFLINE=True)
+ # - repo is private/gated and invalid/missing token sent
+ # - Hub is down
+ # => let's look if we can find the appropriate folder in the cache:
+ # - if the specified revision is a commit hash, look inside "snapshots".
+ # - f the specified revision is a branch or tag, look inside "refs".
+ # => if local_dir is not None, we will return the path to the local folder if it exists.
+ if repo_info is None:
+ # Try to get which commit hash corresponds to the specified revision
+ commit_hash = None
+ if REGEX_COMMIT_HASH.match(revision):
+ commit_hash = revision
+ else:
+ ref_path = os.path.join(storage_folder, "refs", revision)
+ if os.path.exists(ref_path):
+ # retrieve commit_hash from refs file
+ with open(ref_path) as f:
+ commit_hash = f.read()
+
+ # Try to locate snapshot folder for this commit hash
+ if commit_hash is not None and local_dir is None:
+ snapshot_folder = os.path.join(storage_folder, "snapshots", commit_hash)
+ if os.path.exists(snapshot_folder):
+ # Snapshot folder exists => let's return it
+ # (but we can't check if all the files are actually there)
+ return snapshot_folder
+
+ # If local_dir is not None, return it if it exists and is not empty
+ if local_dir is not None:
+ local_dir = Path(local_dir)
+ if local_dir.is_dir() and any(local_dir.iterdir()):
+ logger.warning(
+ f"Returning existing local_dir `{local_dir}` as remote repo cannot be accessed in `snapshot_download` ({api_call_error})."
+ )
+ return str(local_dir.resolve())
+ # If we couldn't find the appropriate folder on disk, raise an error.
+ if local_files_only:
+ raise LocalEntryNotFoundError(
+ "Cannot find an appropriate cached snapshot folder for the specified revision on the local disk and "
+ "outgoing traffic has been disabled. To enable repo look-ups and downloads online, pass "
+ "'local_files_only=False' as input."
+ )
+ elif isinstance(api_call_error, OfflineModeIsEnabled):
+ raise LocalEntryNotFoundError(
+ "Cannot find an appropriate cached snapshot folder for the specified revision on the local disk and "
+ "outgoing traffic has been disabled. To enable repo look-ups and downloads online, set "
+ "'HF_HUB_OFFLINE=0' as environment variable."
+ ) from api_call_error
+ elif isinstance(api_call_error, (RepositoryNotFoundError, GatedRepoError)) or (
+ isinstance(api_call_error, HfHubHTTPError) and api_call_error.response.status_code == 401
+ ):
+ # Repo not found, gated, or specific authentication error => let's raise the actual error
+ raise api_call_error
+ else:
+ # Otherwise: most likely a connection issue or Hub downtime => let's warn the user
+ raise LocalEntryNotFoundError(
+ "An error happened while trying to locate the files on the Hub and we cannot find the appropriate"
+ " snapshot folder for the specified revision on the local disk. Please check your internet connection"
+ " and try again."
+ ) from api_call_error
+
+ # At this stage, internet connection is up and running
+ # => let's download the files!
+ assert repo_info.sha is not None, "Repo info returned from server must have a revision sha."
+
+ # Corner case: on very large repos, the siblings list in `repo_info` might not contain all files.
+ # In that case, we need to use the `list_repo_tree` method to prevent caching issues.
+ repo_files: Iterable[str] = [f.rfilename for f in repo_info.siblings] if repo_info.siblings is not None else []
+ unreliable_nb_files = (
+ repo_info.siblings is None
+ or len(repo_info.siblings) == 0
+ or len(repo_info.siblings) > VERY_LARGE_REPO_THRESHOLD
+ )
+ if unreliable_nb_files:
+ logger.info(
+ "Number of files in the repo is unreliable. Using `list_repo_tree` to ensure all files are listed."
+ )
+ repo_files = (
+ f.rfilename
+ for f in api.list_repo_tree(repo_id=repo_id, recursive=True, revision=revision, repo_type=repo_type)
+ if isinstance(f, RepoFile)
+ )
+
+ filtered_repo_files: Iterable[str] = filter_repo_objects(
+ items=repo_files,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ )
+
+ if not unreliable_nb_files:
+ filtered_repo_files = list(filtered_repo_files)
+ tqdm_desc = f"Fetching {len(filtered_repo_files)} files"
+ else:
+ tqdm_desc = "Fetching ... files"
+
+ commit_hash = repo_info.sha
+ snapshot_folder = os.path.join(storage_folder, "snapshots", commit_hash)
+ # if passed revision is not identical to commit_hash
+ # then revision has to be a branch name or tag name.
+ # In that case store a ref.
+ if revision != commit_hash:
+ ref_path = os.path.join(storage_folder, "refs", revision)
+ try:
+ os.makedirs(os.path.dirname(ref_path), exist_ok=True)
+ with open(ref_path, "w") as f:
+ f.write(commit_hash)
+ except OSError as e:
+ logger.warning(f"Ignored error while writing commit hash to {ref_path}: {e}.")
+
+ # we pass the commit_hash to hf_hub_download
+ # so no network call happens if we already
+ # have the file locally.
+ def _inner_hf_hub_download(repo_file: str):
+ return hf_hub_download(
+ repo_id,
+ filename=repo_file,
+ repo_type=repo_type,
+ revision=commit_hash,
+ endpoint=endpoint,
+ cache_dir=cache_dir,
+ local_dir=local_dir,
+ local_dir_use_symlinks=local_dir_use_symlinks,
+ library_name=library_name,
+ library_version=library_version,
+ user_agent=user_agent,
+ proxies=proxies,
+ etag_timeout=etag_timeout,
+ resume_download=resume_download,
+ force_download=force_download,
+ token=token,
+ headers=headers,
+ )
+
+ if constants.HF_HUB_ENABLE_HF_TRANSFER:
+ # when using hf_transfer we don't want extra parallelism
+ # from the one hf_transfer provides
+ for file in filtered_repo_files:
+ _inner_hf_hub_download(file)
+ else:
+ thread_map(
+ _inner_hf_hub_download,
+ filtered_repo_files,
+ desc=tqdm_desc,
+ max_workers=max_workers,
+ # User can use its own tqdm class or the default one from `huggingface_hub.utils`
+ tqdm_class=tqdm_class or hf_tqdm,
+ )
+
+ if local_dir is not None:
+ return str(os.path.realpath(local_dir))
+ return snapshot_folder
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_space_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_space_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..05fccfbc1ebdfc14840a88751914b8fc0d1a498d
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_space_api.py
@@ -0,0 +1,168 @@
+# coding=utf-8
+# Copyright 2019-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from dataclasses import dataclass
+from datetime import datetime
+from enum import Enum
+from typing import Dict, Optional
+
+from huggingface_hub.utils import parse_datetime
+
+
+class SpaceStage(str, Enum):
+ """
+ Enumeration of possible stage of a Space on the Hub.
+
+ Value can be compared to a string:
+ ```py
+ assert SpaceStage.BUILDING == "BUILDING"
+ ```
+
+ Taken from https://github.com/huggingface/moon-landing/blob/main/server/repo_types/SpaceInfo.ts#L61 (private url).
+ """
+
+ # Copied from moon-landing > server > repo_types > SpaceInfo.ts (private repo)
+ NO_APP_FILE = "NO_APP_FILE"
+ CONFIG_ERROR = "CONFIG_ERROR"
+ BUILDING = "BUILDING"
+ BUILD_ERROR = "BUILD_ERROR"
+ RUNNING = "RUNNING"
+ RUNNING_BUILDING = "RUNNING_BUILDING"
+ RUNTIME_ERROR = "RUNTIME_ERROR"
+ DELETING = "DELETING"
+ STOPPED = "STOPPED"
+ PAUSED = "PAUSED"
+
+
+class SpaceHardware(str, Enum):
+ """
+ Enumeration of hardwares available to run your Space on the Hub.
+
+ Value can be compared to a string:
+ ```py
+ assert SpaceHardware.CPU_BASIC == "cpu-basic"
+ ```
+
+ Taken from https://github.com/huggingface-internal/moon-landing/blob/main/server/repo_types/SpaceHardwareFlavor.ts (private url).
+ """
+
+ # CPU
+ CPU_BASIC = "cpu-basic"
+ CPU_UPGRADE = "cpu-upgrade"
+ CPU_XL = "cpu-xl"
+
+ # ZeroGPU
+ ZERO_A10G = "zero-a10g"
+
+ # GPU
+ T4_SMALL = "t4-small"
+ T4_MEDIUM = "t4-medium"
+ L4X1 = "l4x1"
+ L4X4 = "l4x4"
+ L40SX1 = "l40sx1"
+ L40SX4 = "l40sx4"
+ L40SX8 = "l40sx8"
+ A10G_SMALL = "a10g-small"
+ A10G_LARGE = "a10g-large"
+ A10G_LARGEX2 = "a10g-largex2"
+ A10G_LARGEX4 = "a10g-largex4"
+ A100_LARGE = "a100-large"
+ H100 = "h100"
+ H100X8 = "h100x8"
+
+
+class SpaceStorage(str, Enum):
+ """
+ Enumeration of persistent storage available for your Space on the Hub.
+
+ Value can be compared to a string:
+ ```py
+ assert SpaceStorage.SMALL == "small"
+ ```
+
+ Taken from https://github.com/huggingface/moon-landing/blob/main/server/repo_types/SpaceHardwareFlavor.ts#L24 (private url).
+ """
+
+ SMALL = "small"
+ MEDIUM = "medium"
+ LARGE = "large"
+
+
+@dataclass
+class SpaceRuntime:
+ """
+ Contains information about the current runtime of a Space.
+
+ Args:
+ stage (`str`):
+ Current stage of the space. Example: RUNNING.
+ hardware (`str` or `None`):
+ Current hardware of the space. Example: "cpu-basic". Can be `None` if Space
+ is `BUILDING` for the first time.
+ requested_hardware (`str` or `None`):
+ Requested hardware. Can be different than `hardware` especially if the request
+ has just been made. Example: "t4-medium". Can be `None` if no hardware has
+ been requested yet.
+ sleep_time (`int` or `None`):
+ Number of seconds the Space will be kept alive after the last request. By default (if value is `None`), the
+ Space will never go to sleep if it's running on an upgraded hardware, while it will go to sleep after 48
+ hours on a free 'cpu-basic' hardware. For more details, see https://huggingface.co/docs/hub/spaces-gpus#sleep-time.
+ raw (`dict`):
+ Raw response from the server. Contains more information about the Space
+ runtime like number of replicas, number of cpu, memory size,...
+ """
+
+ stage: SpaceStage
+ hardware: Optional[SpaceHardware]
+ requested_hardware: Optional[SpaceHardware]
+ sleep_time: Optional[int]
+ storage: Optional[SpaceStorage]
+ raw: Dict
+
+ def __init__(self, data: Dict) -> None:
+ self.stage = data["stage"]
+ self.hardware = data.get("hardware", {}).get("current")
+ self.requested_hardware = data.get("hardware", {}).get("requested")
+ self.sleep_time = data.get("gcTimeout")
+ self.storage = data.get("storage")
+ self.raw = data
+
+
+@dataclass
+class SpaceVariable:
+ """
+ Contains information about the current variables of a Space.
+
+ Args:
+ key (`str`):
+ Variable key. Example: `"MODEL_REPO_ID"`
+ value (`str`):
+ Variable value. Example: `"the_model_repo_id"`.
+ description (`str` or None):
+ Description of the variable. Example: `"Model Repo ID of the implemented model"`.
+ updatedAt (`datetime` or None):
+ datetime of the last update of the variable (if the variable has been updated at least once).
+ """
+
+ key: str
+ value: str
+ description: Optional[str]
+ updated_at: Optional[datetime]
+
+ def __init__(self, key: str, values: Dict) -> None:
+ self.key = key
+ self.value = values["value"]
+ self.description = values.get("description")
+ updated_at = values.get("updatedAt")
+ self.updated_at = parse_datetime(updated_at) if updated_at is not None else None
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_tensorboard_logger.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_tensorboard_logger.py
new file mode 100644
index 0000000000000000000000000000000000000000..4d9581d8ee127436ec1e1d585ed0426422a66131
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_tensorboard_logger.py
@@ -0,0 +1,190 @@
+# Copyright 2023 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains a logger to push training logs to the Hub, using Tensorboard."""
+
+from pathlib import Path
+from typing import List, Optional, Union
+
+from ._commit_scheduler import CommitScheduler
+from .errors import EntryNotFoundError
+from .repocard import ModelCard
+from .utils import experimental
+
+
+# Depending on user's setup, SummaryWriter can come either from 'tensorboardX'
+# or from 'torch.utils.tensorboard'. Both are compatible so let's try to load
+# from either of them.
+try:
+ from tensorboardX import SummaryWriter as _RuntimeSummaryWriter
+
+ is_summary_writer_available = True
+except ImportError:
+ try:
+ from torch.utils.tensorboard import SummaryWriter as _RuntimeSummaryWriter
+
+ is_summary_writer_available = True
+ except ImportError:
+ # Dummy class to avoid failing at import. Will raise on instance creation.
+ class _DummySummaryWriter:
+ pass
+
+ _RuntimeSummaryWriter = _DummySummaryWriter # type: ignore[assignment]
+ is_summary_writer_available = False
+
+
+class HFSummaryWriter(_RuntimeSummaryWriter):
+ """
+ Wrapper around the tensorboard's `SummaryWriter` to push training logs to the Hub.
+
+ Data is logged locally and then pushed to the Hub asynchronously. Pushing data to the Hub is done in a separate
+ thread to avoid blocking the training script. In particular, if the upload fails for any reason (e.g. a connection
+ issue), the main script will not be interrupted. Data is automatically pushed to the Hub every `commit_every`
+ minutes (default to every 5 minutes).
+
+ > [!WARNING]
+ > `HFSummaryWriter` is experimental. Its API is subject to change in the future without prior notice.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to which the logs will be pushed.
+ logdir (`str`, *optional*):
+ The directory where the logs will be written. If not specified, a local directory will be created by the
+ underlying `SummaryWriter` object.
+ commit_every (`int` or `float`, *optional*):
+ The frequency (in minutes) at which the logs will be pushed to the Hub. Defaults to 5 minutes.
+ squash_history (`bool`, *optional*):
+ Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is
+ useful to avoid degraded performances on the repo when it grows too large.
+ repo_type (`str`, *optional*):
+ The type of the repo to which the logs will be pushed. Defaults to "model".
+ repo_revision (`str`, *optional*):
+ The revision of the repo to which the logs will be pushed. Defaults to "main".
+ repo_private (`bool`, *optional*):
+ Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
+ path_in_repo (`str`, *optional*):
+ The path to the folder in the repo where the logs will be pushed. Defaults to "tensorboard/".
+ repo_allow_patterns (`List[str]` or `str`, *optional*):
+ A list of patterns to include in the upload. Defaults to `"*.tfevents.*"`. Check out the
+ [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
+ repo_ignore_patterns (`List[str]` or `str`, *optional*):
+ A list of patterns to exclude in the upload. Check out the
+ [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
+ token (`str`, *optional*):
+ Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more
+ details
+ kwargs:
+ Additional keyword arguments passed to `SummaryWriter`.
+
+ Examples:
+ ```diff
+ # Taken from https://pytorch.org/docs/stable/tensorboard.html
+ - from torch.utils.tensorboard import SummaryWriter
+ + from huggingface_hub import HFSummaryWriter
+
+ import numpy as np
+
+ - writer = SummaryWriter()
+ + writer = HFSummaryWriter(repo_id="username/my-trained-model")
+
+ for n_iter in range(100):
+ writer.add_scalar('Loss/train', np.random.random(), n_iter)
+ writer.add_scalar('Loss/test', np.random.random(), n_iter)
+ writer.add_scalar('Accuracy/train', np.random.random(), n_iter)
+ writer.add_scalar('Accuracy/test', np.random.random(), n_iter)
+ ```
+
+ ```py
+ >>> from huggingface_hub import HFSummaryWriter
+
+ # Logs are automatically pushed every 15 minutes (5 by default) + when exiting the context manager
+ >>> with HFSummaryWriter(repo_id="test_hf_logger", commit_every=15) as logger:
+ ... logger.add_scalar("a", 1)
+ ... logger.add_scalar("b", 2)
+ ```
+ """
+
+ @experimental
+ def __new__(cls, *args, **kwargs) -> "HFSummaryWriter":
+ if not is_summary_writer_available:
+ raise ImportError(
+ "You must have `tensorboard` installed to use `HFSummaryWriter`. Please run `pip install --upgrade"
+ " tensorboardX` first."
+ )
+ return super().__new__(cls)
+
+ def __init__(
+ self,
+ repo_id: str,
+ *,
+ logdir: Optional[str] = None,
+ commit_every: Union[int, float] = 5,
+ squash_history: bool = False,
+ repo_type: Optional[str] = None,
+ repo_revision: Optional[str] = None,
+ repo_private: Optional[bool] = None,
+ path_in_repo: Optional[str] = "tensorboard",
+ repo_allow_patterns: Optional[Union[List[str], str]] = "*.tfevents.*",
+ repo_ignore_patterns: Optional[Union[List[str], str]] = None,
+ token: Optional[str] = None,
+ **kwargs,
+ ):
+ # Initialize SummaryWriter
+ super().__init__(logdir=logdir, **kwargs)
+
+ # Check logdir has been correctly initialized and fail early otherwise. In practice, SummaryWriter takes care of it.
+ if not isinstance(self.logdir, str):
+ raise ValueError(f"`self.logdir` must be a string. Got '{self.logdir}' of type {type(self.logdir)}.")
+
+ # Append logdir name to `path_in_repo`
+ if path_in_repo is None or path_in_repo == "":
+ path_in_repo = Path(self.logdir).name
+ else:
+ path_in_repo = path_in_repo.strip("/") + "/" + Path(self.logdir).name
+
+ # Initialize scheduler
+ self.scheduler = CommitScheduler(
+ folder_path=self.logdir,
+ path_in_repo=path_in_repo,
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=repo_revision,
+ private=repo_private,
+ token=token,
+ allow_patterns=repo_allow_patterns,
+ ignore_patterns=repo_ignore_patterns,
+ every=commit_every,
+ squash_history=squash_history,
+ )
+
+ # Exposing some high-level info at root level
+ self.repo_id = self.scheduler.repo_id
+ self.repo_type = self.scheduler.repo_type
+ self.repo_revision = self.scheduler.revision
+
+ # Add `hf-summary-writer` tag to the model card metadata
+ try:
+ card = ModelCard.load(repo_id_or_path=self.repo_id, repo_type=self.repo_type)
+ except EntryNotFoundError:
+ card = ModelCard("")
+ tags = card.data.get("tags", [])
+ if "hf-summary-writer" not in tags:
+ tags.append("hf-summary-writer")
+ card.data["tags"] = tags
+ card.push_to_hub(repo_id=self.repo_id, repo_type=self.repo_type)
+
+ def __exit__(self, exc_type, exc_val, exc_tb):
+ """Push to hub in a non-blocking way when exiting the logger's context manager."""
+ super().__exit__(exc_type, exc_val, exc_tb)
+ future = self.scheduler.trigger()
+ future.result()
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_upload_large_folder.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_upload_large_folder.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ccbc07d39d3d03e9bb8c39f1bb16aa2ca4ab41f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_upload_large_folder.py
@@ -0,0 +1,755 @@
+# coding=utf-8
+# Copyright 2024-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import enum
+import logging
+import os
+import queue
+import shutil
+import sys
+import threading
+import time
+import traceback
+from datetime import datetime
+from pathlib import Path
+from threading import Lock
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
+from urllib.parse import quote
+
+from . import constants
+from ._commit_api import CommitOperationAdd, UploadInfo, _fetch_upload_modes
+from ._local_folder import LocalUploadFileMetadata, LocalUploadFilePaths, get_local_upload_paths, read_upload_metadata
+from .constants import DEFAULT_REVISION, REPO_TYPES
+from .utils import DEFAULT_IGNORE_PATTERNS, filter_repo_objects, tqdm
+from .utils._cache_manager import _format_size
+from .utils._runtime import is_xet_available
+from .utils.sha import sha_fileobj
+
+
+if TYPE_CHECKING:
+ from .hf_api import HfApi
+
+logger = logging.getLogger(__name__)
+
+WAITING_TIME_IF_NO_TASKS = 10 # seconds
+MAX_NB_FILES_FETCH_UPLOAD_MODE = 100
+COMMIT_SIZE_SCALE: List[int] = [20, 50, 75, 100, 125, 200, 250, 400, 600, 1000]
+
+UPLOAD_BATCH_SIZE_XET = 256 # Max 256 files per upload batch for XET-enabled repos
+UPLOAD_BATCH_SIZE_LFS = 1 # Otherwise, batches of 1 for regular LFS upload
+
+# Repository limits (from https://huggingface.co/docs/hub/repositories-recommendations)
+MAX_FILES_PER_REPO = 100_000 # Recommended maximum number of files per repository
+MAX_FILES_PER_FOLDER = 10_000 # Recommended maximum number of files per folder
+MAX_FILE_SIZE_GB = 50 # Hard limit for individual file size
+RECOMMENDED_FILE_SIZE_GB = 20 # Recommended maximum for individual file size
+
+
+def _validate_upload_limits(paths_list: List[LocalUploadFilePaths]) -> None:
+ """
+ Validate upload against repository limits and warn about potential issues.
+
+ Args:
+ paths_list: List of file paths to be uploaded
+
+ Warns about:
+ - Too many files in the repository (>100k)
+ - Too many entries (files or subdirectories) in a single folder (>10k)
+ - Files exceeding size limits (>20GB recommended, >50GB hard limit)
+ """
+ logger.info("Running validation checks on files to upload...")
+
+ # Check 1: Total file count
+ if len(paths_list) > MAX_FILES_PER_REPO:
+ logger.warning(
+ f"You are about to upload {len(paths_list):,} files. "
+ f"This exceeds the recommended limit of {MAX_FILES_PER_REPO:,} files per repository.\n"
+ f"Consider:\n"
+ f" - Splitting your data into multiple repositories\n"
+ f" - Using fewer, larger files (e.g., parquet files)\n"
+ f" - See: https://huggingface.co/docs/hub/repositories-recommendations"
+ )
+
+ # Check 2: Files and subdirectories per folder
+ # Track immediate children (files and subdirs) for each folder
+ from collections import defaultdict
+
+ entries_per_folder: Dict[str, Any] = defaultdict(lambda: {"files": 0, "subdirs": set()})
+
+ for paths in paths_list:
+ path = Path(paths.path_in_repo)
+ parts = path.parts
+
+ # Count this file in its immediate parent directory
+ parent = str(path.parent) if str(path.parent) != "." else "."
+ entries_per_folder[parent]["files"] += 1
+
+ # Track immediate subdirectories for each parent folder
+ # Walk through the path components to track parent-child relationships
+ for i, child in enumerate(parts[:-1]):
+ parent = "." if i == 0 else "/".join(parts[:i])
+ entries_per_folder[parent]["subdirs"].add(child)
+
+ # Check limits for each folder
+ for folder, data in entries_per_folder.items():
+ file_count = data["files"]
+ subdir_count = len(data["subdirs"])
+ total_entries = file_count + subdir_count
+
+ if total_entries > MAX_FILES_PER_FOLDER:
+ folder_display = "root" if folder == "." else folder
+ logger.warning(
+ f"Folder '{folder_display}' contains {total_entries:,} entries "
+ f"({file_count:,} files and {subdir_count:,} subdirectories). "
+ f"This exceeds the recommended {MAX_FILES_PER_FOLDER:,} entries per folder.\n"
+ "Consider reorganising into sub-folders."
+ )
+
+ # Check 3: File sizes
+ large_files = []
+ very_large_files = []
+
+ for paths in paths_list:
+ size = paths.file_path.stat().st_size
+ size_gb = size / 1_000_000_000 # Use decimal GB as per Hub limits
+
+ if size_gb > MAX_FILE_SIZE_GB:
+ very_large_files.append((paths.path_in_repo, size_gb))
+ elif size_gb > RECOMMENDED_FILE_SIZE_GB:
+ large_files.append((paths.path_in_repo, size_gb))
+
+ # Warn about very large files (>50GB)
+ if very_large_files:
+ files_str = "\n - ".join(f"{path}: {size:.1f}GB" for path, size in very_large_files[:5])
+ more_str = f"\n ... and {len(very_large_files) - 5} more files" if len(very_large_files) > 5 else ""
+ logger.warning(
+ f"Found {len(very_large_files)} files exceeding the {MAX_FILE_SIZE_GB}GB hard limit:\n"
+ f" - {files_str}{more_str}\n"
+ f"These files may fail to upload. Consider splitting them into smaller chunks."
+ )
+
+ # Warn about large files (>20GB)
+ if large_files:
+ files_str = "\n - ".join(f"{path}: {size:.1f}GB" for path, size in large_files[:5])
+ more_str = f"\n ... and {len(large_files) - 5} more files" if len(large_files) > 5 else ""
+ logger.warning(
+ f"Found {len(large_files)} files larger than {RECOMMENDED_FILE_SIZE_GB}GB (recommended limit):\n"
+ f" - {files_str}{more_str}\n"
+ f"Large files may slow down loading and processing."
+ )
+
+ logger.info("Validation checks complete.")
+
+
+def upload_large_folder_internal(
+ api: "HfApi",
+ repo_id: str,
+ folder_path: Union[str, Path],
+ *,
+ repo_type: str, # Repo type is required!
+ revision: Optional[str] = None,
+ private: Optional[bool] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ num_workers: Optional[int] = None,
+ print_report: bool = True,
+ print_report_every: int = 60,
+):
+ """Upload a large folder to the Hub in the most resilient way possible.
+
+ See [`HfApi.upload_large_folder`] for the full documentation.
+ """
+ # 1. Check args and setup
+ if repo_type is None:
+ raise ValueError(
+ "For large uploads, `repo_type` is explicitly required. Please set it to `model`, `dataset` or `space`."
+ " If you are using the CLI, pass it as `--repo-type=model`."
+ )
+ if repo_type not in REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {REPO_TYPES}")
+ if revision is None:
+ revision = DEFAULT_REVISION
+
+ folder_path = Path(folder_path).expanduser().resolve()
+ if not folder_path.is_dir():
+ raise ValueError(f"Provided path: '{folder_path}' is not a directory")
+
+ if ignore_patterns is None:
+ ignore_patterns = []
+ elif isinstance(ignore_patterns, str):
+ ignore_patterns = [ignore_patterns]
+ ignore_patterns += DEFAULT_IGNORE_PATTERNS
+
+ if num_workers is None:
+ nb_cores = os.cpu_count() or 1
+ num_workers = max(nb_cores - 2, 2) # Use all but 2 cores, or at least 2 cores
+
+ # 2. Create repo if missing
+ repo_url = api.create_repo(repo_id=repo_id, repo_type=repo_type, private=private, exist_ok=True)
+ logger.info(f"Repo created: {repo_url}")
+ repo_id = repo_url.repo_id
+ # 2.1 Check if xet is enabled to set batch file upload size
+ is_xet_enabled = (
+ is_xet_available()
+ and api.repo_info(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ expand="xetEnabled",
+ ).xet_enabled
+ )
+ upload_batch_size = UPLOAD_BATCH_SIZE_XET if is_xet_enabled else UPLOAD_BATCH_SIZE_LFS
+
+ # 3. List files to upload
+ filtered_paths_list = filter_repo_objects(
+ (path.relative_to(folder_path).as_posix() for path in folder_path.glob("**/*") if path.is_file()),
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ )
+ paths_list = [get_local_upload_paths(folder_path, relpath) for relpath in filtered_paths_list]
+ logger.info(f"Found {len(paths_list)} candidate files to upload")
+
+ # Validate upload against repository limits
+ _validate_upload_limits(paths_list)
+
+ logger.info("Starting upload...")
+
+ # Read metadata for each file
+ items = [
+ (paths, read_upload_metadata(folder_path, paths.path_in_repo))
+ for paths in tqdm(paths_list, desc="Recovering from metadata files")
+ ]
+
+ # 4. Start workers
+ status = LargeUploadStatus(items, upload_batch_size)
+ threads = [
+ threading.Thread(
+ target=_worker_job,
+ kwargs={
+ "status": status,
+ "api": api,
+ "repo_id": repo_id,
+ "repo_type": repo_type,
+ "revision": revision,
+ },
+ )
+ for _ in range(num_workers)
+ ]
+
+ for thread in threads:
+ thread.start()
+
+ # 5. Print regular reports
+ if print_report:
+ print("\n\n" + status.current_report())
+ last_report_ts = time.time()
+ while True:
+ time.sleep(1)
+ if time.time() - last_report_ts >= print_report_every:
+ if print_report:
+ _print_overwrite(status.current_report())
+ last_report_ts = time.time()
+ if status.is_done():
+ logging.info("Is done: exiting main loop")
+ break
+
+ for thread in threads:
+ thread.join()
+
+ logger.info(status.current_report())
+ logging.info("Upload is complete!")
+
+
+####################
+# Logic to manage workers and synchronize tasks
+####################
+
+
+class WorkerJob(enum.Enum):
+ SHA256 = enum.auto()
+ GET_UPLOAD_MODE = enum.auto()
+ PREUPLOAD_LFS = enum.auto()
+ COMMIT = enum.auto()
+ WAIT = enum.auto() # if no tasks are available but we don't want to exit
+
+
+JOB_ITEM_T = Tuple[LocalUploadFilePaths, LocalUploadFileMetadata]
+
+
+class LargeUploadStatus:
+ """Contains information, queues and tasks for a large upload process."""
+
+ def __init__(self, items: List[JOB_ITEM_T], upload_batch_size: int = 1):
+ self.items = items
+ self.queue_sha256: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+ self.queue_get_upload_mode: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+ self.queue_preupload_lfs: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+ self.queue_commit: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+ self.lock = Lock()
+
+ self.nb_workers_sha256: int = 0
+ self.nb_workers_get_upload_mode: int = 0
+ self.nb_workers_preupload_lfs: int = 0
+ self.upload_batch_size: int = upload_batch_size
+ self.nb_workers_commit: int = 0
+ self.nb_workers_waiting: int = 0
+ self.last_commit_attempt: Optional[float] = None
+
+ self._started_at = datetime.now()
+ self._chunk_idx: int = 1
+ self._chunk_lock: Lock = Lock()
+
+ # Setup queues
+ for item in self.items:
+ paths, metadata = item
+ if metadata.sha256 is None:
+ self.queue_sha256.put(item)
+ elif metadata.upload_mode is None:
+ self.queue_get_upload_mode.put(item)
+ elif metadata.upload_mode == "lfs" and not metadata.is_uploaded:
+ self.queue_preupload_lfs.put(item)
+ elif not metadata.is_committed:
+ self.queue_commit.put(item)
+ else:
+ logger.debug(f"Skipping file {paths.path_in_repo} (already uploaded and committed)")
+
+ def target_chunk(self) -> int:
+ with self._chunk_lock:
+ return COMMIT_SIZE_SCALE[self._chunk_idx]
+
+ def update_chunk(self, success: bool, nb_items: int, duration: float) -> None:
+ with self._chunk_lock:
+ if not success:
+ logger.warning(f"Failed to commit {nb_items} files at once. Will retry with less files in next batch.")
+ self._chunk_idx -= 1
+ elif nb_items >= COMMIT_SIZE_SCALE[self._chunk_idx] and duration < 40:
+ logger.info(f"Successfully committed {nb_items} at once. Increasing the limit for next batch.")
+ self._chunk_idx += 1
+
+ self._chunk_idx = max(0, min(self._chunk_idx, len(COMMIT_SIZE_SCALE) - 1))
+
+ def current_report(self) -> str:
+ """Generate a report of the current status of the large upload."""
+ nb_hashed = 0
+ size_hashed = 0
+ nb_preuploaded = 0
+ nb_lfs = 0
+ nb_lfs_unsure = 0
+ size_preuploaded = 0
+ nb_committed = 0
+ size_committed = 0
+ total_size = 0
+ ignored_files = 0
+ total_files = 0
+
+ with self.lock:
+ for _, metadata in self.items:
+ if metadata.should_ignore:
+ ignored_files += 1
+ continue
+ total_size += metadata.size
+ total_files += 1
+ if metadata.sha256 is not None:
+ nb_hashed += 1
+ size_hashed += metadata.size
+ if metadata.upload_mode == "lfs":
+ nb_lfs += 1
+ if metadata.upload_mode is None:
+ nb_lfs_unsure += 1
+ if metadata.is_uploaded:
+ nb_preuploaded += 1
+ size_preuploaded += metadata.size
+ if metadata.is_committed:
+ nb_committed += 1
+ size_committed += metadata.size
+ total_size_str = _format_size(total_size)
+
+ now = datetime.now()
+ now_str = now.strftime("%Y-%m-%d %H:%M:%S")
+ elapsed = now - self._started_at
+ elapsed_str = str(elapsed).split(".")[0] # remove milliseconds
+
+ message = "\n" + "-" * 10
+ message += f" {now_str} ({elapsed_str}) "
+ message += "-" * 10 + "\n"
+
+ message += "Files: "
+ message += f"hashed {nb_hashed}/{total_files} ({_format_size(size_hashed)}/{total_size_str}) | "
+ message += f"pre-uploaded: {nb_preuploaded}/{nb_lfs} ({_format_size(size_preuploaded)}/{total_size_str})"
+ if nb_lfs_unsure > 0:
+ message += f" (+{nb_lfs_unsure} unsure)"
+ message += f" | committed: {nb_committed}/{total_files} ({_format_size(size_committed)}/{total_size_str})"
+ message += f" | ignored: {ignored_files}\n"
+
+ message += "Workers: "
+ message += f"hashing: {self.nb_workers_sha256} | "
+ message += f"get upload mode: {self.nb_workers_get_upload_mode} | "
+ message += f"pre-uploading: {self.nb_workers_preupload_lfs} | "
+ message += f"committing: {self.nb_workers_commit} | "
+ message += f"waiting: {self.nb_workers_waiting}\n"
+ message += "-" * 51
+
+ return message
+
+ def is_done(self) -> bool:
+ with self.lock:
+ return all(metadata.is_committed or metadata.should_ignore for _, metadata in self.items)
+
+
+def _worker_job(
+ status: LargeUploadStatus,
+ api: "HfApi",
+ repo_id: str,
+ repo_type: str,
+ revision: str,
+):
+ """
+ Main process for a worker. The worker will perform tasks based on the priority list until all files are uploaded
+ and committed. If no tasks are available, the worker will wait for 10 seconds before checking again.
+
+ If a task fails for any reason, the item(s) are put back in the queue for another worker to pick up.
+
+ Read `upload_large_folder` docstring for more information on how tasks are prioritized.
+ """
+ while True:
+ next_job: Optional[Tuple[WorkerJob, List[JOB_ITEM_T]]] = None
+
+ # Determine next task
+ next_job = _determine_next_job(status)
+ if next_job is None:
+ return
+ job, items = next_job
+
+ # Perform task
+ if job == WorkerJob.SHA256:
+ item = items[0] # single item
+ try:
+ _compute_sha256(item)
+ status.queue_get_upload_mode.put(item)
+ except KeyboardInterrupt:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to compute sha256: {e}")
+ traceback.format_exc()
+ status.queue_sha256.put(item)
+
+ with status.lock:
+ status.nb_workers_sha256 -= 1
+
+ elif job == WorkerJob.GET_UPLOAD_MODE:
+ try:
+ _get_upload_mode(items, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+ except KeyboardInterrupt:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to get upload mode: {e}")
+ traceback.format_exc()
+
+ # Items are either:
+ # - dropped (if should_ignore)
+ # - put in LFS queue (if LFS)
+ # - put in commit queue (if regular)
+ # - or put back (if error occurred).
+ for item in items:
+ _, metadata = item
+ if metadata.should_ignore:
+ continue
+ if metadata.upload_mode == "lfs":
+ status.queue_preupload_lfs.put(item)
+ elif metadata.upload_mode == "regular":
+ status.queue_commit.put(item)
+ else:
+ status.queue_get_upload_mode.put(item)
+
+ with status.lock:
+ status.nb_workers_get_upload_mode -= 1
+
+ elif job == WorkerJob.PREUPLOAD_LFS:
+ try:
+ _preupload_lfs(items, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+ for item in items:
+ status.queue_commit.put(item)
+ except KeyboardInterrupt:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to preupload LFS: {e}")
+ traceback.format_exc()
+ for item in items:
+ status.queue_preupload_lfs.put(item)
+
+ with status.lock:
+ status.nb_workers_preupload_lfs -= 1
+
+ elif job == WorkerJob.COMMIT:
+ start_ts = time.time()
+ success = True
+ try:
+ _commit(items, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+ except KeyboardInterrupt:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to commit: {e}")
+ traceback.format_exc()
+ for item in items:
+ status.queue_commit.put(item)
+ success = False
+ duration = time.time() - start_ts
+ status.update_chunk(success, len(items), duration)
+ with status.lock:
+ status.last_commit_attempt = time.time()
+ status.nb_workers_commit -= 1
+
+ elif job == WorkerJob.WAIT:
+ time.sleep(WAITING_TIME_IF_NO_TASKS)
+ with status.lock:
+ status.nb_workers_waiting -= 1
+
+
+def _determine_next_job(status: LargeUploadStatus) -> Optional[Tuple[WorkerJob, List[JOB_ITEM_T]]]:
+ with status.lock:
+ # 1. Commit if more than 5 minutes since last commit attempt (and at least 1 file)
+ if (
+ status.nb_workers_commit == 0
+ and status.queue_commit.qsize() > 0
+ and status.last_commit_attempt is not None
+ and time.time() - status.last_commit_attempt > 5 * 60
+ ):
+ status.nb_workers_commit += 1
+ logger.debug("Job: commit (more than 5 minutes since last commit attempt)")
+ return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+ # 2. Commit if at least 100 files are ready to commit
+ elif status.nb_workers_commit == 0 and status.queue_commit.qsize() >= 150:
+ status.nb_workers_commit += 1
+ logger.debug("Job: commit (>100 files ready)")
+ return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+ # 3. Get upload mode if at least 100 files
+ elif status.queue_get_upload_mode.qsize() >= MAX_NB_FILES_FETCH_UPLOAD_MODE:
+ status.nb_workers_get_upload_mode += 1
+ logger.debug(f"Job: get upload mode (>{MAX_NB_FILES_FETCH_UPLOAD_MODE} files ready)")
+ return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+ # 4. Preupload LFS file if at least `status.upload_batch_size` files and no worker is preuploading LFS
+ elif status.queue_preupload_lfs.qsize() >= status.upload_batch_size and status.nb_workers_preupload_lfs == 0:
+ status.nb_workers_preupload_lfs += 1
+ logger.debug("Job: preupload LFS (no other worker preuploading LFS)")
+ return (WorkerJob.PREUPLOAD_LFS, _get_n(status.queue_preupload_lfs, status.upload_batch_size))
+
+ # 5. Compute sha256 if at least 1 file and no worker is computing sha256
+ elif status.queue_sha256.qsize() > 0 and status.nb_workers_sha256 == 0:
+ status.nb_workers_sha256 += 1
+ logger.debug("Job: sha256 (no other worker computing sha256)")
+ return (WorkerJob.SHA256, _get_one(status.queue_sha256))
+
+ # 6. Get upload mode if at least 1 file and no worker is getting upload mode
+ elif status.queue_get_upload_mode.qsize() > 0 and status.nb_workers_get_upload_mode == 0:
+ status.nb_workers_get_upload_mode += 1
+ logger.debug("Job: get upload mode (no other worker getting upload mode)")
+ return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+ # 7. Preupload LFS file if at least `status.upload_batch_size` files
+ # Skip if hf_transfer is enabled and there is already a worker preuploading LFS
+ elif status.queue_preupload_lfs.qsize() >= status.upload_batch_size and (
+ status.nb_workers_preupload_lfs == 0 or not constants.HF_HUB_ENABLE_HF_TRANSFER
+ ):
+ status.nb_workers_preupload_lfs += 1
+ logger.debug("Job: preupload LFS")
+ return (WorkerJob.PREUPLOAD_LFS, _get_n(status.queue_preupload_lfs, status.upload_batch_size))
+
+ # 8. Compute sha256 if at least 1 file
+ elif status.queue_sha256.qsize() > 0:
+ status.nb_workers_sha256 += 1
+ logger.debug("Job: sha256")
+ return (WorkerJob.SHA256, _get_one(status.queue_sha256))
+
+ # 9. Get upload mode if at least 1 file
+ elif status.queue_get_upload_mode.qsize() > 0:
+ status.nb_workers_get_upload_mode += 1
+ logger.debug("Job: get upload mode")
+ return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+ # 10. Preupload LFS file if at least 1 file
+ elif status.queue_preupload_lfs.qsize() > 0:
+ status.nb_workers_preupload_lfs += 1
+ logger.debug("Job: preupload LFS")
+ return (WorkerJob.PREUPLOAD_LFS, _get_n(status.queue_preupload_lfs, status.upload_batch_size))
+
+ # 11. Commit if at least 1 file and 1 min since last commit attempt
+ elif (
+ status.nb_workers_commit == 0
+ and status.queue_commit.qsize() > 0
+ and status.last_commit_attempt is not None
+ and time.time() - status.last_commit_attempt > 1 * 60
+ ):
+ status.nb_workers_commit += 1
+ logger.debug("Job: commit (1 min since last commit attempt)")
+ return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+ # 12. Commit if at least 1 file all other queues are empty and all workers are waiting
+ # e.g. when it's the last commit
+ elif (
+ status.nb_workers_commit == 0
+ and status.queue_commit.qsize() > 0
+ and status.queue_sha256.qsize() == 0
+ and status.queue_get_upload_mode.qsize() == 0
+ and status.queue_preupload_lfs.qsize() == 0
+ and status.nb_workers_sha256 == 0
+ and status.nb_workers_get_upload_mode == 0
+ and status.nb_workers_preupload_lfs == 0
+ ):
+ status.nb_workers_commit += 1
+ logger.debug("Job: commit")
+ return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+ # 13. If all queues are empty, exit
+ elif all(metadata.is_committed or metadata.should_ignore for _, metadata in status.items):
+ logger.info("All files have been processed! Exiting worker.")
+ return None
+
+ # 14. If no task is available, wait
+ else:
+ status.nb_workers_waiting += 1
+ logger.debug(f"No task available, waiting... ({WAITING_TIME_IF_NO_TASKS}s)")
+ return (WorkerJob.WAIT, [])
+
+
+####################
+# Atomic jobs (sha256, get_upload_mode, preupload_lfs, commit)
+####################
+
+
+def _compute_sha256(item: JOB_ITEM_T) -> None:
+ """Compute sha256 of a file and save it in metadata."""
+ paths, metadata = item
+ if metadata.sha256 is None:
+ with paths.file_path.open("rb") as f:
+ metadata.sha256 = sha_fileobj(f).hex()
+ metadata.save(paths)
+
+
+def _get_upload_mode(items: List[JOB_ITEM_T], api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+ """Get upload mode for each file and update metadata.
+
+ Also receive info if the file should be ignored.
+ """
+ additions = [_build_hacky_operation(item) for item in items]
+ _fetch_upload_modes(
+ additions=additions,
+ repo_type=repo_type,
+ repo_id=repo_id,
+ headers=api._build_hf_headers(),
+ revision=quote(revision, safe=""),
+ endpoint=api.endpoint,
+ )
+ for item, addition in zip(items, additions):
+ paths, metadata = item
+ metadata.upload_mode = addition._upload_mode
+ metadata.should_ignore = addition._should_ignore
+ metadata.remote_oid = addition._remote_oid
+ metadata.save(paths)
+
+
+def _preupload_lfs(items: List[JOB_ITEM_T], api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+ """Preupload LFS files and update metadata."""
+ additions = [_build_hacky_operation(item) for item in items]
+ api.preupload_lfs_files(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ additions=additions,
+ )
+
+ for paths, metadata in items:
+ metadata.is_uploaded = True
+ metadata.save(paths)
+
+
+def _commit(items: List[JOB_ITEM_T], api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+ """Commit files to the repo."""
+ additions = [_build_hacky_operation(item) for item in items]
+ api.create_commit(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ operations=additions,
+ commit_message="Add files using upload-large-folder tool",
+ )
+ for paths, metadata in items:
+ metadata.is_committed = True
+ metadata.save(paths)
+
+
+####################
+# Hacks with CommitOperationAdd to bypass checks/sha256 calculation
+####################
+
+
+class HackyCommitOperationAdd(CommitOperationAdd):
+ def __post_init__(self) -> None:
+ if isinstance(self.path_or_fileobj, Path):
+ self.path_or_fileobj = str(self.path_or_fileobj)
+
+
+def _build_hacky_operation(item: JOB_ITEM_T) -> HackyCommitOperationAdd:
+ paths, metadata = item
+ operation = HackyCommitOperationAdd(path_in_repo=paths.path_in_repo, path_or_fileobj=paths.file_path)
+ with paths.file_path.open("rb") as file:
+ sample = file.peek(512)[:512]
+ if metadata.sha256 is None:
+ raise ValueError("sha256 must have been computed by now!")
+ operation.upload_info = UploadInfo(sha256=bytes.fromhex(metadata.sha256), size=metadata.size, sample=sample)
+ operation._upload_mode = metadata.upload_mode # type: ignore[assignment]
+ operation._should_ignore = metadata.should_ignore
+ operation._remote_oid = metadata.remote_oid
+ return operation
+
+
+####################
+# Misc helpers
+####################
+
+
+def _get_one(queue: "queue.Queue[JOB_ITEM_T]") -> List[JOB_ITEM_T]:
+ return [queue.get()]
+
+
+def _get_n(queue: "queue.Queue[JOB_ITEM_T]", n: int) -> List[JOB_ITEM_T]:
+ return [queue.get() for _ in range(min(queue.qsize(), n))]
+
+
+def _print_overwrite(report: str) -> None:
+ """Print a report, overwriting the previous lines.
+
+ Since tqdm in using `sys.stderr` to (re-)write progress bars, we need to use `sys.stdout`
+ to print the report.
+
+ Note: works well only if no other process is writing to `sys.stdout`!
+ """
+ report += "\n"
+ # Get terminal width
+ terminal_width = shutil.get_terminal_size().columns
+
+ # Count number of lines that should be cleared
+ nb_lines = sum(len(line) // terminal_width + 1 for line in report.splitlines())
+
+ # Clear previous lines based on the number of lines in the report
+ for _ in range(nb_lines):
+ sys.stdout.write("\r\033[K") # Clear line
+ sys.stdout.write("\033[F") # Move cursor up one line
+
+ # Print the new report, filling remaining space with whitespace
+ sys.stdout.write(report)
+ sys.stdout.write(" " * (terminal_width - len(report.splitlines()[-1])))
+ sys.stdout.flush()
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_payload.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_payload.py
new file mode 100644
index 0000000000000000000000000000000000000000..288f4b08b9428980e99ca06703442eab62fad277
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_payload.py
@@ -0,0 +1,137 @@
+# coding=utf-8
+# Copyright 2023-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains data structures to parse the webhooks payload."""
+
+from typing import List, Literal, Optional
+
+from .utils import is_pydantic_available
+
+
+if is_pydantic_available():
+ from pydantic import BaseModel
+else:
+ # Define a dummy BaseModel to avoid import errors when pydantic is not installed
+ # Import error will be raised when trying to use the class
+
+ class BaseModel: # type: ignore [no-redef]
+ def __init__(self, *args, **kwargs) -> None:
+ raise ImportError(
+ "You must have `pydantic` installed to use `WebhookPayload`. This is an optional dependency that"
+ " should be installed separately. Please run `pip install --upgrade pydantic` and retry."
+ )
+
+
+# This is an adaptation of the ReportV3 interface implemented in moon-landing. V0, V1 and V2 have been ignored as they
+# are not in used anymore. To keep in sync when format is updated in
+# https://github.com/huggingface/moon-landing/blob/main/server/lib/HFWebhooks.ts (internal link).
+
+
+WebhookEvent_T = Literal[
+ "create",
+ "delete",
+ "move",
+ "update",
+]
+RepoChangeEvent_T = Literal[
+ "add",
+ "move",
+ "remove",
+ "update",
+]
+RepoType_T = Literal[
+ "dataset",
+ "model",
+ "space",
+]
+DiscussionStatus_T = Literal[
+ "closed",
+ "draft",
+ "open",
+ "merged",
+]
+SupportedWebhookVersion = Literal[3]
+
+
+class ObjectId(BaseModel):
+ id: str
+
+
+class WebhookPayloadUrl(BaseModel):
+ web: str
+ api: Optional[str] = None
+
+
+class WebhookPayloadMovedTo(BaseModel):
+ name: str
+ owner: ObjectId
+
+
+class WebhookPayloadWebhook(ObjectId):
+ version: SupportedWebhookVersion
+
+
+class WebhookPayloadEvent(BaseModel):
+ action: WebhookEvent_T
+ scope: str
+
+
+class WebhookPayloadDiscussionChanges(BaseModel):
+ base: str
+ mergeCommitId: Optional[str] = None
+
+
+class WebhookPayloadComment(ObjectId):
+ author: ObjectId
+ hidden: bool
+ content: Optional[str] = None
+ url: WebhookPayloadUrl
+
+
+class WebhookPayloadDiscussion(ObjectId):
+ num: int
+ author: ObjectId
+ url: WebhookPayloadUrl
+ title: str
+ isPullRequest: bool
+ status: DiscussionStatus_T
+ changes: Optional[WebhookPayloadDiscussionChanges] = None
+ pinned: Optional[bool] = None
+
+
+class WebhookPayloadRepo(ObjectId):
+ owner: ObjectId
+ head_sha: Optional[str] = None
+ name: str
+ private: bool
+ subdomain: Optional[str] = None
+ tags: Optional[List[str]] = None
+ type: Literal["dataset", "model", "space"]
+ url: WebhookPayloadUrl
+
+
+class WebhookPayloadUpdatedRef(BaseModel):
+ ref: str
+ oldSha: Optional[str] = None
+ newSha: Optional[str] = None
+
+
+class WebhookPayload(BaseModel):
+ event: WebhookPayloadEvent
+ repo: WebhookPayloadRepo
+ discussion: Optional[WebhookPayloadDiscussion] = None
+ comment: Optional[WebhookPayloadComment] = None
+ webhook: WebhookPayloadWebhook
+ movedTo: Optional[WebhookPayloadMovedTo] = None
+ updatedRefs: Optional[List[WebhookPayloadUpdatedRef]] = None
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_server.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_server.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3668304553e13f9605a59ec623aceb5202a2488
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/_webhooks_server.py
@@ -0,0 +1,376 @@
+# coding=utf-8
+# Copyright 2023-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains `WebhooksServer` and `webhook_endpoint` to create a webhook server easily."""
+
+import atexit
+import inspect
+import os
+from functools import wraps
+from typing import TYPE_CHECKING, Any, Callable, Dict, Optional
+
+from .utils import experimental, is_fastapi_available, is_gradio_available
+
+
+if TYPE_CHECKING:
+ import gradio as gr
+ from fastapi import Request
+
+if is_fastapi_available():
+ from fastapi import FastAPI, Request
+ from fastapi.responses import JSONResponse
+else:
+ # Will fail at runtime if FastAPI is not available
+ FastAPI = Request = JSONResponse = None # type: ignore
+
+
+_global_app: Optional["WebhooksServer"] = None
+_is_local = os.environ.get("SPACE_ID") is None
+
+
+@experimental
+class WebhooksServer:
+ """
+ The [`WebhooksServer`] class lets you create an instance of a Gradio app that can receive Huggingface webhooks.
+ These webhooks can be registered using the [`~WebhooksServer.add_webhook`] decorator. Webhook endpoints are added to
+ the app as a POST endpoint to the FastAPI router. Once all the webhooks are registered, the `launch` method has to be
+ called to start the app.
+
+ It is recommended to accept [`WebhookPayload`] as the first argument of the webhook function. It is a Pydantic
+ model that contains all the information about the webhook event. The data will be parsed automatically for you.
+
+ Check out the [webhooks guide](../guides/webhooks_server) for a step-by-step tutorial on how to setup your
+ WebhooksServer and deploy it on a Space.
+
+ > [!WARNING]
+ > `WebhooksServer` is experimental. Its API is subject to change in the future.
+
+ > [!WARNING]
+ > You must have `gradio` installed to use `WebhooksServer` (`pip install --upgrade gradio`).
+
+ Args:
+ ui (`gradio.Blocks`, optional):
+ A Gradio UI instance to be used as the Space landing page. If `None`, a UI displaying instructions
+ about the configured webhooks is created.
+ webhook_secret (`str`, optional):
+ A secret key to verify incoming webhook requests. You can set this value to any secret you want as long as
+ you also configure it in your [webhooks settings panel](https://huggingface.co/settings/webhooks). You
+ can also set this value as the `WEBHOOK_SECRET` environment variable. If no secret is provided, the
+ webhook endpoints are opened without any security.
+
+ Example:
+
+ ```python
+ import gradio as gr
+ from huggingface_hub import WebhooksServer, WebhookPayload
+
+ with gr.Blocks() as ui:
+ ...
+
+ app = WebhooksServer(ui=ui, webhook_secret="my_secret_key")
+
+ @app.add_webhook("/say_hello")
+ async def hello(payload: WebhookPayload):
+ return {"message": "hello"}
+
+ app.launch()
+ ```
+ """
+
+ def __new__(cls, *args, **kwargs) -> "WebhooksServer":
+ if not is_gradio_available():
+ raise ImportError(
+ "You must have `gradio` installed to use `WebhooksServer`. Please run `pip install --upgrade gradio`"
+ " first."
+ )
+ if not is_fastapi_available():
+ raise ImportError(
+ "You must have `fastapi` installed to use `WebhooksServer`. Please run `pip install --upgrade fastapi`"
+ " first."
+ )
+ return super().__new__(cls)
+
+ def __init__(
+ self,
+ ui: Optional["gr.Blocks"] = None,
+ webhook_secret: Optional[str] = None,
+ ) -> None:
+ self._ui = ui
+
+ self.webhook_secret = webhook_secret or os.getenv("WEBHOOK_SECRET")
+ self.registered_webhooks: Dict[str, Callable] = {}
+ _warn_on_empty_secret(self.webhook_secret)
+
+ def add_webhook(self, path: Optional[str] = None) -> Callable:
+ """
+ Decorator to add a webhook to the [`WebhooksServer`] server.
+
+ Args:
+ path (`str`, optional):
+ The URL path to register the webhook function. If not provided, the function name will be used as the
+ path. In any case, all webhooks are registered under `/webhooks`.
+
+ Raises:
+ ValueError: If the provided path is already registered as a webhook.
+
+ Example:
+ ```python
+ from huggingface_hub import WebhooksServer, WebhookPayload
+
+ app = WebhooksServer()
+
+ @app.add_webhook
+ async def trigger_training(payload: WebhookPayload):
+ if payload.repo.type == "dataset" and payload.event.action == "update":
+ # Trigger a training job if a dataset is updated
+ ...
+
+ app.launch()
+ ```
+ """
+ # Usage: directly as decorator. Example: `@app.add_webhook`
+ if callable(path):
+ # If path is a function, it means it was used as a decorator without arguments
+ return self.add_webhook()(path)
+
+ # Usage: provide a path. Example: `@app.add_webhook(...)`
+ @wraps(FastAPI.post)
+ def _inner_post(*args, **kwargs):
+ func = args[0]
+ abs_path = f"/webhooks/{(path or func.__name__).strip('/')}"
+ if abs_path in self.registered_webhooks:
+ raise ValueError(f"Webhook {abs_path} already exists.")
+ self.registered_webhooks[abs_path] = func
+
+ return _inner_post
+
+ def launch(self, prevent_thread_lock: bool = False, **launch_kwargs: Any) -> None:
+ """Launch the Gradio app and register webhooks to the underlying FastAPI server.
+
+ Input parameters are forwarded to Gradio when launching the app.
+ """
+ ui = self._ui or self._get_default_ui()
+
+ # Start Gradio App
+ # - as non-blocking so that webhooks can be added afterwards
+ # - as shared if launch locally (to debug webhooks)
+ launch_kwargs.setdefault("share", _is_local)
+ self.fastapi_app, _, _ = ui.launch(prevent_thread_lock=True, **launch_kwargs)
+
+ # Register webhooks to FastAPI app
+ for path, func in self.registered_webhooks.items():
+ # Add secret check if required
+ if self.webhook_secret is not None:
+ func = _wrap_webhook_to_check_secret(func, webhook_secret=self.webhook_secret)
+
+ # Add route to FastAPI app
+ self.fastapi_app.post(path)(func)
+
+ # Print instructions and block main thread
+ space_host = os.environ.get("SPACE_HOST")
+ url = "https://" + space_host if space_host is not None else (ui.share_url or ui.local_url)
+ if url is None:
+ raise ValueError("Cannot find the URL of the app. Please provide a valid `ui` or update `gradio` version.")
+ url = url.strip("/")
+ message = "\nWebhooks are correctly setup and ready to use:"
+ message += "\n" + "\n".join(f" - POST {url}{webhook}" for webhook in self.registered_webhooks)
+ message += "\nGo to https://huggingface.co/settings/webhooks to setup your webhooks."
+ print(message)
+
+ if not prevent_thread_lock:
+ ui.block_thread()
+
+ def _get_default_ui(self) -> "gr.Blocks":
+ """Default UI if not provided (lists webhooks and provides basic instructions)."""
+ import gradio as gr
+
+ with gr.Blocks() as ui:
+ gr.Markdown("# This is an app to process 🤗 Webhooks")
+ gr.Markdown(
+ "Webhooks are a foundation for MLOps-related features. They allow you to listen for new changes on"
+ " specific repos or to all repos belonging to particular set of users/organizations (not just your"
+ " repos, but any repo). Check out this [guide](https://huggingface.co/docs/hub/webhooks) to get to"
+ " know more about webhooks on the Huggingface Hub."
+ )
+ gr.Markdown(
+ f"{len(self.registered_webhooks)} webhook(s) are registered:"
+ + "\n\n"
+ + "\n ".join(
+ f"- [{webhook_path}]({_get_webhook_doc_url(webhook.__name__, webhook_path)})"
+ for webhook_path, webhook in self.registered_webhooks.items()
+ )
+ )
+ gr.Markdown(
+ "Go to https://huggingface.co/settings/webhooks to setup your webhooks."
+ + "\nYou app is running locally. Please look at the logs to check the full URL you need to set."
+ if _is_local
+ else (
+ "\nThis app is running on a Space. You can find the corresponding URL in the options menu"
+ " (top-right) > 'Embed the Space'. The URL looks like 'https://{username}-{repo_name}.hf.space'."
+ )
+ )
+ return ui
+
+
+@experimental
+def webhook_endpoint(path: Optional[str] = None) -> Callable:
+ """Decorator to start a [`WebhooksServer`] and register the decorated function as a webhook endpoint.
+
+ This is a helper to get started quickly. If you need more flexibility (custom landing page or webhook secret),
+ you can use [`WebhooksServer`] directly. You can register multiple webhook endpoints (to the same server) by using
+ this decorator multiple times.
+
+ Check out the [webhooks guide](../guides/webhooks_server) for a step-by-step tutorial on how to setup your
+ server and deploy it on a Space.
+
+ > [!WARNING]
+ > `webhook_endpoint` is experimental. Its API is subject to change in the future.
+
+ > [!WARNING]
+ > You must have `gradio` installed to use `webhook_endpoint` (`pip install --upgrade gradio`).
+
+ Args:
+ path (`str`, optional):
+ The URL path to register the webhook function. If not provided, the function name will be used as the path.
+ In any case, all webhooks are registered under `/webhooks`.
+
+ Examples:
+ The default usage is to register a function as a webhook endpoint. The function name will be used as the path.
+ The server will be started automatically at exit (i.e. at the end of the script).
+
+ ```python
+ from huggingface_hub import webhook_endpoint, WebhookPayload
+
+ @webhook_endpoint
+ async def trigger_training(payload: WebhookPayload):
+ if payload.repo.type == "dataset" and payload.event.action == "update":
+ # Trigger a training job if a dataset is updated
+ ...
+
+ # Server is automatically started at the end of the script.
+ ```
+
+ Advanced usage: register a function as a webhook endpoint and start the server manually. This is useful if you
+ are running it in a notebook.
+
+ ```python
+ from huggingface_hub import webhook_endpoint, WebhookPayload
+
+ @webhook_endpoint
+ async def trigger_training(payload: WebhookPayload):
+ if payload.repo.type == "dataset" and payload.event.action == "update":
+ # Trigger a training job if a dataset is updated
+ ...
+
+ # Start the server manually
+ trigger_training.launch()
+ ```
+ """
+ if callable(path):
+ # If path is a function, it means it was used as a decorator without arguments
+ return webhook_endpoint()(path)
+
+ @wraps(WebhooksServer.add_webhook)
+ def _inner(func: Callable) -> Callable:
+ app = _get_global_app()
+ app.add_webhook(path)(func)
+ if len(app.registered_webhooks) == 1:
+ # Register `app.launch` to run at exit (only once)
+ atexit.register(app.launch)
+
+ @wraps(app.launch)
+ def _launch_now():
+ # Run the app directly (without waiting atexit)
+ atexit.unregister(app.launch)
+ app.launch()
+
+ func.launch = _launch_now # type: ignore
+ return func
+
+ return _inner
+
+
+def _get_global_app() -> WebhooksServer:
+ global _global_app
+ if _global_app is None:
+ _global_app = WebhooksServer()
+ return _global_app
+
+
+def _warn_on_empty_secret(webhook_secret: Optional[str]) -> None:
+ if webhook_secret is None:
+ print("Webhook secret is not defined. This means your webhook endpoints will be open to everyone.")
+ print(
+ "To add a secret, set `WEBHOOK_SECRET` as environment variable or pass it at initialization: "
+ "\n\t`app = WebhooksServer(webhook_secret='my_secret', ...)`"
+ )
+ print(
+ "For more details about webhook secrets, please refer to"
+ " https://huggingface.co/docs/hub/webhooks#webhook-secret."
+ )
+ else:
+ print("Webhook secret is correctly defined.")
+
+
+def _get_webhook_doc_url(webhook_name: str, webhook_path: str) -> str:
+ """Returns the anchor to a given webhook in the docs (experimental)"""
+ return "/docs#/default/" + webhook_name + webhook_path.replace("/", "_") + "_post"
+
+
+def _wrap_webhook_to_check_secret(func: Callable, webhook_secret: str) -> Callable:
+ """Wraps a webhook function to check the webhook secret before calling the function.
+
+ This is a hacky way to add the `request` parameter to the function signature. Since FastAPI based itself on route
+ parameters to inject the values to the function, we need to hack the function signature to retrieve the `Request`
+ object (and hence the headers). A far cleaner solution would be to use a middleware. However, since
+ `fastapi==0.90.1`, a middleware cannot be added once the app has started. And since the FastAPI app is started by
+ Gradio internals (and not by us), we cannot add a middleware.
+
+ This method is called only when a secret has been defined by the user. If a request is sent without the
+ "x-webhook-secret", the function will return a 401 error (unauthorized). If the header is sent but is incorrect,
+ the function will return a 403 error (forbidden).
+
+ Inspired by https://stackoverflow.com/a/33112180.
+ """
+ initial_sig = inspect.signature(func)
+
+ @wraps(func)
+ async def _protected_func(request: Request, **kwargs):
+ request_secret = request.headers.get("x-webhook-secret")
+ if request_secret is None:
+ return JSONResponse({"error": "x-webhook-secret header not set."}, status_code=401)
+ if request_secret != webhook_secret:
+ return JSONResponse({"error": "Invalid webhook secret."}, status_code=403)
+
+ # Inject `request` in kwargs if required
+ if "request" in initial_sig.parameters:
+ kwargs["request"] = request
+
+ # Handle both sync and async routes
+ if inspect.iscoroutinefunction(func):
+ return await func(**kwargs)
+ else:
+ return func(**kwargs)
+
+ # Update signature to include request
+ if "request" not in initial_sig.parameters:
+ _protected_func.__signature__ = initial_sig.replace( # type: ignore
+ parameters=(
+ inspect.Parameter(name="request", kind=inspect.Parameter.POSITIONAL_OR_KEYWORD, annotation=Request),
+ )
+ + tuple(initial_sig.parameters.values())
+ )
+
+ # Return protected route
+ return _protected_func
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/community.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/community.py
new file mode 100644
index 0000000000000000000000000000000000000000..ffaab355174689b1dfb5b1c95f06fc088859d4cf
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/community.py
@@ -0,0 +1,363 @@
+"""
+Data structures to interact with Discussions and Pull Requests on the Hub.
+
+See [the Discussions and Pull Requests guide](https://huggingface.co/docs/hub/repositories-pull-requests-discussions)
+for more information on Pull Requests, Discussions, and the community tab.
+"""
+
+from dataclasses import dataclass
+from datetime import datetime
+from typing import List, Literal, Optional, TypedDict, Union
+
+from . import constants
+from .utils import parse_datetime
+
+
+DiscussionStatus = Literal["open", "closed", "merged", "draft"]
+
+
+@dataclass
+class Discussion:
+ """
+ A Discussion or Pull Request on the Hub.
+
+ This dataclass is not intended to be instantiated directly.
+
+ Attributes:
+ title (`str`):
+ The title of the Discussion / Pull Request
+ status (`str`):
+ The status of the Discussion / Pull Request.
+ It must be one of:
+ * `"open"`
+ * `"closed"`
+ * `"merged"` (only for Pull Requests )
+ * `"draft"` (only for Pull Requests )
+ num (`int`):
+ The number of the Discussion / Pull Request.
+ repo_id (`str`):
+ The id (`"{namespace}/{repo_name}"`) of the repo on which
+ the Discussion / Pull Request was open.
+ repo_type (`str`):
+ The type of the repo on which the Discussion / Pull Request was open.
+ Possible values are: `"model"`, `"dataset"`, `"space"`.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ is_pull_request (`bool`):
+ Whether or not this is a Pull Request.
+ created_at (`datetime`):
+ The `datetime` of creation of the Discussion / Pull Request.
+ endpoint (`str`):
+ Endpoint of the Hub. Default is https://huggingface.co.
+ git_reference (`str`, *optional*):
+ (property) Git reference to which changes can be pushed if this is a Pull Request, `None` otherwise.
+ url (`str`):
+ (property) URL of the discussion on the Hub.
+ """
+
+ title: str
+ status: DiscussionStatus
+ num: int
+ repo_id: str
+ repo_type: str
+ author: str
+ is_pull_request: bool
+ created_at: datetime
+ endpoint: str
+
+ @property
+ def git_reference(self) -> Optional[str]:
+ """
+ If this is a Pull Request , returns the git reference to which changes can be pushed.
+ Returns `None` otherwise.
+ """
+ if self.is_pull_request:
+ return f"refs/pr/{self.num}"
+ return None
+
+ @property
+ def url(self) -> str:
+ """Returns the URL of the discussion on the Hub."""
+ if self.repo_type is None or self.repo_type == constants.REPO_TYPE_MODEL:
+ return f"{self.endpoint}/{self.repo_id}/discussions/{self.num}"
+ return f"{self.endpoint}/{self.repo_type}s/{self.repo_id}/discussions/{self.num}"
+
+
+@dataclass
+class DiscussionWithDetails(Discussion):
+ """
+ Subclass of [`Discussion`].
+
+ Attributes:
+ title (`str`):
+ The title of the Discussion / Pull Request
+ status (`str`):
+ The status of the Discussion / Pull Request.
+ It can be one of:
+ * `"open"`
+ * `"closed"`
+ * `"merged"` (only for Pull Requests )
+ * `"draft"` (only for Pull Requests )
+ num (`int`):
+ The number of the Discussion / Pull Request.
+ repo_id (`str`):
+ The id (`"{namespace}/{repo_name}"`) of the repo on which
+ the Discussion / Pull Request was open.
+ repo_type (`str`):
+ The type of the repo on which the Discussion / Pull Request was open.
+ Possible values are: `"model"`, `"dataset"`, `"space"`.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ is_pull_request (`bool`):
+ Whether or not this is a Pull Request.
+ created_at (`datetime`):
+ The `datetime` of creation of the Discussion / Pull Request.
+ events (`list` of [`DiscussionEvent`])
+ The list of [`DiscussionEvents`] in this Discussion or Pull Request.
+ conflicting_files (`Union[List[str], bool, None]`, *optional*):
+ A list of conflicting files if this is a Pull Request.
+ `None` if `self.is_pull_request` is `False`.
+ `True` if there are conflicting files but the list can't be retrieved.
+ target_branch (`str`, *optional*):
+ The branch into which changes are to be merged if this is a
+ Pull Request . `None` if `self.is_pull_request` is `False`.
+ merge_commit_oid (`str`, *optional*):
+ If this is a merged Pull Request , this is set to the OID / SHA of
+ the merge commit, `None` otherwise.
+ diff (`str`, *optional*):
+ The git diff if this is a Pull Request , `None` otherwise.
+ endpoint (`str`):
+ Endpoint of the Hub. Default is https://huggingface.co.
+ git_reference (`str`, *optional*):
+ (property) Git reference to which changes can be pushed if this is a Pull Request, `None` otherwise.
+ url (`str`):
+ (property) URL of the discussion on the Hub.
+ """
+
+ events: List["DiscussionEvent"]
+ conflicting_files: Union[List[str], bool, None]
+ target_branch: Optional[str]
+ merge_commit_oid: Optional[str]
+ diff: Optional[str]
+
+
+class DiscussionEventArgs(TypedDict):
+ id: str
+ type: str
+ created_at: datetime
+ author: str
+ _event: dict
+
+
+@dataclass
+class DiscussionEvent:
+ """
+ An event in a Discussion or Pull Request.
+
+ Use concrete classes:
+ * [`DiscussionComment`]
+ * [`DiscussionStatusChange`]
+ * [`DiscussionCommit`]
+ * [`DiscussionTitleChange`]
+
+ Attributes:
+ id (`str`):
+ The ID of the event. An hexadecimal string.
+ type (`str`):
+ The type of the event.
+ created_at (`datetime`):
+ A [`datetime`](https://docs.python.org/3/library/datetime.html?highlight=datetime#datetime.datetime)
+ object holding the creation timestamp for the event.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ """
+
+ id: str
+ type: str
+ created_at: datetime
+ author: str
+
+ _event: dict
+ """Stores the original event data, in case we need to access it later."""
+
+
+@dataclass
+class DiscussionComment(DiscussionEvent):
+ """A comment in a Discussion / Pull Request.
+
+ Subclass of [`DiscussionEvent`].
+
+
+ Attributes:
+ id (`str`):
+ The ID of the event. An hexadecimal string.
+ type (`str`):
+ The type of the event.
+ created_at (`datetime`):
+ A [`datetime`](https://docs.python.org/3/library/datetime.html?highlight=datetime#datetime.datetime)
+ object holding the creation timestamp for the event.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ content (`str`):
+ The raw markdown content of the comment. Mentions, links and images are not rendered.
+ edited (`bool`):
+ Whether or not this comment has been edited.
+ hidden (`bool`):
+ Whether or not this comment has been hidden.
+ """
+
+ content: str
+ edited: bool
+ hidden: bool
+
+ @property
+ def rendered(self) -> str:
+ """The rendered comment, as a HTML string"""
+ return self._event["data"]["latest"]["html"]
+
+ @property
+ def last_edited_at(self) -> datetime:
+ """The last edit time, as a `datetime` object."""
+ return parse_datetime(self._event["data"]["latest"]["updatedAt"])
+
+ @property
+ def last_edited_by(self) -> str:
+ """The last edit time, as a `datetime` object."""
+ return self._event["data"]["latest"].get("author", {}).get("name", "deleted")
+
+ @property
+ def edit_history(self) -> List[dict]:
+ """The edit history of the comment"""
+ return self._event["data"]["history"]
+
+ @property
+ def number_of_edits(self) -> int:
+ return len(self.edit_history)
+
+
+@dataclass
+class DiscussionStatusChange(DiscussionEvent):
+ """A change of status in a Discussion / Pull Request.
+
+ Subclass of [`DiscussionEvent`].
+
+ Attributes:
+ id (`str`):
+ The ID of the event. An hexadecimal string.
+ type (`str`):
+ The type of the event.
+ created_at (`datetime`):
+ A [`datetime`](https://docs.python.org/3/library/datetime.html?highlight=datetime#datetime.datetime)
+ object holding the creation timestamp for the event.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ new_status (`str`):
+ The status of the Discussion / Pull Request after the change.
+ It can be one of:
+ * `"open"`
+ * `"closed"`
+ * `"merged"` (only for Pull Requests )
+ """
+
+ new_status: str
+
+
+@dataclass
+class DiscussionCommit(DiscussionEvent):
+ """A commit in a Pull Request.
+
+ Subclass of [`DiscussionEvent`].
+
+ Attributes:
+ id (`str`):
+ The ID of the event. An hexadecimal string.
+ type (`str`):
+ The type of the event.
+ created_at (`datetime`):
+ A [`datetime`](https://docs.python.org/3/library/datetime.html?highlight=datetime#datetime.datetime)
+ object holding the creation timestamp for the event.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ summary (`str`):
+ The summary of the commit.
+ oid (`str`):
+ The OID / SHA of the commit, as a hexadecimal string.
+ """
+
+ summary: str
+ oid: str
+
+
+@dataclass
+class DiscussionTitleChange(DiscussionEvent):
+ """A rename event in a Discussion / Pull Request.
+
+ Subclass of [`DiscussionEvent`].
+
+ Attributes:
+ id (`str`):
+ The ID of the event. An hexadecimal string.
+ type (`str`):
+ The type of the event.
+ created_at (`datetime`):
+ A [`datetime`](https://docs.python.org/3/library/datetime.html?highlight=datetime#datetime.datetime)
+ object holding the creation timestamp for the event.
+ author (`str`):
+ The username of the Discussion / Pull Request author.
+ Can be `"deleted"` if the user has been deleted since.
+ old_title (`str`):
+ The previous title for the Discussion / Pull Request.
+ new_title (`str`):
+ The new title.
+ """
+
+ old_title: str
+ new_title: str
+
+
+def deserialize_event(event: dict) -> DiscussionEvent:
+ """Instantiates a [`DiscussionEvent`] from a dict"""
+ event_id: str = event["id"]
+ event_type: str = event["type"]
+ created_at = parse_datetime(event["createdAt"])
+
+ common_args: DiscussionEventArgs = {
+ "id": event_id,
+ "type": event_type,
+ "created_at": created_at,
+ "author": event.get("author", {}).get("name", "deleted"),
+ "_event": event,
+ }
+
+ if event_type == "comment":
+ return DiscussionComment(
+ **common_args,
+ edited=event["data"]["edited"],
+ hidden=event["data"]["hidden"],
+ content=event["data"]["latest"]["raw"],
+ )
+ if event_type == "status-change":
+ return DiscussionStatusChange(
+ **common_args,
+ new_status=event["data"]["status"],
+ )
+ if event_type == "commit":
+ return DiscussionCommit(
+ **common_args,
+ summary=event["data"]["subject"],
+ oid=event["data"]["oid"],
+ )
+ if event_type == "title-change":
+ return DiscussionTitleChange(
+ **common_args,
+ old_title=event["data"]["from"],
+ new_title=event["data"]["to"],
+ )
+
+ return DiscussionEvent(**common_args)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/constants.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/constants.py
new file mode 100644
index 0000000000000000000000000000000000000000..b30b2c01d99c5ee5428875f3711227024f5d0829
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/constants.py
@@ -0,0 +1,294 @@
+import os
+import re
+import typing
+from typing import Literal, Optional, Tuple
+
+
+# Possible values for env variables
+
+
+ENV_VARS_TRUE_VALUES = {"1", "ON", "YES", "TRUE"}
+ENV_VARS_TRUE_AND_AUTO_VALUES = ENV_VARS_TRUE_VALUES.union({"AUTO"})
+
+
+def _is_true(value: Optional[str]) -> bool:
+ if value is None:
+ return False
+ return value.upper() in ENV_VARS_TRUE_VALUES
+
+
+def _as_int(value: Optional[str]) -> Optional[int]:
+ if value is None:
+ return None
+ return int(value)
+
+
+# Constants for file downloads
+
+PYTORCH_WEIGHTS_NAME = "pytorch_model.bin"
+TF2_WEIGHTS_NAME = "tf_model.h5"
+TF_WEIGHTS_NAME = "model.ckpt"
+FLAX_WEIGHTS_NAME = "flax_model.msgpack"
+CONFIG_NAME = "config.json"
+REPOCARD_NAME = "README.md"
+DEFAULT_ETAG_TIMEOUT = 10
+DEFAULT_DOWNLOAD_TIMEOUT = 10
+DEFAULT_REQUEST_TIMEOUT = 10
+DOWNLOAD_CHUNK_SIZE = 10 * 1024 * 1024
+HF_TRANSFER_CONCURRENCY = 100
+MAX_HTTP_DOWNLOAD_SIZE = 50 * 1000 * 1000 * 1000 # 50 GB
+
+# Constants for serialization
+
+PYTORCH_WEIGHTS_FILE_PATTERN = "pytorch_model{suffix}.bin" # Unsafe pickle: use safetensors instead
+SAFETENSORS_WEIGHTS_FILE_PATTERN = "model{suffix}.safetensors"
+TF2_WEIGHTS_FILE_PATTERN = "tf_model{suffix}.h5"
+
+# Constants for safetensors repos
+
+SAFETENSORS_SINGLE_FILE = "model.safetensors"
+SAFETENSORS_INDEX_FILE = "model.safetensors.index.json"
+SAFETENSORS_MAX_HEADER_LENGTH = 25_000_000
+
+# Timeout of aquiring file lock and logging the attempt
+FILELOCK_LOG_EVERY_SECONDS = 10
+
+# Git-related constants
+
+DEFAULT_REVISION = "main"
+REGEX_COMMIT_OID = re.compile(r"[A-Fa-f0-9]{5,40}")
+
+HUGGINGFACE_CO_URL_HOME = "https://huggingface.co/"
+
+_staging_mode = _is_true(os.environ.get("HUGGINGFACE_CO_STAGING"))
+
+_HF_DEFAULT_ENDPOINT = "https://huggingface.co"
+_HF_DEFAULT_STAGING_ENDPOINT = "https://hub-ci.huggingface.co"
+ENDPOINT = os.getenv("HF_ENDPOINT", _HF_DEFAULT_ENDPOINT).rstrip("/")
+HUGGINGFACE_CO_URL_TEMPLATE = ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
+
+if _staging_mode:
+ ENDPOINT = _HF_DEFAULT_STAGING_ENDPOINT
+ HUGGINGFACE_CO_URL_TEMPLATE = _HF_DEFAULT_STAGING_ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
+
+HUGGINGFACE_HEADER_X_REPO_COMMIT = "X-Repo-Commit"
+HUGGINGFACE_HEADER_X_LINKED_ETAG = "X-Linked-Etag"
+HUGGINGFACE_HEADER_X_LINKED_SIZE = "X-Linked-Size"
+HUGGINGFACE_HEADER_X_BILL_TO = "X-HF-Bill-To"
+
+INFERENCE_ENDPOINT = os.environ.get("HF_INFERENCE_ENDPOINT", "https://api-inference.huggingface.co")
+
+# See https://huggingface.co/docs/inference-endpoints/index
+INFERENCE_ENDPOINTS_ENDPOINT = "https://api.endpoints.huggingface.cloud/v2"
+INFERENCE_CATALOG_ENDPOINT = "https://endpoints.huggingface.co/api/catalog"
+
+# See https://api.endpoints.huggingface.cloud/#post-/v2/endpoint/-namespace-
+INFERENCE_ENDPOINT_IMAGE_KEYS = [
+ "custom",
+ "huggingface",
+ "huggingfaceNeuron",
+ "llamacpp",
+ "tei",
+ "tgi",
+ "tgiNeuron",
+]
+
+# Proxy for third-party providers
+INFERENCE_PROXY_TEMPLATE = "https://router.huggingface.co/{provider}"
+
+REPO_ID_SEPARATOR = "--"
+# ^ this substring is not allowed in repo_ids on hf.co
+# and is the canonical one we use for serialization of repo ids elsewhere.
+
+
+REPO_TYPE_DATASET = "dataset"
+REPO_TYPE_SPACE = "space"
+REPO_TYPE_MODEL = "model"
+REPO_TYPES = [None, REPO_TYPE_MODEL, REPO_TYPE_DATASET, REPO_TYPE_SPACE]
+SPACES_SDK_TYPES = ["gradio", "streamlit", "docker", "static"]
+
+REPO_TYPES_URL_PREFIXES = {
+ REPO_TYPE_DATASET: "datasets/",
+ REPO_TYPE_SPACE: "spaces/",
+}
+REPO_TYPES_MAPPING = {
+ "datasets": REPO_TYPE_DATASET,
+ "spaces": REPO_TYPE_SPACE,
+ "models": REPO_TYPE_MODEL,
+}
+
+DiscussionTypeFilter = Literal["all", "discussion", "pull_request"]
+DISCUSSION_TYPES: Tuple[DiscussionTypeFilter, ...] = typing.get_args(DiscussionTypeFilter)
+DiscussionStatusFilter = Literal["all", "open", "closed"]
+DISCUSSION_STATUS: Tuple[DiscussionTypeFilter, ...] = typing.get_args(DiscussionStatusFilter)
+
+# Webhook subscription types
+WEBHOOK_DOMAIN_T = Literal["repo", "discussions"]
+
+# default cache
+default_home = os.path.join(os.path.expanduser("~"), ".cache")
+HF_HOME = os.path.expandvars(
+ os.path.expanduser(
+ os.getenv(
+ "HF_HOME",
+ os.path.join(os.getenv("XDG_CACHE_HOME", default_home), "huggingface"),
+ )
+ )
+)
+hf_cache_home = HF_HOME # for backward compatibility. TODO: remove this in 1.0.0
+
+default_cache_path = os.path.join(HF_HOME, "hub")
+default_assets_cache_path = os.path.join(HF_HOME, "assets")
+
+# Legacy env variables
+HUGGINGFACE_HUB_CACHE = os.getenv("HUGGINGFACE_HUB_CACHE", default_cache_path)
+HUGGINGFACE_ASSETS_CACHE = os.getenv("HUGGINGFACE_ASSETS_CACHE", default_assets_cache_path)
+
+# New env variables
+HF_HUB_CACHE = os.path.expandvars(
+ os.path.expanduser(
+ os.getenv(
+ "HF_HUB_CACHE",
+ HUGGINGFACE_HUB_CACHE,
+ )
+ )
+)
+HF_ASSETS_CACHE = os.path.expandvars(
+ os.path.expanduser(
+ os.getenv(
+ "HF_ASSETS_CACHE",
+ HUGGINGFACE_ASSETS_CACHE,
+ )
+ )
+)
+
+HF_HUB_OFFLINE = _is_true(os.environ.get("HF_HUB_OFFLINE") or os.environ.get("TRANSFORMERS_OFFLINE"))
+
+# If set, log level will be set to DEBUG and all requests made to the Hub will be logged
+# as curl commands for reproducibility.
+HF_DEBUG = _is_true(os.environ.get("HF_DEBUG"))
+
+# Opt-out from telemetry requests
+HF_HUB_DISABLE_TELEMETRY = (
+ _is_true(os.environ.get("HF_HUB_DISABLE_TELEMETRY")) # HF-specific env variable
+ or _is_true(os.environ.get("DISABLE_TELEMETRY"))
+ or _is_true(os.environ.get("DO_NOT_TRACK")) # https://consoledonottrack.com/
+)
+
+HF_TOKEN_PATH = os.path.expandvars(
+ os.path.expanduser(
+ os.getenv(
+ "HF_TOKEN_PATH",
+ os.path.join(HF_HOME, "token"),
+ )
+ )
+)
+HF_STORED_TOKENS_PATH = os.path.join(os.path.dirname(HF_TOKEN_PATH), "stored_tokens")
+
+if _staging_mode:
+ # In staging mode, we use a different cache to ensure we don't mix up production and staging data or tokens
+ # In practice in `huggingface_hub` tests, we monkeypatch these values with temporary directories. The following
+ # lines are only used in third-party libraries tests (e.g. `transformers`, `diffusers`, etc.).
+ _staging_home = os.path.join(os.path.expanduser("~"), ".cache", "huggingface_staging")
+ HUGGINGFACE_HUB_CACHE = os.path.join(_staging_home, "hub")
+ HF_TOKEN_PATH = os.path.join(_staging_home, "token")
+
+# Here, `True` will disable progress bars globally without possibility of enabling it
+# programmatically. `False` will enable them without possibility of disabling them.
+# If environment variable is not set (None), then the user is free to enable/disable
+# them programmatically.
+# TL;DR: env variable has priority over code
+__HF_HUB_DISABLE_PROGRESS_BARS = os.environ.get("HF_HUB_DISABLE_PROGRESS_BARS")
+HF_HUB_DISABLE_PROGRESS_BARS: Optional[bool] = (
+ _is_true(__HF_HUB_DISABLE_PROGRESS_BARS) if __HF_HUB_DISABLE_PROGRESS_BARS is not None else None
+)
+
+# Disable warning on machines that do not support symlinks (e.g. Windows non-developer)
+HF_HUB_DISABLE_SYMLINKS_WARNING: bool = _is_true(os.environ.get("HF_HUB_DISABLE_SYMLINKS_WARNING"))
+
+# Disable warning when using experimental features
+HF_HUB_DISABLE_EXPERIMENTAL_WARNING: bool = _is_true(os.environ.get("HF_HUB_DISABLE_EXPERIMENTAL_WARNING"))
+
+# Disable sending the cached token by default is all HTTP requests to the Hub
+HF_HUB_DISABLE_IMPLICIT_TOKEN: bool = _is_true(os.environ.get("HF_HUB_DISABLE_IMPLICIT_TOKEN"))
+
+# Enable fast-download using external dependency "hf_transfer"
+# See:
+# - https://pypi.org/project/hf-transfer/
+# - https://github.com/huggingface/hf_transfer (private)
+HF_HUB_ENABLE_HF_TRANSFER: bool = _is_true(os.environ.get("HF_HUB_ENABLE_HF_TRANSFER"))
+
+
+# UNUSED
+# We don't use symlinks in local dir anymore.
+HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD: int = (
+ _as_int(os.environ.get("HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD")) or 5 * 1024 * 1024
+)
+
+# Used to override the etag timeout on a system level
+HF_HUB_ETAG_TIMEOUT: int = _as_int(os.environ.get("HF_HUB_ETAG_TIMEOUT")) or DEFAULT_ETAG_TIMEOUT
+
+# Used to override the get request timeout on a system level
+HF_HUB_DOWNLOAD_TIMEOUT: int = _as_int(os.environ.get("HF_HUB_DOWNLOAD_TIMEOUT")) or DEFAULT_DOWNLOAD_TIMEOUT
+
+# Allows to add information about the requester in the user-agent (eg. partner name)
+HF_HUB_USER_AGENT_ORIGIN: Optional[str] = os.environ.get("HF_HUB_USER_AGENT_ORIGIN")
+
+# List frameworks that are handled by the InferenceAPI service. Useful to scan endpoints and check which models are
+# deployed and running. Since 95% of the models are using the top 4 frameworks listed below, we scan only those by
+# default. We still keep the full list of supported frameworks in case we want to scan all of them.
+MAIN_INFERENCE_API_FRAMEWORKS = [
+ "diffusers",
+ "sentence-transformers",
+ "text-generation-inference",
+ "transformers",
+]
+
+ALL_INFERENCE_API_FRAMEWORKS = MAIN_INFERENCE_API_FRAMEWORKS + [
+ "adapter-transformers",
+ "allennlp",
+ "asteroid",
+ "bertopic",
+ "doctr",
+ "espnet",
+ "fairseq",
+ "fastai",
+ "fasttext",
+ "flair",
+ "k2",
+ "keras",
+ "mindspore",
+ "nemo",
+ "open_clip",
+ "paddlenlp",
+ "peft",
+ "pyannote-audio",
+ "sklearn",
+ "spacy",
+ "span-marker",
+ "speechbrain",
+ "stanza",
+ "timm",
+]
+
+# If OAuth didn't work after 2 redirects, there's likely a third-party cookie issue in the Space iframe view.
+# In this case, we redirect the user to the non-iframe view.
+OAUTH_MAX_REDIRECTS = 2
+
+# OAuth-related environment variables injected by the Space
+OAUTH_CLIENT_ID = os.environ.get("OAUTH_CLIENT_ID")
+OAUTH_CLIENT_SECRET = os.environ.get("OAUTH_CLIENT_SECRET")
+OAUTH_SCOPES = os.environ.get("OAUTH_SCOPES")
+OPENID_PROVIDER_URL = os.environ.get("OPENID_PROVIDER_URL")
+
+# Xet constants
+HUGGINGFACE_HEADER_X_XET_ENDPOINT = "X-Xet-Cas-Url"
+HUGGINGFACE_HEADER_X_XET_ACCESS_TOKEN = "X-Xet-Access-Token"
+HUGGINGFACE_HEADER_X_XET_EXPIRATION = "X-Xet-Token-Expiration"
+HUGGINGFACE_HEADER_X_XET_HASH = "X-Xet-Hash"
+HUGGINGFACE_HEADER_X_XET_REFRESH_ROUTE = "X-Xet-Refresh-Route"
+HUGGINGFACE_HEADER_LINK_XET_AUTH_KEY = "xet-auth"
+
+default_xet_cache_path = os.path.join(HF_HOME, "xet")
+HF_XET_CACHE = os.getenv("HF_XET_CACHE", default_xet_cache_path)
+HF_HUB_DISABLE_XET: bool = _is_true(os.environ.get("HF_HUB_DISABLE_XET"))
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/dataclasses.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/dataclasses.py
new file mode 100644
index 0000000000000000000000000000000000000000..636a0ac64b327448e6f8f56b10add54528071f29
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/dataclasses.py
@@ -0,0 +1,484 @@
+import inspect
+from dataclasses import _MISSING_TYPE, MISSING, Field, field, fields
+from functools import wraps
+from typing import (
+ Any,
+ Callable,
+ Dict,
+ ForwardRef,
+ List,
+ Literal,
+ Optional,
+ Tuple,
+ Type,
+ TypeVar,
+ Union,
+ get_args,
+ get_origin,
+ overload,
+)
+
+from .errors import (
+ StrictDataclassClassValidationError,
+ StrictDataclassDefinitionError,
+ StrictDataclassFieldValidationError,
+)
+
+
+Validator_T = Callable[[Any], None]
+T = TypeVar("T")
+
+
+# The overload decorator helps type checkers understand the different return types
+@overload
+def strict(cls: Type[T]) -> Type[T]: ...
+
+
+@overload
+def strict(*, accept_kwargs: bool = False) -> Callable[[Type[T]], Type[T]]: ...
+
+
+def strict(
+ cls: Optional[Type[T]] = None, *, accept_kwargs: bool = False
+) -> Union[Type[T], Callable[[Type[T]], Type[T]]]:
+ """
+ Decorator to add strict validation to a dataclass.
+
+ This decorator must be used on top of `@dataclass` to ensure IDEs and static typing tools
+ recognize the class as a dataclass.
+
+ Can be used with or without arguments:
+ - `@strict`
+ - `@strict(accept_kwargs=True)`
+
+ Args:
+ cls:
+ The class to convert to a strict dataclass.
+ accept_kwargs (`bool`, *optional*):
+ If True, allows arbitrary keyword arguments in `__init__`. Defaults to False.
+
+ Returns:
+ The enhanced dataclass with strict validation on field assignment.
+
+ Example:
+ ```py
+ >>> from dataclasses import dataclass
+ >>> from huggingface_hub.dataclasses import as_validated_field, strict, validated_field
+
+ >>> @as_validated_field
+ >>> def positive_int(value: int):
+ ... if not value >= 0:
+ ... raise ValueError(f"Value must be positive, got {value}")
+
+ >>> @strict(accept_kwargs=True)
+ ... @dataclass
+ ... class User:
+ ... name: str
+ ... age: int = positive_int(default=10)
+
+ # Initialize
+ >>> User(name="John")
+ User(name='John', age=10)
+
+ # Extra kwargs are accepted
+ >>> User(name="John", age=30, lastname="Doe")
+ User(name='John', age=30, *lastname='Doe')
+
+ # Invalid type => raises
+ >>> User(name="John", age="30")
+ huggingface_hub.errors.StrictDataclassFieldValidationError: Validation error for field 'age':
+ TypeError: Field 'age' expected int, got str (value: '30')
+
+ # Invalid value => raises
+ >>> User(name="John", age=-1)
+ huggingface_hub.errors.StrictDataclassFieldValidationError: Validation error for field 'age':
+ ValueError: Value must be positive, got -1
+ ```
+ """
+
+ def wrap(cls: Type[T]) -> Type[T]:
+ if not hasattr(cls, "__dataclass_fields__"):
+ raise StrictDataclassDefinitionError(
+ f"Class '{cls.__name__}' must be a dataclass before applying @strict."
+ )
+
+ # List and store validators
+ field_validators: Dict[str, List[Validator_T]] = {}
+ for f in fields(cls): # type: ignore [arg-type]
+ validators = []
+ validators.append(_create_type_validator(f))
+ custom_validator = f.metadata.get("validator")
+ if custom_validator is not None:
+ if not isinstance(custom_validator, list):
+ custom_validator = [custom_validator]
+ for validator in custom_validator:
+ if not _is_validator(validator):
+ raise StrictDataclassDefinitionError(
+ f"Invalid validator for field '{f.name}': {validator}. Must be a callable taking a single argument."
+ )
+ validators.extend(custom_validator)
+ field_validators[f.name] = validators
+ cls.__validators__ = field_validators # type: ignore
+
+ # Override __setattr__ to validate fields on assignment
+ original_setattr = cls.__setattr__
+
+ def __strict_setattr__(self: Any, name: str, value: Any) -> None:
+ """Custom __setattr__ method for strict dataclasses."""
+ # Run all validators
+ for validator in self.__validators__.get(name, []):
+ try:
+ validator(value)
+ except (ValueError, TypeError) as e:
+ raise StrictDataclassFieldValidationError(field=name, cause=e) from e
+
+ # If validation passed, set the attribute
+ original_setattr(self, name, value)
+
+ cls.__setattr__ = __strict_setattr__ # type: ignore[method-assign]
+
+ if accept_kwargs:
+ # (optional) Override __init__ to accept arbitrary keyword arguments
+ original_init = cls.__init__
+
+ @wraps(original_init)
+ def __init__(self, **kwargs: Any) -> None:
+ # Extract only the fields that are part of the dataclass
+ dataclass_fields = {f.name for f in fields(cls)} # type: ignore [arg-type]
+ standard_kwargs = {k: v for k, v in kwargs.items() if k in dataclass_fields}
+
+ # Call the original __init__ with standard fields
+ original_init(self, **standard_kwargs)
+
+ # Add any additional kwargs as attributes
+ for name, value in kwargs.items():
+ if name not in dataclass_fields:
+ self.__setattr__(name, value)
+
+ cls.__init__ = __init__ # type: ignore[method-assign]
+
+ # (optional) Override __repr__ to include additional kwargs
+ original_repr = cls.__repr__
+
+ @wraps(original_repr)
+ def __repr__(self) -> str:
+ # Call the original __repr__ to get the standard fields
+ standard_repr = original_repr(self)
+
+ # Get additional kwargs
+ additional_kwargs = [
+ # add a '*' in front of additional kwargs to let the user know they are not part of the dataclass
+ f"*{k}={v!r}"
+ for k, v in self.__dict__.items()
+ if k not in cls.__dataclass_fields__ # type: ignore [attr-defined]
+ ]
+ additional_repr = ", ".join(additional_kwargs)
+
+ # Combine both representations
+ return f"{standard_repr[:-1]}, {additional_repr})" if additional_kwargs else standard_repr
+
+ cls.__repr__ = __repr__ # type: ignore [method-assign]
+
+ # List all public methods starting with `validate_` => class validators.
+ class_validators = []
+
+ for name in dir(cls):
+ if not name.startswith("validate_"):
+ continue
+ method = getattr(cls, name)
+ if not callable(method):
+ continue
+ if len(inspect.signature(method).parameters) != 1:
+ raise StrictDataclassDefinitionError(
+ f"Class '{cls.__name__}' has a class validator '{name}' that takes more than one argument."
+ " Class validators must take only 'self' as an argument. Methods starting with 'validate_'"
+ " are considered to be class validators."
+ )
+ class_validators.append(method)
+
+ cls.__class_validators__ = class_validators # type: ignore [attr-defined]
+
+ # Add `validate` method to the class, but first check if it already exists
+ def validate(self: T) -> None:
+ """Run class validators on the instance."""
+ for validator in cls.__class_validators__: # type: ignore [attr-defined]
+ try:
+ validator(self)
+ except (ValueError, TypeError) as e:
+ raise StrictDataclassClassValidationError(validator=validator.__name__, cause=e) from e
+
+ # Hack to be able to raise if `.validate()` already exists except if it was created by this decorator on a parent class
+ # (in which case we just override it)
+ validate.__is_defined_by_strict_decorator__ = True # type: ignore [attr-defined]
+
+ if hasattr(cls, "validate"):
+ if not getattr(cls.validate, "__is_defined_by_strict_decorator__", False): # type: ignore [attr-defined]
+ raise StrictDataclassDefinitionError(
+ f"Class '{cls.__name__}' already implements a method called 'validate'."
+ " This method name is reserved when using the @strict decorator on a dataclass."
+ " If you want to keep your own method, please rename it."
+ )
+
+ cls.validate = validate # type: ignore
+
+ # Run class validators after initialization
+ initial_init = cls.__init__
+
+ @wraps(initial_init)
+ def init_with_validate(self, *args, **kwargs) -> None:
+ """Run class validators after initialization."""
+ initial_init(self, *args, **kwargs) # type: ignore [call-arg]
+ cls.validate(self) # type: ignore [attr-defined]
+
+ setattr(cls, "__init__", init_with_validate)
+
+ return cls
+
+ # Return wrapped class or the decorator itself
+ return wrap(cls) if cls is not None else wrap
+
+
+def validated_field(
+ validator: Union[List[Validator_T], Validator_T],
+ default: Union[Any, _MISSING_TYPE] = MISSING,
+ default_factory: Union[Callable[[], Any], _MISSING_TYPE] = MISSING,
+ init: bool = True,
+ repr: bool = True,
+ hash: Optional[bool] = None,
+ compare: bool = True,
+ metadata: Optional[Dict] = None,
+ **kwargs: Any,
+) -> Any:
+ """
+ Create a dataclass field with a custom validator.
+
+ Useful to apply several checks to a field. If only applying one rule, check out the [`as_validated_field`] decorator.
+
+ Args:
+ validator (`Callable` or `List[Callable]`):
+ A method that takes a value as input and raises ValueError/TypeError if the value is invalid.
+ Can be a list of validators to apply multiple checks.
+ **kwargs:
+ Additional arguments to pass to `dataclasses.field()`.
+
+ Returns:
+ A field with the validator attached in metadata
+ """
+ if not isinstance(validator, list):
+ validator = [validator]
+ if metadata is None:
+ metadata = {}
+ metadata["validator"] = validator
+ return field( # type: ignore
+ default=default, # type: ignore [arg-type]
+ default_factory=default_factory, # type: ignore [arg-type]
+ init=init,
+ repr=repr,
+ hash=hash,
+ compare=compare,
+ metadata=metadata,
+ **kwargs,
+ )
+
+
+def as_validated_field(validator: Validator_T):
+ """
+ Decorates a validator function as a [`validated_field`] (i.e. a dataclass field with a custom validator).
+
+ Args:
+ validator (`Callable`):
+ A method that takes a value as input and raises ValueError/TypeError if the value is invalid.
+ """
+
+ def _inner(
+ default: Union[Any, _MISSING_TYPE] = MISSING,
+ default_factory: Union[Callable[[], Any], _MISSING_TYPE] = MISSING,
+ init: bool = True,
+ repr: bool = True,
+ hash: Optional[bool] = None,
+ compare: bool = True,
+ metadata: Optional[Dict] = None,
+ **kwargs: Any,
+ ):
+ return validated_field(
+ validator,
+ default=default,
+ default_factory=default_factory,
+ init=init,
+ repr=repr,
+ hash=hash,
+ compare=compare,
+ metadata=metadata,
+ **kwargs,
+ )
+
+ return _inner
+
+
+def type_validator(name: str, value: Any, expected_type: Any) -> None:
+ """Validate that 'value' matches 'expected_type'."""
+ origin = get_origin(expected_type)
+ args = get_args(expected_type)
+
+ if expected_type is Any:
+ return
+ elif validator := _BASIC_TYPE_VALIDATORS.get(origin):
+ validator(name, value, args)
+ elif isinstance(expected_type, type): # simple types
+ _validate_simple_type(name, value, expected_type)
+ elif isinstance(expected_type, ForwardRef) or isinstance(expected_type, str):
+ return
+ else:
+ raise TypeError(f"Unsupported type for field '{name}': {expected_type}")
+
+
+def _validate_union(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate that value matches one of the types in a Union."""
+ errors = []
+ for t in args:
+ try:
+ type_validator(name, value, t)
+ return # Valid if any type matches
+ except TypeError as e:
+ errors.append(str(e))
+
+ raise TypeError(
+ f"Field '{name}' with value {repr(value)} doesn't match any type in {args}. Errors: {'; '.join(errors)}"
+ )
+
+
+def _validate_literal(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate Literal type."""
+ if value not in args:
+ raise TypeError(f"Field '{name}' expected one of {args}, got {value}")
+
+
+def _validate_list(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate List[T] type."""
+ if not isinstance(value, list):
+ raise TypeError(f"Field '{name}' expected a list, got {type(value).__name__}")
+
+ # Validate each item in the list
+ item_type = args[0]
+ for i, item in enumerate(value):
+ try:
+ type_validator(f"{name}[{i}]", item, item_type)
+ except TypeError as e:
+ raise TypeError(f"Invalid item at index {i} in list '{name}'") from e
+
+
+def _validate_dict(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate Dict[K, V] type."""
+ if not isinstance(value, dict):
+ raise TypeError(f"Field '{name}' expected a dict, got {type(value).__name__}")
+
+ # Validate keys and values
+ key_type, value_type = args
+ for k, v in value.items():
+ try:
+ type_validator(f"{name}.key", k, key_type)
+ type_validator(f"{name}[{k!r}]", v, value_type)
+ except TypeError as e:
+ raise TypeError(f"Invalid key or value in dict '{name}'") from e
+
+
+def _validate_tuple(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate Tuple type."""
+ if not isinstance(value, tuple):
+ raise TypeError(f"Field '{name}' expected a tuple, got {type(value).__name__}")
+
+ # Handle variable-length tuples: Tuple[T, ...]
+ if len(args) == 2 and args[1] is Ellipsis:
+ for i, item in enumerate(value):
+ try:
+ type_validator(f"{name}[{i}]", item, args[0])
+ except TypeError as e:
+ raise TypeError(f"Invalid item at index {i} in tuple '{name}'") from e
+ # Handle fixed-length tuples: Tuple[T1, T2, ...]
+ elif len(args) != len(value):
+ raise TypeError(f"Field '{name}' expected a tuple of length {len(args)}, got {len(value)}")
+ else:
+ for i, (item, expected) in enumerate(zip(value, args)):
+ try:
+ type_validator(f"{name}[{i}]", item, expected)
+ except TypeError as e:
+ raise TypeError(f"Invalid item at index {i} in tuple '{name}'") from e
+
+
+def _validate_set(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+ """Validate Set[T] type."""
+ if not isinstance(value, set):
+ raise TypeError(f"Field '{name}' expected a set, got {type(value).__name__}")
+
+ # Validate each item in the set
+ item_type = args[0]
+ for i, item in enumerate(value):
+ try:
+ type_validator(f"{name} item", item, item_type)
+ except TypeError as e:
+ raise TypeError(f"Invalid item in set '{name}'") from e
+
+
+def _validate_simple_type(name: str, value: Any, expected_type: type) -> None:
+ """Validate simple type (int, str, etc.)."""
+ if not isinstance(value, expected_type):
+ raise TypeError(
+ f"Field '{name}' expected {expected_type.__name__}, got {type(value).__name__} (value: {repr(value)})"
+ )
+
+
+def _create_type_validator(field: Field) -> Validator_T:
+ """Create a type validator function for a field."""
+ # Hacky: we cannot use a lambda here because of reference issues
+
+ def validator(value: Any) -> None:
+ type_validator(field.name, value, field.type)
+
+ return validator
+
+
+def _is_validator(validator: Any) -> bool:
+ """Check if a function is a validator.
+
+ A validator is a Callable that can be called with a single positional argument.
+ The validator can have more arguments with default values.
+
+ Basically, returns True if `validator(value)` is possible.
+ """
+ if not callable(validator):
+ return False
+
+ signature = inspect.signature(validator)
+ parameters = list(signature.parameters.values())
+ if len(parameters) == 0:
+ return False
+ if parameters[0].kind not in (
+ inspect.Parameter.POSITIONAL_OR_KEYWORD,
+ inspect.Parameter.POSITIONAL_ONLY,
+ inspect.Parameter.VAR_POSITIONAL,
+ ):
+ return False
+ for parameter in parameters[1:]:
+ if parameter.default == inspect.Parameter.empty:
+ return False
+ return True
+
+
+_BASIC_TYPE_VALIDATORS = {
+ Union: _validate_union,
+ Literal: _validate_literal,
+ list: _validate_list,
+ dict: _validate_dict,
+ tuple: _validate_tuple,
+ set: _validate_set,
+}
+
+
+__all__ = [
+ "strict",
+ "validated_field",
+ "Validator_T",
+ "StrictDataclassClassValidationError",
+ "StrictDataclassDefinitionError",
+ "StrictDataclassFieldValidationError",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/errors.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/errors.py
new file mode 100644
index 0000000000000000000000000000000000000000..e7cc5647ef02bade7f4eb81c93ca31825437af0e
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/errors.py
@@ -0,0 +1,379 @@
+"""Contains all custom errors."""
+
+from pathlib import Path
+from typing import Optional, Union
+
+from requests import HTTPError, Response
+
+
+# CACHE ERRORS
+
+
+class CacheNotFound(Exception):
+ """Exception thrown when the Huggingface cache is not found."""
+
+ cache_dir: Union[str, Path]
+
+ def __init__(self, msg: str, cache_dir: Union[str, Path], *args, **kwargs):
+ super().__init__(msg, *args, **kwargs)
+ self.cache_dir = cache_dir
+
+
+class CorruptedCacheException(Exception):
+ """Exception for any unexpected structure in the Huggingface cache-system."""
+
+
+# HEADERS ERRORS
+
+
+class LocalTokenNotFoundError(EnvironmentError):
+ """Raised if local token is required but not found."""
+
+
+# HTTP ERRORS
+
+
+class OfflineModeIsEnabled(ConnectionError):
+ """Raised when a request is made but `HF_HUB_OFFLINE=1` is set as environment variable."""
+
+
+class HfHubHTTPError(HTTPError):
+ """
+ HTTPError to inherit from for any custom HTTP Error raised in HF Hub.
+
+ Any HTTPError is converted at least into a `HfHubHTTPError`. If some information is
+ sent back by the server, it will be added to the error message.
+
+ Added details:
+ - Request ID sourced from headers in order of precedence: "X-Request-Id", "X-Amzn-Trace-Id", "X-Amz-Cf-Id".
+ - Server error message from the header "X-Error-Message".
+ - Server error message if we can found one in the response body.
+
+ Example:
+ ```py
+ import requests
+ from huggingface_hub.utils import get_session, hf_raise_for_status, HfHubHTTPError
+
+ response = get_session().post(...)
+ try:
+ hf_raise_for_status(response)
+ except HfHubHTTPError as e:
+ print(str(e)) # formatted message
+ e.request_id, e.server_message # details returned by server
+
+ # Complete the error message with additional information once it's raised
+ e.append_to_message("\n`create_commit` expects the repository to exist.")
+ raise
+ ```
+ """
+
+ def __init__(self, message: str, response: Optional[Response] = None, *, server_message: Optional[str] = None):
+ self.request_id = (
+ response.headers.get("x-request-id")
+ or response.headers.get("X-Amzn-Trace-Id")
+ or response.headers.get("x-amz-cf-id")
+ if response is not None
+ else None
+ )
+ self.server_message = server_message
+
+ super().__init__(
+ message,
+ response=response, # type: ignore [arg-type]
+ request=response.request if response is not None else None, # type: ignore [arg-type]
+ )
+
+ def append_to_message(self, additional_message: str) -> None:
+ """Append additional information to the `HfHubHTTPError` initial message."""
+ self.args = (self.args[0] + additional_message,) + self.args[1:]
+
+
+# INFERENCE CLIENT ERRORS
+
+
+class InferenceTimeoutError(HTTPError, TimeoutError):
+ """Error raised when a model is unavailable or the request times out."""
+
+
+# INFERENCE ENDPOINT ERRORS
+
+
+class InferenceEndpointError(Exception):
+ """Generic exception when dealing with Inference Endpoints."""
+
+
+class InferenceEndpointTimeoutError(InferenceEndpointError, TimeoutError):
+ """Exception for timeouts while waiting for Inference Endpoint."""
+
+
+# SAFETENSORS ERRORS
+
+
+class SafetensorsParsingError(Exception):
+ """Raised when failing to parse a safetensors file metadata.
+
+ This can be the case if the file is not a safetensors file or does not respect the specification.
+ """
+
+
+class NotASafetensorsRepoError(Exception):
+ """Raised when a repo is not a Safetensors repo i.e. doesn't have either a `model.safetensors` or a
+ `model.safetensors.index.json` file.
+ """
+
+
+# TEXT GENERATION ERRORS
+
+
+class TextGenerationError(HTTPError):
+ """Generic error raised if text-generation went wrong."""
+
+
+# Text Generation Inference Errors
+class ValidationError(TextGenerationError):
+ """Server-side validation error."""
+
+
+class GenerationError(TextGenerationError):
+ pass
+
+
+class OverloadedError(TextGenerationError):
+ pass
+
+
+class IncompleteGenerationError(TextGenerationError):
+ pass
+
+
+class UnknownError(TextGenerationError):
+ pass
+
+
+# VALIDATION ERRORS
+
+
+class HFValidationError(ValueError):
+ """Generic exception thrown by `huggingface_hub` validators.
+
+ Inherits from [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError).
+ """
+
+
+# FILE METADATA ERRORS
+
+
+class FileMetadataError(OSError):
+ """Error triggered when the metadata of a file on the Hub cannot be retrieved (missing ETag or commit_hash).
+
+ Inherits from `OSError` for backward compatibility.
+ """
+
+
+# REPOSITORY ERRORS
+
+
+class RepositoryNotFoundError(HfHubHTTPError):
+ """
+ Raised when trying to access a hf.co URL with an invalid repository name, or
+ with a private repo name the user does not have access to.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import model_info
+ >>> model_info("")
+ (...)
+ huggingface_hub.utils._errors.RepositoryNotFoundError: 401 Client Error. (Request ID: PvMw_VjBMjVdMz53WKIzP)
+
+ Repository Not Found for url: https://huggingface.co/api/models/%3Cnon_existent_repository%3E.
+ Please make sure you specified the correct `repo_id` and `repo_type`.
+ If the repo is private, make sure you are authenticated.
+ Invalid username or password.
+ ```
+ """
+
+
+class GatedRepoError(RepositoryNotFoundError):
+ """
+ Raised when trying to access a gated repository for which the user is not on the
+ authorized list.
+
+ Note: derives from `RepositoryNotFoundError` to ensure backward compatibility.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import model_info
+ >>> model_info("")
+ (...)
+ huggingface_hub.utils._errors.GatedRepoError: 403 Client Error. (Request ID: ViT1Bf7O_026LGSQuVqfa)
+
+ Cannot access gated repo for url https://huggingface.co/api/models/ardent-figment/gated-model.
+ Access to model ardent-figment/gated-model is restricted and you are not in the authorized list.
+ Visit https://huggingface.co/ardent-figment/gated-model to ask for access.
+ ```
+ """
+
+
+class DisabledRepoError(HfHubHTTPError):
+ """
+ Raised when trying to access a repository that has been disabled by its author.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import dataset_info
+ >>> dataset_info("laion/laion-art")
+ (...)
+ huggingface_hub.utils._errors.DisabledRepoError: 403 Client Error. (Request ID: Root=1-659fc3fa-3031673e0f92c71a2260dbe2;bc6f4dfb-b30a-4862-af0a-5cfe827610d8)
+
+ Cannot access repository for url https://huggingface.co/api/datasets/laion/laion-art.
+ Access to this resource is disabled.
+ ```
+ """
+
+
+# REVISION ERROR
+
+
+class RevisionNotFoundError(HfHubHTTPError):
+ """
+ Raised when trying to access a hf.co URL with a valid repository but an invalid
+ revision.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import hf_hub_download
+ >>> hf_hub_download('bert-base-cased', 'config.json', revision='')
+ (...)
+ huggingface_hub.utils._errors.RevisionNotFoundError: 404 Client Error. (Request ID: Mwhe_c3Kt650GcdKEFomX)
+
+ Revision Not Found for url: https://huggingface.co/bert-base-cased/resolve/%3Cnon-existent-revision%3E/config.json.
+ ```
+ """
+
+
+# ENTRY ERRORS
+class EntryNotFoundError(HfHubHTTPError):
+ """
+ Raised when trying to access a hf.co URL with a valid repository and revision
+ but an invalid filename.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import hf_hub_download
+ >>> hf_hub_download('bert-base-cased', '')
+ (...)
+ huggingface_hub.utils._errors.EntryNotFoundError: 404 Client Error. (Request ID: 53pNl6M0MxsnG5Sw8JA6x)
+
+ Entry Not Found for url: https://huggingface.co/bert-base-cased/resolve/main/%3Cnon-existent-file%3E.
+ ```
+ """
+
+
+class LocalEntryNotFoundError(EntryNotFoundError, FileNotFoundError, ValueError):
+ """
+ Raised when trying to access a file or snapshot that is not on the disk when network is
+ disabled or unavailable (connection issue). The entry may exist on the Hub.
+
+ Note: `ValueError` type is to ensure backward compatibility.
+ Note: `LocalEntryNotFoundError` derives from `HTTPError` because of `EntryNotFoundError`
+ even when it is not a network issue.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import hf_hub_download
+ >>> hf_hub_download('bert-base-cased', '', local_files_only=True)
+ (...)
+ huggingface_hub.utils._errors.LocalEntryNotFoundError: Cannot find the requested files in the disk cache and outgoing traffic has been disabled. To enable hf.co look-ups and downloads online, set 'local_files_only' to False.
+ ```
+ """
+
+ def __init__(self, message: str):
+ super().__init__(message, response=None)
+
+
+# REQUEST ERROR
+class BadRequestError(HfHubHTTPError, ValueError):
+ """
+ Raised by `hf_raise_for_status` when the server returns a HTTP 400 error.
+
+ Example:
+
+ ```py
+ >>> resp = requests.post("hf.co/api/check", ...)
+ >>> hf_raise_for_status(resp, endpoint_name="check")
+ huggingface_hub.utils._errors.BadRequestError: Bad request for check endpoint: {details} (Request ID: XXX)
+ ```
+ """
+
+
+# DDUF file format ERROR
+
+
+class DDUFError(Exception):
+ """Base exception for errors related to the DDUF format."""
+
+
+class DDUFCorruptedFileError(DDUFError):
+ """Exception thrown when the DDUF file is corrupted."""
+
+
+class DDUFExportError(DDUFError):
+ """Base exception for errors during DDUF export."""
+
+
+class DDUFInvalidEntryNameError(DDUFExportError):
+ """Exception thrown when the entry name is invalid."""
+
+
+# STRICT DATACLASSES ERRORS
+
+
+class StrictDataclassError(Exception):
+ """Base exception for strict dataclasses."""
+
+
+class StrictDataclassDefinitionError(StrictDataclassError):
+ """Exception thrown when a strict dataclass is defined incorrectly."""
+
+
+class StrictDataclassFieldValidationError(StrictDataclassError):
+ """Exception thrown when a strict dataclass fails validation for a given field."""
+
+ def __init__(self, field: str, cause: Exception):
+ error_message = f"Validation error for field '{field}':"
+ error_message += f"\n {cause.__class__.__name__}: {cause}"
+ super().__init__(error_message)
+
+
+class StrictDataclassClassValidationError(StrictDataclassError):
+ """Exception thrown when a strict dataclass fails validation on a class validator."""
+
+ def __init__(self, validator: str, cause: Exception):
+ error_message = f"Class validation error for validator '{validator}':"
+ error_message += f"\n {cause.__class__.__name__}: {cause}"
+ super().__init__(error_message)
+
+
+# XET ERRORS
+
+
+class XetError(Exception):
+ """Base exception for errors related to Xet Storage."""
+
+
+class XetAuthorizationError(XetError):
+ """Exception thrown when the user does not have the right authorization to use Xet Storage."""
+
+
+class XetRefreshTokenError(XetError):
+ """Exception thrown when the refresh token is invalid."""
+
+
+class XetDownloadError(Exception):
+ """Exception thrown when the download from Xet Storage fails."""
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..fc3b42323a251140aac813da24493918be267472
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/fastai_utils.py
@@ -0,0 +1,415 @@
+import json
+import os
+from pathlib import Path
+from pickle import DEFAULT_PROTOCOL, PicklingError
+from typing import Any, Dict, List, Optional, Union
+
+from packaging import version
+
+from huggingface_hub import constants, snapshot_download
+from huggingface_hub.hf_api import HfApi
+from huggingface_hub.utils import (
+ SoftTemporaryDirectory,
+ get_fastai_version,
+ get_fastcore_version,
+ get_python_version,
+)
+
+from .utils import logging, validate_hf_hub_args
+from .utils._runtime import _PY_VERSION # noqa: F401 # for backward compatibility...
+
+
+logger = logging.get_logger(__name__)
+
+
+def _check_fastai_fastcore_versions(
+ fastai_min_version: str = "2.4",
+ fastcore_min_version: str = "1.3.27",
+):
+ """
+ Checks that the installed fastai and fastcore versions are compatible for pickle serialization.
+
+ Args:
+ fastai_min_version (`str`, *optional*):
+ The minimum fastai version supported.
+ fastcore_min_version (`str`, *optional*):
+ The minimum fastcore version supported.
+
+ > [!TIP]
+ > Raises the following error:
+ >
+ > - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+ > if the fastai or fastcore libraries are not available or are of an invalid version.
+ """
+
+ if (get_fastcore_version() or get_fastai_version()) == "N/A":
+ raise ImportError(
+ f"fastai>={fastai_min_version} and fastcore>={fastcore_min_version} are"
+ f" required. Currently using fastai=={get_fastai_version()} and"
+ f" fastcore=={get_fastcore_version()}."
+ )
+
+ current_fastai_version = version.Version(get_fastai_version())
+ current_fastcore_version = version.Version(get_fastcore_version())
+
+ if current_fastai_version < version.Version(fastai_min_version):
+ raise ImportError(
+ "`push_to_hub_fastai` and `from_pretrained_fastai` require a"
+ f" fastai>={fastai_min_version} version, but you are using fastai version"
+ f" {get_fastai_version()} which is incompatible. Upgrade with `pip install"
+ " fastai==2.5.6`."
+ )
+
+ if current_fastcore_version < version.Version(fastcore_min_version):
+ raise ImportError(
+ "`push_to_hub_fastai` and `from_pretrained_fastai` require a"
+ f" fastcore>={fastcore_min_version} version, but you are using fastcore"
+ f" version {get_fastcore_version()} which is incompatible. Upgrade with"
+ " `pip install fastcore==1.3.27`."
+ )
+
+
+def _check_fastai_fastcore_pyproject_versions(
+ storage_folder: str,
+ fastai_min_version: str = "2.4",
+ fastcore_min_version: str = "1.3.27",
+):
+ """
+ Checks that the `pyproject.toml` file in the directory `storage_folder` has fastai and fastcore versions
+ that are compatible with `from_pretrained_fastai` and `push_to_hub_fastai`. If `pyproject.toml` does not exist
+ or does not contain versions for fastai and fastcore, then it logs a warning.
+
+ Args:
+ storage_folder (`str`):
+ Folder to look for the `pyproject.toml` file.
+ fastai_min_version (`str`, *optional*):
+ The minimum fastai version supported.
+ fastcore_min_version (`str`, *optional*):
+ The minimum fastcore version supported.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+ > if the `toml` module is not installed.
+ > - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+ > if the `pyproject.toml` indicates a lower than minimum supported version of fastai or fastcore.
+ """
+
+ try:
+ import toml
+ except ModuleNotFoundError:
+ raise ImportError(
+ "`push_to_hub_fastai` and `from_pretrained_fastai` require the toml module."
+ " Install it with `pip install toml`."
+ )
+
+ # Checks that a `pyproject.toml`, with `build-system` and `requires` sections, exists in the repository. If so, get a list of required packages.
+ if not os.path.isfile(f"{storage_folder}/pyproject.toml"):
+ logger.warning(
+ "There is no `pyproject.toml` in the repository that contains the fastai"
+ " `Learner`. The `pyproject.toml` would allow us to verify that your fastai"
+ " and fastcore versions are compatible with those of the model you want to"
+ " load."
+ )
+ return
+ pyproject_toml = toml.load(f"{storage_folder}/pyproject.toml")
+
+ if "build-system" not in pyproject_toml.keys():
+ logger.warning(
+ "There is no `build-system` section in the pyproject.toml of the repository"
+ " that contains the fastai `Learner`. The `build-system` would allow us to"
+ " verify that your fastai and fastcore versions are compatible with those"
+ " of the model you want to load."
+ )
+ return
+ build_system_toml = pyproject_toml["build-system"]
+
+ if "requires" not in build_system_toml.keys():
+ logger.warning(
+ "There is no `requires` section in the pyproject.toml of the repository"
+ " that contains the fastai `Learner`. The `requires` would allow us to"
+ " verify that your fastai and fastcore versions are compatible with those"
+ " of the model you want to load."
+ )
+ return
+ package_versions = build_system_toml["requires"]
+
+ # Extracts contains fastai and fastcore versions from `pyproject.toml` if available.
+ # If the package is specified but not the version (e.g. "fastai" instead of "fastai=2.4"), the default versions are the highest.
+ fastai_packages = [pck for pck in package_versions if pck.startswith("fastai")]
+ if len(fastai_packages) == 0:
+ logger.warning("The repository does not have a fastai version specified in the `pyproject.toml`.")
+ # fastai_version is an empty string if not specified
+ else:
+ fastai_version = str(fastai_packages[0]).partition("=")[2]
+ if fastai_version != "" and version.Version(fastai_version) < version.Version(fastai_min_version):
+ raise ImportError(
+ "`from_pretrained_fastai` requires"
+ f" fastai>={fastai_min_version} version but the model to load uses"
+ f" {fastai_version} which is incompatible."
+ )
+
+ fastcore_packages = [pck for pck in package_versions if pck.startswith("fastcore")]
+ if len(fastcore_packages) == 0:
+ logger.warning("The repository does not have a fastcore version specified in the `pyproject.toml`.")
+ # fastcore_version is an empty string if not specified
+ else:
+ fastcore_version = str(fastcore_packages[0]).partition("=")[2]
+ if fastcore_version != "" and version.Version(fastcore_version) < version.Version(fastcore_min_version):
+ raise ImportError(
+ "`from_pretrained_fastai` requires"
+ f" fastcore>={fastcore_min_version} version, but you are using fastcore"
+ f" version {fastcore_version} which is incompatible."
+ )
+
+
+README_TEMPLATE = """---
+tags:
+- fastai
+---
+
+# Amazing!
+
+🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
+
+# Some next steps
+1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
+
+2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([documentation here](https://huggingface.co/docs/hub/spaces)).
+
+3. Join the fastai community on the [Fastai Discord](https://discord.com/invite/YKrxeNn)!
+
+Greetings fellow fastlearner 🤝! Don't forget to delete this content from your model card.
+
+
+---
+
+
+# Model card
+
+## Model description
+More information needed
+
+## Intended uses & limitations
+More information needed
+
+## Training and evaluation data
+More information needed
+"""
+
+PYPROJECT_TEMPLATE = f"""[build-system]
+requires = ["setuptools>=40.8.0", "wheel", "python={get_python_version()}", "fastai={get_fastai_version()}", "fastcore={get_fastcore_version()}"]
+build-backend = "setuptools.build_meta:__legacy__"
+"""
+
+
+def _create_model_card(repo_dir: Path):
+ """
+ Creates a model card for the repository.
+
+ Args:
+ repo_dir (`Path`):
+ Directory where model card is created.
+ """
+ readme_path = repo_dir / "README.md"
+
+ if not readme_path.exists():
+ with readme_path.open("w", encoding="utf-8") as f:
+ f.write(README_TEMPLATE)
+
+
+def _create_model_pyproject(repo_dir: Path):
+ """
+ Creates a `pyproject.toml` for the repository.
+
+ Args:
+ repo_dir (`Path`):
+ Directory where `pyproject.toml` is created.
+ """
+ pyproject_path = repo_dir / "pyproject.toml"
+
+ if not pyproject_path.exists():
+ with pyproject_path.open("w", encoding="utf-8") as f:
+ f.write(PYPROJECT_TEMPLATE)
+
+
+def _save_pretrained_fastai(
+ learner,
+ save_directory: Union[str, Path],
+ config: Optional[Dict[str, Any]] = None,
+):
+ """
+ Saves a fastai learner to `save_directory` in pickle format using the default pickle protocol for the version of python used.
+
+ Args:
+ learner (`Learner`):
+ The `fastai.Learner` you'd like to save.
+ save_directory (`str` or `Path`):
+ Specific directory in which you want to save the fastai learner.
+ config (`dict`, *optional*):
+ Configuration object. Will be uploaded as a .json file. Example: 'https://huggingface.co/espejelomar/fastai-pet-breeds-classification/blob/main/config.json'.
+
+ > [!TIP]
+ > Raises the following error:
+ >
+ > - [`RuntimeError`](https://docs.python.org/3/library/exceptions.html#RuntimeError)
+ > if the config file provided is not a dictionary.
+ """
+ _check_fastai_fastcore_versions()
+
+ os.makedirs(save_directory, exist_ok=True)
+
+ # if the user provides config then we update it with the fastai and fastcore versions in CONFIG_TEMPLATE.
+ if config is not None:
+ if not isinstance(config, dict):
+ raise RuntimeError(f"Provided config should be a dict. Got: '{type(config)}'")
+ path = os.path.join(save_directory, constants.CONFIG_NAME)
+ with open(path, "w") as f:
+ json.dump(config, f)
+
+ _create_model_card(Path(save_directory))
+ _create_model_pyproject(Path(save_directory))
+
+ # learner.export saves the model in `self.path`.
+ learner.path = Path(save_directory)
+ os.makedirs(save_directory, exist_ok=True)
+ try:
+ learner.export(
+ fname="model.pkl",
+ pickle_protocol=DEFAULT_PROTOCOL,
+ )
+ except PicklingError:
+ raise PicklingError(
+ "You are using a lambda function, i.e., an anonymous function. `pickle`"
+ " cannot pickle function objects and requires that all functions have"
+ " names. One possible solution is to name the function."
+ )
+
+
+@validate_hf_hub_args
+def from_pretrained_fastai(
+ repo_id: str,
+ revision: Optional[str] = None,
+):
+ """
+ Load pretrained fastai model from the Hub or from a local directory.
+
+ Args:
+ repo_id (`str`):
+ The location where the pickled fastai.Learner is. It can be either of the two:
+ - Hosted on the Hugging Face Hub. E.g.: 'espejelomar/fatai-pet-breeds-classification' or 'distilgpt2'.
+ You can add a `revision` by appending `@` at the end of `repo_id`. E.g.: `dbmdz/bert-base-german-cased@main`.
+ Revision is the specific model version to use. Since we use a git-based system for storing models and other
+ artifacts on the Hugging Face Hub, it can be a branch name, a tag name, or a commit id.
+ - Hosted locally. `repo_id` would be a directory containing the pickle and a pyproject.toml
+ indicating the fastai and fastcore versions used to build the `fastai.Learner`. E.g.: `./my_model_directory/`.
+ revision (`str`, *optional*):
+ Revision at which the repo's files are downloaded. See documentation of `snapshot_download`.
+
+ Returns:
+ The `fastai.Learner` model in the `repo_id` repo.
+ """
+ _check_fastai_fastcore_versions()
+
+ # Load the `repo_id` repo.
+ # `snapshot_download` returns the folder where the model was stored.
+ # `cache_dir` will be the default '/root/.cache/huggingface/hub'
+ if not os.path.isdir(repo_id):
+ storage_folder = snapshot_download(
+ repo_id=repo_id,
+ revision=revision,
+ library_name="fastai",
+ library_version=get_fastai_version(),
+ )
+ else:
+ storage_folder = repo_id
+
+ _check_fastai_fastcore_pyproject_versions(storage_folder)
+
+ from fastai.learner import load_learner # type: ignore
+
+ return load_learner(os.path.join(storage_folder, "model.pkl"))
+
+
+@validate_hf_hub_args
+def push_to_hub_fastai(
+ learner,
+ *,
+ repo_id: str,
+ commit_message: str = "Push FastAI model using huggingface_hub.",
+ private: Optional[bool] = None,
+ token: Optional[str] = None,
+ config: Optional[dict] = None,
+ branch: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ api_endpoint: Optional[str] = None,
+):
+ """
+ Upload learner checkpoint files to the Hub.
+
+ Use `allow_patterns` and `ignore_patterns` to precisely filter which files should be pushed to the hub. Use
+ `delete_patterns` to delete existing remote files in the same commit. See [`upload_folder`] reference for more
+ details.
+
+ Args:
+ learner (`Learner`):
+ The `fastai.Learner' you'd like to push to the Hub.
+ repo_id (`str`):
+ The repository id for your model in Hub in the format of "namespace/repo_name". The namespace can be your individual account or an organization to which you have write access (for example, 'stanfordnlp/stanza-de').
+ commit_message (`str`, *optional*):
+ Message to commit while pushing. Will default to :obj:`"add model"`.
+ private (`bool`, *optional*):
+ Whether or not the repository created should be private.
+ If `None` (default), will default to been public except if the organization's default is private.
+ token (`str`, *optional*):
+ The Hugging Face account token to use as HTTP bearer authorization for remote files. If :obj:`None`, the token will be asked by a prompt.
+ config (`dict`, *optional*):
+ Configuration object to be saved alongside the model weights.
+ branch (`str`, *optional*):
+ The git branch on which to push the model. This defaults to
+ the default branch as specified in your repository, which
+ defaults to `"main"`.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request from `branch` with that commit.
+ Defaults to `False`.
+ api_endpoint (`str`, *optional*):
+ The API endpoint to use when pushing the model to the hub.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are pushed.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not pushed.
+ delete_patterns (`List[str]` or `str`, *optional*):
+ If provided, remote files matching any of the patterns will be deleted from the repo.
+
+ Returns:
+ The url of the commit of your model in the given repository.
+
+ > [!TIP]
+ > Raises the following error:
+ >
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if the user is not log on to the Hugging Face Hub.
+ """
+ _check_fastai_fastcore_versions()
+ api = HfApi(endpoint=api_endpoint)
+ repo_id = api.create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True).repo_id
+
+ # Push the files to the repo in a single commit
+ with SoftTemporaryDirectory() as tmp:
+ saved_path = Path(tmp) / repo_id
+ _save_pretrained_fastai(learner, saved_path, config=config)
+ return api.upload_folder(
+ repo_id=repo_id,
+ token=token,
+ folder_path=saved_path,
+ commit_message=commit_message,
+ revision=branch,
+ create_pr=create_pr,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ delete_patterns=delete_patterns,
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/file_download.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/file_download.py
new file mode 100644
index 0000000000000000000000000000000000000000..aff7236b4da41271e77a3cd58e84352904362ee9
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/file_download.py
@@ -0,0 +1,1820 @@
+import copy
+import errno
+import inspect
+import os
+import re
+import shutil
+import stat
+import time
+import uuid
+import warnings
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, BinaryIO, Dict, Literal, NoReturn, Optional, Tuple, Union
+from urllib.parse import quote, urlparse
+
+import requests
+
+from . import (
+ __version__, # noqa: F401 # for backward compatibility
+ constants,
+)
+from ._local_folder import get_local_download_paths, read_download_metadata, write_download_metadata
+from .constants import (
+ HUGGINGFACE_CO_URL_TEMPLATE, # noqa: F401 # for backward compatibility
+ HUGGINGFACE_HUB_CACHE, # noqa: F401 # for backward compatibility
+)
+from .errors import (
+ EntryNotFoundError,
+ FileMetadataError,
+ GatedRepoError,
+ HfHubHTTPError,
+ LocalEntryNotFoundError,
+ RepositoryNotFoundError,
+ RevisionNotFoundError,
+)
+from .utils import (
+ OfflineModeIsEnabled,
+ SoftTemporaryDirectory,
+ WeakFileLock,
+ XetFileData,
+ build_hf_headers,
+ get_fastai_version, # noqa: F401 # for backward compatibility
+ get_fastcore_version, # noqa: F401 # for backward compatibility
+ get_graphviz_version, # noqa: F401 # for backward compatibility
+ get_jinja_version, # noqa: F401 # for backward compatibility
+ get_pydot_version, # noqa: F401 # for backward compatibility
+ get_tf_version, # noqa: F401 # for backward compatibility
+ get_torch_version, # noqa: F401 # for backward compatibility
+ hf_raise_for_status,
+ is_fastai_available, # noqa: F401 # for backward compatibility
+ is_fastcore_available, # noqa: F401 # for backward compatibility
+ is_graphviz_available, # noqa: F401 # for backward compatibility
+ is_jinja_available, # noqa: F401 # for backward compatibility
+ is_pydot_available, # noqa: F401 # for backward compatibility
+ is_tf_available, # noqa: F401 # for backward compatibility
+ is_torch_available, # noqa: F401 # for backward compatibility
+ logging,
+ parse_xet_file_data_from_response,
+ refresh_xet_connection_info,
+ reset_sessions,
+ tqdm,
+ validate_hf_hub_args,
+)
+from .utils._http import _adjust_range_header, http_backoff
+from .utils._runtime import _PY_VERSION, is_xet_available # noqa: F401 # for backward compatibility
+from .utils._typing import HTTP_METHOD_T
+from .utils.sha import sha_fileobj
+from .utils.tqdm import _get_progress_bar_context
+
+
+logger = logging.get_logger(__name__)
+
+# Return value when trying to load a file from cache but the file does not exist in the distant repo.
+_CACHED_NO_EXIST = object()
+_CACHED_NO_EXIST_T = Any
+
+# Regex to get filename from a "Content-Disposition" header for CDN-served files
+HEADER_FILENAME_PATTERN = re.compile(r'filename="(?P.*?)";')
+
+# Regex to check if the revision IS directly a commit_hash
+REGEX_COMMIT_HASH = re.compile(r"^[0-9a-f]{40}$")
+
+# Regex to check if the file etag IS a valid sha256
+REGEX_SHA256 = re.compile(r"^[0-9a-f]{64}$")
+
+_are_symlinks_supported_in_dir: Dict[str, bool] = {}
+
+
+def are_symlinks_supported(cache_dir: Union[str, Path, None] = None) -> bool:
+ """Return whether the symlinks are supported on the machine.
+
+ Since symlinks support can change depending on the mounted disk, we need to check
+ on the precise cache folder. By default, the default HF cache directory is checked.
+
+ Args:
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+
+ Returns: [bool] Whether symlinks are supported in the directory.
+ """
+ # Defaults to HF cache
+ if cache_dir is None:
+ cache_dir = constants.HF_HUB_CACHE
+ cache_dir = str(Path(cache_dir).expanduser().resolve()) # make it unique
+
+ # Check symlink compatibility only once (per cache directory) at first time use
+ if cache_dir not in _are_symlinks_supported_in_dir:
+ _are_symlinks_supported_in_dir[cache_dir] = True
+
+ os.makedirs(cache_dir, exist_ok=True)
+ with SoftTemporaryDirectory(dir=cache_dir) as tmpdir:
+ src_path = Path(tmpdir) / "dummy_file_src"
+ src_path.touch()
+ dst_path = Path(tmpdir) / "dummy_file_dst"
+
+ # Relative source path as in `_create_symlink``
+ relative_src = os.path.relpath(src_path, start=os.path.dirname(dst_path))
+ try:
+ os.symlink(relative_src, dst_path)
+ except OSError:
+ # Likely running on Windows
+ _are_symlinks_supported_in_dir[cache_dir] = False
+
+ if not constants.HF_HUB_DISABLE_SYMLINKS_WARNING:
+ message = (
+ "`huggingface_hub` cache-system uses symlinks by default to"
+ " efficiently store duplicated files but your machine does not"
+ f" support them in {cache_dir}. Caching files will still work"
+ " but in a degraded version that might require more space on"
+ " your disk. This warning can be disabled by setting the"
+ " `HF_HUB_DISABLE_SYMLINKS_WARNING` environment variable. For"
+ " more details, see"
+ " https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations."
+ )
+ if os.name == "nt":
+ message += (
+ "\nTo support symlinks on Windows, you either need to"
+ " activate Developer Mode or to run Python as an"
+ " administrator. In order to activate developer mode,"
+ " see this article:"
+ " https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development"
+ )
+ warnings.warn(message)
+
+ return _are_symlinks_supported_in_dir[cache_dir]
+
+
+@dataclass(frozen=True)
+class HfFileMetadata:
+ """Data structure containing information about a file versioned on the Hub.
+
+ Returned by [`get_hf_file_metadata`] based on a URL.
+
+ Args:
+ commit_hash (`str`, *optional*):
+ The commit_hash related to the file.
+ etag (`str`, *optional*):
+ Etag of the file on the server.
+ location (`str`):
+ Location where to download the file. Can be a Hub url or not (CDN).
+ size (`size`):
+ Size of the file. In case of an LFS file, contains the size of the actual
+ LFS file, not the pointer.
+ xet_file_data (`XetFileData`, *optional*):
+ Xet information for the file. This is only set if the file is stored using Xet storage.
+ """
+
+ commit_hash: Optional[str]
+ etag: Optional[str]
+ location: str
+ size: Optional[int]
+ xet_file_data: Optional[XetFileData]
+
+
+@validate_hf_hub_args
+def hf_hub_url(
+ repo_id: str,
+ filename: str,
+ *,
+ subfolder: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ endpoint: Optional[str] = None,
+) -> str:
+ """Construct the URL of a file from the given information.
+
+ The resolved address can either be a huggingface.co-hosted url, or a link to
+ Cloudfront (a Content Delivery Network, or CDN) for large files which are
+ more than a few MBs.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) name and a repo name separated
+ by a `/`.
+ filename (`str`):
+ The name of the file in the repo.
+ subfolder (`str`, *optional*):
+ An optional value corresponding to a folder inside the repo.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+ `None` or `"model"` if downloading from a model. Default is `None`.
+ revision (`str`, *optional*):
+ An optional Git revision id which can be a branch name, a tag, or a
+ commit hash.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import hf_hub_url
+
+ >>> hf_hub_url(
+ ... repo_id="julien-c/EsperBERTo-small", filename="pytorch_model.bin"
+ ... )
+ 'https://huggingface.co/julien-c/EsperBERTo-small/resolve/main/pytorch_model.bin'
+ ```
+
+ > [!TIP]
+ > Notes:
+ >
+ > Cloudfront is replicated over the globe so downloads are way faster for
+ > the end user (and it also lowers our bandwidth costs).
+ >
+ > Cloudfront aggressively caches files by default (default TTL is 24
+ > hours), however this is not an issue here because we implement a
+ > git-based versioning system on huggingface.co, which means that we store
+ > the files on S3/Cloudfront in a content-addressable way (i.e., the file
+ > name is its hash). Using content-addressable filenames means cache can't
+ > ever be stale.
+ >
+ > In terms of client-side caching from this library, we base our caching
+ > on the objects' entity tag (`ETag`), which is an identifier of a
+ > specific version of a resource [1]_. An object's ETag is: its git-sha1
+ > if stored in git, or its sha256 if stored in git-lfs.
+
+ References:
+
+ - [1] https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/ETag
+ """
+ if subfolder == "":
+ subfolder = None
+ if subfolder is not None:
+ filename = f"{subfolder}/{filename}"
+
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError("Invalid repo type")
+
+ if repo_type in constants.REPO_TYPES_URL_PREFIXES:
+ repo_id = constants.REPO_TYPES_URL_PREFIXES[repo_type] + repo_id
+
+ if revision is None:
+ revision = constants.DEFAULT_REVISION
+ url = HUGGINGFACE_CO_URL_TEMPLATE.format(
+ repo_id=repo_id, revision=quote(revision, safe=""), filename=quote(filename)
+ )
+ # Update endpoint if provided
+ if endpoint is not None and url.startswith(constants.ENDPOINT):
+ url = endpoint + url[len(constants.ENDPOINT) :]
+ return url
+
+
+def _request_wrapper(
+ method: HTTP_METHOD_T, url: str, *, follow_relative_redirects: bool = False, **params
+) -> requests.Response:
+ """Wrapper around requests methods to follow relative redirects if `follow_relative_redirects=True` even when
+ `allow_redirection=False`.
+
+ A backoff mechanism retries the HTTP call on 5xx errors and network errors.
+
+ Args:
+ method (`str`):
+ HTTP method, such as 'GET' or 'HEAD'.
+ url (`str`):
+ The URL of the resource to fetch.
+ follow_relative_redirects (`bool`, *optional*, defaults to `False`)
+ If True, relative redirection (redirection to the same site) will be resolved even when `allow_redirection`
+ kwarg is set to False. Useful when we want to follow a redirection to a renamed repository without
+ following redirection to a CDN.
+ **params (`dict`, *optional*):
+ Params to pass to `requests.request`.
+ """
+ # Recursively follow relative redirects
+ if follow_relative_redirects:
+ response = _request_wrapper(
+ method=method,
+ url=url,
+ follow_relative_redirects=False,
+ **params,
+ )
+
+ # If redirection, we redirect only relative paths.
+ # This is useful in case of a renamed repository.
+ if 300 <= response.status_code <= 399:
+ parsed_target = urlparse(response.headers["Location"])
+ if parsed_target.netloc == "":
+ # This means it is a relative 'location' headers, as allowed by RFC 7231.
+ # (e.g. '/path/to/resource' instead of 'http://domain.tld/path/to/resource')
+ # We want to follow this relative redirect !
+ #
+ # Highly inspired by `resolve_redirects` from requests library.
+ # See https://github.com/psf/requests/blob/main/requests/sessions.py#L159
+ next_url = urlparse(url)._replace(path=parsed_target.path).geturl()
+ return _request_wrapper(method=method, url=next_url, follow_relative_redirects=True, **params)
+ return response
+
+ # Perform request and return if status_code is not in the retry list.
+ response = http_backoff(method=method, url=url, **params)
+ hf_raise_for_status(response)
+ return response
+
+
+def _get_file_length_from_http_response(response: requests.Response) -> Optional[int]:
+ """
+ Get the length of the file from the HTTP response headers.
+
+ This function extracts the file size from the HTTP response headers, either from the
+ `Content-Range` or `Content-Length` header, if available (in that order).
+
+ Args:
+ response (`requests.Response`):
+ The HTTP response object.
+
+ Returns:
+ `int` or `None`: The length of the file in bytes, or None if not available.
+ """
+
+ # If HTTP response contains compressed body (e.g. gzip), the `Content-Length` header will
+ # contain the length of the compressed body, not the uncompressed file size.
+ # And at the start of transmission there's no way to know the uncompressed file size for gzip,
+ # thus we return None in that case.
+ content_encoding = response.headers.get("Content-Encoding", "identity").lower()
+ if content_encoding != "identity":
+ # gzip/br/deflate/zstd etc
+ return None
+
+ content_range = response.headers.get("Content-Range")
+ if content_range is not None:
+ return int(content_range.rsplit("/")[-1])
+
+ content_length = response.headers.get("Content-Length")
+ if content_length is not None:
+ return int(content_length)
+
+ return None
+
+
+def http_get(
+ url: str,
+ temp_file: BinaryIO,
+ *,
+ proxies: Optional[Dict] = None,
+ resume_size: int = 0,
+ headers: Optional[Dict[str, Any]] = None,
+ expected_size: Optional[int] = None,
+ displayed_filename: Optional[str] = None,
+ _nb_retries: int = 5,
+ _tqdm_bar: Optional[tqdm] = None,
+) -> None:
+ """
+ Download a remote file. Do not gobble up errors, and will return errors tailored to the Hugging Face Hub.
+
+ If ConnectionError (SSLError) or ReadTimeout happen while streaming data from the server, it is most likely a
+ transient error (network outage?). We log a warning message and try to resume the download a few times before
+ giving up. The method gives up after 5 attempts if no new data has being received from the server.
+
+ Args:
+ url (`str`):
+ The URL of the file to download.
+ temp_file (`BinaryIO`):
+ The file-like object where to save the file.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to `requests.request`.
+ resume_size (`int`, *optional*):
+ The number of bytes already downloaded. If set to 0 (default), the whole file is download. If set to a
+ positive number, the download will resume at the given position.
+ headers (`dict`, *optional*):
+ Dictionary of HTTP Headers to send with the request.
+ expected_size (`int`, *optional*):
+ The expected size of the file to download. If set, the download will raise an error if the size of the
+ received content is different from the expected one.
+ displayed_filename (`str`, *optional*):
+ The filename of the file that is being downloaded. Value is used only to display a nice progress bar. If
+ not set, the filename is guessed from the URL or the `Content-Disposition` header.
+ """
+ if expected_size is not None and resume_size == expected_size:
+ # If the file is already fully downloaded, we don't need to download it again.
+ return
+
+ has_custom_range_header = headers is not None and any(h.lower() == "range" for h in headers)
+ hf_transfer = None
+ if constants.HF_HUB_ENABLE_HF_TRANSFER:
+ if resume_size != 0:
+ warnings.warn("'hf_transfer' does not support `resume_size`: falling back to regular download method")
+ elif proxies is not None:
+ warnings.warn("'hf_transfer' does not support `proxies`: falling back to regular download method")
+ elif has_custom_range_header:
+ warnings.warn("'hf_transfer' ignores custom 'Range' headers; falling back to regular download method")
+ else:
+ try:
+ import hf_transfer # type: ignore[no-redef]
+ except ImportError:
+ raise ValueError(
+ "Fast download using 'hf_transfer' is enabled"
+ " (HF_HUB_ENABLE_HF_TRANSFER=1) but 'hf_transfer' package is not"
+ " available in your environment. Try `pip install hf_transfer`."
+ )
+
+ initial_headers = headers
+ headers = copy.deepcopy(headers) or {}
+ if resume_size > 0:
+ headers["Range"] = _adjust_range_header(headers.get("Range"), resume_size)
+ elif expected_size and expected_size > constants.MAX_HTTP_DOWNLOAD_SIZE:
+ # Any files over 50GB will not be available through basic http request.
+ # Setting the range header to 0-0 will force the server to return the file size in the Content-Range header.
+ # Since hf_transfer splits the download into chunks, the process will succeed afterwards.
+ if hf_transfer:
+ headers["Range"] = "bytes=0-0"
+ else:
+ raise ValueError(
+ "The file is too large to be downloaded using the regular download method. Use `hf_transfer` or `hf_xet` instead."
+ " Try `pip install hf_transfer` or `pip install hf_xet`."
+ )
+
+ r = _request_wrapper(
+ method="GET", url=url, stream=True, proxies=proxies, headers=headers, timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT
+ )
+ hf_raise_for_status(r)
+
+ # If we requested a Range but got 200 back, the server ignored our Range header
+ # (e.g. CloudFront with Accept-Encoding: gzip). Reset file to avoid corruption.
+ if resume_size > 0 and r.status_code == 200:
+ temp_file.seek(0)
+ temp_file.truncate()
+ resume_size = 0
+
+ total: Optional[int] = _get_file_length_from_http_response(r)
+
+ if displayed_filename is None:
+ displayed_filename = url
+ content_disposition = r.headers.get("Content-Disposition")
+ if content_disposition is not None:
+ match = HEADER_FILENAME_PATTERN.search(content_disposition)
+ if match is not None:
+ # Means file is on CDN
+ displayed_filename = match.groupdict()["filename"]
+
+ # Truncate filename if too long to display
+ if len(displayed_filename) > 40:
+ displayed_filename = f"(…){displayed_filename[-40:]}"
+
+ consistency_error_message = (
+ f"Consistency check failed: file should be of size {expected_size} but has size"
+ f" {{actual_size}} ({displayed_filename}).\nThis is usually due to network issues while downloading the file."
+ " Please retry with `force_download=True`."
+ )
+ progress_cm = _get_progress_bar_context(
+ desc=displayed_filename,
+ log_level=logger.getEffectiveLevel(),
+ total=total,
+ initial=resume_size,
+ name="huggingface_hub.http_get",
+ _tqdm_bar=_tqdm_bar,
+ )
+
+ with progress_cm as progress:
+ if hf_transfer and total is not None and total > 5 * constants.DOWNLOAD_CHUNK_SIZE:
+ supports_callback = "callback" in inspect.signature(hf_transfer.download).parameters
+ if not supports_callback:
+ warnings.warn(
+ "You are using an outdated version of `hf_transfer`. "
+ "Consider upgrading to latest version to enable progress bars "
+ "using `pip install -U hf_transfer`."
+ )
+ try:
+ hf_transfer.download(
+ url=url,
+ filename=temp_file.name,
+ max_files=constants.HF_TRANSFER_CONCURRENCY,
+ chunk_size=constants.DOWNLOAD_CHUNK_SIZE,
+ headers=initial_headers,
+ parallel_failures=3,
+ max_retries=5,
+ **({"callback": progress.update} if supports_callback else {}),
+ )
+ except Exception as e:
+ raise RuntimeError(
+ "An error occurred while downloading using `hf_transfer`. Consider"
+ " disabling HF_HUB_ENABLE_HF_TRANSFER for better error handling."
+ ) from e
+ if not supports_callback:
+ progress.update(total)
+ if expected_size is not None and expected_size != os.path.getsize(temp_file.name):
+ raise EnvironmentError(
+ consistency_error_message.format(
+ actual_size=os.path.getsize(temp_file.name),
+ )
+ )
+ return
+ new_resume_size = resume_size
+ try:
+ for chunk in r.iter_content(chunk_size=constants.DOWNLOAD_CHUNK_SIZE):
+ if chunk: # filter out keep-alive new chunks
+ progress.update(len(chunk))
+ temp_file.write(chunk)
+ new_resume_size += len(chunk)
+ # Some data has been downloaded from the server so we reset the number of retries.
+ _nb_retries = 5
+ except (requests.ConnectionError, requests.ReadTimeout) as e:
+ # If ConnectionError (SSLError) or ReadTimeout happen while streaming data from the server, it is most likely
+ # a transient error (network outage?). We log a warning message and try to resume the download a few times
+ # before giving up. Tre retry mechanism is basic but should be enough in most cases.
+ if _nb_retries <= 0:
+ logger.warning("Error while downloading from %s: %s\nMax retries exceeded.", url, str(e))
+ raise
+ logger.warning("Error while downloading from %s: %s\nTrying to resume download...", url, str(e))
+ time.sleep(1)
+ reset_sessions() # In case of SSLError it's best to reset the shared requests.Session objects
+ return http_get(
+ url=url,
+ temp_file=temp_file,
+ proxies=proxies,
+ resume_size=new_resume_size,
+ headers=initial_headers,
+ expected_size=expected_size,
+ _nb_retries=_nb_retries - 1,
+ _tqdm_bar=_tqdm_bar,
+ )
+
+ if expected_size is not None and expected_size != temp_file.tell():
+ raise EnvironmentError(
+ consistency_error_message.format(
+ actual_size=temp_file.tell(),
+ )
+ )
+
+
+def xet_get(
+ *,
+ incomplete_path: Path,
+ xet_file_data: XetFileData,
+ headers: Dict[str, str],
+ expected_size: Optional[int] = None,
+ displayed_filename: Optional[str] = None,
+ _tqdm_bar: Optional[tqdm] = None,
+) -> None:
+ """
+ Download a file using Xet storage service.
+
+ Args:
+ incomplete_path (`Path`):
+ The path to the file to download.
+ xet_file_data (`XetFileData`):
+ The file metadata needed to make the request to the xet storage service.
+ headers (`Dict[str, str]`):
+ The headers to send to the xet storage service.
+ expected_size (`int`, *optional*):
+ The expected size of the file to download. If set, the download will raise an error if the size of the
+ received content is different from the expected one.
+ displayed_filename (`str`, *optional*):
+ The filename of the file that is being downloaded. Value is used only to display a nice progress bar. If
+ not set, the filename is guessed from the URL or the `Content-Disposition` header.
+
+ **How it works:**
+ The file download system uses Xet storage, which is a content-addressable storage system that breaks files into chunks
+ for efficient storage and transfer.
+
+ `hf_xet.download_files` manages downloading files by:
+ - Taking a list of files to download (each with its unique content hash)
+ - Connecting to a storage server (CAS server) that knows how files are chunked
+ - Using authentication to ensure secure access
+ - Providing progress updates during download
+
+ Authentication works by regularly refreshing access tokens through `refresh_xet_connection_info` to maintain a valid
+ connection to the storage server.
+
+ The download process works like this:
+ 1. Create a local cache folder at `~/.cache/huggingface/xet/chunk-cache` to store reusable file chunks
+ 2. Download files in parallel:
+ 2.1. Prepare to write the file to disk
+ 2.2. Ask the server "how is this file split into chunks?" using the file's unique hash
+ The server responds with:
+ - Which chunks make up the complete file
+ - Where each chunk can be downloaded from
+ 2.3. For each needed chunk:
+ - Checks if we already have it in our local cache
+ - If not, download it from cloud storage (S3)
+ - Save it to cache for future use
+ - Assemble the chunks in order to recreate the original file
+
+ """
+ try:
+ from hf_xet import PyXetDownloadInfo, download_files # type: ignore[no-redef]
+ except ImportError:
+ raise ValueError(
+ "To use optimized download using Xet storage, you need to install the hf_xet package. "
+ 'Try `pip install "huggingface_hub[hf_xet]"` or `pip install hf_xet`.'
+ )
+
+ connection_info = refresh_xet_connection_info(file_data=xet_file_data, headers=headers)
+
+ def token_refresher() -> Tuple[str, int]:
+ connection_info = refresh_xet_connection_info(file_data=xet_file_data, headers=headers)
+ if connection_info is None:
+ raise ValueError("Failed to refresh token using xet metadata.")
+ return connection_info.access_token, connection_info.expiration_unix_epoch
+
+ xet_download_info = [
+ PyXetDownloadInfo(
+ destination_path=str(incomplete_path.absolute()), hash=xet_file_data.file_hash, file_size=expected_size
+ )
+ ]
+
+ if not displayed_filename:
+ displayed_filename = incomplete_path.name
+
+ # Truncate filename if too long to display
+ if len(displayed_filename) > 40:
+ displayed_filename = f"{displayed_filename[:40]}(…)"
+
+ progress_cm = _get_progress_bar_context(
+ desc=displayed_filename,
+ log_level=logger.getEffectiveLevel(),
+ total=expected_size,
+ initial=0,
+ name="huggingface_hub.xet_get",
+ _tqdm_bar=_tqdm_bar,
+ )
+
+ with progress_cm as progress:
+
+ def progress_updater(progress_bytes: float):
+ progress.update(progress_bytes)
+
+ download_files(
+ xet_download_info,
+ endpoint=connection_info.endpoint,
+ token_info=(connection_info.access_token, connection_info.expiration_unix_epoch),
+ token_refresher=token_refresher,
+ progress_updater=[progress_updater],
+ )
+
+
+def _normalize_etag(etag: Optional[str]) -> Optional[str]:
+ """Normalize ETag HTTP header, so it can be used to create nice filepaths.
+
+ The HTTP spec allows two forms of ETag:
+ ETag: W/""
+ ETag: ""
+
+ For now, we only expect the second form from the server, but we want to be future-proof so we support both. For
+ more context, see `TestNormalizeEtag` tests and https://github.com/huggingface/huggingface_hub/pull/1428.
+
+ Args:
+ etag (`str`, *optional*): HTTP header
+
+ Returns:
+ `str` or `None`: string that can be used as a nice directory name.
+ Returns `None` if input is None.
+ """
+ if etag is None:
+ return None
+ return etag.lstrip("W/").strip('"')
+
+
+def _create_relative_symlink(src: str, dst: str, new_blob: bool = False) -> None:
+ """Alias method used in `transformers` conversion script."""
+ return _create_symlink(src=src, dst=dst, new_blob=new_blob)
+
+
+def _create_symlink(src: str, dst: str, new_blob: bool = False) -> None:
+ """Create a symbolic link named dst pointing to src.
+
+ By default, it will try to create a symlink using a relative path. Relative paths have 2 advantages:
+ - If the cache_folder is moved (example: back-up on a shared drive), relative paths within the cache folder will
+ not break.
+ - Relative paths seems to be better handled on Windows. Issue was reported 3 times in less than a week when
+ changing from relative to absolute paths. See https://github.com/huggingface/huggingface_hub/issues/1398,
+ https://github.com/huggingface/diffusers/issues/2729 and https://github.com/huggingface/transformers/pull/22228.
+ NOTE: The issue with absolute paths doesn't happen on admin mode.
+ When creating a symlink from the cache to a local folder, it is possible that a relative path cannot be created.
+ This happens when paths are not on the same volume. In that case, we use absolute paths.
+
+
+ The result layout looks something like
+ └── [ 128] snapshots
+ ├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f
+ │ ├── [ 52] README.md -> ../../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812
+ │ └── [ 76] pytorch_model.bin -> ../../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+
+ If symlinks cannot be created on this platform (most likely to be Windows), the workaround is to avoid symlinks by
+ having the actual file in `dst`. If it is a new file (`new_blob=True`), we move it to `dst`. If it is not a new file
+ (`new_blob=False`), we don't know if the blob file is already referenced elsewhere. To avoid breaking existing
+ cache, the file is duplicated on the disk.
+
+ In case symlinks are not supported, a warning message is displayed to the user once when loading `huggingface_hub`.
+ The warning message can be disabled with the `DISABLE_SYMLINKS_WARNING` environment variable.
+ """
+ try:
+ os.remove(dst)
+ except OSError:
+ pass
+
+ abs_src = os.path.abspath(os.path.expanduser(src))
+ abs_dst = os.path.abspath(os.path.expanduser(dst))
+ abs_dst_folder = os.path.dirname(abs_dst)
+
+ # Use relative_dst in priority
+ try:
+ relative_src = os.path.relpath(abs_src, abs_dst_folder)
+ except ValueError:
+ # Raised on Windows if src and dst are not on the same volume. This is the case when creating a symlink to a
+ # local_dir instead of within the cache directory.
+ # See https://docs.python.org/3/library/os.path.html#os.path.relpath
+ relative_src = None
+
+ try:
+ commonpath = os.path.commonpath([abs_src, abs_dst])
+ _support_symlinks = are_symlinks_supported(commonpath)
+ except ValueError:
+ # Raised if src and dst are not on the same volume. Symlinks will still work on Linux/Macos.
+ # See https://docs.python.org/3/library/os.path.html#os.path.commonpath
+ _support_symlinks = os.name != "nt"
+ except PermissionError:
+ # Permission error means src and dst are not in the same volume (e.g. destination path has been provided
+ # by the user via `local_dir`. Let's test symlink support there)
+ _support_symlinks = are_symlinks_supported(abs_dst_folder)
+ except OSError as e:
+ # OS error (errno=30) means that the commonpath is readonly on Linux/MacOS.
+ if e.errno == errno.EROFS:
+ _support_symlinks = are_symlinks_supported(abs_dst_folder)
+ else:
+ raise
+
+ # Symlinks are supported => let's create a symlink.
+ if _support_symlinks:
+ src_rel_or_abs = relative_src or abs_src
+ logger.debug(f"Creating pointer from {src_rel_or_abs} to {abs_dst}")
+ try:
+ os.symlink(src_rel_or_abs, abs_dst)
+ return
+ except FileExistsError:
+ if os.path.islink(abs_dst) and os.path.realpath(abs_dst) == os.path.realpath(abs_src):
+ # `abs_dst` already exists and is a symlink to the `abs_src` blob. It is most likely that the file has
+ # been cached twice concurrently (exactly between `os.remove` and `os.symlink`). Do nothing.
+ return
+ else:
+ # Very unlikely to happen. Means a file `dst` has been created exactly between `os.remove` and
+ # `os.symlink` and is not a symlink to the `abs_src` blob file. Raise exception.
+ raise
+ except PermissionError:
+ # Permission error means src and dst are not in the same volume (e.g. download to local dir) and symlink
+ # is supported on both volumes but not between them. Let's just make a hard copy in that case.
+ pass
+
+ # Symlinks are not supported => let's move or copy the file.
+ if new_blob:
+ logger.info(f"Symlink not supported. Moving file from {abs_src} to {abs_dst}")
+ shutil.move(abs_src, abs_dst, copy_function=_copy_no_matter_what)
+ else:
+ logger.info(f"Symlink not supported. Copying file from {abs_src} to {abs_dst}")
+ shutil.copyfile(abs_src, abs_dst)
+
+
+def _cache_commit_hash_for_specific_revision(storage_folder: str, revision: str, commit_hash: str) -> None:
+ """Cache reference between a revision (tag, branch or truncated commit hash) and the corresponding commit hash.
+
+ Does nothing if `revision` is already a proper `commit_hash` or reference is already cached.
+ """
+ if revision != commit_hash:
+ ref_path = Path(storage_folder) / "refs" / revision
+ ref_path.parent.mkdir(parents=True, exist_ok=True)
+ if not ref_path.exists() or commit_hash != ref_path.read_text():
+ # Update ref only if has been updated. Could cause useless error in case
+ # repo is already cached and user doesn't have write access to cache folder.
+ # See https://github.com/huggingface/huggingface_hub/issues/1216.
+ ref_path.write_text(commit_hash)
+
+
+@validate_hf_hub_args
+def repo_folder_name(*, repo_id: str, repo_type: str) -> str:
+ """Return a serialized version of a hf.co repo name and type, safe for disk storage
+ as a single non-nested folder.
+
+ Example: models--julien-c--EsperBERTo-small
+ """
+ # remove all `/` occurrences to correctly convert repo to directory name
+ parts = [f"{repo_type}s", *repo_id.split("/")]
+ return constants.REPO_ID_SEPARATOR.join(parts)
+
+
+def _check_disk_space(expected_size: int, target_dir: Union[str, Path]) -> None:
+ """Check disk usage and log a warning if there is not enough disk space to download the file.
+
+ Args:
+ expected_size (`int`):
+ The expected size of the file in bytes.
+ target_dir (`str`):
+ The directory where the file will be stored after downloading.
+ """
+
+ target_dir = Path(target_dir) # format as `Path`
+ for path in [target_dir] + list(target_dir.parents): # first check target_dir, then each parents one by one
+ try:
+ target_dir_free = shutil.disk_usage(path).free
+ if target_dir_free < expected_size:
+ warnings.warn(
+ "Not enough free disk space to download the file. "
+ f"The expected file size is: {expected_size / 1e6:.2f} MB. "
+ f"The target location {target_dir} only has {target_dir_free / 1e6:.2f} MB free disk space."
+ )
+ return
+ except OSError: # raise on anything: file does not exist or space disk cannot be checked
+ pass
+
+
+@validate_hf_hub_args
+def hf_hub_download(
+ repo_id: str,
+ filename: str,
+ *,
+ subfolder: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ library_name: Optional[str] = None,
+ library_version: Optional[str] = None,
+ cache_dir: Union[str, Path, None] = None,
+ local_dir: Union[str, Path, None] = None,
+ user_agent: Union[Dict, str, None] = None,
+ force_download: bool = False,
+ proxies: Optional[Dict] = None,
+ etag_timeout: float = constants.DEFAULT_ETAG_TIMEOUT,
+ token: Union[bool, str, None] = None,
+ local_files_only: bool = False,
+ headers: Optional[Dict[str, str]] = None,
+ endpoint: Optional[str] = None,
+ resume_download: Optional[bool] = None,
+ force_filename: Optional[str] = None,
+ local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
+) -> str:
+ """Download a given file if it's not already present in the local cache.
+
+ The new cache file layout looks like this:
+ - The cache directory contains one subfolder per repo_id (namespaced by repo type)
+ - inside each repo folder:
+ - refs is a list of the latest known revision => commit_hash pairs
+ - blobs contains the actual file blobs (identified by their git-sha or sha256, depending on
+ whether they're LFS files or not)
+ - snapshots contains one subfolder per commit, each "commit" contains the subset of the files
+ that have been resolved at that particular commit. Each filename is a symlink to the blob
+ at that particular commit.
+
+ ```
+ [ 96] .
+ └── [ 160] models--julien-c--EsperBERTo-small
+ ├── [ 160] blobs
+ │ ├── [321M] 403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ │ ├── [ 398] 7cb18dc9bafbfcf74629a4b760af1b160957a83e
+ │ └── [1.4K] d7edf6bd2a681fb0175f7735299831ee1b22b812
+ ├── [ 96] refs
+ │ └── [ 40] main
+ └── [ 128] snapshots
+ ├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f
+ │ ├── [ 52] README.md -> ../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812
+ │ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ └── [ 128] bbc77c8132af1cc5cf678da3f1ddf2de43606d48
+ ├── [ 52] README.md -> ../../blobs/7cb18dc9bafbfcf74629a4b760af1b160957a83e
+ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ ```
+
+ If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
+ option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
+ to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
+ cache-system, it's optimized for regularly pulling the latest version of a repository.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ filename (`str`):
+ The name of the file in the repo.
+ subfolder (`str`, *optional*):
+ An optional value corresponding to a folder inside the model repo.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+ `None` or `"model"` if downloading from a model. Default is `None`.
+ revision (`str`, *optional*):
+ An optional Git revision id which can be a branch name, a tag, or a
+ commit hash.
+ library_name (`str`, *optional*):
+ The name of the library to which the object corresponds.
+ library_version (`str`, *optional*):
+ The version of the library.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_dir (`str` or `Path`, *optional*):
+ If provided, the downloaded file will be placed under this directory.
+ user_agent (`dict`, `str`, *optional*):
+ The user-agent info in the form of a dictionary or a string.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether the file should be downloaded even if it already exists in
+ the local cache.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to
+ `requests.request`.
+ etag_timeout (`float`, *optional*, defaults to `10`):
+ When fetching ETag, how many seconds to wait for the server to send
+ data before giving up which is passed to `requests.request`.
+ token (`str`, `bool`, *optional*):
+ A token to be used for the download.
+ - If `True`, the token is read from the HuggingFace config
+ folder.
+ - If a string, it's used as the authentication token.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the
+ local cached file if it exists.
+ headers (`dict`, *optional*):
+ Additional headers to be sent with the request.
+
+ Returns:
+ `str`: Local path of file or if networking is off, last version of file cached on disk.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to download from cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ [`~utils.RevisionNotFoundError`]
+ If the revision to download from cannot be found.
+ [`~utils.EntryNotFoundError`]
+ If the file to download cannot be found.
+ [`~utils.LocalEntryNotFoundError`]
+ If network is disabled or unavailable and file is not found in cache.
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If `token=True` but the token cannot be found.
+ [`OSError`](https://docs.python.org/3/library/exceptions.html#OSError)
+ If ETag cannot be determined.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If some parameter value is invalid.
+
+ """
+ if constants.HF_HUB_ETAG_TIMEOUT != constants.DEFAULT_ETAG_TIMEOUT:
+ # Respect environment variable above user value
+ etag_timeout = constants.HF_HUB_ETAG_TIMEOUT
+
+ if force_filename is not None:
+ warnings.warn(
+ "The `force_filename` parameter is deprecated as a new caching system, "
+ "which keeps the filenames as they are on the Hub, is now in place.",
+ FutureWarning,
+ )
+ if resume_download is not None:
+ warnings.warn(
+ "`resume_download` is deprecated and will be removed in version 1.0.0. "
+ "Downloads always resume when possible. "
+ "If you want to force a new download, use `force_download=True`.",
+ FutureWarning,
+ )
+
+ if cache_dir is None:
+ cache_dir = constants.HF_HUB_CACHE
+ if revision is None:
+ revision = constants.DEFAULT_REVISION
+ if isinstance(cache_dir, Path):
+ cache_dir = str(cache_dir)
+ if isinstance(local_dir, Path):
+ local_dir = str(local_dir)
+
+ if subfolder == "":
+ subfolder = None
+ if subfolder is not None:
+ # This is used to create a URL, and not a local path, hence the forward slash.
+ filename = f"{subfolder}/{filename}"
+
+ if repo_type is None:
+ repo_type = "model"
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type: {repo_type}. Accepted repo types are: {str(constants.REPO_TYPES)}")
+
+ hf_headers = build_hf_headers(
+ token=token,
+ library_name=library_name,
+ library_version=library_version,
+ user_agent=user_agent,
+ headers=headers,
+ )
+
+ if local_dir is not None:
+ if local_dir_use_symlinks != "auto":
+ warnings.warn(
+ "`local_dir_use_symlinks` parameter is deprecated and will be ignored. "
+ "The process to download files to a local folder has been updated and do "
+ "not rely on symlinks anymore. You only need to pass a destination folder "
+ "as`local_dir`.\n"
+ "For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/download#download-files-to-local-folder."
+ )
+
+ return _hf_hub_download_to_local_dir(
+ # Destination
+ local_dir=local_dir,
+ # File info
+ repo_id=repo_id,
+ repo_type=repo_type,
+ filename=filename,
+ revision=revision,
+ # HTTP info
+ endpoint=endpoint,
+ etag_timeout=etag_timeout,
+ headers=hf_headers,
+ proxies=proxies,
+ token=token,
+ # Additional options
+ cache_dir=cache_dir,
+ force_download=force_download,
+ local_files_only=local_files_only,
+ )
+ else:
+ return _hf_hub_download_to_cache_dir(
+ # Destination
+ cache_dir=cache_dir,
+ # File info
+ repo_id=repo_id,
+ filename=filename,
+ repo_type=repo_type,
+ revision=revision,
+ # HTTP info
+ endpoint=endpoint,
+ etag_timeout=etag_timeout,
+ headers=hf_headers,
+ proxies=proxies,
+ token=token,
+ # Additional options
+ local_files_only=local_files_only,
+ force_download=force_download,
+ )
+
+
+def _hf_hub_download_to_cache_dir(
+ *,
+ # Destination
+ cache_dir: str,
+ # File info
+ repo_id: str,
+ filename: str,
+ repo_type: str,
+ revision: str,
+ # HTTP info
+ endpoint: Optional[str],
+ etag_timeout: float,
+ headers: Dict[str, str],
+ proxies: Optional[Dict],
+ token: Optional[Union[bool, str]],
+ # Additional options
+ local_files_only: bool,
+ force_download: bool,
+) -> str:
+ """Download a given file to a cache folder, if not already present.
+
+ Method should not be called directly. Please use `hf_hub_download` instead.
+ """
+ locks_dir = os.path.join(cache_dir, ".locks")
+ storage_folder = os.path.join(cache_dir, repo_folder_name(repo_id=repo_id, repo_type=repo_type))
+
+ # cross platform transcription of filename, to be used as a local file path.
+ relative_filename = os.path.join(*filename.split("/"))
+ if os.name == "nt":
+ if relative_filename.startswith("..\\") or "\\..\\" in relative_filename:
+ raise ValueError(
+ f"Invalid filename: cannot handle filename '{relative_filename}' on Windows. Please ask the repository"
+ " owner to rename this file."
+ )
+
+ # if user provides a commit_hash and they already have the file on disk, shortcut everything.
+ if REGEX_COMMIT_HASH.match(revision):
+ pointer_path = _get_pointer_path(storage_folder, revision, relative_filename)
+ if os.path.exists(pointer_path) and not force_download:
+ return pointer_path
+
+ # Try to get metadata (etag, commit_hash, url, size) from the server.
+ # If we can't, a HEAD request error is returned.
+ (url_to_download, etag, commit_hash, expected_size, xet_file_data, head_call_error) = _get_metadata_or_catch_error(
+ repo_id=repo_id,
+ filename=filename,
+ repo_type=repo_type,
+ revision=revision,
+ endpoint=endpoint,
+ proxies=proxies,
+ etag_timeout=etag_timeout,
+ headers=headers,
+ token=token,
+ local_files_only=local_files_only,
+ storage_folder=storage_folder,
+ relative_filename=relative_filename,
+ )
+
+ # etag can be None for several reasons:
+ # 1. we passed local_files_only.
+ # 2. we don't have a connection
+ # 3. Hub is down (HTTP 500, 503, 504)
+ # 4. repo is not found -for example private or gated- and invalid/missing token sent
+ # 5. Hub is blocked by a firewall or proxy is not set correctly.
+ # => Try to get the last downloaded one from the specified revision.
+ #
+ # If the specified revision is a commit hash, look inside "snapshots".
+ # If the specified revision is a branch or tag, look inside "refs".
+ if head_call_error is not None:
+ # Couldn't make a HEAD call => let's try to find a local file
+ if not force_download:
+ commit_hash = None
+ if REGEX_COMMIT_HASH.match(revision):
+ commit_hash = revision
+ else:
+ ref_path = os.path.join(storage_folder, "refs", revision)
+ if os.path.isfile(ref_path):
+ with open(ref_path) as f:
+ commit_hash = f.read()
+
+ # Return pointer file if exists
+ if commit_hash is not None:
+ pointer_path = _get_pointer_path(storage_folder, commit_hash, relative_filename)
+ if os.path.exists(pointer_path) and not force_download:
+ return pointer_path
+
+ # Otherwise, raise appropriate error
+ _raise_on_head_call_error(head_call_error, force_download, local_files_only)
+
+ # From now on, etag, commit_hash, url and size are not None.
+ assert etag is not None, "etag must have been retrieved from server"
+ assert commit_hash is not None, "commit_hash must have been retrieved from server"
+ assert url_to_download is not None, "file location must have been retrieved from server"
+ assert expected_size is not None, "expected_size must have been retrieved from server"
+ blob_path = os.path.join(storage_folder, "blobs", etag)
+ pointer_path = _get_pointer_path(storage_folder, commit_hash, relative_filename)
+
+ os.makedirs(os.path.dirname(blob_path), exist_ok=True)
+ os.makedirs(os.path.dirname(pointer_path), exist_ok=True)
+
+ # if passed revision is not identical to commit_hash
+ # then revision has to be a branch name or tag name.
+ # In that case store a ref.
+ _cache_commit_hash_for_specific_revision(storage_folder, revision, commit_hash)
+
+ # Prevent parallel downloads of the same file with a lock.
+ # etag could be duplicated across repos,
+ lock_path = os.path.join(locks_dir, repo_folder_name(repo_id=repo_id, repo_type=repo_type), f"{etag}.lock")
+
+ # Some Windows versions do not allow for paths longer than 255 characters.
+ # In this case, we must specify it as an extended path by using the "\\?\" prefix.
+ if (
+ os.name == "nt"
+ and len(os.path.abspath(lock_path)) > 255
+ and not os.path.abspath(lock_path).startswith("\\\\?\\")
+ ):
+ lock_path = "\\\\?\\" + os.path.abspath(lock_path)
+
+ if (
+ os.name == "nt"
+ and len(os.path.abspath(blob_path)) > 255
+ and not os.path.abspath(blob_path).startswith("\\\\?\\")
+ ):
+ blob_path = "\\\\?\\" + os.path.abspath(blob_path)
+
+ Path(lock_path).parent.mkdir(parents=True, exist_ok=True)
+
+ # pointer already exists -> immediate return
+ if not force_download and os.path.exists(pointer_path):
+ return pointer_path
+
+ # Blob exists but pointer must be (safely) created -> take the lock
+ if not force_download and os.path.exists(blob_path):
+ with WeakFileLock(lock_path):
+ if not os.path.exists(pointer_path):
+ _create_symlink(blob_path, pointer_path, new_blob=False)
+ return pointer_path
+
+ # Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)
+
+ with WeakFileLock(lock_path):
+ _download_to_tmp_and_move(
+ incomplete_path=Path(blob_path + ".incomplete"),
+ destination_path=Path(blob_path),
+ url_to_download=url_to_download,
+ proxies=proxies,
+ headers=headers,
+ expected_size=expected_size,
+ filename=filename,
+ force_download=force_download,
+ etag=etag,
+ xet_file_data=xet_file_data,
+ )
+ if not os.path.exists(pointer_path):
+ _create_symlink(blob_path, pointer_path, new_blob=True)
+
+ return pointer_path
+
+
+def _hf_hub_download_to_local_dir(
+ *,
+ # Destination
+ local_dir: Union[str, Path],
+ # File info
+ repo_id: str,
+ repo_type: str,
+ filename: str,
+ revision: str,
+ # HTTP info
+ endpoint: Optional[str],
+ etag_timeout: float,
+ headers: Dict[str, str],
+ proxies: Optional[Dict],
+ token: Union[bool, str, None],
+ # Additional options
+ cache_dir: str,
+ force_download: bool,
+ local_files_only: bool,
+) -> str:
+ """Download a given file to a local folder, if not already present.
+
+ Method should not be called directly. Please use `hf_hub_download` instead.
+ """
+ # Some Windows versions do not allow for paths longer than 255 characters.
+ # In this case, we must specify it as an extended path by using the "\\?\" prefix.
+ if os.name == "nt" and len(os.path.abspath(local_dir)) > 255:
+ local_dir = "\\\\?\\" + os.path.abspath(local_dir)
+ local_dir = Path(local_dir)
+ paths = get_local_download_paths(local_dir=local_dir, filename=filename)
+ local_metadata = read_download_metadata(local_dir=local_dir, filename=filename)
+
+ # Local file exists + metadata exists + commit_hash matches => return file
+ if (
+ not force_download
+ and REGEX_COMMIT_HASH.match(revision)
+ and paths.file_path.is_file()
+ and local_metadata is not None
+ and local_metadata.commit_hash == revision
+ ):
+ return str(paths.file_path)
+
+ # Local file doesn't exist or commit_hash doesn't match => we need the etag
+ (url_to_download, etag, commit_hash, expected_size, xet_file_data, head_call_error) = _get_metadata_or_catch_error(
+ repo_id=repo_id,
+ filename=filename,
+ repo_type=repo_type,
+ revision=revision,
+ endpoint=endpoint,
+ proxies=proxies,
+ etag_timeout=etag_timeout,
+ headers=headers,
+ token=token,
+ local_files_only=local_files_only,
+ )
+
+ if head_call_error is not None:
+ # No HEAD call but local file exists => default to local file
+ if not force_download and paths.file_path.is_file():
+ logger.warning(
+ f"Couldn't access the Hub to check for update but local file already exists. Defaulting to existing file. (error: {head_call_error})"
+ )
+ return str(paths.file_path)
+ # Otherwise => raise
+ _raise_on_head_call_error(head_call_error, force_download, local_files_only)
+
+ # From now on, etag, commit_hash, url and size are not None.
+ assert etag is not None, "etag must have been retrieved from server"
+ assert commit_hash is not None, "commit_hash must have been retrieved from server"
+ assert url_to_download is not None, "file location must have been retrieved from server"
+ assert expected_size is not None, "expected_size must have been retrieved from server"
+
+ # Local file exists => check if it's up-to-date
+ if not force_download and paths.file_path.is_file():
+ # etag matches => update metadata and return file
+ if local_metadata is not None and local_metadata.etag == etag:
+ write_download_metadata(local_dir=local_dir, filename=filename, commit_hash=commit_hash, etag=etag)
+ return str(paths.file_path)
+
+ # metadata is outdated + etag is a sha256
+ # => means it's an LFS file (large)
+ # => let's compute local hash and compare
+ # => if match, update metadata and return file
+ if local_metadata is None and REGEX_SHA256.match(etag) is not None:
+ with open(paths.file_path, "rb") as f:
+ file_hash = sha_fileobj(f).hex()
+ if file_hash == etag:
+ write_download_metadata(local_dir=local_dir, filename=filename, commit_hash=commit_hash, etag=etag)
+ return str(paths.file_path)
+
+ # Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)
+
+ # If we are lucky enough, the file is already in the cache => copy it
+ if not force_download:
+ cached_path = try_to_load_from_cache(
+ repo_id=repo_id,
+ filename=filename,
+ cache_dir=cache_dir,
+ revision=commit_hash,
+ repo_type=repo_type,
+ )
+ if isinstance(cached_path, str):
+ with WeakFileLock(paths.lock_path):
+ paths.file_path.parent.mkdir(parents=True, exist_ok=True)
+ shutil.copyfile(cached_path, paths.file_path)
+ write_download_metadata(local_dir=local_dir, filename=filename, commit_hash=commit_hash, etag=etag)
+ return str(paths.file_path)
+
+ # Otherwise, let's download the file!
+ with WeakFileLock(paths.lock_path):
+ paths.file_path.unlink(missing_ok=True) # delete outdated file first
+ _download_to_tmp_and_move(
+ incomplete_path=paths.incomplete_path(etag),
+ destination_path=paths.file_path,
+ url_to_download=url_to_download,
+ proxies=proxies,
+ headers=headers,
+ expected_size=expected_size,
+ filename=filename,
+ force_download=force_download,
+ etag=etag,
+ xet_file_data=xet_file_data,
+ )
+
+ write_download_metadata(local_dir=local_dir, filename=filename, commit_hash=commit_hash, etag=etag)
+ return str(paths.file_path)
+
+
+@validate_hf_hub_args
+def try_to_load_from_cache(
+ repo_id: str,
+ filename: str,
+ cache_dir: Union[str, Path, None] = None,
+ revision: Optional[str] = None,
+ repo_type: Optional[str] = None,
+) -> Union[str, _CACHED_NO_EXIST_T, None]:
+ """
+ Explores the cache to return the latest cached file for a given revision if found.
+
+ This function will not raise any exception if the file in not cached.
+
+ Args:
+ cache_dir (`str` or `os.PathLike`):
+ The folder where the cached files lie.
+ repo_id (`str`):
+ The ID of the repo on huggingface.co.
+ filename (`str`):
+ The filename to look for inside `repo_id`.
+ revision (`str`, *optional*):
+ The specific model version to use. Will default to `"main"` if it's not provided and no `commit_hash` is
+ provided either.
+ repo_type (`str`, *optional*):
+ The type of the repository. Will default to `"model"`.
+
+ Returns:
+ `Optional[str]` or `_CACHED_NO_EXIST`:
+ Will return `None` if the file was not cached. Otherwise:
+ - The exact path to the cached file if it's found in the cache
+ - A special value `_CACHED_NO_EXIST` if the file does not exist at the given commit hash and this fact was
+ cached.
+
+ Example:
+
+ ```python
+ from huggingface_hub import try_to_load_from_cache, _CACHED_NO_EXIST
+
+ filepath = try_to_load_from_cache()
+ if isinstance(filepath, str):
+ # file exists and is cached
+ ...
+ elif filepath is _CACHED_NO_EXIST:
+ # non-existence of file is cached
+ ...
+ else:
+ # file is not cached
+ ...
+ ```
+ """
+ if revision is None:
+ revision = "main"
+ if repo_type is None:
+ repo_type = "model"
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type: {repo_type}. Accepted repo types are: {str(constants.REPO_TYPES)}")
+ if cache_dir is None:
+ cache_dir = constants.HF_HUB_CACHE
+
+ object_id = repo_id.replace("/", "--")
+ repo_cache = os.path.join(cache_dir, f"{repo_type}s--{object_id}")
+ if not os.path.isdir(repo_cache):
+ # No cache for this model
+ return None
+
+ refs_dir = os.path.join(repo_cache, "refs")
+ snapshots_dir = os.path.join(repo_cache, "snapshots")
+ no_exist_dir = os.path.join(repo_cache, ".no_exist")
+
+ # Resolve refs (for instance to convert main to the associated commit sha)
+ if os.path.isdir(refs_dir):
+ revision_file = os.path.join(refs_dir, revision)
+ if os.path.isfile(revision_file):
+ with open(revision_file) as f:
+ revision = f.read()
+
+ # Check if file is cached as "no_exist"
+ if os.path.isfile(os.path.join(no_exist_dir, revision, filename)):
+ return _CACHED_NO_EXIST
+
+ # Check if revision folder exists
+ if not os.path.exists(snapshots_dir):
+ return None
+ cached_shas = os.listdir(snapshots_dir)
+ if revision not in cached_shas:
+ # No cache for this revision and we won't try to return a random revision
+ return None
+
+ # Check if file exists in cache
+ cached_file = os.path.join(snapshots_dir, revision, filename)
+ return cached_file if os.path.isfile(cached_file) else None
+
+
+@validate_hf_hub_args
+def get_hf_file_metadata(
+ url: str,
+ token: Union[bool, str, None] = None,
+ proxies: Optional[Dict] = None,
+ timeout: Optional[float] = constants.DEFAULT_REQUEST_TIMEOUT,
+ library_name: Optional[str] = None,
+ library_version: Optional[str] = None,
+ user_agent: Union[Dict, str, None] = None,
+ headers: Optional[Dict[str, str]] = None,
+ endpoint: Optional[str] = None,
+) -> HfFileMetadata:
+ """Fetch metadata of a file versioned on the Hub for a given url.
+
+ Args:
+ url (`str`):
+ File url, for example returned by [`hf_hub_url`].
+ token (`str` or `bool`, *optional*):
+ A token to be used for the download.
+ - If `True`, the token is read from the HuggingFace config
+ folder.
+ - If `False` or `None`, no token is provided.
+ - If a string, it's used as the authentication token.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to
+ `requests.request`.
+ timeout (`float`, *optional*, defaults to 10):
+ How many seconds to wait for the server to send metadata before giving up.
+ library_name (`str`, *optional*):
+ The name of the library to which the object corresponds.
+ library_version (`str`, *optional*):
+ The version of the library.
+ user_agent (`dict`, `str`, *optional*):
+ The user-agent info in the form of a dictionary or a string.
+ headers (`dict`, *optional*):
+ Additional headers to be sent with the request.
+ endpoint (`str`, *optional*):
+ Endpoint of the Hub. Defaults to .
+
+ Returns:
+ A [`HfFileMetadata`] object containing metadata such as location, etag, size and
+ commit_hash.
+ """
+ hf_headers = build_hf_headers(
+ token=token,
+ library_name=library_name,
+ library_version=library_version,
+ user_agent=user_agent,
+ headers=headers,
+ )
+ hf_headers["Accept-Encoding"] = "identity" # prevent any compression => we want to know the real size of the file
+
+ # Retrieve metadata
+ r = _request_wrapper(
+ method="HEAD",
+ url=url,
+ headers=hf_headers,
+ allow_redirects=False,
+ follow_relative_redirects=True,
+ proxies=proxies,
+ timeout=timeout,
+ )
+ hf_raise_for_status(r)
+
+ # Return
+ return HfFileMetadata(
+ commit_hash=r.headers.get(constants.HUGGINGFACE_HEADER_X_REPO_COMMIT),
+ # We favor a custom header indicating the etag of the linked resource, and
+ # we fallback to the regular etag header.
+ etag=_normalize_etag(r.headers.get(constants.HUGGINGFACE_HEADER_X_LINKED_ETAG) or r.headers.get("ETag")),
+ # Either from response headers (if redirected) or defaults to request url
+ # Do not use directly `url`, as `_request_wrapper` might have followed relative
+ # redirects.
+ location=r.headers.get("Location") or r.request.url, # type: ignore
+ size=_int_or_none(
+ r.headers.get(constants.HUGGINGFACE_HEADER_X_LINKED_SIZE) or r.headers.get("Content-Length")
+ ),
+ xet_file_data=parse_xet_file_data_from_response(r, endpoint=endpoint), # type: ignore
+ )
+
+
+def _get_metadata_or_catch_error(
+ *,
+ repo_id: str,
+ filename: str,
+ repo_type: str,
+ revision: str,
+ endpoint: Optional[str],
+ proxies: Optional[Dict],
+ etag_timeout: Optional[float],
+ headers: Dict[str, str], # mutated inplace!
+ token: Union[bool, str, None],
+ local_files_only: bool,
+ relative_filename: Optional[str] = None, # only used to store `.no_exists` in cache
+ storage_folder: Optional[str] = None, # only used to store `.no_exists` in cache
+) -> Union[
+ # Either an exception is caught and returned
+ Tuple[None, None, None, None, None, Exception],
+ # Or the metadata is returned as
+ # `(url_to_download, etag, commit_hash, expected_size, xet_file_data, None)`
+ Tuple[str, str, str, int, Optional[XetFileData], None],
+]:
+ """Get metadata for a file on the Hub, safely handling network issues.
+
+ Returns either the etag, commit_hash and expected size of the file, or the error
+ raised while fetching the metadata.
+
+ NOTE: This function mutates `headers` inplace! It removes the `authorization` header
+ if the file is a LFS blob and the domain of the url is different from the
+ domain of the location (typically an S3 bucket).
+ """
+ if local_files_only:
+ return (
+ None,
+ None,
+ None,
+ None,
+ None,
+ OfflineModeIsEnabled(
+ f"Cannot access file since 'local_files_only=True' as been set. (repo_id: {repo_id}, repo_type: {repo_type}, revision: {revision}, filename: {filename})"
+ ),
+ )
+
+ url = hf_hub_url(repo_id, filename, repo_type=repo_type, revision=revision, endpoint=endpoint)
+ url_to_download: str = url
+ etag: Optional[str] = None
+ commit_hash: Optional[str] = None
+ expected_size: Optional[int] = None
+ head_error_call: Optional[Exception] = None
+ xet_file_data: Optional[XetFileData] = None
+
+ # Try to get metadata from the server.
+ # Do not raise yet if the file is not found or not accessible.
+ if not local_files_only:
+ try:
+ try:
+ metadata = get_hf_file_metadata(
+ url=url, proxies=proxies, timeout=etag_timeout, headers=headers, token=token, endpoint=endpoint
+ )
+ except EntryNotFoundError as http_error:
+ if storage_folder is not None and relative_filename is not None:
+ # Cache the non-existence of the file
+ commit_hash = http_error.response.headers.get(constants.HUGGINGFACE_HEADER_X_REPO_COMMIT)
+ if commit_hash is not None:
+ no_exist_file_path = Path(storage_folder) / ".no_exist" / commit_hash / relative_filename
+ try:
+ no_exist_file_path.parent.mkdir(parents=True, exist_ok=True)
+ no_exist_file_path.touch()
+ except OSError as e:
+ logger.error(
+ f"Could not cache non-existence of file. Will ignore error and continue. Error: {e}"
+ )
+ _cache_commit_hash_for_specific_revision(storage_folder, revision, commit_hash)
+ raise
+
+ # Commit hash must exist
+ commit_hash = metadata.commit_hash
+ if commit_hash is None:
+ raise FileMetadataError(
+ "Distant resource does not seem to be on huggingface.co. It is possible that a configuration issue"
+ " prevents you from downloading resources from https://huggingface.co. Please check your firewall"
+ " and proxy settings and make sure your SSL certificates are updated."
+ )
+
+ # Etag must exist
+ # If we don't have any of those, raise an error.
+ etag = metadata.etag
+ if etag is None:
+ raise FileMetadataError(
+ "Distant resource does not have an ETag, we won't be able to reliably ensure reproducibility."
+ )
+
+ # Size must exist
+ expected_size = metadata.size
+ if expected_size is None:
+ raise FileMetadataError("Distant resource does not have a Content-Length.")
+
+ xet_file_data = metadata.xet_file_data
+
+ # In case of a redirect, save an extra redirect on the request.get call,
+ # and ensure we download the exact atomic version even if it changed
+ # between the HEAD and the GET (unlikely, but hey).
+ #
+ # If url domain is different => we are downloading from a CDN => url is signed => don't send auth
+ # If url domain is the same => redirect due to repo rename AND downloading a regular file => keep auth
+ if xet_file_data is None and url != metadata.location:
+ url_to_download = metadata.location
+ if urlparse(url).netloc != urlparse(metadata.location).netloc:
+ # Remove authorization header when downloading a LFS blob
+ headers.pop("authorization", None)
+ except (requests.exceptions.SSLError, requests.exceptions.ProxyError):
+ # Actually raise for those subclasses of ConnectionError
+ raise
+ except (
+ requests.exceptions.ConnectionError,
+ requests.exceptions.Timeout,
+ OfflineModeIsEnabled,
+ ) as error:
+ # Otherwise, our Internet connection is down.
+ # etag is None
+ head_error_call = error
+ except (RevisionNotFoundError, EntryNotFoundError):
+ # The repo was found but the revision or entry doesn't exist on the Hub (never existed or got deleted)
+ raise
+ except requests.HTTPError as error:
+ # Multiple reasons for an http error:
+ # - Repository is private and invalid/missing token sent
+ # - Repository is gated and invalid/missing token sent
+ # - Hub is down (error 500 or 504)
+ # => let's switch to 'local_files_only=True' to check if the files are already cached.
+ # (if it's not the case, the error will be re-raised)
+ head_error_call = error
+ except FileMetadataError as error:
+ # Multiple reasons for a FileMetadataError:
+ # - Wrong network configuration (proxy, firewall, SSL certificates)
+ # - Inconsistency on the Hub
+ # => let's switch to 'local_files_only=True' to check if the files are already cached.
+ # (if it's not the case, the error will be re-raised)
+ head_error_call = error
+
+ if not (local_files_only or etag is not None or head_error_call is not None):
+ raise RuntimeError("etag is empty due to uncovered problems")
+
+ return (url_to_download, etag, commit_hash, expected_size, xet_file_data, head_error_call) # type: ignore [return-value]
+
+
+def _raise_on_head_call_error(head_call_error: Exception, force_download: bool, local_files_only: bool) -> NoReturn:
+ """Raise an appropriate error when the HEAD call failed and we cannot locate a local file."""
+ # No head call => we cannot force download.
+ if force_download:
+ if local_files_only:
+ raise ValueError("Cannot pass 'force_download=True' and 'local_files_only=True' at the same time.")
+ elif isinstance(head_call_error, OfflineModeIsEnabled):
+ raise ValueError("Cannot pass 'force_download=True' when offline mode is enabled.") from head_call_error
+ else:
+ raise ValueError("Force download failed due to the above error.") from head_call_error
+
+ # No head call + couldn't find an appropriate file on disk => raise an error.
+ if local_files_only:
+ raise LocalEntryNotFoundError(
+ "Cannot find the requested files in the disk cache and outgoing traffic has been disabled. To enable"
+ " hf.co look-ups and downloads online, set 'local_files_only' to False."
+ )
+ elif isinstance(head_call_error, (RepositoryNotFoundError, GatedRepoError)) or (
+ isinstance(head_call_error, HfHubHTTPError) and head_call_error.response.status_code == 401
+ ):
+ # Repo not found or gated => let's raise the actual error
+ # Unauthorized => likely a token issue => let's raise the actual error
+ raise head_call_error
+ else:
+ # Otherwise: most likely a connection issue or Hub downtime => let's warn the user
+ raise LocalEntryNotFoundError(
+ "An error happened while trying to locate the file on the Hub and we cannot find the requested files"
+ " in the local cache. Please check your connection and try again or make sure your Internet connection"
+ " is on."
+ ) from head_call_error
+
+
+def _download_to_tmp_and_move(
+ incomplete_path: Path,
+ destination_path: Path,
+ url_to_download: str,
+ proxies: Optional[Dict],
+ headers: Dict[str, str],
+ expected_size: Optional[int],
+ filename: str,
+ force_download: bool,
+ etag: Optional[str],
+ xet_file_data: Optional[XetFileData],
+) -> None:
+ """Download content from a URL to a destination path.
+
+ Internal logic:
+ - return early if file is already downloaded
+ - resume download if possible (from incomplete file)
+ - do not resume download if `force_download=True` or `HF_HUB_ENABLE_HF_TRANSFER=True`
+ - check disk space before downloading
+ - download content to a temporary file
+ - set correct permissions on temporary file
+ - move the temporary file to the destination path
+
+ Both `incomplete_path` and `destination_path` must be on the same volume to avoid a local copy.
+ """
+ if destination_path.exists() and not force_download:
+ # Do nothing if already exists (except if force_download=True)
+ return
+
+ if incomplete_path.exists() and (force_download or (constants.HF_HUB_ENABLE_HF_TRANSFER and not proxies)):
+ # By default, we will try to resume the download if possible.
+ # However, if the user has set `force_download=True` or if `hf_transfer` is enabled, then we should
+ # not resume the download => delete the incomplete file.
+ message = f"Removing incomplete file '{incomplete_path}'"
+ if force_download:
+ message += " (force_download=True)"
+ elif constants.HF_HUB_ENABLE_HF_TRANSFER and not proxies:
+ message += " (hf_transfer=True)"
+ logger.info(message)
+ incomplete_path.unlink(missing_ok=True)
+
+ with incomplete_path.open("ab") as f:
+ resume_size = f.tell()
+ message = f"Downloading '{filename}' to '{incomplete_path}'"
+ if resume_size > 0 and expected_size is not None:
+ message += f" (resume from {resume_size}/{expected_size})"
+ logger.info(message)
+
+ if expected_size is not None: # might be None if HTTP header not set correctly
+ # Check disk space in both tmp and destination path
+ _check_disk_space(expected_size, incomplete_path.parent)
+ _check_disk_space(expected_size, destination_path.parent)
+
+ if xet_file_data is not None and is_xet_available():
+ logger.debug("Xet Storage is enabled for this repo. Downloading file from Xet Storage..")
+ xet_get(
+ incomplete_path=incomplete_path,
+ xet_file_data=xet_file_data,
+ headers=headers,
+ expected_size=expected_size,
+ displayed_filename=filename,
+ )
+ else:
+ if xet_file_data is not None and not constants.HF_HUB_DISABLE_XET:
+ logger.warning(
+ "Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. "
+ "Falling back to regular HTTP download. "
+ "For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`"
+ )
+
+ http_get(
+ url_to_download,
+ f,
+ proxies=proxies,
+ resume_size=resume_size,
+ headers=headers,
+ expected_size=expected_size,
+ )
+
+ logger.info(f"Download complete. Moving file to {destination_path}")
+ _chmod_and_move(incomplete_path, destination_path)
+
+
+def _int_or_none(value: Optional[str]) -> Optional[int]:
+ try:
+ return int(value) # type: ignore
+ except (TypeError, ValueError):
+ return None
+
+
+def _chmod_and_move(src: Path, dst: Path) -> None:
+ """Set correct permission before moving a blob from tmp directory to cache dir.
+
+ Do not take into account the `umask` from the process as there is no convenient way
+ to get it that is thread-safe.
+
+ See:
+ - About umask: https://docs.python.org/3/library/os.html#os.umask
+ - Thread-safety: https://stackoverflow.com/a/70343066
+ - About solution: https://github.com/huggingface/huggingface_hub/pull/1220#issuecomment-1326211591
+ - Fix issue: https://github.com/huggingface/huggingface_hub/issues/1141
+ - Fix issue: https://github.com/huggingface/huggingface_hub/issues/1215
+ """
+ # Get umask by creating a temporary file in the cached repo folder.
+ tmp_file = dst.parent.parent / f"tmp_{uuid.uuid4()}"
+ try:
+ tmp_file.touch()
+ cache_dir_mode = Path(tmp_file).stat().st_mode
+ os.chmod(str(src), stat.S_IMODE(cache_dir_mode))
+ except OSError as e:
+ logger.warning(
+ f"Could not set the permissions on the file '{src}'. Error: {e}.\nContinuing without setting permissions."
+ )
+ finally:
+ try:
+ tmp_file.unlink()
+ except OSError:
+ # fails if `tmp_file.touch()` failed => do nothing
+ # See https://github.com/huggingface/huggingface_hub/issues/2359
+ pass
+
+ shutil.move(str(src), str(dst), copy_function=_copy_no_matter_what)
+
+
+def _copy_no_matter_what(src: str, dst: str) -> None:
+ """Copy file from src to dst.
+
+ If `shutil.copy2` fails, fallback to `shutil.copyfile`.
+ """
+ try:
+ # Copy file with metadata and permission
+ # Can fail e.g. if dst is an S3 mount
+ shutil.copy2(src, dst)
+ except OSError:
+ # Copy only file content
+ shutil.copyfile(src, dst)
+
+
+def _get_pointer_path(storage_folder: str, revision: str, relative_filename: str) -> str:
+ # Using `os.path.abspath` instead of `Path.resolve()` to avoid resolving symlinks
+ snapshot_path = os.path.join(storage_folder, "snapshots")
+ pointer_path = os.path.join(snapshot_path, revision, relative_filename)
+ if Path(os.path.abspath(snapshot_path)) not in Path(os.path.abspath(pointer_path)).parents:
+ raise ValueError(
+ "Invalid pointer path: cannot create pointer path in snapshot folder if"
+ f" `storage_folder='{storage_folder}'`, `revision='{revision}'` and"
+ f" `relative_filename='{relative_filename}'`."
+ )
+ return pointer_path
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..8977e202da9631530dee3009427eae6ad26ec17f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py
@@ -0,0 +1,11036 @@
+# coding=utf-8
+# Copyright 2019-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import inspect
+import json
+import re
+import struct
+import time
+import warnings
+from collections import defaultdict
+from concurrent.futures import Future, ThreadPoolExecutor
+from dataclasses import asdict, dataclass, field
+from datetime import datetime
+from functools import wraps
+from itertools import islice
+from pathlib import Path
+from textwrap import dedent
+from typing import (
+ TYPE_CHECKING,
+ Any,
+ BinaryIO,
+ Callable,
+ Dict,
+ Iterable,
+ Iterator,
+ List,
+ Literal,
+ Optional,
+ Tuple,
+ Type,
+ TypeVar,
+ Union,
+ overload,
+)
+from urllib.parse import quote
+
+import requests
+from requests.exceptions import HTTPError
+from tqdm.auto import tqdm as base_tqdm
+from tqdm.contrib.concurrent import thread_map
+
+from . import constants
+from ._commit_api import (
+ CommitOperation,
+ CommitOperationAdd,
+ CommitOperationCopy,
+ CommitOperationDelete,
+ _fetch_files_to_copy,
+ _fetch_upload_modes,
+ _prepare_commit_payload,
+ _upload_files,
+ _warn_on_overwriting_operations,
+)
+from ._inference_endpoints import InferenceEndpoint, InferenceEndpointType
+from ._jobs_api import JobInfo, JobSpec, ScheduledJobInfo, _create_job_spec
+from ._space_api import SpaceHardware, SpaceRuntime, SpaceStorage, SpaceVariable
+from ._upload_large_folder import upload_large_folder_internal
+from .community import (
+ Discussion,
+ DiscussionComment,
+ DiscussionStatusChange,
+ DiscussionTitleChange,
+ DiscussionWithDetails,
+ deserialize_event,
+)
+from .constants import (
+ DEFAULT_ETAG_TIMEOUT, # noqa: F401 # kept for backward compatibility
+ DEFAULT_REQUEST_TIMEOUT, # noqa: F401 # kept for backward compatibility
+ DEFAULT_REVISION, # noqa: F401 # kept for backward compatibility
+ DISCUSSION_STATUS, # noqa: F401 # kept for backward compatibility
+ DISCUSSION_TYPES, # noqa: F401 # kept for backward compatibility
+ ENDPOINT, # noqa: F401 # kept for backward compatibility
+ INFERENCE_ENDPOINTS_ENDPOINT, # noqa: F401 # kept for backward compatibility
+ REGEX_COMMIT_OID, # noqa: F401 # kept for backward compatibility
+ REPO_TYPE_MODEL, # noqa: F401 # kept for backward compatibility
+ REPO_TYPES, # noqa: F401 # kept for backward compatibility
+ REPO_TYPES_MAPPING, # noqa: F401 # kept for backward compatibility
+ REPO_TYPES_URL_PREFIXES, # noqa: F401 # kept for backward compatibility
+ SAFETENSORS_INDEX_FILE, # noqa: F401 # kept for backward compatibility
+ SAFETENSORS_MAX_HEADER_LENGTH, # noqa: F401 # kept for backward compatibility
+ SAFETENSORS_SINGLE_FILE, # noqa: F401 # kept for backward compatibility
+ SPACES_SDK_TYPES, # noqa: F401 # kept for backward compatibility
+ WEBHOOK_DOMAIN_T, # noqa: F401 # kept for backward compatibility
+ DiscussionStatusFilter, # noqa: F401 # kept for backward compatibility
+ DiscussionTypeFilter, # noqa: F401 # kept for backward compatibility
+)
+from .errors import (
+ BadRequestError,
+ EntryNotFoundError,
+ GatedRepoError,
+ HfHubHTTPError,
+ RepositoryNotFoundError,
+ RevisionNotFoundError,
+)
+from .file_download import HfFileMetadata, get_hf_file_metadata, hf_hub_url
+from .repocard_data import DatasetCardData, ModelCardData, SpaceCardData
+from .utils import (
+ DEFAULT_IGNORE_PATTERNS,
+ HfFolder, # noqa: F401 # kept for backward compatibility
+ LocalTokenNotFoundError,
+ NotASafetensorsRepoError,
+ SafetensorsFileMetadata,
+ SafetensorsParsingError,
+ SafetensorsRepoMetadata,
+ TensorInfo,
+ build_hf_headers,
+ chunk_iterable,
+ experimental,
+ filter_repo_objects,
+ fix_hf_endpoint_in_url,
+ get_session,
+ get_token,
+ hf_raise_for_status,
+ logging,
+ paginate,
+ parse_datetime,
+ validate_hf_hub_args,
+)
+from .utils import tqdm as hf_tqdm
+from .utils._auth import _get_token_from_environment, _get_token_from_file, _get_token_from_google_colab
+from .utils._deprecation import _deprecate_arguments, _deprecate_method
+from .utils._typing import CallableT
+from .utils.endpoint_helpers import _is_emission_within_threshold
+
+
+if TYPE_CHECKING:
+ from .inference._providers import PROVIDER_T
+
+R = TypeVar("R") # Return type
+CollectionItemType_T = Literal["model", "dataset", "space", "paper", "collection"]
+
+ExpandModelProperty_T = Literal[
+ "author",
+ "baseModels",
+ "cardData",
+ "childrenModelCount",
+ "config",
+ "createdAt",
+ "disabled",
+ "downloads",
+ "downloadsAllTime",
+ "gated",
+ "gguf",
+ "inference",
+ "inferenceProviderMapping",
+ "lastModified",
+ "library_name",
+ "likes",
+ "mask_token",
+ "model-index",
+ "pipeline_tag",
+ "private",
+ "resourceGroup",
+ "safetensors",
+ "sha",
+ "siblings",
+ "spaces",
+ "tags",
+ "transformersInfo",
+ "trendingScore",
+ "usedStorage",
+ "widgetData",
+ "xetEnabled",
+]
+
+ExpandDatasetProperty_T = Literal[
+ "author",
+ "cardData",
+ "citation",
+ "createdAt",
+ "description",
+ "disabled",
+ "downloads",
+ "downloadsAllTime",
+ "gated",
+ "lastModified",
+ "likes",
+ "paperswithcode_id",
+ "private",
+ "resourceGroup",
+ "sha",
+ "siblings",
+ "tags",
+ "trendingScore",
+ "usedStorage",
+ "xetEnabled",
+]
+
+ExpandSpaceProperty_T = Literal[
+ "author",
+ "cardData",
+ "createdAt",
+ "datasets",
+ "disabled",
+ "lastModified",
+ "likes",
+ "models",
+ "private",
+ "resourceGroup",
+ "runtime",
+ "sdk",
+ "sha",
+ "siblings",
+ "subdomain",
+ "tags",
+ "trendingScore",
+ "usedStorage",
+ "xetEnabled",
+]
+
+USERNAME_PLACEHOLDER = "hf_user"
+_REGEX_DISCUSSION_URL = re.compile(r".*/discussions/(\d+)$")
+
+_CREATE_COMMIT_NO_REPO_ERROR_MESSAGE = (
+ "\nNote: Creating a commit assumes that the repo already exists on the"
+ " Huggingface Hub. Please use `create_repo` if it's not the case."
+)
+_AUTH_CHECK_NO_REPO_ERROR_MESSAGE = (
+ "\nNote: The repository either does not exist or you do not have access rights."
+ " Please check the repository ID and your access permissions."
+ " If this is a private repository, ensure that your token is correct."
+)
+logger = logging.get_logger(__name__)
+
+
+def repo_type_and_id_from_hf_id(hf_id: str, hub_url: Optional[str] = None) -> Tuple[Optional[str], Optional[str], str]:
+ """
+ Returns the repo type and ID from a huggingface.co URL linking to a
+ repository
+
+ Args:
+ hf_id (`str`):
+ An URL or ID of a repository on the HF hub. Accepted values are:
+
+ - https://huggingface.co///
+ - https://huggingface.co//
+ - hf:////
+ - hf:///
+ - //
+ - /
+ -
+ hub_url (`str`, *optional*):
+ The URL of the HuggingFace Hub, defaults to https://huggingface.co
+
+ Returns:
+ A tuple with three items: repo_type (`str` or `None`), namespace (`str` or
+ `None`) and repo_id (`str`).
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If URL cannot be parsed.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `repo_type` is unknown.
+ """
+ input_hf_id = hf_id
+
+ hub_url = re.sub(r"https?://", "", hub_url if hub_url is not None else constants.ENDPOINT)
+ is_hf_url = hub_url in hf_id and "@" not in hf_id
+
+ HFFS_PREFIX = "hf://"
+ if hf_id.startswith(HFFS_PREFIX): # Remove "hf://" prefix if exists
+ hf_id = hf_id[len(HFFS_PREFIX) :]
+
+ url_segments = hf_id.split("/")
+ is_hf_id = len(url_segments) <= 3
+
+ namespace: Optional[str]
+ if is_hf_url:
+ namespace, repo_id = url_segments[-2:]
+ if namespace == hub_url:
+ namespace = None
+ if len(url_segments) > 2 and hub_url not in url_segments[-3]:
+ repo_type = url_segments[-3]
+ elif namespace in constants.REPO_TYPES_MAPPING:
+ # Mean canonical dataset or model
+ repo_type = constants.REPO_TYPES_MAPPING[namespace]
+ namespace = None
+ else:
+ repo_type = None
+ elif is_hf_id:
+ if len(url_segments) == 3:
+ # Passed // or //
+ repo_type, namespace, repo_id = url_segments[-3:]
+ elif len(url_segments) == 2:
+ if url_segments[0] in constants.REPO_TYPES_MAPPING:
+ # Passed '' or 'datasets/' for a canonical model or dataset
+ repo_type = constants.REPO_TYPES_MAPPING[url_segments[0]]
+ namespace = None
+ repo_id = hf_id.split("/")[-1]
+ else:
+ # Passed / or /
+ namespace, repo_id = hf_id.split("/")[-2:]
+ repo_type = None
+ else:
+ # Passed
+ repo_id = url_segments[0]
+ namespace, repo_type = None, None
+ else:
+ raise ValueError(f"Unable to retrieve user and repo ID from the passed HF ID: {hf_id}")
+
+ # Check if repo type is known (mapping "spaces" => "space" + empty value => `None`)
+ if repo_type in constants.REPO_TYPES_MAPPING:
+ repo_type = constants.REPO_TYPES_MAPPING[repo_type]
+ if repo_type == "":
+ repo_type = None
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Unknown `repo_type`: '{repo_type}' ('{input_hf_id}')")
+
+ return repo_type, namespace, repo_id
+
+
+@dataclass
+class LastCommitInfo(dict):
+ oid: str
+ title: str
+ date: datetime
+
+ def __post_init__(self): # hack to make LastCommitInfo backward compatible
+ self.update(asdict(self))
+
+
+@dataclass
+class BlobLfsInfo(dict):
+ size: int
+ sha256: str
+ pointer_size: int
+
+ def __post_init__(self): # hack to make BlobLfsInfo backward compatible
+ self.update(asdict(self))
+
+
+@dataclass
+class BlobSecurityInfo(dict):
+ safe: bool # duplicate information with "status" field, keeping it for backward compatibility
+ status: str
+ av_scan: Optional[Dict]
+ pickle_import_scan: Optional[Dict]
+
+ def __post_init__(self): # hack to make BlogSecurityInfo backward compatible
+ self.update(asdict(self))
+
+
+@dataclass
+class TransformersInfo(dict):
+ auto_model: str
+ custom_class: Optional[str] = None
+ # possible `pipeline_tag` values: https://github.com/huggingface/huggingface.js/blob/3ee32554b8620644a6287e786b2a83bf5caf559c/packages/tasks/src/pipelines.ts#L72
+ pipeline_tag: Optional[str] = None
+ processor: Optional[str] = None
+
+ def __post_init__(self): # hack to make TransformersInfo backward compatible
+ self.update(asdict(self))
+
+
+@dataclass
+class SafeTensorsInfo(dict):
+ parameters: Dict[str, int]
+ total: int
+
+ def __post_init__(self): # hack to make SafeTensorsInfo backward compatible
+ self.update(asdict(self))
+
+
+@dataclass
+class CommitInfo(str):
+ """Data structure containing information about a newly created commit.
+
+ Returned by any method that creates a commit on the Hub: [`create_commit`], [`upload_file`], [`upload_folder`],
+ [`delete_file`], [`delete_folder`]. It inherits from `str` for backward compatibility but using methods specific
+ to `str` is deprecated.
+
+ Attributes:
+ commit_url (`str`):
+ Url where to find the commit.
+
+ commit_message (`str`):
+ The summary (first line) of the commit that has been created.
+
+ commit_description (`str`):
+ Description of the commit that has been created. Can be empty.
+
+ oid (`str`):
+ Commit hash id. Example: `"91c54ad1727ee830252e457677f467be0bfd8a57"`.
+
+ pr_url (`str`, *optional*):
+ Url to the PR that has been created, if any. Populated when `create_pr=True`
+ is passed.
+
+ pr_revision (`str`, *optional*):
+ Revision of the PR that has been created, if any. Populated when
+ `create_pr=True` is passed. Example: `"refs/pr/1"`.
+
+ pr_num (`int`, *optional*):
+ Number of the PR discussion that has been created, if any. Populated when
+ `create_pr=True` is passed. Can be passed as `discussion_num` in
+ [`get_discussion_details`]. Example: `1`.
+
+ repo_url (`RepoUrl`):
+ Repo URL of the commit containing info like repo_id, repo_type, etc.
+
+ _url (`str`, *optional*):
+ Legacy url for `str` compatibility. Can be the url to the uploaded file on the Hub (if returned by
+ [`upload_file`]), to the uploaded folder on the Hub (if returned by [`upload_folder`]) or to the commit on
+ the Hub (if returned by [`create_commit`]). Defaults to `commit_url`. It is deprecated to use this
+ attribute. Please use `commit_url` instead.
+ """
+
+ commit_url: str
+ commit_message: str
+ commit_description: str
+ oid: str
+ pr_url: Optional[str] = None
+
+ # Computed from `commit_url` in `__post_init__`
+ repo_url: RepoUrl = field(init=False)
+
+ # Computed from `pr_url` in `__post_init__`
+ pr_revision: Optional[str] = field(init=False)
+ pr_num: Optional[str] = field(init=False)
+
+ # legacy url for `str` compatibility (ex: url to uploaded file, url to uploaded folder, url to PR, etc.)
+ _url: str = field(repr=False, default=None) # type: ignore # defaults to `commit_url`
+
+ def __new__(cls, *args, commit_url: str, _url: Optional[str] = None, **kwargs):
+ return str.__new__(cls, _url or commit_url)
+
+ def __post_init__(self):
+ """Populate pr-related fields after initialization.
+
+ See https://docs.python.org/3.10/library/dataclasses.html#post-init-processing.
+ """
+ # Repo info
+ self.repo_url = RepoUrl(self.commit_url.split("/commit/")[0])
+
+ # PR info
+ if self.pr_url is not None:
+ self.pr_revision = _parse_revision_from_pr_url(self.pr_url)
+ self.pr_num = int(self.pr_revision.split("/")[-1])
+ else:
+ self.pr_revision = None
+ self.pr_num = None
+
+
+@dataclass
+class AccessRequest:
+ """Data structure containing information about a user access request.
+
+ Attributes:
+ username (`str`):
+ Username of the user who requested access.
+ fullname (`str`):
+ Fullname of the user who requested access.
+ email (`Optional[str]`):
+ Email of the user who requested access.
+ Can only be `None` in the /accepted list if the user was granted access manually.
+ timestamp (`datetime`):
+ Timestamp of the request.
+ status (`Literal["pending", "accepted", "rejected"]`):
+ Status of the request. Can be one of `["pending", "accepted", "rejected"]`.
+ fields (`Dict[str, Any]`, *optional*):
+ Additional fields filled by the user in the gate form.
+ """
+
+ username: str
+ fullname: str
+ email: Optional[str]
+ timestamp: datetime
+ status: Literal["pending", "accepted", "rejected"]
+
+ # Additional fields filled by the user in the gate form
+ fields: Optional[Dict[str, Any]] = None
+
+
+@dataclass
+class WebhookWatchedItem:
+ """Data structure containing information about the items watched by a webhook.
+
+ Attributes:
+ type (`Literal["dataset", "model", "org", "space", "user"]`):
+ Type of the item to be watched. Can be one of `["dataset", "model", "org", "space", "user"]`.
+ name (`str`):
+ Name of the item to be watched. Can be the username, organization name, model name, dataset name or space name.
+ """
+
+ type: Literal["dataset", "model", "org", "space", "user"]
+ name: str
+
+
+@dataclass
+class WebhookInfo:
+ """Data structure containing information about a webhook.
+
+ One of `url` or `job` is specified, but not both.
+
+ Attributes:
+ id (`str`):
+ ID of the webhook.
+ url (`str`, *optional*):
+ URL of the webhook.
+ job (`JobSpec`, *optional*):
+ Specifications of the Job to trigger.
+ watched (`List[WebhookWatchedItem]`):
+ List of items watched by the webhook, see [`WebhookWatchedItem`].
+ domains (`List[WEBHOOK_DOMAIN_T]`):
+ List of domains the webhook is watching. Can be one of `["repo", "discussions"]`.
+ secret (`str`, *optional*):
+ Secret of the webhook.
+ disabled (`bool`):
+ Whether the webhook is disabled or not.
+ """
+
+ id: str
+ url: Optional[str]
+ job: Optional[JobSpec]
+ watched: List[WebhookWatchedItem]
+ domains: List[constants.WEBHOOK_DOMAIN_T]
+ secret: Optional[str]
+ disabled: bool
+
+
+class RepoUrl(str):
+ """Subclass of `str` describing a repo URL on the Hub.
+
+ `RepoUrl` is returned by `HfApi.create_repo`. It inherits from `str` for backward
+ compatibility. At initialization, the URL is parsed to populate properties:
+ - endpoint (`str`)
+ - namespace (`Optional[str]`)
+ - repo_name (`str`)
+ - repo_id (`str`)
+ - repo_type (`Literal["model", "dataset", "space"]`)
+ - url (`str`)
+
+ Args:
+ url (`Any`):
+ String value of the repo url.
+ endpoint (`str`, *optional*):
+ Endpoint of the Hub. Defaults to .
+
+ Example:
+ ```py
+ >>> RepoUrl('https://huggingface.co/gpt2')
+ RepoUrl('https://huggingface.co/gpt2', endpoint='https://huggingface.co', repo_type='model', repo_id='gpt2')
+
+ >>> RepoUrl('https://hub-ci.huggingface.co/datasets/dummy_user/dummy_dataset', endpoint='https://hub-ci.huggingface.co')
+ RepoUrl('https://hub-ci.huggingface.co/datasets/dummy_user/dummy_dataset', endpoint='https://hub-ci.huggingface.co', repo_type='dataset', repo_id='dummy_user/dummy_dataset')
+
+ >>> RepoUrl('hf://datasets/my-user/my-dataset')
+ RepoUrl('hf://datasets/my-user/my-dataset', endpoint='https://huggingface.co', repo_type='dataset', repo_id='user/dataset')
+
+ >>> HfApi.create_repo("dummy_model")
+ RepoUrl('https://huggingface.co/Wauplin/dummy_model', endpoint='https://huggingface.co', repo_type='model', repo_id='Wauplin/dummy_model')
+ ```
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If URL cannot be parsed.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `repo_type` is unknown.
+ """
+
+ def __new__(cls, url: Any, endpoint: Optional[str] = None):
+ url = fix_hf_endpoint_in_url(url, endpoint=endpoint)
+ return super(RepoUrl, cls).__new__(cls, url)
+
+ def __init__(self, url: Any, endpoint: Optional[str] = None) -> None:
+ super().__init__()
+ # Parse URL
+ self.endpoint = endpoint or constants.ENDPOINT
+ repo_type, namespace, repo_name = repo_type_and_id_from_hf_id(self, hub_url=self.endpoint)
+
+ # Populate fields
+ self.namespace = namespace
+ self.repo_name = repo_name
+ self.repo_id = repo_name if namespace is None else f"{namespace}/{repo_name}"
+ self.repo_type = repo_type or constants.REPO_TYPE_MODEL
+ self.url = str(self) # just in case it's needed
+
+ def __repr__(self) -> str:
+ return f"RepoUrl('{self}', endpoint='{self.endpoint}', repo_type='{self.repo_type}', repo_id='{self.repo_id}')"
+
+
+@dataclass
+class RepoSibling:
+ """
+ Contains basic information about a repo file inside a repo on the Hub.
+
+ > [!TIP]
+ > All attributes of this class are optional except `rfilename`. This is because only the file names are returned when
+ > listing repositories on the Hub (with [`list_models`], [`list_datasets`] or [`list_spaces`]). If you need more
+ > information like file size, blob id or lfs details, you must request them specifically from one repo at a time
+ > (using [`model_info`], [`dataset_info`] or [`space_info`]) as it adds more constraints on the backend server to
+ > retrieve these.
+
+ Attributes:
+ rfilename (str):
+ file name, relative to the repo root.
+ size (`int`, *optional*):
+ The file's size, in bytes. This attribute is defined when `files_metadata` argument of [`repo_info`] is set
+ to `True`. It's `None` otherwise.
+ blob_id (`str`, *optional*):
+ The file's git OID. This attribute is defined when `files_metadata` argument of [`repo_info`] is set to
+ `True`. It's `None` otherwise.
+ lfs (`BlobLfsInfo`, *optional*):
+ The file's LFS metadata. This attribute is defined when`files_metadata` argument of [`repo_info`] is set to
+ `True` and the file is stored with Git LFS. It's `None` otherwise.
+ """
+
+ rfilename: str
+ size: Optional[int] = None
+ blob_id: Optional[str] = None
+ lfs: Optional[BlobLfsInfo] = None
+
+
+@dataclass
+class RepoFile:
+ """
+ Contains information about a file on the Hub.
+
+ Attributes:
+ path (str):
+ file path relative to the repo root.
+ size (`int`):
+ The file's size, in bytes.
+ blob_id (`str`):
+ The file's git OID.
+ lfs (`BlobLfsInfo`):
+ The file's LFS metadata.
+ last_commit (`LastCommitInfo`, *optional*):
+ The file's last commit metadata. Only defined if [`list_repo_tree`] and [`get_paths_info`]
+ are called with `expand=True`.
+ security (`BlobSecurityInfo`, *optional*):
+ The file's security scan metadata. Only defined if [`list_repo_tree`] and [`get_paths_info`]
+ are called with `expand=True`.
+ """
+
+ path: str
+ size: int
+ blob_id: str
+ lfs: Optional[BlobLfsInfo] = None
+ last_commit: Optional[LastCommitInfo] = None
+ security: Optional[BlobSecurityInfo] = None
+
+ def __init__(self, **kwargs):
+ self.path = kwargs.pop("path")
+ self.size = kwargs.pop("size")
+ self.blob_id = kwargs.pop("oid")
+ lfs = kwargs.pop("lfs", None)
+ if lfs is not None:
+ lfs = BlobLfsInfo(size=lfs["size"], sha256=lfs["oid"], pointer_size=lfs["pointerSize"])
+ self.lfs = lfs
+ last_commit = kwargs.pop("lastCommit", None) or kwargs.pop("last_commit", None)
+ if last_commit is not None:
+ last_commit = LastCommitInfo(
+ oid=last_commit["id"], title=last_commit["title"], date=parse_datetime(last_commit["date"])
+ )
+ self.last_commit = last_commit
+ security = kwargs.pop("securityFileStatus", None)
+ if security is not None:
+ safe = security["status"] == "safe"
+ security = BlobSecurityInfo(
+ safe=safe,
+ status=security["status"],
+ av_scan=security["avScan"],
+ pickle_import_scan=security["pickleImportScan"],
+ )
+ self.security = security
+
+ # backwards compatibility
+ self.rfilename = self.path
+ self.lastCommit = self.last_commit
+
+
+@dataclass
+class RepoFolder:
+ """
+ Contains information about a folder on the Hub.
+
+ Attributes:
+ path (str):
+ folder path relative to the repo root.
+ tree_id (`str`):
+ The folder's git OID.
+ last_commit (`LastCommitInfo`, *optional*):
+ The folder's last commit metadata. Only defined if [`list_repo_tree`] and [`get_paths_info`]
+ are called with `expand=True`.
+ """
+
+ path: str
+ tree_id: str
+ last_commit: Optional[LastCommitInfo] = None
+
+ def __init__(self, **kwargs):
+ self.path = kwargs.pop("path")
+ self.tree_id = kwargs.pop("oid")
+ last_commit = kwargs.pop("lastCommit", None) or kwargs.pop("last_commit", None)
+ if last_commit is not None:
+ last_commit = LastCommitInfo(
+ oid=last_commit["id"], title=last_commit["title"], date=parse_datetime(last_commit["date"])
+ )
+ self.last_commit = last_commit
+
+
+@dataclass
+class InferenceProviderMapping:
+ provider: "PROVIDER_T" # Provider name
+ hf_model_id: str # ID of the model on the Hugging Face Hub
+ provider_id: str # ID of the model on the provider's side
+ status: Literal["error", "live", "staging"]
+ task: str
+
+ adapter: Optional[str] = None
+ adapter_weights_path: Optional[str] = None
+ type: Optional[Literal["single-model", "tag-filter"]] = None
+
+ def __init__(self, **kwargs):
+ self.provider = kwargs.pop("provider")
+ self.hf_model_id = kwargs.pop("hf_model_id")
+ self.provider_id = kwargs.pop("providerId")
+ self.status = kwargs.pop("status")
+ self.task = kwargs.pop("task")
+
+ self.adapter = kwargs.pop("adapter", None)
+ self.adapter_weights_path = kwargs.pop("adapterWeightsPath", None)
+ self.type = kwargs.pop("type", None)
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class ModelInfo:
+ """
+ Contains information about a model on the Hub. This object is returned by [`model_info`] and [`list_models`].
+
+ > [!TIP]
+ > Most attributes of this class are optional. This is because the data returned by the Hub depends on the query made.
+ > In general, the more specific the query, the more information is returned. On the contrary, when listing models
+ > using [`list_models`] only a subset of the attributes are returned.
+
+ Attributes:
+ id (`str`):
+ ID of model.
+ author (`str`, *optional*):
+ Author of the model.
+ sha (`str`, *optional*):
+ Repo SHA at this particular revision.
+ created_at (`datetime`, *optional*):
+ Date of creation of the repo on the Hub. Note that the lowest value is `2022-03-02T23:29:04.000Z`,
+ corresponding to the date when we began to store creation dates.
+ last_modified (`datetime`, *optional*):
+ Date of last commit to the repo.
+ private (`bool`):
+ Is the repo private.
+ disabled (`bool`, *optional*):
+ Is the repo disabled.
+ downloads (`int`):
+ Number of downloads of the model over the last 30 days.
+ downloads_all_time (`int`):
+ Cumulated number of downloads of the model since its creation.
+ gated (`Literal["auto", "manual", False]`, *optional*):
+ Is the repo gated.
+ If so, whether there is manual or automatic approval.
+ gguf (`Dict`, *optional*):
+ GGUF information of the model.
+ inference (`Literal["warm"]`, *optional*):
+ Status of the model on Inference Providers. Warm if the model is served by at least one provider.
+ inference_provider_mapping (`List[InferenceProviderMapping]`, *optional*):
+ A list of [`InferenceProviderMapping`] ordered after the user's provider order.
+ likes (`int`):
+ Number of likes of the model.
+ library_name (`str`, *optional*):
+ Library associated with the model.
+ tags (`List[str]`):
+ List of tags of the model. Compared to `card_data.tags`, contains extra tags computed by the Hub
+ (e.g. supported libraries, model's arXiv).
+ pipeline_tag (`str`, *optional*):
+ Pipeline tag associated with the model.
+ mask_token (`str`, *optional*):
+ Mask token used by the model.
+ widget_data (`Any`, *optional*):
+ Widget data associated with the model.
+ model_index (`Dict`, *optional*):
+ Model index for evaluation.
+ config (`Dict`, *optional*):
+ Model configuration.
+ transformers_info (`TransformersInfo`, *optional*):
+ Transformers-specific info (auto class, processor, etc.) associated with the model.
+ trending_score (`int`, *optional*):
+ Trending score of the model.
+ card_data (`ModelCardData`, *optional*):
+ Model Card Metadata as a [`huggingface_hub.repocard_data.ModelCardData`] object.
+ siblings (`List[RepoSibling]`):
+ List of [`huggingface_hub.hf_api.RepoSibling`] objects that constitute the model.
+ spaces (`List[str]`, *optional*):
+ List of spaces using the model.
+ safetensors (`SafeTensorsInfo`, *optional*):
+ Model's safetensors information.
+ security_repo_status (`Dict`, *optional*):
+ Model's security scan status.
+ """
+
+ id: str
+ author: Optional[str]
+ sha: Optional[str]
+ created_at: Optional[datetime]
+ last_modified: Optional[datetime]
+ private: Optional[bool]
+ disabled: Optional[bool]
+ downloads: Optional[int]
+ downloads_all_time: Optional[int]
+ gated: Optional[Literal["auto", "manual", False]]
+ gguf: Optional[Dict]
+ inference: Optional[Literal["warm"]]
+ inference_provider_mapping: Optional[List[InferenceProviderMapping]]
+ likes: Optional[int]
+ library_name: Optional[str]
+ tags: Optional[List[str]]
+ pipeline_tag: Optional[str]
+ mask_token: Optional[str]
+ card_data: Optional[ModelCardData]
+ widget_data: Optional[Any]
+ model_index: Optional[Dict]
+ config: Optional[Dict]
+ transformers_info: Optional[TransformersInfo]
+ trending_score: Optional[int]
+ siblings: Optional[List[RepoSibling]]
+ spaces: Optional[List[str]]
+ safetensors: Optional[SafeTensorsInfo]
+ security_repo_status: Optional[Dict]
+ xet_enabled: Optional[bool]
+
+ def __init__(self, **kwargs):
+ self.id = kwargs.pop("id")
+ self.author = kwargs.pop("author", None)
+ self.sha = kwargs.pop("sha", None)
+ last_modified = kwargs.pop("lastModified", None) or kwargs.pop("last_modified", None)
+ self.last_modified = parse_datetime(last_modified) if last_modified else None
+ created_at = kwargs.pop("createdAt", None) or kwargs.pop("created_at", None)
+ self.created_at = parse_datetime(created_at) if created_at else None
+ self.private = kwargs.pop("private", None)
+ self.gated = kwargs.pop("gated", None)
+ self.disabled = kwargs.pop("disabled", None)
+ self.downloads = kwargs.pop("downloads", None)
+ self.downloads_all_time = kwargs.pop("downloadsAllTime", None)
+ self.likes = kwargs.pop("likes", None)
+ self.library_name = kwargs.pop("library_name", None)
+ self.gguf = kwargs.pop("gguf", None)
+
+ self.inference = kwargs.pop("inference", None)
+
+ # little hack to simplify Inference Providers logic and make it backward and forward compatible
+ # right now, API returns a dict on model_info and a list on list_models. Let's harmonize to list.
+ mapping = kwargs.pop("inferenceProviderMapping", None)
+ if isinstance(mapping, list):
+ self.inference_provider_mapping = [
+ InferenceProviderMapping(**{**value, "hf_model_id": self.id}) for value in mapping
+ ]
+ elif isinstance(mapping, dict):
+ self.inference_provider_mapping = [
+ InferenceProviderMapping(**{**value, "hf_model_id": self.id, "provider": provider})
+ for provider, value in mapping.items()
+ ]
+ elif mapping is None:
+ self.inference_provider_mapping = None
+ else:
+ raise ValueError(
+ f"Unexpected type for `inferenceProviderMapping`. Expecting `dict` or `list`. Got {mapping}."
+ )
+
+ self.tags = kwargs.pop("tags", None)
+ self.pipeline_tag = kwargs.pop("pipeline_tag", None)
+ self.mask_token = kwargs.pop("mask_token", None)
+ self.trending_score = kwargs.pop("trendingScore", None)
+
+ card_data = kwargs.pop("cardData", None) or kwargs.pop("card_data", None)
+ self.card_data = (
+ ModelCardData(**card_data, ignore_metadata_errors=True) if isinstance(card_data, dict) else card_data
+ )
+
+ self.widget_data = kwargs.pop("widgetData", None)
+ self.model_index = kwargs.pop("model-index", None) or kwargs.pop("model_index", None)
+ self.config = kwargs.pop("config", None)
+ transformers_info = kwargs.pop("transformersInfo", None) or kwargs.pop("transformers_info", None)
+ self.transformers_info = TransformersInfo(**transformers_info) if transformers_info else None
+ siblings = kwargs.pop("siblings", None)
+ self.siblings = (
+ [
+ RepoSibling(
+ rfilename=sibling["rfilename"],
+ size=sibling.get("size"),
+ blob_id=sibling.get("blobId"),
+ lfs=(
+ BlobLfsInfo(
+ size=sibling["lfs"]["size"],
+ sha256=sibling["lfs"]["sha256"],
+ pointer_size=sibling["lfs"]["pointerSize"],
+ )
+ if sibling.get("lfs")
+ else None
+ ),
+ )
+ for sibling in siblings
+ ]
+ if siblings is not None
+ else None
+ )
+ self.spaces = kwargs.pop("spaces", None)
+ safetensors = kwargs.pop("safetensors", None)
+ self.safetensors = (
+ SafeTensorsInfo(
+ parameters=safetensors["parameters"],
+ total=safetensors["total"],
+ )
+ if safetensors
+ else None
+ )
+ self.security_repo_status = kwargs.pop("securityRepoStatus", None)
+ self.xet_enabled = kwargs.pop("xetEnabled", None)
+ # backwards compatibility
+ self.lastModified = self.last_modified
+ self.cardData = self.card_data
+ self.transformersInfo = self.transformers_info
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class DatasetInfo:
+ """
+ Contains information about a dataset on the Hub. This object is returned by [`dataset_info`] and [`list_datasets`].
+
+ > [!TIP]
+ > Most attributes of this class are optional. This is because the data returned by the Hub depends on the query made.
+ > In general, the more specific the query, the more information is returned. On the contrary, when listing datasets
+ > using [`list_datasets`] only a subset of the attributes are returned.
+
+ Attributes:
+ id (`str`):
+ ID of dataset.
+ author (`str`):
+ Author of the dataset.
+ sha (`str`):
+ Repo SHA at this particular revision.
+ created_at (`datetime`, *optional*):
+ Date of creation of the repo on the Hub. Note that the lowest value is `2022-03-02T23:29:04.000Z`,
+ corresponding to the date when we began to store creation dates.
+ last_modified (`datetime`, *optional*):
+ Date of last commit to the repo.
+ private (`bool`):
+ Is the repo private.
+ disabled (`bool`, *optional*):
+ Is the repo disabled.
+ gated (`Literal["auto", "manual", False]`, *optional*):
+ Is the repo gated.
+ If so, whether there is manual or automatic approval.
+ downloads (`int`):
+ Number of downloads of the dataset over the last 30 days.
+ downloads_all_time (`int`):
+ Cumulated number of downloads of the model since its creation.
+ likes (`int`):
+ Number of likes of the dataset.
+ tags (`List[str]`):
+ List of tags of the dataset.
+ card_data (`DatasetCardData`, *optional*):
+ Model Card Metadata as a [`huggingface_hub.repocard_data.DatasetCardData`] object.
+ siblings (`List[RepoSibling]`):
+ List of [`huggingface_hub.hf_api.RepoSibling`] objects that constitute the dataset.
+ paperswithcode_id (`str`, *optional*):
+ Papers with code ID of the dataset.
+ trending_score (`int`, *optional*):
+ Trending score of the dataset.
+ """
+
+ id: str
+ author: Optional[str]
+ sha: Optional[str]
+ created_at: Optional[datetime]
+ last_modified: Optional[datetime]
+ private: Optional[bool]
+ gated: Optional[Literal["auto", "manual", False]]
+ disabled: Optional[bool]
+ downloads: Optional[int]
+ downloads_all_time: Optional[int]
+ likes: Optional[int]
+ paperswithcode_id: Optional[str]
+ tags: Optional[List[str]]
+ trending_score: Optional[int]
+ card_data: Optional[DatasetCardData]
+ siblings: Optional[List[RepoSibling]]
+ xet_enabled: Optional[bool]
+
+ def __init__(self, **kwargs):
+ self.id = kwargs.pop("id")
+ self.author = kwargs.pop("author", None)
+ self.sha = kwargs.pop("sha", None)
+ created_at = kwargs.pop("createdAt", None) or kwargs.pop("created_at", None)
+ self.created_at = parse_datetime(created_at) if created_at else None
+ last_modified = kwargs.pop("lastModified", None) or kwargs.pop("last_modified", None)
+ self.last_modified = parse_datetime(last_modified) if last_modified else None
+ self.private = kwargs.pop("private", None)
+ self.gated = kwargs.pop("gated", None)
+ self.disabled = kwargs.pop("disabled", None)
+ self.downloads = kwargs.pop("downloads", None)
+ self.downloads_all_time = kwargs.pop("downloadsAllTime", None)
+ self.likes = kwargs.pop("likes", None)
+ self.paperswithcode_id = kwargs.pop("paperswithcode_id", None)
+ self.tags = kwargs.pop("tags", None)
+ self.trending_score = kwargs.pop("trendingScore", None)
+
+ card_data = kwargs.pop("cardData", None) or kwargs.pop("card_data", None)
+ self.card_data = (
+ DatasetCardData(**card_data, ignore_metadata_errors=True) if isinstance(card_data, dict) else card_data
+ )
+ siblings = kwargs.pop("siblings", None)
+ self.siblings = (
+ [
+ RepoSibling(
+ rfilename=sibling["rfilename"],
+ size=sibling.get("size"),
+ blob_id=sibling.get("blobId"),
+ lfs=(
+ BlobLfsInfo(
+ size=sibling["lfs"]["size"],
+ sha256=sibling["lfs"]["sha256"],
+ pointer_size=sibling["lfs"]["pointerSize"],
+ )
+ if sibling.get("lfs")
+ else None
+ ),
+ )
+ for sibling in siblings
+ ]
+ if siblings is not None
+ else None
+ )
+ self.xet_enabled = kwargs.pop("xetEnabled", None)
+ # backwards compatibility
+ self.lastModified = self.last_modified
+ self.cardData = self.card_data
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class SpaceInfo:
+ """
+ Contains information about a Space on the Hub. This object is returned by [`space_info`] and [`list_spaces`].
+
+ > [!TIP]
+ > Most attributes of this class are optional. This is because the data returned by the Hub depends on the query made.
+ > In general, the more specific the query, the more information is returned. On the contrary, when listing spaces
+ > using [`list_spaces`] only a subset of the attributes are returned.
+
+ Attributes:
+ id (`str`):
+ ID of the Space.
+ author (`str`, *optional*):
+ Author of the Space.
+ sha (`str`, *optional*):
+ Repo SHA at this particular revision.
+ created_at (`datetime`, *optional*):
+ Date of creation of the repo on the Hub. Note that the lowest value is `2022-03-02T23:29:04.000Z`,
+ corresponding to the date when we began to store creation dates.
+ last_modified (`datetime`, *optional*):
+ Date of last commit to the repo.
+ private (`bool`):
+ Is the repo private.
+ gated (`Literal["auto", "manual", False]`, *optional*):
+ Is the repo gated.
+ If so, whether there is manual or automatic approval.
+ disabled (`bool`, *optional*):
+ Is the Space disabled.
+ host (`str`, *optional*):
+ Host URL of the Space.
+ subdomain (`str`, *optional*):
+ Subdomain of the Space.
+ likes (`int`):
+ Number of likes of the Space.
+ tags (`List[str]`):
+ List of tags of the Space.
+ siblings (`List[RepoSibling]`):
+ List of [`huggingface_hub.hf_api.RepoSibling`] objects that constitute the Space.
+ card_data (`SpaceCardData`, *optional*):
+ Space Card Metadata as a [`huggingface_hub.repocard_data.SpaceCardData`] object.
+ runtime (`SpaceRuntime`, *optional*):
+ Space runtime information as a [`huggingface_hub.hf_api.SpaceRuntime`] object.
+ sdk (`str`, *optional*):
+ SDK used by the Space.
+ models (`List[str]`, *optional*):
+ List of models used by the Space.
+ datasets (`List[str]`, *optional*):
+ List of datasets used by the Space.
+ trending_score (`int`, *optional*):
+ Trending score of the Space.
+ """
+
+ id: str
+ author: Optional[str]
+ sha: Optional[str]
+ created_at: Optional[datetime]
+ last_modified: Optional[datetime]
+ private: Optional[bool]
+ gated: Optional[Literal["auto", "manual", False]]
+ disabled: Optional[bool]
+ host: Optional[str]
+ subdomain: Optional[str]
+ likes: Optional[int]
+ sdk: Optional[str]
+ tags: Optional[List[str]]
+ siblings: Optional[List[RepoSibling]]
+ trending_score: Optional[int]
+ card_data: Optional[SpaceCardData]
+ runtime: Optional[SpaceRuntime]
+ models: Optional[List[str]]
+ datasets: Optional[List[str]]
+ xet_enabled: Optional[bool]
+
+ def __init__(self, **kwargs):
+ self.id = kwargs.pop("id")
+ self.author = kwargs.pop("author", None)
+ self.sha = kwargs.pop("sha", None)
+ created_at = kwargs.pop("createdAt", None) or kwargs.pop("created_at", None)
+ self.created_at = parse_datetime(created_at) if created_at else None
+ last_modified = kwargs.pop("lastModified", None) or kwargs.pop("last_modified", None)
+ self.last_modified = parse_datetime(last_modified) if last_modified else None
+ self.private = kwargs.pop("private", None)
+ self.gated = kwargs.pop("gated", None)
+ self.disabled = kwargs.pop("disabled", None)
+ self.host = kwargs.pop("host", None)
+ self.subdomain = kwargs.pop("subdomain", None)
+ self.likes = kwargs.pop("likes", None)
+ self.sdk = kwargs.pop("sdk", None)
+ self.tags = kwargs.pop("tags", None)
+ self.trending_score = kwargs.pop("trendingScore", None)
+ card_data = kwargs.pop("cardData", None) or kwargs.pop("card_data", None)
+ self.card_data = (
+ SpaceCardData(**card_data, ignore_metadata_errors=True) if isinstance(card_data, dict) else card_data
+ )
+ siblings = kwargs.pop("siblings", None)
+ self.siblings = (
+ [
+ RepoSibling(
+ rfilename=sibling["rfilename"],
+ size=sibling.get("size"),
+ blob_id=sibling.get("blobId"),
+ lfs=(
+ BlobLfsInfo(
+ size=sibling["lfs"]["size"],
+ sha256=sibling["lfs"]["sha256"],
+ pointer_size=sibling["lfs"]["pointerSize"],
+ )
+ if sibling.get("lfs")
+ else None
+ ),
+ )
+ for sibling in siblings
+ ]
+ if siblings is not None
+ else None
+ )
+ runtime = kwargs.pop("runtime", None)
+ self.runtime = SpaceRuntime(runtime) if runtime else None
+ self.models = kwargs.pop("models", None)
+ self.datasets = kwargs.pop("datasets", None)
+ self.xet_enabled = kwargs.pop("xetEnabled", None)
+ # backwards compatibility
+ self.lastModified = self.last_modified
+ self.cardData = self.card_data
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class CollectionItem:
+ """
+ Contains information about an item of a Collection (model, dataset, Space, paper or collection).
+
+ Attributes:
+ item_object_id (`str`):
+ Unique ID of the item in the collection.
+ item_id (`str`):
+ ID of the underlying object on the Hub. Can be either a repo_id, a paper id or a collection slug.
+ e.g. `"jbilcke-hf/ai-comic-factory"`, `"2307.09288"`, `"celinah/cerebras-function-calling-682607169c35fbfa98b30b9a"`.
+ item_type (`str`):
+ Type of the underlying object. Can be one of `"model"`, `"dataset"`, `"space"`, `"paper"` or `"collection"`.
+ position (`int`):
+ Position of the item in the collection.
+ note (`str`, *optional*):
+ Note associated with the item, as plain text.
+ """
+
+ item_object_id: str # id in database
+ item_id: str # repo_id or paper id
+ item_type: str
+ position: int
+ note: Optional[str] = None
+
+ def __init__(
+ self,
+ _id: str,
+ id: str,
+ type: CollectionItemType_T,
+ position: int,
+ note: Optional[Dict] = None,
+ **kwargs,
+ ) -> None:
+ self.item_object_id: str = _id # id in database
+ self.item_id: str = id # repo_id or paper id
+ # if the item is a collection, override item_id with the slug
+ slug = kwargs.get("slug")
+ if slug is not None:
+ self.item_id = slug # collection slug
+ self.item_type: CollectionItemType_T = type
+ self.position: int = position
+ self.note: str = note["text"] if note is not None else None
+
+
+@dataclass
+class Collection:
+ """
+ Contains information about a Collection on the Hub.
+
+ Attributes:
+ slug (`str`):
+ Slug of the collection. E.g. `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ title (`str`):
+ Title of the collection. E.g. `"Recent models"`.
+ owner (`str`):
+ Owner of the collection. E.g. `"TheBloke"`.
+ items (`List[CollectionItem]`):
+ List of items in the collection.
+ last_updated (`datetime`):
+ Date of the last update of the collection.
+ position (`int`):
+ Position of the collection in the list of collections of the owner.
+ private (`bool`):
+ Whether the collection is private or not.
+ theme (`str`):
+ Theme of the collection. E.g. `"green"`.
+ upvotes (`int`):
+ Number of upvotes of the collection.
+ description (`str`, *optional*):
+ Description of the collection, as plain text.
+ url (`str`):
+ (property) URL of the collection on the Hub.
+ """
+
+ slug: str
+ title: str
+ owner: str
+ items: List[CollectionItem]
+ last_updated: datetime
+ position: int
+ private: bool
+ theme: str
+ upvotes: int
+ description: Optional[str] = None
+
+ def __init__(self, **kwargs) -> None:
+ self.slug = kwargs.pop("slug")
+ self.title = kwargs.pop("title")
+ self.owner = kwargs.pop("owner")
+ self.items = [CollectionItem(**item) for item in kwargs.pop("items")]
+ self.last_updated = parse_datetime(kwargs.pop("lastUpdated"))
+ self.position = kwargs.pop("position")
+ self.private = kwargs.pop("private")
+ self.theme = kwargs.pop("theme")
+ self.upvotes = kwargs.pop("upvotes")
+ self.description = kwargs.pop("description", None)
+ endpoint = kwargs.pop("endpoint", None)
+ if endpoint is None:
+ endpoint = constants.ENDPOINT
+ self._url = f"{endpoint}/collections/{self.slug}"
+
+ @property
+ def url(self) -> str:
+ """Returns the URL of the collection on the Hub."""
+ return self._url
+
+
+@dataclass
+class GitRefInfo:
+ """
+ Contains information about a git reference for a repo on the Hub.
+
+ Attributes:
+ name (`str`):
+ Name of the reference (e.g. tag name or branch name).
+ ref (`str`):
+ Full git ref on the Hub (e.g. `"refs/heads/main"` or `"refs/tags/v1.0"`).
+ target_commit (`str`):
+ OID of the target commit for the ref (e.g. `"e7da7f221d5bf496a48136c0cd264e630fe9fcc8"`)
+ """
+
+ name: str
+ ref: str
+ target_commit: str
+
+
+@dataclass
+class GitRefs:
+ """
+ Contains information about all git references for a repo on the Hub.
+
+ Object is returned by [`list_repo_refs`].
+
+ Attributes:
+ branches (`List[GitRefInfo]`):
+ A list of [`GitRefInfo`] containing information about branches on the repo.
+ converts (`List[GitRefInfo]`):
+ A list of [`GitRefInfo`] containing information about "convert" refs on the repo.
+ Converts are refs used (internally) to push preprocessed data in Dataset repos.
+ tags (`List[GitRefInfo]`):
+ A list of [`GitRefInfo`] containing information about tags on the repo.
+ pull_requests (`List[GitRefInfo]`, *optional*):
+ A list of [`GitRefInfo`] containing information about pull requests on the repo.
+ Only returned if `include_prs=True` is set.
+ """
+
+ branches: List[GitRefInfo]
+ converts: List[GitRefInfo]
+ tags: List[GitRefInfo]
+ pull_requests: Optional[List[GitRefInfo]] = None
+
+
+@dataclass
+class GitCommitInfo:
+ """
+ Contains information about a git commit for a repo on the Hub. Check out [`list_repo_commits`] for more details.
+
+ Attributes:
+ commit_id (`str`):
+ OID of the commit (e.g. `"e7da7f221d5bf496a48136c0cd264e630fe9fcc8"`)
+ authors (`List[str]`):
+ List of authors of the commit.
+ created_at (`datetime`):
+ Datetime when the commit was created.
+ title (`str`):
+ Title of the commit. This is a free-text value entered by the authors.
+ message (`str`):
+ Description of the commit. This is a free-text value entered by the authors.
+ formatted_title (`str`):
+ Title of the commit formatted as HTML. Only returned if `formatted=True` is set.
+ formatted_message (`str`):
+ Description of the commit formatted as HTML. Only returned if `formatted=True` is set.
+ """
+
+ commit_id: str
+
+ authors: List[str]
+ created_at: datetime
+ title: str
+ message: str
+
+ formatted_title: Optional[str]
+ formatted_message: Optional[str]
+
+
+@dataclass
+class UserLikes:
+ """
+ Contains information about a user likes on the Hub.
+
+ Attributes:
+ user (`str`):
+ Name of the user for which we fetched the likes.
+ total (`int`):
+ Total number of likes.
+ datasets (`List[str]`):
+ List of datasets liked by the user (as repo_ids).
+ models (`List[str]`):
+ List of models liked by the user (as repo_ids).
+ spaces (`List[str]`):
+ List of spaces liked by the user (as repo_ids).
+ """
+
+ # Metadata
+ user: str
+ total: int
+
+ # User likes
+ datasets: List[str]
+ models: List[str]
+ spaces: List[str]
+
+
+@dataclass
+class Organization:
+ """
+ Contains information about an organization on the Hub.
+
+ Attributes:
+ avatar_url (`str`):
+ URL of the organization's avatar.
+ name (`str`):
+ Name of the organization on the Hub (unique).
+ fullname (`str`):
+ Organization's full name.
+ details (`str`, *optional*):
+ Organization's description.
+ is_verified (`bool`, *optional*):
+ Whether the organization is verified.
+ is_following (`bool`, *optional*):
+ Whether the authenticated user follows this organization.
+ num_users (`int`, *optional*):
+ Number of members in the organization.
+ num_models (`int`, *optional*):
+ Number of models owned by the organization.
+ num_spaces (`int`, *optional*):
+ Number of Spaces owned by the organization.
+ num_datasets (`int`, *optional*):
+ Number of datasets owned by the organization.
+ num_followers (`int`, *optional*):
+ Number of followers of the organization.
+ """
+
+ avatar_url: str
+ name: str
+ fullname: str
+ details: Optional[str] = None
+ is_verified: Optional[bool] = None
+ is_following: Optional[bool] = None
+ num_users: Optional[int] = None
+ num_models: Optional[int] = None
+ num_spaces: Optional[int] = None
+ num_datasets: Optional[int] = None
+ num_followers: Optional[int] = None
+
+ def __init__(self, **kwargs) -> None:
+ self.avatar_url = kwargs.pop("avatarUrl", "")
+ self.name = kwargs.pop("name", "")
+ self.fullname = kwargs.pop("fullname", "")
+ self.details = kwargs.pop("details", None)
+ self.is_verified = kwargs.pop("isVerified", None)
+ self.is_following = kwargs.pop("isFollowing", None)
+ self.num_users = kwargs.pop("numUsers", None)
+ self.num_models = kwargs.pop("numModels", None)
+ self.num_spaces = kwargs.pop("numSpaces", None)
+ self.num_datasets = kwargs.pop("numDatasets", None)
+ self.num_followers = kwargs.pop("numFollowers", None)
+
+ # forward compatibility
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class User:
+ """
+ Contains information about a user on the Hub.
+
+ Attributes:
+ username (`str`):
+ Name of the user on the Hub (unique).
+ fullname (`str`):
+ User's full name.
+ avatar_url (`str`):
+ URL of the user's avatar.
+ details (`str`, *optional*):
+ User's details.
+ is_following (`bool`, *optional*):
+ Whether the authenticated user is following this user.
+ is_pro (`bool`, *optional*):
+ Whether the user is a pro user.
+ num_models (`int`, *optional*):
+ Number of models created by the user.
+ num_datasets (`int`, *optional*):
+ Number of datasets created by the user.
+ num_spaces (`int`, *optional*):
+ Number of spaces created by the user.
+ num_discussions (`int`, *optional*):
+ Number of discussions initiated by the user.
+ num_papers (`int`, *optional*):
+ Number of papers authored by the user.
+ num_upvotes (`int`, *optional*):
+ Number of upvotes received by the user.
+ num_likes (`int`, *optional*):
+ Number of likes given by the user.
+ num_following (`int`, *optional*):
+ Number of users this user is following.
+ num_followers (`int`, *optional*):
+ Number of users following this user.
+ orgs (list of [`Organization`]):
+ List of organizations the user is part of.
+ """
+
+ # Metadata
+ username: str
+ fullname: str
+ avatar_url: str
+ details: Optional[str] = None
+ is_following: Optional[bool] = None
+ is_pro: Optional[bool] = None
+ num_models: Optional[int] = None
+ num_datasets: Optional[int] = None
+ num_spaces: Optional[int] = None
+ num_discussions: Optional[int] = None
+ num_papers: Optional[int] = None
+ num_upvotes: Optional[int] = None
+ num_likes: Optional[int] = None
+ num_following: Optional[int] = None
+ num_followers: Optional[int] = None
+ orgs: List[Organization] = field(default_factory=list)
+
+ def __init__(self, **kwargs) -> None:
+ self.username = kwargs.pop("user", "")
+ self.fullname = kwargs.pop("fullname", "")
+ self.avatar_url = kwargs.pop("avatarUrl", "")
+ self.is_following = kwargs.pop("isFollowing", None)
+ self.is_pro = kwargs.pop("isPro", None)
+ self.details = kwargs.pop("details", None)
+ self.num_models = kwargs.pop("numModels", None)
+ self.num_datasets = kwargs.pop("numDatasets", None)
+ self.num_spaces = kwargs.pop("numSpaces", None)
+ self.num_discussions = kwargs.pop("numDiscussions", None)
+ self.num_papers = kwargs.pop("numPapers", None)
+ self.num_upvotes = kwargs.pop("numUpvotes", None)
+ self.num_likes = kwargs.pop("numLikes", None)
+ self.num_following = kwargs.pop("numFollowing", None)
+ self.num_followers = kwargs.pop("numFollowers", None)
+ self.user_type = kwargs.pop("type", None)
+ self.orgs = [Organization(**org) for org in kwargs.pop("orgs", [])]
+
+ # forward compatibility
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class PaperInfo:
+ """
+ Contains information about a paper on the Hub.
+
+ Attributes:
+ id (`str`):
+ arXiv paper ID.
+ authors (`List[str]`, **optional**):
+ Names of paper authors
+ published_at (`datetime`, **optional**):
+ Date paper published.
+ title (`str`, **optional**):
+ Title of the paper.
+ summary (`str`, **optional**):
+ Summary of the paper.
+ upvotes (`int`, **optional**):
+ Number of upvotes for the paper on the Hub.
+ discussion_id (`str`, **optional**):
+ Discussion ID for the paper on the Hub.
+ source (`str`, **optional**):
+ Source of the paper.
+ comments (`int`, **optional**):
+ Number of comments for the paper on the Hub.
+ submitted_at (`datetime`, **optional**):
+ Date paper appeared in daily papers on the Hub.
+ submitted_by (`User`, **optional**):
+ Information about who submitted the daily paper.
+ """
+
+ id: str
+ authors: Optional[List[str]]
+ published_at: Optional[datetime]
+ title: Optional[str]
+ summary: Optional[str]
+ upvotes: Optional[int]
+ discussion_id: Optional[str]
+ source: Optional[str]
+ comments: Optional[int]
+ submitted_at: Optional[datetime]
+ submitted_by: Optional[User]
+
+ def __init__(self, **kwargs) -> None:
+ paper = kwargs.pop("paper", {})
+ self.id = kwargs.pop("id", None) or paper.pop("id", None)
+ authors = paper.pop("authors", None) or kwargs.pop("authors", None)
+ self.authors = [author.pop("name", None) for author in authors] if authors else None
+ published_at = paper.pop("publishedAt", None) or kwargs.pop("publishedAt", None)
+ self.published_at = parse_datetime(published_at) if published_at else None
+ self.title = kwargs.pop("title", None)
+ self.source = kwargs.pop("source", None)
+ self.summary = paper.pop("summary", None) or kwargs.pop("summary", None)
+ self.upvotes = paper.pop("upvotes", None) or kwargs.pop("upvotes", None)
+ self.discussion_id = paper.pop("discussionId", None) or kwargs.pop("discussionId", None)
+ self.comments = kwargs.pop("numComments", 0)
+ submitted_at = kwargs.pop("publishedAt", None) or kwargs.pop("submittedOnDailyAt", None)
+ self.submitted_at = parse_datetime(submitted_at) if submitted_at else None
+ submitted_by = kwargs.pop("submittedBy", None) or kwargs.pop("submittedOnDailyBy", None)
+ self.submitted_by = User(**submitted_by) if submitted_by else None
+
+ # forward compatibility
+ self.__dict__.update(**kwargs)
+
+
+@dataclass
+class LFSFileInfo:
+ """
+ Contains information about a file stored as LFS on a repo on the Hub.
+
+ Used in the context of listing and permanently deleting LFS files from a repo to free-up space.
+ See [`list_lfs_files`] and [`permanently_delete_lfs_files`] for more details.
+
+ Git LFS files are tracked using SHA-256 object IDs, rather than file paths, to optimize performance
+ This approach is necessary because a single object can be referenced by multiple paths across different commits,
+ making it impractical to search and resolve these connections. Check out [our documentation](https://huggingface.co/docs/hub/storage-limits#advanced-track-lfs-file-references)
+ to learn how to know which filename(s) is(are) associated with each SHA.
+
+ Attributes:
+ file_oid (`str`):
+ SHA-256 object ID of the file. This is the identifier to pass when permanently deleting the file.
+ filename (`str`):
+ Possible filename for the LFS object. See the note above for more information.
+ oid (`str`):
+ OID of the LFS object.
+ pushed_at (`datetime`):
+ Date the LFS object was pushed to the repo.
+ ref (`str`, *optional*):
+ Ref where the LFS object has been pushed (if any).
+ size (`int`):
+ Size of the LFS object.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> lfs_files = api.list_lfs_files("username/my-cool-repo")
+
+ # Filter files files to delete based on a combination of `filename`, `pushed_at`, `ref` or `size`.
+ # e.g. select only LFS files in the "checkpoints" folder
+ >>> lfs_files_to_delete = (lfs_file for lfs_file in lfs_files if lfs_file.filename.startswith("checkpoints/"))
+
+ # Permanently delete LFS files
+ >>> api.permanently_delete_lfs_files("username/my-cool-repo", lfs_files_to_delete)
+ ```
+ """
+
+ file_oid: str
+ filename: str
+ oid: str
+ pushed_at: datetime
+ ref: Optional[str]
+ size: int
+
+ def __init__(self, **kwargs) -> None:
+ self.file_oid = kwargs.pop("fileOid")
+ self.filename = kwargs.pop("filename")
+ self.oid = kwargs.pop("oid")
+ self.pushed_at = parse_datetime(kwargs.pop("pushedAt"))
+ self.ref = kwargs.pop("ref", None)
+ self.size = kwargs.pop("size")
+
+ # forward compatibility
+ self.__dict__.update(**kwargs)
+
+
+def future_compatible(fn: CallableT) -> CallableT:
+ """Wrap a method of `HfApi` to handle `run_as_future=True`.
+
+ A method flagged as "future_compatible" will be called in a thread if `run_as_future=True` and return a
+ `concurrent.futures.Future` instance. Otherwise, it will be called normally and return the result.
+ """
+ sig = inspect.signature(fn)
+ args_params = list(sig.parameters)[1:] # remove "self" from list
+
+ @wraps(fn)
+ def _inner(self, *args, **kwargs):
+ # Get `run_as_future` value if provided (default to False)
+ if "run_as_future" in kwargs:
+ run_as_future = kwargs["run_as_future"]
+ kwargs["run_as_future"] = False # avoid recursion error
+ else:
+ run_as_future = False
+ for param, value in zip(args_params, args):
+ if param == "run_as_future":
+ run_as_future = value
+ break
+
+ # Call the function in a thread if `run_as_future=True`
+ if run_as_future:
+ return self.run_as_future(fn, self, *args, **kwargs)
+
+ # Otherwise, call the function normally
+ return fn(self, *args, **kwargs)
+
+ _inner.is_future_compatible = True # type: ignore
+ return _inner # type: ignore
+
+
+class HfApi:
+ """
+ Client to interact with the Hugging Face Hub via HTTP.
+
+ The client is initialized with some high-level settings used in all requests
+ made to the Hub (HF endpoint, authentication, user agents...). Using the `HfApi`
+ client is preferred but not mandatory as all of its public methods are exposed
+ directly at the root of `huggingface_hub`.
+
+ Args:
+ endpoint (`str`, *optional*):
+ Endpoint of the Hub. Defaults to .
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ library_name (`str`, *optional*):
+ The name of the library that is making the HTTP request. Will be added to
+ the user-agent header. Example: `"transformers"`.
+ library_version (`str`, *optional*):
+ The version of the library that is making the HTTP request. Will be added
+ to the user-agent header. Example: `"4.24.0"`.
+ user_agent (`str`, `dict`, *optional*):
+ The user agent info in the form of a dictionary or a single string. It will
+ be completed with information about the installed packages.
+ headers (`dict`, *optional*):
+ Additional headers to be sent with each request. Example: `{"X-My-Header": "value"}`.
+ Headers passed here are taking precedence over the default headers.
+ """
+
+ def __init__(
+ self,
+ endpoint: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ library_name: Optional[str] = None,
+ library_version: Optional[str] = None,
+ user_agent: Union[Dict, str, None] = None,
+ headers: Optional[Dict[str, str]] = None,
+ ) -> None:
+ self.endpoint = endpoint if endpoint is not None else constants.ENDPOINT
+ self.token = token
+ self.library_name = library_name
+ self.library_version = library_version
+ self.user_agent = user_agent
+ self.headers = headers
+ self._thread_pool: Optional[ThreadPoolExecutor] = None
+
+ def run_as_future(self, fn: Callable[..., R], *args, **kwargs) -> Future[R]:
+ """
+ Run a method in the background and return a Future instance.
+
+ The main goal is to run methods without blocking the main thread (e.g. to push data during a training).
+ Background jobs are queued to preserve order but are not ran in parallel. If you need to speed-up your scripts
+ by parallelizing lots of call to the API, you must setup and use your own [ThreadPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor).
+
+ Note: Most-used methods like [`upload_file`], [`upload_folder`] and [`create_commit`] have a `run_as_future: bool`
+ argument to directly call them in the background. This is equivalent to calling `api.run_as_future(...)` on them
+ but less verbose.
+
+ Args:
+ fn (`Callable`):
+ The method to run in the background.
+ *args, **kwargs:
+ Arguments with which the method will be called.
+
+ Return:
+ `Future`: a [Future](https://docs.python.org/3/library/concurrent.futures.html#future-objects) instance to
+ get the result of the task.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> future = api.run_as_future(api.whoami) # instant
+ >>> future.done()
+ False
+ >>> future.result() # wait until complete and return result
+ (...)
+ >>> future.done()
+ True
+ ```
+ """
+ if self._thread_pool is None:
+ self._thread_pool = ThreadPoolExecutor(max_workers=1)
+ self._thread_pool
+ return self._thread_pool.submit(fn, *args, **kwargs)
+
+ @validate_hf_hub_args
+ def whoami(self, token: Union[bool, str, None] = None) -> Dict:
+ """
+ Call HF API to know "whoami".
+
+ Args:
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ # Get the effective token using the helper function get_token
+ effective_token = token or self.token or get_token() or True
+ r = get_session().get(
+ f"{self.endpoint}/api/whoami-v2",
+ headers=self._build_hf_headers(token=effective_token),
+ )
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as e:
+ if e.response.status_code == 401:
+ error_message = "Invalid user token."
+ # Check which token is the effective one and generate the error message accordingly
+ if effective_token == _get_token_from_google_colab():
+ error_message += " The token from Google Colab vault is invalid. Please update it from the UI."
+ elif effective_token == _get_token_from_environment():
+ error_message += (
+ " The token from HF_TOKEN environment variable is invalid. "
+ "Note that HF_TOKEN takes precedence over `hf auth login`."
+ )
+ elif effective_token == _get_token_from_file():
+ error_message += " The token stored is invalid. Please run `hf auth login` to update it."
+ raise HTTPError(error_message, request=e.request, response=e.response) from e
+ raise
+ return r.json()
+
+ @_deprecate_method(
+ version="1.0",
+ message=(
+ "Permissions are more complex than when `get_token_permission` was first introduced. "
+ "OAuth and fine-grain tokens allows for more detailed permissions. "
+ "If you need to know the permissions associated with a token, please use `whoami` and check the `'auth'` key."
+ ),
+ )
+ def get_token_permission(
+ self, token: Union[bool, str, None] = None
+ ) -> Literal["read", "write", "fineGrained", None]:
+ """
+ Check if a given `token` is valid and return its permissions.
+
+ > [!WARNING]
+ > This method is deprecated and will be removed in version 1.0. Permissions are more complex than when
+ > `get_token_permission` was first introduced. OAuth and fine-grain tokens allows for more detailed permissions.
+ > If you need to know the permissions associated with a token, please use `whoami` and check the `'auth'` key.
+
+ For more details about tokens, please refer to https://huggingface.co/docs/hub/security-tokens#what-are-user-access-tokens.
+
+ Args:
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Literal["read", "write", "fineGrained", None]`: Permission granted by the token ("read" or "write"). Returns `None` if no
+ token passed, if token is invalid or if role is not returned by the server. This typically happens when the token is an OAuth token.
+ """
+ try:
+ return self.whoami(token=token)["auth"]["accessToken"]["role"]
+ except (LocalTokenNotFoundError, HTTPError, KeyError):
+ return None
+
+ def get_model_tags(self) -> Dict:
+ """
+ List all valid model tags as a nested namespace object
+ """
+ path = f"{self.endpoint}/api/models-tags-by-type"
+ r = get_session().get(path)
+ hf_raise_for_status(r)
+ return r.json()
+
+ def get_dataset_tags(self) -> Dict:
+ """
+ List all valid dataset tags as a nested namespace object.
+ """
+ path = f"{self.endpoint}/api/datasets-tags-by-type"
+ r = get_session().get(path)
+ hf_raise_for_status(r)
+ return r.json()
+
+ @_deprecate_arguments(
+ version="1.0", deprecated_args=["language", "library", "task", "tags"], custom_message="Use `filter` instead."
+ )
+ @validate_hf_hub_args
+ def list_models(
+ self,
+ *,
+ # Search-query parameter
+ filter: Union[str, Iterable[str], None] = None,
+ author: Optional[str] = None,
+ apps: Optional[Union[str, List[str]]] = None,
+ gated: Optional[bool] = None,
+ inference: Optional[Literal["warm"]] = None,
+ inference_provider: Optional[Union[Literal["all"], "PROVIDER_T", List["PROVIDER_T"]]] = None,
+ model_name: Optional[str] = None,
+ trained_dataset: Optional[Union[str, List[str]]] = None,
+ search: Optional[str] = None,
+ pipeline_tag: Optional[str] = None,
+ emissions_thresholds: Optional[Tuple[float, float]] = None,
+ # Sorting and pagination parameters
+ sort: Union[Literal["last_modified"], str, None] = None,
+ direction: Optional[Literal[-1]] = None,
+ limit: Optional[int] = None,
+ # Additional data to fetch
+ expand: Optional[List[ExpandModelProperty_T]] = None,
+ full: Optional[bool] = None,
+ cardData: bool = False,
+ fetch_config: bool = False,
+ token: Union[bool, str, None] = None,
+ # Deprecated arguments - use `filter` instead
+ language: Optional[Union[str, List[str]]] = None,
+ library: Optional[Union[str, List[str]]] = None,
+ tags: Optional[Union[str, List[str]]] = None,
+ task: Optional[Union[str, List[str]]] = None,
+ ) -> Iterable[ModelInfo]:
+ """
+ List models hosted on the Huggingface Hub, given some filters.
+
+ Args:
+ filter (`str` or `Iterable[str]`, *optional*):
+ A string or list of string to filter models on the Hub.
+ Models can be filtered by library, language, task, tags, and more.
+ author (`str`, *optional*):
+ A string which identify the author (user or organization) of the
+ returned models.
+ apps (`str` or `List`, *optional*):
+ A string or list of strings to filter models on the Hub that
+ support the specified apps. Example values include `"ollama"` or `["ollama", "vllm"]`.
+ gated (`bool`, *optional*):
+ A boolean to filter models on the Hub that are gated or not. By default, all models are returned.
+ If `gated=True` is passed, only gated models are returned.
+ If `gated=False` is passed, only non-gated models are returned.
+ inference (`Literal["warm"]`, *optional*):
+ If "warm", filter models on the Hub currently served by at least one provider.
+ inference_provider (`Literal["all"]` or `str`, *optional*):
+ A string to filter models on the Hub that are served by a specific provider.
+ Pass `"all"` to get all models served by at least one provider.
+ library (`str` or `List`, *optional*):
+ Deprecated. Pass a library name in `filter` to filter models by library.
+ language (`str` or `List`, *optional*):
+ Deprecated. Pass a language in `filter` to filter models by language.
+ model_name (`str`, *optional*):
+ A string that contain complete or partial names for models on the
+ Hub, such as "bert" or "bert-base-cased"
+ task (`str` or `List`, *optional*):
+ Deprecated. Pass a task in `filter` to filter models by task.
+ trained_dataset (`str` or `List`, *optional*):
+ A string tag or a list of string tags of the trained dataset for a
+ model on the Hub.
+ tags (`str` or `List`, *optional*):
+ Deprecated. Pass tags in `filter` to filter models by tags.
+ search (`str`, *optional*):
+ A string that will be contained in the returned model ids.
+ pipeline_tag (`str`, *optional*):
+ A string pipeline tag to filter models on the Hub by, such as `summarization`.
+ emissions_thresholds (`Tuple`, *optional*):
+ A tuple of two ints or floats representing a minimum and maximum
+ carbon footprint to filter the resulting models with in grams.
+ sort (`Literal["last_modified"]` or `str`, *optional*):
+ The key with which to sort the resulting models. Possible values are "last_modified", "trending_score",
+ "created_at", "downloads" and "likes".
+ direction (`Literal[-1]` or `int`, *optional*):
+ Direction in which to sort. The value `-1` sorts by descending
+ order while all other values sort by ascending order.
+ limit (`int`, *optional*):
+ The limit on the number of models fetched. Leaving this option
+ to `None` fetches all models.
+ expand (`List[ExpandModelProperty_T]`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `full`, `cardData` or `fetch_config` are passed.
+ Possible values are `"author"`, `"cardData"`, `"config"`, `"createdAt"`, `"disabled"`, `"downloads"`, `"downloadsAllTime"`, `"gated"`, `"gguf"`, `"inference"`, `"inferenceProviderMapping"`, `"lastModified"`, `"library_name"`, `"likes"`, `"mask_token"`, `"model-index"`, `"pipeline_tag"`, `"private"`, `"safetensors"`, `"sha"`, `"siblings"`, `"spaces"`, `"tags"`, `"transformersInfo"`, `"trendingScore"`, `"widgetData"`, `"resourceGroup"` and `"xetEnabled"`.
+ full (`bool`, *optional*):
+ Whether to fetch all model data, including the `last_modified`,
+ the `sha`, the files and the `tags`. This is set to `True` by
+ default when using a filter.
+ cardData (`bool`, *optional*):
+ Whether to grab the metadata for the model as well. Can contain
+ useful information such as carbon emissions, metrics, and
+ datasets trained on.
+ fetch_config (`bool`, *optional*):
+ Whether to fetch the model configs as well. This is not included
+ in `full` due to its size.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+
+ Returns:
+ `Iterable[ModelInfo]`: an iterable of [`huggingface_hub.hf_api.ModelInfo`] objects.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import HfApi
+
+ >>> api = HfApi()
+
+ # List all models
+ >>> api.list_models()
+
+ # List text classification models
+ >>> api.list_models(filter="text-classification")
+
+ # List models from the KerasHub library
+ >>> api.list_models(filter="keras-hub")
+
+ # List models served by Cohere
+ >>> api.list_models(inference_provider="cohere")
+
+ # List models with "bert" in their name
+ >>> api.list_models(search="bert")
+
+ # List models with "bert" in their name and pushed by google
+ >>> api.list_models(search="bert", author="google")
+ ```
+ """
+ if expand and (full or cardData or fetch_config):
+ raise ValueError("`expand` cannot be used if `full`, `cardData` or `fetch_config` are passed.")
+
+ if emissions_thresholds is not None and not cardData:
+ raise ValueError("`emissions_thresholds` were passed without setting `cardData=True`.")
+
+ path = f"{self.endpoint}/api/models"
+ headers = self._build_hf_headers(token=token)
+ params: Dict[str, Any] = {}
+
+ # Build the filter list
+ filter_list: List[str] = []
+ if filter:
+ filter_list.extend([filter] if isinstance(filter, str) else filter)
+ if library:
+ filter_list.extend([library] if isinstance(library, str) else library)
+ if task:
+ filter_list.extend([task] if isinstance(task, str) else task)
+ if trained_dataset:
+ if isinstance(trained_dataset, str):
+ trained_dataset = [trained_dataset]
+ for dataset in trained_dataset:
+ if not dataset.startswith("dataset:"):
+ dataset = f"dataset:{dataset}"
+ filter_list.append(dataset)
+ if language:
+ filter_list.extend([language] if isinstance(language, str) else language)
+ if tags:
+ filter_list.extend([tags] if isinstance(tags, str) else tags)
+ if len(filter_list) > 0:
+ params["filter"] = filter_list
+
+ # Handle other query params
+ if author:
+ params["author"] = author
+ if apps:
+ if isinstance(apps, str):
+ apps = [apps]
+ params["apps"] = apps
+ if gated is not None:
+ params["gated"] = gated
+ if inference is not None:
+ params["inference"] = inference
+ if inference_provider is not None:
+ params["inference_provider"] = inference_provider
+ if pipeline_tag:
+ params["pipeline_tag"] = pipeline_tag
+ search_list = []
+ if model_name:
+ search_list.append(model_name)
+ if search:
+ search_list.append(search)
+ if len(search_list) > 0:
+ params["search"] = search_list
+ if sort is not None:
+ params["sort"] = (
+ "lastModified"
+ if sort == "last_modified"
+ else "trendingScore"
+ if sort == "trending_score"
+ else "createdAt"
+ if sort == "created_at"
+ else sort
+ )
+ if direction is not None:
+ params["direction"] = direction
+ if limit is not None:
+ params["limit"] = limit
+
+ # Request additional data
+ if full:
+ params["full"] = True
+ if fetch_config:
+ params["config"] = True
+ if cardData:
+ params["cardData"] = True
+ if expand:
+ params["expand"] = expand
+
+ # `items` is a generator
+ items = paginate(path, params=params, headers=headers)
+ if limit is not None:
+ items = islice(items, limit) # Do not iterate over all pages
+ for item in items:
+ if "siblings" not in item:
+ item["siblings"] = None
+ model_info = ModelInfo(**item)
+ if emissions_thresholds is None or _is_emission_within_threshold(model_info, *emissions_thresholds):
+ yield model_info
+
+ @_deprecate_arguments(version="1.0", deprecated_args=["tags"], custom_message="Use `filter` instead.")
+ @validate_hf_hub_args
+ def list_datasets(
+ self,
+ *,
+ # Search-query parameter
+ filter: Union[str, Iterable[str], None] = None,
+ author: Optional[str] = None,
+ benchmark: Optional[Union[str, List[str]]] = None,
+ dataset_name: Optional[str] = None,
+ gated: Optional[bool] = None,
+ language_creators: Optional[Union[str, List[str]]] = None,
+ language: Optional[Union[str, List[str]]] = None,
+ multilinguality: Optional[Union[str, List[str]]] = None,
+ size_categories: Optional[Union[str, List[str]]] = None,
+ task_categories: Optional[Union[str, List[str]]] = None,
+ task_ids: Optional[Union[str, List[str]]] = None,
+ search: Optional[str] = None,
+ # Sorting and pagination parameters
+ sort: Optional[Union[Literal["last_modified"], str]] = None,
+ direction: Optional[Literal[-1]] = None,
+ limit: Optional[int] = None,
+ # Additional data to fetch
+ expand: Optional[List[ExpandDatasetProperty_T]] = None,
+ full: Optional[bool] = None,
+ token: Union[bool, str, None] = None,
+ # Deprecated arguments - use `filter` instead
+ tags: Optional[Union[str, List[str]]] = None,
+ ) -> Iterable[DatasetInfo]:
+ """
+ List datasets hosted on the Huggingface Hub, given some filters.
+
+ Args:
+ filter (`str` or `Iterable[str]`, *optional*):
+ A string or list of string to filter datasets on the hub.
+ author (`str`, *optional*):
+ A string which identify the author of the returned datasets.
+ benchmark (`str` or `List`, *optional*):
+ A string or list of strings that can be used to identify datasets on
+ the Hub by their official benchmark.
+ dataset_name (`str`, *optional*):
+ A string or list of strings that can be used to identify datasets on
+ the Hub by its name, such as `SQAC` or `wikineural`
+ gated (`bool`, *optional*):
+ A boolean to filter datasets on the Hub that are gated or not. By default, all datasets are returned.
+ If `gated=True` is passed, only gated datasets are returned.
+ If `gated=False` is passed, only non-gated datasets are returned.
+ language_creators (`str` or `List`, *optional*):
+ A string or list of strings that can be used to identify datasets on
+ the Hub with how the data was curated, such as `crowdsourced` or
+ `machine_generated`.
+ language (`str` or `List`, *optional*):
+ A string or list of strings representing a two-character language to
+ filter datasets by on the Hub.
+ multilinguality (`str` or `List`, *optional*):
+ A string or list of strings representing a filter for datasets that
+ contain multiple languages.
+ size_categories (`str` or `List`, *optional*):
+ A string or list of strings that can be used to identify datasets on
+ the Hub by the size of the dataset such as `100K>> from huggingface_hub import HfApi
+
+ >>> api = HfApi()
+
+ # List all datasets
+ >>> api.list_datasets()
+
+
+ # List only the text classification datasets
+ >>> api.list_datasets(filter="task_categories:text-classification")
+
+
+ # List only the datasets in russian for language modeling
+ >>> api.list_datasets(
+ ... filter=("language:ru", "task_ids:language-modeling")
+ ... )
+
+ # List FiftyOne datasets (identified by the tag "fiftyone" in dataset card)
+ >>> api.list_datasets(tags="fiftyone")
+ ```
+
+ Example usage with the `search` argument:
+
+ ```python
+ >>> from huggingface_hub import HfApi
+
+ >>> api = HfApi()
+
+ # List all datasets with "text" in their name
+ >>> api.list_datasets(search="text")
+
+ # List all datasets with "text" in their name made by google
+ >>> api.list_datasets(search="text", author="google")
+ ```
+ """
+ if expand and full:
+ raise ValueError("`expand` cannot be used if `full` is passed.")
+
+ path = f"{self.endpoint}/api/datasets"
+ headers = self._build_hf_headers(token=token)
+ params: Dict[str, Any] = {}
+
+ # Build `filter` list
+ filter_list = []
+ if filter is not None:
+ if isinstance(filter, str):
+ filter_list.append(filter)
+ else:
+ filter_list.extend(filter)
+ for key, value in (
+ ("benchmark", benchmark),
+ ("language_creators", language_creators),
+ ("language", language),
+ ("multilinguality", multilinguality),
+ ("size_categories", size_categories),
+ ("task_categories", task_categories),
+ ("task_ids", task_ids),
+ ):
+ if value:
+ if isinstance(value, str):
+ value = [value]
+ for value_item in value:
+ if not value_item.startswith(f"{key}:"):
+ data = f"{key}:{value_item}"
+ filter_list.append(data)
+ if tags is not None:
+ filter_list.extend([tags] if isinstance(tags, str) else tags)
+ if len(filter_list) > 0:
+ params["filter"] = filter_list
+
+ # Handle other query params
+ if author:
+ params["author"] = author
+ if gated is not None:
+ params["gated"] = gated
+ search_list = []
+ if dataset_name:
+ search_list.append(dataset_name)
+ if search:
+ search_list.append(search)
+ if len(search_list) > 0:
+ params["search"] = search_list
+ if sort is not None:
+ params["sort"] = (
+ "lastModified"
+ if sort == "last_modified"
+ else "trendingScore"
+ if sort == "trending_score"
+ else "createdAt"
+ if sort == "created_at"
+ else sort
+ )
+ if direction is not None:
+ params["direction"] = direction
+ if limit is not None:
+ params["limit"] = limit
+
+ # Request additional data
+ if expand:
+ params["expand"] = expand
+ if full:
+ params["full"] = True
+
+ items = paginate(path, params=params, headers=headers)
+ if limit is not None:
+ items = islice(items, limit) # Do not iterate over all pages
+ for item in items:
+ if "siblings" not in item:
+ item["siblings"] = None
+ yield DatasetInfo(**item)
+
+ @validate_hf_hub_args
+ def list_spaces(
+ self,
+ *,
+ # Search-query parameter
+ filter: Union[str, Iterable[str], None] = None,
+ author: Optional[str] = None,
+ search: Optional[str] = None,
+ datasets: Union[str, Iterable[str], None] = None,
+ models: Union[str, Iterable[str], None] = None,
+ linked: bool = False,
+ # Sorting and pagination parameters
+ sort: Union[Literal["last_modified"], str, None] = None,
+ direction: Optional[Literal[-1]] = None,
+ limit: Optional[int] = None,
+ # Additional data to fetch
+ expand: Optional[List[ExpandSpaceProperty_T]] = None,
+ full: Optional[bool] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[SpaceInfo]:
+ """
+ List spaces hosted on the Huggingface Hub, given some filters.
+
+ Args:
+ filter (`str` or `Iterable`, *optional*):
+ A string tag or list of tags that can be used to identify Spaces on the Hub.
+ author (`str`, *optional*):
+ A string which identify the author of the returned Spaces.
+ search (`str`, *optional*):
+ A string that will be contained in the returned Spaces.
+ datasets (`str` or `Iterable`, *optional*):
+ Whether to return Spaces that make use of a dataset.
+ The name of a specific dataset can be passed as a string.
+ models (`str` or `Iterable`, *optional*):
+ Whether to return Spaces that make use of a model.
+ The name of a specific model can be passed as a string.
+ linked (`bool`, *optional*):
+ Whether to return Spaces that make use of either a model or a dataset.
+ sort (`Literal["last_modified"]` or `str`, *optional*):
+ The key with which to sort the resulting models. Possible values are "last_modified", "trending_score",
+ "created_at" and "likes".
+ direction (`Literal[-1]` or `int`, *optional*):
+ Direction in which to sort. The value `-1` sorts by descending
+ order while all other values sort by ascending order.
+ limit (`int`, *optional*):
+ The limit on the number of Spaces fetched. Leaving this option
+ to `None` fetches all Spaces.
+ expand (`List[ExpandSpaceProperty_T]`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `full` is passed.
+ Possible values are `"author"`, `"cardData"`, `"datasets"`, `"disabled"`, `"lastModified"`, `"createdAt"`, `"likes"`, `"models"`, `"private"`, `"runtime"`, `"sdk"`, `"siblings"`, `"sha"`, `"subdomain"`, `"tags"`, `"trendingScore"`, `"usedStorage"`, `"resourceGroup"` and `"xetEnabled"`.
+ full (`bool`, *optional*):
+ Whether to fetch all Spaces data, including the `last_modified`, `siblings`
+ and `card_data` fields.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[SpaceInfo]`: an iterable of [`huggingface_hub.hf_api.SpaceInfo`] objects.
+ """
+ if expand and full:
+ raise ValueError("`expand` cannot be used if `full` is passed.")
+
+ path = f"{self.endpoint}/api/spaces"
+ headers = self._build_hf_headers(token=token)
+ params: Dict[str, Any] = {}
+ if filter is not None:
+ params["filter"] = filter
+ if author is not None:
+ params["author"] = author
+ if search is not None:
+ params["search"] = search
+ if sort is not None:
+ params["sort"] = (
+ "lastModified"
+ if sort == "last_modified"
+ else "trendingScore"
+ if sort == "trending_score"
+ else "createdAt"
+ if sort == "created_at"
+ else sort
+ )
+ if direction is not None:
+ params["direction"] = direction
+ if limit is not None:
+ params["limit"] = limit
+ if linked:
+ params["linked"] = True
+ if datasets is not None:
+ params["datasets"] = datasets
+ if models is not None:
+ params["models"] = models
+
+ # Request additional data
+ if expand:
+ params["expand"] = expand
+ if full:
+ params["full"] = True
+
+ items = paginate(path, params=params, headers=headers)
+ if limit is not None:
+ items = islice(items, limit) # Do not iterate over all pages
+ for item in items:
+ if "siblings" not in item:
+ item["siblings"] = None
+ yield SpaceInfo(**item)
+
+ @validate_hf_hub_args
+ def unlike(
+ self,
+ repo_id: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> None:
+ """
+ Unlike a given repo on the Hub (e.g. remove from favorite list).
+
+ To prevent spam usage, it is not possible to `like` a repository from a script.
+
+ See also [`list_liked_repos`].
+
+ Args:
+ repo_id (`str`):
+ The repository to unlike. Example: `"user/my-cool-model"`.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if unliking a dataset or space, `None` or
+ `"model"` if unliking a model. Default is `None`.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import list_liked_repos, unlike
+ >>> "gpt2" in list_liked_repos().models # we assume you have already liked gpt2
+ True
+ >>> unlike("gpt2")
+ >>> "gpt2" in list_liked_repos().models
+ False
+ ```
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ response = get_session().delete(
+ url=f"{self.endpoint}/api/{repo_type}s/{repo_id}/like", headers=self._build_hf_headers(token=token)
+ )
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def list_liked_repos(
+ self,
+ user: Optional[str] = None,
+ *,
+ token: Union[bool, str, None] = None,
+ ) -> UserLikes:
+ """
+ List all public repos liked by a user on huggingface.co.
+
+ This list is public so token is optional. If `user` is not passed, it defaults to
+ the logged in user.
+
+ See also [`unlike`].
+
+ Args:
+ user (`str`, *optional*):
+ Name of the user for which you want to fetch the likes.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`UserLikes`]: object containing the user name and 3 lists of repo ids (1 for
+ models, 1 for datasets and 1 for Spaces).
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `user` is not passed and no token found (either from argument or from machine).
+
+ Example:
+ ```python
+ >>> from huggingface_hub import list_liked_repos
+
+ >>> likes = list_liked_repos("julien-c")
+
+ >>> likes.user
+ "julien-c"
+
+ >>> likes.models
+ ["osanseviero/streamlit_1.15", "Xhaheen/ChatGPT_HF", ...]
+ ```
+ """
+ # User is either provided explicitly or retrieved from current token.
+ if user is None:
+ me = self.whoami(token=token)
+ if me["type"] == "user":
+ user = me["name"]
+ else:
+ raise ValueError(
+ "Cannot list liked repos. You must provide a 'user' as input or be logged in as a user."
+ )
+
+ path = f"{self.endpoint}/api/users/{user}/likes"
+ headers = self._build_hf_headers(token=token)
+
+ likes = list(paginate(path, params={}, headers=headers))
+ # Looping over a list of items similar to:
+ # {
+ # 'createdAt': '2021-09-09T21:53:27.000Z',
+ # 'repo': {
+ # 'name': 'PaddlePaddle/PaddleOCR',
+ # 'type': 'space'
+ # }
+ # }
+ # Let's loop 3 times over the received list. Less efficient but more straightforward to read.
+ return UserLikes(
+ user=user,
+ total=len(likes),
+ models=[like["repo"]["name"] for like in likes if like["repo"]["type"] == "model"],
+ datasets=[like["repo"]["name"] for like in likes if like["repo"]["type"] == "dataset"],
+ spaces=[like["repo"]["name"] for like in likes if like["repo"]["type"] == "space"],
+ )
+
+ @validate_hf_hub_args
+ def list_repo_likers(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[User]:
+ """
+ List all users who liked a given repo on the hugging Face Hub.
+
+ See also [`list_liked_repos`].
+
+ Args:
+ repo_id (`str`):
+ The repository to retrieve . Example: `"user/my-cool-model"`.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+
+ Returns:
+ `Iterable[User]`: an iterable of [`huggingface_hub.hf_api.User`] objects.
+ """
+
+ # Construct the API endpoint
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ path = f"{self.endpoint}/api/{repo_type}s/{repo_id}/likers"
+ for liker in paginate(path, params={}, headers=self._build_hf_headers(token=token)):
+ yield User(username=liker["user"], fullname=liker["fullname"], avatar_url=liker["avatarUrl"])
+
+ @validate_hf_hub_args
+ def model_info(
+ self,
+ repo_id: str,
+ *,
+ revision: Optional[str] = None,
+ timeout: Optional[float] = None,
+ securityStatus: Optional[bool] = None,
+ files_metadata: bool = False,
+ expand: Optional[List[ExpandModelProperty_T]] = None,
+ token: Union[bool, str, None] = None,
+ ) -> ModelInfo:
+ """
+ Get info on one specific model on huggingface.co
+
+ Model can be private if you pass an acceptable token or are logged in.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`, *optional*):
+ The revision of the model repository from which to get the
+ information.
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+ securityStatus (`bool`, *optional*):
+ Whether to retrieve the security status from the model
+ repository as well. The security status will be returned in the `security_repo_status` field.
+ files_metadata (`bool`, *optional*):
+ Whether or not to retrieve metadata for files in the repository
+ (size, LFS metadata, etc). Defaults to `False`.
+ expand (`List[ExpandModelProperty_T]`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `securityStatus` or `files_metadata` are passed.
+ Possible values are `"author"`, `"baseModels"`, `"cardData"`, `"childrenModelCount"`, `"config"`, `"createdAt"`, `"disabled"`, `"downloads"`, `"downloadsAllTime"`, `"gated"`, `"gguf"`, `"inference"`, `"inferenceProviderMapping"`, `"lastModified"`, `"library_name"`, `"likes"`, `"mask_token"`, `"model-index"`, `"pipeline_tag"`, `"private"`, `"safetensors"`, `"sha"`, `"siblings"`, `"spaces"`, `"tags"`, `"transformersInfo"`, `"trendingScore"`, `"widgetData"`, `"usedStorage"`, `"resourceGroup"` and `"xetEnabled"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`huggingface_hub.hf_api.ModelInfo`]: The model repository information.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+ """
+ if expand and (securityStatus or files_metadata):
+ raise ValueError("`expand` cannot be used if `securityStatus` or `files_metadata` are set.")
+
+ headers = self._build_hf_headers(token=token)
+ path = (
+ f"{self.endpoint}/api/models/{repo_id}"
+ if revision is None
+ else (f"{self.endpoint}/api/models/{repo_id}/revision/{quote(revision, safe='')}")
+ )
+ params: Dict = {}
+ if securityStatus:
+ params["securityStatus"] = True
+ if files_metadata:
+ params["blobs"] = True
+ if expand:
+ params["expand"] = expand
+ r = get_session().get(path, headers=headers, timeout=timeout, params=params)
+ hf_raise_for_status(r)
+ data = r.json()
+ return ModelInfo(**data)
+
+ @validate_hf_hub_args
+ def dataset_info(
+ self,
+ repo_id: str,
+ *,
+ revision: Optional[str] = None,
+ timeout: Optional[float] = None,
+ files_metadata: bool = False,
+ expand: Optional[List[ExpandDatasetProperty_T]] = None,
+ token: Union[bool, str, None] = None,
+ ) -> DatasetInfo:
+ """
+ Get info on one specific dataset on huggingface.co.
+
+ Dataset can be private if you pass an acceptable token.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`, *optional*):
+ The revision of the dataset repository from which to get the
+ information.
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+ files_metadata (`bool`, *optional*):
+ Whether or not to retrieve metadata for files in the repository
+ (size, LFS metadata, etc). Defaults to `False`.
+ expand (`List[ExpandDatasetProperty_T]`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `files_metadata` is passed.
+ Possible values are `"author"`, `"cardData"`, `"citation"`, `"createdAt"`, `"disabled"`, `"description"`, `"downloads"`, `"downloadsAllTime"`, `"gated"`, `"lastModified"`, `"likes"`, `"paperswithcode_id"`, `"private"`, `"siblings"`, `"sha"`, `"tags"`, `"trendingScore"`,`"usedStorage"`, `"resourceGroup"` and `"xetEnabled"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`hf_api.DatasetInfo`]: The dataset repository information.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+ """
+ if expand and files_metadata:
+ raise ValueError("`expand` cannot be used if `files_metadata` is set.")
+
+ headers = self._build_hf_headers(token=token)
+ path = (
+ f"{self.endpoint}/api/datasets/{repo_id}"
+ if revision is None
+ else (f"{self.endpoint}/api/datasets/{repo_id}/revision/{quote(revision, safe='')}")
+ )
+ params: Dict = {}
+ if files_metadata:
+ params["blobs"] = True
+ if expand:
+ params["expand"] = expand
+
+ r = get_session().get(path, headers=headers, timeout=timeout, params=params)
+ hf_raise_for_status(r)
+ data = r.json()
+ return DatasetInfo(**data)
+
+ @validate_hf_hub_args
+ def space_info(
+ self,
+ repo_id: str,
+ *,
+ revision: Optional[str] = None,
+ timeout: Optional[float] = None,
+ files_metadata: bool = False,
+ expand: Optional[List[ExpandSpaceProperty_T]] = None,
+ token: Union[bool, str, None] = None,
+ ) -> SpaceInfo:
+ """
+ Get info on one specific Space on huggingface.co.
+
+ Space can be private if you pass an acceptable token.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`, *optional*):
+ The revision of the space repository from which to get the
+ information.
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+ files_metadata (`bool`, *optional*):
+ Whether or not to retrieve metadata for files in the repository
+ (size, LFS metadata, etc). Defaults to `False`.
+ expand (`List[ExpandSpaceProperty_T]`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `full` is passed.
+ Possible values are `"author"`, `"cardData"`, `"createdAt"`, `"datasets"`, `"disabled"`, `"lastModified"`, `"likes"`, `"models"`, `"private"`, `"runtime"`, `"sdk"`, `"siblings"`, `"sha"`, `"subdomain"`, `"tags"`, `"trendingScore"`, `"usedStorage"`, `"resourceGroup"` and `"xetEnabled"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`~hf_api.SpaceInfo`]: The space repository information.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+ """
+ if expand and files_metadata:
+ raise ValueError("`expand` cannot be used if `files_metadata` is set.")
+
+ headers = self._build_hf_headers(token=token)
+ path = (
+ f"{self.endpoint}/api/spaces/{repo_id}"
+ if revision is None
+ else (f"{self.endpoint}/api/spaces/{repo_id}/revision/{quote(revision, safe='')}")
+ )
+ params: Dict = {}
+ if files_metadata:
+ params["blobs"] = True
+ if expand:
+ params["expand"] = expand
+
+ r = get_session().get(path, headers=headers, timeout=timeout, params=params)
+ hf_raise_for_status(r)
+ data = r.json()
+ return SpaceInfo(**data)
+
+ @validate_hf_hub_args
+ def repo_info(
+ self,
+ repo_id: str,
+ *,
+ revision: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ timeout: Optional[float] = None,
+ files_metadata: bool = False,
+ expand: Optional[Union[ExpandModelProperty_T, ExpandDatasetProperty_T, ExpandSpaceProperty_T]] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Union[ModelInfo, DatasetInfo, SpaceInfo]:
+ """
+ Get the info object for a given repo of a given type.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`, *optional*):
+ The revision of the repository from which to get the
+ information.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if getting repository info from a dataset or a space,
+ `None` or `"model"` if getting repository info from a model. Default is `None`.
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+ expand (`ExpandModelProperty_T` or `ExpandDatasetProperty_T` or `ExpandSpaceProperty_T`, *optional*):
+ List properties to return in the response. When used, only the properties in the list will be returned.
+ This parameter cannot be used if `files_metadata` is passed.
+ For an exhaustive list of available properties, check out [`model_info`], [`dataset_info`] or [`space_info`].
+ files_metadata (`bool`, *optional*):
+ Whether or not to retrieve metadata for files in the repository
+ (size, LFS metadata, etc). Defaults to `False`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Union[SpaceInfo, DatasetInfo, ModelInfo]`: The repository information, as a
+ [`huggingface_hub.hf_api.DatasetInfo`], [`huggingface_hub.hf_api.ModelInfo`]
+ or [`huggingface_hub.hf_api.SpaceInfo`] object.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+ """
+ if repo_type is None or repo_type == "model":
+ method = self.model_info
+ elif repo_type == "dataset":
+ method = self.dataset_info # type: ignore
+ elif repo_type == "space":
+ method = self.space_info # type: ignore
+ else:
+ raise ValueError("Unsupported repo type.")
+ return method(
+ repo_id,
+ revision=revision,
+ token=token,
+ timeout=timeout,
+ expand=expand, # type: ignore[arg-type]
+ files_metadata=files_metadata,
+ )
+
+ @validate_hf_hub_args
+ def repo_exists(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> bool:
+ """
+ Checks if a repository exists on the Hugging Face Hub.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if getting repository info from a dataset or a space,
+ `None` or `"model"` if getting repository info from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ True if the repository exists, False otherwise.
+
+ Examples:
+ ```py
+ >>> from huggingface_hub import repo_exists
+ >>> repo_exists("google/gemma-7b")
+ True
+ >>> repo_exists("google/not-a-repo")
+ False
+ ```
+ """
+ try:
+ self.repo_info(repo_id=repo_id, repo_type=repo_type, token=token)
+ return True
+ except GatedRepoError:
+ return True # we don't have access but it exists
+ except RepositoryNotFoundError:
+ return False
+
+ @validate_hf_hub_args
+ def revision_exists(
+ self,
+ repo_id: str,
+ revision: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> bool:
+ """
+ Checks if a specific revision exists on a repo on the Hugging Face Hub.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`):
+ The revision of the repository to check.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if getting repository info from a dataset or a space,
+ `None` or `"model"` if getting repository info from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ True if the repository and the revision exists, False otherwise.
+
+ Examples:
+ ```py
+ >>> from huggingface_hub import revision_exists
+ >>> revision_exists("google/gemma-7b", "float16")
+ True
+ >>> revision_exists("google/gemma-7b", "not-a-revision")
+ False
+ ```
+ """
+ try:
+ self.repo_info(repo_id=repo_id, revision=revision, repo_type=repo_type, token=token)
+ return True
+ except RevisionNotFoundError:
+ return False
+ except RepositoryNotFoundError:
+ return False
+
+ @validate_hf_hub_args
+ def file_exists(
+ self,
+ repo_id: str,
+ filename: str,
+ *,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> bool:
+ """
+ Checks if a file exists in a repository on the Hugging Face Hub.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ filename (`str`):
+ The name of the file to check, for example:
+ `"config.json"`
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if getting repository info from a dataset or a space,
+ `None` or `"model"` if getting repository info from a model. Default is `None`.
+ revision (`str`, *optional*):
+ The revision of the repository from which to get the information. Defaults to `"main"` branch.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ True if the file exists, False otherwise.
+
+ Examples:
+ ```py
+ >>> from huggingface_hub import file_exists
+ >>> file_exists("bigcode/starcoder", "config.json")
+ True
+ >>> file_exists("bigcode/starcoder", "not-a-file")
+ False
+ >>> file_exists("bigcode/not-a-repo", "config.json")
+ False
+ ```
+ """
+ url = hf_hub_url(
+ repo_id=repo_id, repo_type=repo_type, revision=revision, filename=filename, endpoint=self.endpoint
+ )
+ try:
+ if token is None:
+ token = self.token
+ get_hf_file_metadata(url, token=token)
+ return True
+ except GatedRepoError: # raise specifically on gated repo
+ raise
+ except (RepositoryNotFoundError, EntryNotFoundError, RevisionNotFoundError):
+ return False
+
+ @validate_hf_hub_args
+ def list_repo_files(
+ self,
+ repo_id: str,
+ *,
+ revision: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> List[str]:
+ """
+ Get the list of files in a given repo.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ revision (`str`, *optional*):
+ The revision of the repository from which to get the information.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or space, `None` or `"model"` if uploading to
+ a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[str]`: the list of files in a given repository.
+ """
+ return [
+ f.rfilename
+ for f in self.list_repo_tree(
+ repo_id=repo_id, recursive=True, revision=revision, repo_type=repo_type, token=token
+ )
+ if isinstance(f, RepoFile)
+ ]
+
+ @validate_hf_hub_args
+ def list_repo_tree(
+ self,
+ repo_id: str,
+ path_in_repo: Optional[str] = None,
+ *,
+ recursive: bool = False,
+ expand: bool = False,
+ revision: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> Iterable[Union[RepoFile, RepoFolder]]:
+ """
+ List a repo tree's files and folders and get information about them.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ path_in_repo (`str`, *optional*):
+ Relative path of the tree (folder) in the repo, for example:
+ `"checkpoints/1fec34a/results"`. Will default to the root tree (folder) of the repository.
+ recursive (`bool`, *optional*, defaults to `False`):
+ Whether to list tree's files and folders recursively.
+ expand (`bool`, *optional*, defaults to `False`):
+ Whether to fetch more information about the tree's files and folders (e.g. last commit and files' security scan results). This
+ operation is more expensive for the server so only 50 results are returned per page (instead of 1000).
+ As pagination is implemented in `huggingface_hub`, this is transparent for you except for the time it
+ takes to get the results.
+ revision (`str`, *optional*):
+ The revision of the repository from which to get the tree. Defaults to `"main"` branch.
+ repo_type (`str`, *optional*):
+ The type of the repository from which to get the tree (`"model"`, `"dataset"` or `"space"`.
+ Defaults to `"model"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[Union[RepoFile, RepoFolder]]`:
+ The information about the tree's files and folders, as an iterable of [`RepoFile`] and [`RepoFolder`] objects. The order of the files and folders is
+ not guaranteed.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private but not authenticated or repo
+ does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If revision is not found (error 404) on the repo.
+ [`~utils.EntryNotFoundError`]:
+ If the tree (folder) does not exist (error 404) on the repo.
+
+ Examples:
+
+ Get information about a repo's tree.
+ ```py
+ >>> from huggingface_hub import list_repo_tree
+ >>> repo_tree = list_repo_tree("lysandre/arxiv-nlp")
+ >>> repo_tree
+
+ >>> list(repo_tree)
+ [
+ RepoFile(path='.gitattributes', size=391, blob_id='ae8c63daedbd4206d7d40126955d4e6ab1c80f8f', lfs=None, last_commit=None, security=None),
+ RepoFile(path='README.md', size=391, blob_id='43bd404b159de6fba7c2f4d3264347668d43af25', lfs=None, last_commit=None, security=None),
+ RepoFile(path='config.json', size=554, blob_id='2f9618c3a19b9a61add74f70bfb121335aeef666', lfs=None, last_commit=None, security=None),
+ RepoFile(
+ path='flax_model.msgpack', size=497764107, blob_id='8095a62ccb4d806da7666fcda07467e2d150218e',
+ lfs={'size': 497764107, 'sha256': 'd88b0d6a6ff9c3f8151f9d3228f57092aaea997f09af009eefd7373a77b5abb9', 'pointer_size': 134}, last_commit=None, security=None
+ ),
+ RepoFile(path='merges.txt', size=456318, blob_id='226b0752cac7789c48f0cb3ec53eda48b7be36cc', lfs=None, last_commit=None, security=None),
+ RepoFile(
+ path='pytorch_model.bin', size=548123560, blob_id='64eaa9c526867e404b68f2c5d66fd78e27026523',
+ lfs={'size': 548123560, 'sha256': '9be78edb5b928eba33aa88f431551348f7466ba9f5ef3daf1d552398722a5436', 'pointer_size': 134}, last_commit=None, security=None
+ ),
+ RepoFile(path='vocab.json', size=898669, blob_id='b00361fece0387ca34b4b8b8539ed830d644dbeb', lfs=None, last_commit=None, security=None)]
+ ]
+ ```
+
+ Get even more information about a repo's tree (last commit and files' security scan results)
+ ```py
+ >>> from huggingface_hub import list_repo_tree
+ >>> repo_tree = list_repo_tree("prompthero/openjourney-v4", expand=True)
+ >>> list(repo_tree)
+ [
+ RepoFolder(
+ path='feature_extractor',
+ tree_id='aa536c4ea18073388b5b0bc791057a7296a00398',
+ last_commit={
+ 'oid': '47b62b20b20e06b9de610e840282b7e6c3d51190',
+ 'title': 'Upload diffusers weights (#48)',
+ 'date': datetime.datetime(2023, 3, 21, 9, 5, 27, tzinfo=datetime.timezone.utc)
+ }
+ ),
+ RepoFolder(
+ path='safety_checker',
+ tree_id='65aef9d787e5557373fdf714d6c34d4fcdd70440',
+ last_commit={
+ 'oid': '47b62b20b20e06b9de610e840282b7e6c3d51190',
+ 'title': 'Upload diffusers weights (#48)',
+ 'date': datetime.datetime(2023, 3, 21, 9, 5, 27, tzinfo=datetime.timezone.utc)
+ }
+ ),
+ RepoFile(
+ path='model_index.json',
+ size=582,
+ blob_id='d3d7c1e8c3e78eeb1640b8e2041ee256e24c9ee1',
+ lfs=None,
+ last_commit={
+ 'oid': 'b195ed2d503f3eb29637050a886d77bd81d35f0e',
+ 'title': 'Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#54)',
+ 'date': datetime.datetime(2023, 5, 15, 21, 41, 59, tzinfo=datetime.timezone.utc)
+ },
+ security={
+ 'safe': True,
+ 'av_scan': {'virusFound': False, 'virusNames': None},
+ 'pickle_import_scan': None
+ }
+ )
+ ...
+ ]
+ ```
+ """
+ repo_type = repo_type or constants.REPO_TYPE_MODEL
+ revision = quote(revision, safe="") if revision is not None else constants.DEFAULT_REVISION
+ headers = self._build_hf_headers(token=token)
+
+ encoded_path_in_repo = "/" + quote(path_in_repo, safe="") if path_in_repo else ""
+ tree_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/tree/{revision}{encoded_path_in_repo}"
+ for path_info in paginate(path=tree_url, headers=headers, params={"recursive": recursive, "expand": expand}):
+ yield (RepoFile(**path_info) if path_info["type"] == "file" else RepoFolder(**path_info))
+
+ @validate_hf_hub_args
+ def list_repo_refs(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ include_pull_requests: bool = False,
+ token: Union[str, bool, None] = None,
+ ) -> GitRefs:
+ """
+ Get the list of refs of a given repo (both tags and branches).
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if listing refs from a dataset or a Space,
+ `None` or `"model"` if listing from a model. Default is `None`.
+ include_pull_requests (`bool`, *optional*):
+ Whether to include refs from pull requests in the list. Defaults to `False`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> api.list_repo_refs("gpt2")
+ GitRefs(branches=[GitRefInfo(name='main', ref='refs/heads/main', target_commit='e7da7f221d5bf496a48136c0cd264e630fe9fcc8')], converts=[], tags=[])
+
+ >>> api.list_repo_refs("bigcode/the-stack", repo_type='dataset')
+ GitRefs(
+ branches=[
+ GitRefInfo(name='main', ref='refs/heads/main', target_commit='18edc1591d9ce72aa82f56c4431b3c969b210ae3'),
+ GitRefInfo(name='v1.1.a1', ref='refs/heads/v1.1.a1', target_commit='f9826b862d1567f3822d3d25649b0d6d22ace714')
+ ],
+ converts=[],
+ tags=[
+ GitRefInfo(name='v1.0', ref='refs/tags/v1.0', target_commit='c37a8cd1e382064d8aced5e05543c5f7753834da')
+ ]
+ )
+ ```
+
+ Returns:
+ [`GitRefs`]: object containing all information about branches and tags for a
+ repo on the Hub.
+ """
+ repo_type = repo_type or constants.REPO_TYPE_MODEL
+ response = get_session().get(
+ f"{self.endpoint}/api/{repo_type}s/{repo_id}/refs",
+ headers=self._build_hf_headers(token=token),
+ params={"include_prs": 1} if include_pull_requests else {},
+ )
+ hf_raise_for_status(response)
+ data = response.json()
+
+ def _format_as_git_ref_info(item: Dict) -> GitRefInfo:
+ return GitRefInfo(name=item["name"], ref=item["ref"], target_commit=item["targetCommit"])
+
+ return GitRefs(
+ branches=[_format_as_git_ref_info(item) for item in data["branches"]],
+ converts=[_format_as_git_ref_info(item) for item in data["converts"]],
+ tags=[_format_as_git_ref_info(item) for item in data["tags"]],
+ pull_requests=[_format_as_git_ref_info(item) for item in data["pullRequests"]]
+ if include_pull_requests
+ else None,
+ )
+
+ @validate_hf_hub_args
+ def list_repo_commits(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ revision: Optional[str] = None,
+ formatted: bool = False,
+ ) -> List[GitCommitInfo]:
+ """
+ Get the list of commits of a given revision for a repo on the Hub.
+
+ Commits are sorted by date (last commit first).
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if listing commits from a dataset or a Space, `None` or `"model"` if
+ listing from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ formatted (`bool`):
+ Whether to return the HTML-formatted title and description of the commits. Defaults to False.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+
+ # Commits are sorted by date (last commit first)
+ >>> initial_commit = api.list_repo_commits("gpt2")[-1]
+
+ # Initial commit is always a system commit containing the `.gitattributes` file.
+ >>> initial_commit
+ GitCommitInfo(
+ commit_id='9b865efde13a30c13e0a33e536cf3e4a5a9d71d8',
+ authors=['system'],
+ created_at=datetime.datetime(2019, 2, 18, 10, 36, 15, tzinfo=datetime.timezone.utc),
+ title='initial commit',
+ message='',
+ formatted_title=None,
+ formatted_message=None
+ )
+
+ # Create an empty branch by deriving from initial commit
+ >>> api.create_branch("gpt2", "new_empty_branch", revision=initial_commit.commit_id)
+ ```
+
+ Returns:
+ List[[`GitCommitInfo`]]: list of objects containing information about the commits for a repo on the Hub.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private but not authenticated or repo
+ does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If revision is not found (error 404) on the repo.
+ """
+ repo_type = repo_type or constants.REPO_TYPE_MODEL
+ revision = quote(revision, safe="") if revision is not None else constants.DEFAULT_REVISION
+
+ # Paginate over results and return the list of commits.
+ return [
+ GitCommitInfo(
+ commit_id=item["id"],
+ authors=[author["user"] for author in item["authors"]],
+ created_at=parse_datetime(item["date"]),
+ title=item["title"],
+ message=item["message"],
+ formatted_title=item.get("formatted", {}).get("title"),
+ formatted_message=item.get("formatted", {}).get("message"),
+ )
+ for item in paginate(
+ f"{self.endpoint}/api/{repo_type}s/{repo_id}/commits/{revision}",
+ headers=self._build_hf_headers(token=token),
+ params={"expand[]": "formatted"} if formatted else {},
+ )
+ ]
+
+ @validate_hf_hub_args
+ def get_paths_info(
+ self,
+ repo_id: str,
+ paths: Union[List[str], str],
+ *,
+ expand: bool = False,
+ revision: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> List[Union[RepoFile, RepoFolder]]:
+ """
+ Get information about a repo's paths.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ paths (`Union[List[str], str]`, *optional*):
+ The paths to get information about. If a path do not exist, it is ignored without raising
+ an exception.
+ expand (`bool`, *optional*, defaults to `False`):
+ Whether to fetch more information about the paths (e.g. last commit and files' security scan results). This
+ operation is more expensive for the server so only 50 results are returned per page (instead of 1000).
+ As pagination is implemented in `huggingface_hub`, this is transparent for you except for the time it
+ takes to get the results.
+ revision (`str`, *optional*):
+ The revision of the repository from which to get the information. Defaults to `"main"` branch.
+ repo_type (`str`, *optional*):
+ The type of the repository from which to get the information (`"model"`, `"dataset"` or `"space"`.
+ Defaults to `"model"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[Union[RepoFile, RepoFolder]]`:
+ The information about the paths, as a list of [`RepoFile`] and [`RepoFolder`] objects.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private but not authenticated or repo
+ does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If revision is not found (error 404) on the repo.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import get_paths_info
+ >>> paths_info = get_paths_info("allenai/c4", ["README.md", "en"], repo_type="dataset")
+ >>> paths_info
+ [
+ RepoFile(path='README.md', size=2379, blob_id='f84cb4c97182890fc1dbdeaf1a6a468fd27b4fff', lfs=None, last_commit=None, security=None),
+ RepoFolder(path='en', tree_id='dc943c4c40f53d02b31ced1defa7e5f438d5862e', last_commit=None)
+ ]
+ ```
+ """
+ repo_type = repo_type or constants.REPO_TYPE_MODEL
+ revision = quote(revision, safe="") if revision is not None else constants.DEFAULT_REVISION
+ headers = self._build_hf_headers(token=token)
+
+ response = get_session().post(
+ f"{self.endpoint}/api/{repo_type}s/{repo_id}/paths-info/{revision}",
+ data={
+ "paths": paths if isinstance(paths, list) else [paths],
+ "expand": expand,
+ },
+ headers=headers,
+ )
+ hf_raise_for_status(response)
+ paths_info = response.json()
+ return [
+ RepoFile(**path_info) if path_info["type"] == "file" else RepoFolder(**path_info)
+ for path_info in paths_info
+ ]
+
+ @validate_hf_hub_args
+ def super_squash_history(
+ self,
+ repo_id: str,
+ *,
+ branch: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ) -> None:
+ """Squash commit history on a branch for a repo on the Hub.
+
+ Squashing the repo history is useful when you know you'll make hundreds of commits and you don't want to
+ clutter the history. Squashing commits can only be performed from the head of a branch.
+
+ > [!WARNING]
+ > Once squashed, the commit history cannot be retrieved. This is a non-revertible operation.
+
+ > [!WARNING]
+ > Once the history of a branch has been squashed, it is not possible to merge it back into another branch since
+ > their history will have diverged.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ branch (`str`, *optional*):
+ The branch to squash. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The commit message to use for the squashed commit.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if listing commits from a dataset or a Space, `None` or `"model"` if
+ listing from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private but not authenticated or repo
+ does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If the branch to squash cannot be found.
+ [`~utils.BadRequestError`]:
+ If invalid reference for a branch. You cannot squash history on tags.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+
+ # Create repo
+ >>> repo_id = api.create_repo("test-squash").repo_id
+
+ # Make a lot of commits.
+ >>> api.upload_file(repo_id=repo_id, path_in_repo="file.txt", path_or_fileobj=b"content")
+ >>> api.upload_file(repo_id=repo_id, path_in_repo="lfs.bin", path_or_fileobj=b"content")
+ >>> api.upload_file(repo_id=repo_id, path_in_repo="file.txt", path_or_fileobj=b"another_content")
+
+ # Squash history
+ >>> api.super_squash_history(repo_id=repo_id)
+ ```
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError("Invalid repo type")
+ if branch is None:
+ branch = constants.DEFAULT_REVISION
+
+ # Prepare request
+ url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/super-squash/{quote(branch, safe='')}"
+ headers = self._build_hf_headers(token=token)
+ commit_message = commit_message or f"Super-squash branch '{branch}' using huggingface_hub"
+
+ # Super-squash
+ response = get_session().post(url=url, headers=headers, json={"message": commit_message})
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def list_lfs_files(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[LFSFileInfo]:
+ """
+ List all LFS files in a repo on the Hub.
+
+ This is primarily useful to count how much storage a repo is using and to eventually clean up large files
+ with [`permanently_delete_lfs_files`]. Note that this would be a permanent action that will affect all commits
+ referencing this deleted files and that cannot be undone.
+
+ Args:
+ repo_id (`str`):
+ The repository for which you are listing LFS files.
+ repo_type (`str`, *optional*):
+ Type of repository. Set to `"dataset"` or `"space"` if listing from a dataset or space, `None` or
+ `"model"` if listing from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[LFSFileInfo]`: An iterator of [`LFSFileInfo`] objects.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> lfs_files = api.list_lfs_files("username/my-cool-repo")
+
+ # Filter files files to delete based on a combination of `filename`, `pushed_at`, `ref` or `size`.
+ # e.g. select only LFS files in the "checkpoints" folder
+ >>> lfs_files_to_delete = (lfs_file for lfs_file in lfs_files if lfs_file.filename.startswith("checkpoints/"))
+
+ # Permanently delete LFS files
+ >>> api.permanently_delete_lfs_files("username/my-cool-repo", lfs_files_to_delete)
+ ```
+ """
+ # Prepare request
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/lfs-files"
+ headers = self._build_hf_headers(token=token)
+
+ # Paginate over LFS items
+ for item in paginate(url, params={}, headers=headers):
+ yield LFSFileInfo(**item)
+
+ @validate_hf_hub_args
+ def permanently_delete_lfs_files(
+ self,
+ repo_id: str,
+ lfs_files: Iterable[LFSFileInfo],
+ *,
+ rewrite_history: bool = True,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Permanently delete LFS files from a repo on the Hub.
+
+ > [!WARNING]
+ > This is a permanent action that will affect all commits referencing the deleted files and might corrupt your
+ > repository. This is a non-revertible operation. Use it only if you know what you are doing.
+
+ Args:
+ repo_id (`str`):
+ The repository for which you are listing LFS files.
+ lfs_files (`Iterable[LFSFileInfo]`):
+ An iterable of [`LFSFileInfo`] items to permanently delete from the repo. Use [`list_lfs_files`] to list
+ all LFS files from a repo.
+ rewrite_history (`bool`, *optional*, default to `True`):
+ Whether to rewrite repository history to remove file pointers referencing the deleted LFS files (recommended).
+ repo_type (`str`, *optional*):
+ Type of repository. Set to `"dataset"` or `"space"` if listing from a dataset or space, `None` or
+ `"model"` if listing from a model. Default is `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> lfs_files = api.list_lfs_files("username/my-cool-repo")
+
+ # Filter files files to delete based on a combination of `filename`, `pushed_at`, `ref` or `size`.
+ # e.g. select only LFS files in the "checkpoints" folder
+ >>> lfs_files_to_delete = (lfs_file for lfs_file in lfs_files if lfs_file.filename.startswith("checkpoints/"))
+
+ # Permanently delete LFS files
+ >>> api.permanently_delete_lfs_files("username/my-cool-repo", lfs_files_to_delete)
+ ```
+ """
+ # Prepare request
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/lfs-files/batch"
+ headers = self._build_hf_headers(token=token)
+
+ # Delete LFS items by batches of 1000
+ for batch in chunk_iterable(lfs_files, 1000):
+ shas = [item.file_oid for item in batch]
+ if len(shas) == 0:
+ return
+ payload = {
+ "deletions": {
+ "sha": shas,
+ "rewriteHistory": rewrite_history,
+ }
+ }
+ response = get_session().post(url, headers=headers, json=payload)
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def create_repo(
+ self,
+ repo_id: str,
+ *,
+ token: Union[str, bool, None] = None,
+ private: Optional[bool] = None,
+ repo_type: Optional[str] = None,
+ exist_ok: bool = False,
+ resource_group_id: Optional[str] = None,
+ space_sdk: Optional[str] = None,
+ space_hardware: Optional[SpaceHardware] = None,
+ space_storage: Optional[SpaceStorage] = None,
+ space_sleep_time: Optional[int] = None,
+ space_secrets: Optional[List[Dict[str, str]]] = None,
+ space_variables: Optional[List[Dict[str, str]]] = None,
+ ) -> RepoUrl:
+ """Create an empty repo on the HuggingFace Hub.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ private (`bool`, *optional*):
+ Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ exist_ok (`bool`, *optional*, defaults to `False`):
+ If `True`, do not raise an error if repo already exists.
+ resource_group_id (`str`, *optional*):
+ Resource group in which to create the repo. Resource groups is only available for Enterprise Hub organizations and
+ allow to define which members of the organization can access the resource. The ID of a resource group
+ can be found in the URL of the resource's page on the Hub (e.g. `"66670e5163145ca562cb1988"`).
+ To learn more about resource groups, see https://huggingface.co/docs/hub/en/security-resource-groups.
+ space_sdk (`str`, *optional*):
+ Choice of SDK to use if repo_type is "space". Can be "streamlit", "gradio", "docker", or "static".
+ space_hardware (`SpaceHardware` or `str`, *optional*):
+ Choice of Hardware if repo_type is "space". See [`SpaceHardware`] for a complete list.
+ space_storage (`SpaceStorage` or `str`, *optional*):
+ Choice of persistent storage tier. Example: `"small"`. See [`SpaceStorage`] for a complete list.
+ space_sleep_time (`int`, *optional*):
+ Number of seconds of inactivity to wait before a Space is put to sleep. Set to `-1` if you don't want
+ your Space to sleep (default behavior for upgraded hardware). For free hardware, you can't configure
+ the sleep time (value is fixed to 48 hours of inactivity).
+ See https://huggingface.co/docs/hub/spaces-gpus#sleep-time for more details.
+ space_secrets (`List[Dict[str, str]]`, *optional*):
+ A list of secret keys to set in your Space. Each item is in the form `{"key": ..., "value": ..., "description": ...}` where description is optional.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets.
+ space_variables (`List[Dict[str, str]]`, *optional*):
+ A list of public environment variables to set in your Space. Each item is in the form `{"key": ..., "value": ..., "description": ...}` where description is optional.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables.
+
+ Returns:
+ [`RepoUrl`]: URL to the newly created repo. Value is a subclass of `str` containing
+ attributes like `endpoint`, `repo_type` and `repo_id`.
+ """
+ organization, name = repo_id.split("/") if "/" in repo_id else (None, repo_id)
+
+ path = f"{self.endpoint}/api/repos/create"
+
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError("Invalid repo type")
+
+ json: Dict[str, Any] = {"name": name, "organization": organization}
+ if private is not None:
+ json["private"] = private
+ if repo_type is not None:
+ json["type"] = repo_type
+ if repo_type == "space":
+ if space_sdk is None:
+ raise ValueError(
+ "No space_sdk provided. `create_repo` expects space_sdk to be one"
+ f" of {constants.SPACES_SDK_TYPES} when repo_type is 'space'`"
+ )
+ if space_sdk not in constants.SPACES_SDK_TYPES:
+ raise ValueError(f"Invalid space_sdk. Please choose one of {constants.SPACES_SDK_TYPES}.")
+ json["sdk"] = space_sdk
+
+ if space_sdk is not None and repo_type != "space":
+ warnings.warn("Ignoring provided space_sdk because repo_type is not 'space'.")
+
+ function_args = [
+ "space_hardware",
+ "space_storage",
+ "space_sleep_time",
+ "space_secrets",
+ "space_variables",
+ ]
+ json_keys = ["hardware", "storageTier", "sleepTimeSeconds", "secrets", "variables"]
+ values = [space_hardware, space_storage, space_sleep_time, space_secrets, space_variables]
+
+ if repo_type == "space":
+ json.update({k: v for k, v in zip(json_keys, values) if v is not None})
+ else:
+ provided_space_args = [key for key, value in zip(function_args, values) if value is not None]
+
+ if provided_space_args:
+ warnings.warn(f"Ignoring provided {', '.join(provided_space_args)} because repo_type is not 'space'.")
+
+ if getattr(self, "_lfsmultipartthresh", None):
+ # Testing purposes only.
+ # See https://github.com/huggingface/huggingface_hub/pull/733/files#r820604472
+ json["lfsmultipartthresh"] = self._lfsmultipartthresh # type: ignore
+
+ if resource_group_id is not None:
+ json["resourceGroupId"] = resource_group_id
+
+ headers = self._build_hf_headers(token=token)
+ while True:
+ r = get_session().post(path, headers=headers, json=json)
+ if r.status_code == 409 and "Cannot create repo: another conflicting operation is in progress" in r.text:
+ # Since https://github.com/huggingface/moon-landing/pull/7272 (private repo), it is not possible to
+ # concurrently create repos on the Hub for a same user. This is rarely an issue, except when running
+ # tests. To avoid any inconvenience, we retry to create the repo for this specific error.
+ # NOTE: This could have being fixed directly in the tests but adding it here should fixed CIs for all
+ # dependent libraries.
+ # NOTE: If a fix is implemented server-side, we should be able to remove this retry mechanism.
+ logger.debug("Create repo failed due to a concurrency issue. Retrying...")
+ continue
+ break
+
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if exist_ok and err.response.status_code == 409:
+ # Repo already exists and `exist_ok=True`
+ pass
+ elif exist_ok and err.response.status_code == 403:
+ # No write permission on the namespace but repo might already exist
+ try:
+ self.repo_info(repo_id=repo_id, repo_type=repo_type, token=token)
+ if repo_type is None or repo_type == constants.REPO_TYPE_MODEL:
+ return RepoUrl(f"{self.endpoint}/{repo_id}")
+ return RepoUrl(f"{self.endpoint}/{repo_type}/{repo_id}")
+ except HfHubHTTPError:
+ raise err
+ else:
+ raise
+
+ d = r.json()
+ return RepoUrl(d["url"], endpoint=self.endpoint)
+
+ @validate_hf_hub_args
+ def delete_repo(
+ self,
+ repo_id: str,
+ *,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ missing_ok: bool = False,
+ ) -> None:
+ """
+ Delete a repo from the HuggingFace Hub. CAUTION: this is irreversible.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model.
+ missing_ok (`bool`, *optional*, defaults to `False`):
+ If `True`, do not raise an error if repo does not exist.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to delete from cannot be found and `missing_ok` is set to False (default).
+ """
+ organization, name = repo_id.split("/") if "/" in repo_id else (None, repo_id)
+
+ path = f"{self.endpoint}/api/repos/delete"
+
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError("Invalid repo type")
+
+ json = {"name": name, "organization": organization}
+ if repo_type is not None:
+ json["type"] = repo_type
+
+ headers = self._build_hf_headers(token=token)
+ r = get_session().delete(path, headers=headers, json=json)
+ try:
+ hf_raise_for_status(r)
+ except RepositoryNotFoundError:
+ if not missing_ok:
+ raise
+
+ @_deprecate_method(version="0.32", message="Please use `update_repo_settings` instead.")
+ @validate_hf_hub_args
+ def update_repo_visibility(
+ self,
+ repo_id: str,
+ private: bool = False,
+ *,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> Dict[str, bool]:
+ """Update the visibility setting of a repository.
+
+ Deprecated. Use `update_repo_settings` instead.
+
+ Args:
+ repo_id (`str`, *optional*):
+ A namespace (user or an organization) and a repo name separated by a `/`.
+ private (`bool`, *optional*, defaults to `False`):
+ Whether the repository should be private.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+
+ Returns:
+ The HTTP response in json.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL # default repo type
+
+ r = get_session().put(
+ url=f"{self.endpoint}/api/{repo_type}s/{repo_id}/settings",
+ headers=self._build_hf_headers(token=token),
+ json={"private": private},
+ )
+ hf_raise_for_status(r)
+ return r.json()
+
+ @validate_hf_hub_args
+ def update_repo_settings(
+ self,
+ repo_id: str,
+ *,
+ gated: Optional[Literal["auto", "manual", False]] = None,
+ private: Optional[bool] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ xet_enabled: Optional[bool] = None,
+ ) -> None:
+ """
+ Update the settings of a repository, including gated access and visibility.
+
+ To give more control over how repos are used, the Hub allows repo authors to enable
+ access requests for their repos, and also to set the visibility of the repo to private.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated by a /.
+ gated (`Literal["auto", "manual", False]`, *optional*):
+ The gated status for the repository. If set to `None` (default), the `gated` setting of the repository won't be updated.
+ * "auto": The repository is gated, and access requests are automatically approved or denied based on predefined criteria.
+ * "manual": The repository is gated, and access requests require manual approval.
+ * False : The repository is not gated, and anyone can access it.
+ private (`bool`, *optional*):
+ Whether the repository should be private.
+ token (`Union[str, bool, None]`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token,
+ which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass False.
+ repo_type (`str`, *optional*):
+ The type of the repository to update settings from (`"model"`, `"dataset"` or `"space"`).
+ Defaults to `"model"`.
+ xet_enabled (`bool`, *optional*):
+ Whether the repository should be enabled for Xet Storage.
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If gated is not one of "auto", "manual", or False.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If repo_type is not one of the values in constants.REPO_TYPES.
+ [`~utils.HfHubHTTPError`]:
+ If the request to the Hugging Face Hub API fails.
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to download from cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ """
+
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL # default repo type
+
+ # Prepare the JSON payload for the PUT request
+ payload: Dict = {}
+
+ if gated is not None:
+ if gated not in ["auto", "manual", False]:
+ raise ValueError(f"Invalid gated status, must be one of 'auto', 'manual', or False. Got '{gated}'.")
+ payload["gated"] = gated
+
+ if private is not None:
+ payload["private"] = private
+
+ if xet_enabled is not None:
+ payload["xetEnabled"] = xet_enabled
+
+ if len(payload) == 0:
+ raise ValueError("At least one setting must be updated.")
+
+ # Build headers
+ headers = self._build_hf_headers(token=token)
+
+ r = get_session().put(
+ url=f"{self.endpoint}/api/{repo_type}s/{repo_id}/settings",
+ headers=headers,
+ json=payload,
+ )
+ hf_raise_for_status(r)
+
+ def move_repo(
+ self,
+ from_id: str,
+ to_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ ):
+ """
+ Moving a repository from namespace1/repo_name1 to namespace2/repo_name2
+
+ Note there are certain limitations. For more information about moving
+ repositories, please see
+ https://hf.co/docs/hub/repositories-settings#renaming-or-transferring-a-repo.
+
+ Args:
+ from_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`. Original repository identifier.
+ to_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`. Final repository identifier.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ if len(from_id.split("/")) != 2:
+ raise ValueError(f"Invalid repo_id: {from_id}. It should have a namespace (:namespace:/:repo_name:)")
+
+ if len(to_id.split("/")) != 2:
+ raise ValueError(f"Invalid repo_id: {to_id}. It should have a namespace (:namespace:/:repo_name:)")
+
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL # Hub won't accept `None`.
+
+ json = {"fromRepo": from_id, "toRepo": to_id, "type": repo_type}
+
+ path = f"{self.endpoint}/api/repos/move"
+ headers = self._build_hf_headers(token=token)
+ r = get_session().post(path, headers=headers, json=json)
+ try:
+ hf_raise_for_status(r)
+ except HfHubHTTPError as e:
+ e.append_to_message(
+ "\nFor additional documentation please see"
+ " https://hf.co/docs/hub/repositories-settings#renaming-or-transferring-a-repo."
+ )
+ raise
+
+ @overload
+ def create_commit( # type: ignore
+ self,
+ repo_id: str,
+ operations: Iterable[CommitOperation],
+ *,
+ commit_message: str,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ num_threads: int = 5,
+ parent_commit: Optional[str] = None,
+ run_as_future: Literal[False] = ...,
+ ) -> CommitInfo: ...
+
+ @overload
+ def create_commit(
+ self,
+ repo_id: str,
+ operations: Iterable[CommitOperation],
+ *,
+ commit_message: str,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ num_threads: int = 5,
+ parent_commit: Optional[str] = None,
+ run_as_future: Literal[True] = ...,
+ ) -> Future[CommitInfo]: ...
+
+ @validate_hf_hub_args
+ @future_compatible
+ def create_commit(
+ self,
+ repo_id: str,
+ operations: Iterable[CommitOperation],
+ *,
+ commit_message: str,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ num_threads: int = 5,
+ parent_commit: Optional[str] = None,
+ run_as_future: bool = False,
+ ) -> Union[CommitInfo, Future[CommitInfo]]:
+ """
+ Creates a commit in the given repo, deleting & uploading files as needed.
+
+ > [!WARNING]
+ > The input list of `CommitOperation` will be mutated during the commit process. Do not reuse the same objects
+ > for multiple commits.
+
+ > [!WARNING]
+ > `create_commit` assumes that the repo already exists on the Hub. If you get a
+ > Client error 404, please make sure you are authenticated and that `repo_id` and
+ > `repo_type` are set correctly. If repo does not exist, create it first using
+ > [`~hf_api.create_repo`].
+
+ > [!WARNING]
+ > `create_commit` is limited to 25k LFS files and a 1GB payload for regular files.
+
+ Args:
+ repo_id (`str`):
+ The repository in which the commit will be created, for example:
+ `"username/custom_transformers"`
+
+ operations (`Iterable` of [`~hf_api.CommitOperation`]):
+ An iterable of operations to include in the commit, either:
+
+ - [`~hf_api.CommitOperationAdd`] to upload a file
+ - [`~hf_api.CommitOperationDelete`] to delete a file
+ - [`~hf_api.CommitOperationCopy`] to copy a file
+
+ Operation objects will be mutated to include information relative to the upload. Do not reuse the
+ same objects for multiple commits.
+
+ commit_message (`str`):
+ The summary (first line) of the commit that will be created.
+
+ commit_description (`str`, *optional*):
+ The description of the commit that will be created
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`.
+ If `revision` is not set, PR is opened against the `"main"` branch. If
+ `revision` is set and is a branch, PR is opened against this branch. If
+ `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+
+ num_threads (`int`, *optional*):
+ Number of concurrent threads for uploading files. Defaults to 5.
+ Setting it to 2 means at most 2 files will be uploaded concurrently.
+
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string.
+ Shorthands (7 first characters) are also supported. If specified and `create_pr` is `False`,
+ the commit will fail if `revision` does not point to `parent_commit`. If specified and `create_pr`
+ is `True`, the pull request will be created from `parent_commit`. Specifying `parent_commit`
+ ensures the repo has not changed before committing the changes, and can be especially useful
+ if the repo is updated / committed to concurrently.
+ run_as_future (`bool`, *optional*):
+ Whether or not to run this method in the background. Background jobs are run sequentially without
+ blocking the main thread. Passing `run_as_future=True` will return a [Future](https://docs.python.org/3/library/concurrent.futures.html#future-objects)
+ object. Defaults to `False`.
+
+ Returns:
+ [`CommitInfo`] or `Future`:
+ Instance of [`CommitInfo`] containing information about the newly created commit (commit hash, commit
+ url, pr url, commit message,...). If `run_as_future=True` is passed, returns a Future object which will
+ contain the result when executed.
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If commit message is empty.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If parent commit is not a valid commit OID.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If a README.md file with an invalid metadata section is committed. In this case, the commit will fail
+ early, before trying to upload any file.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `create_pr` is `True` and revision is neither `None` nor `"main"`.
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+ """
+ if parent_commit is not None and not constants.REGEX_COMMIT_OID.fullmatch(parent_commit):
+ raise ValueError(
+ f"`parent_commit` is not a valid commit OID. It must match the following regex: {constants.REGEX_COMMIT_OID}"
+ )
+
+ if commit_message is None or len(commit_message) == 0:
+ raise ValueError("`commit_message` can't be empty, please pass a value.")
+
+ commit_description = commit_description if commit_description is not None else ""
+ repo_type = repo_type if repo_type is not None else constants.REPO_TYPE_MODEL
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ unquoted_revision = revision or constants.DEFAULT_REVISION
+ revision = quote(unquoted_revision, safe="")
+ create_pr = create_pr if create_pr is not None else False
+
+ headers = self._build_hf_headers(token=token)
+
+ operations = list(operations)
+ additions = [op for op in operations if isinstance(op, CommitOperationAdd)]
+ copies = [op for op in operations if isinstance(op, CommitOperationCopy)]
+ nb_additions = len(additions)
+ nb_copies = len(copies)
+ nb_deletions = len(operations) - nb_additions - nb_copies
+
+ for addition in additions:
+ if addition._is_committed:
+ raise ValueError(
+ f"CommitOperationAdd {addition} has already being committed and cannot be reused. Please create a"
+ " new CommitOperationAdd object if you want to create a new commit."
+ )
+
+ if repo_type != "dataset":
+ for addition in additions:
+ if addition.path_in_repo.endswith((".arrow", ".parquet")):
+ warnings.warn(
+ f"It seems that you are about to commit a data file ({addition.path_in_repo}) to a {repo_type}"
+ " repository. You are sure this is intended? If you are trying to upload a dataset, please"
+ " set `repo_type='dataset'` or `--repo-type=dataset` in a CLI."
+ )
+
+ logger.debug(
+ f"About to commit to the hub: {len(additions)} addition(s), {len(copies)} copie(s) and"
+ f" {nb_deletions} deletion(s)."
+ )
+
+ # If updating a README.md file, make sure the metadata format is valid
+ # It's better to fail early than to fail after all the files have been uploaded.
+ for addition in additions:
+ if addition.path_in_repo == "README.md":
+ with addition.as_file() as file:
+ content = file.read().decode()
+ self._validate_yaml(content, repo_type=repo_type, token=token)
+ # Skip other additions after `README.md` has been processed
+ break
+
+ # If updating twice the same file or update then delete a file in a single commit
+ _warn_on_overwriting_operations(operations)
+
+ self.preupload_lfs_files(
+ repo_id=repo_id,
+ additions=additions,
+ token=token,
+ repo_type=repo_type,
+ revision=unquoted_revision, # first-class methods take unquoted revision
+ create_pr=create_pr,
+ num_threads=num_threads,
+ free_memory=False, # do not remove `CommitOperationAdd.path_or_fileobj` on LFS files for "normal" users
+ )
+
+ files_to_copy = _fetch_files_to_copy(
+ copies=copies,
+ repo_type=repo_type,
+ repo_id=repo_id,
+ headers=headers,
+ revision=unquoted_revision,
+ endpoint=self.endpoint,
+ )
+ # Remove no-op operations (files that have not changed)
+ operations_without_no_op = []
+ for operation in operations:
+ if (
+ isinstance(operation, CommitOperationAdd)
+ and operation._remote_oid is not None
+ and operation._remote_oid == operation._local_oid
+ ):
+ # File already exists on the Hub and has not changed: we can skip it.
+ logger.debug(f"Skipping upload for '{operation.path_in_repo}' as the file has not changed.")
+ continue
+ if (
+ isinstance(operation, CommitOperationCopy)
+ and operation._dest_oid is not None
+ and operation._dest_oid == operation._src_oid
+ ):
+ # Source and destination files are identical - skip
+ logger.debug(
+ f"Skipping copy for '{operation.src_path_in_repo}' -> '{operation.path_in_repo}' as the content of the source file is the same as the destination file."
+ )
+ continue
+ operations_without_no_op.append(operation)
+ if len(operations) != len(operations_without_no_op):
+ logger.info(
+ f"Removing {len(operations) - len(operations_without_no_op)} file(s) from commit that have not changed."
+ )
+
+ # Return early if empty commit
+ if len(operations_without_no_op) == 0:
+ logger.warning("No files have been modified since last commit. Skipping to prevent empty commit.")
+
+ # Get latest commit info
+ try:
+ info = self.repo_info(repo_id=repo_id, repo_type=repo_type, revision=unquoted_revision, token=token)
+ except RepositoryNotFoundError as e:
+ e.append_to_message(_CREATE_COMMIT_NO_REPO_ERROR_MESSAGE)
+ raise
+
+ # Return commit info based on latest commit
+ url_prefix = self.endpoint
+ if repo_type is not None and repo_type != constants.REPO_TYPE_MODEL:
+ url_prefix = f"{url_prefix}/{repo_type}s"
+ return CommitInfo(
+ commit_url=f"{url_prefix}/{repo_id}/commit/{info.sha}",
+ commit_message=commit_message,
+ commit_description=commit_description,
+ oid=info.sha, # type: ignore[arg-type]
+ )
+
+ commit_payload = _prepare_commit_payload(
+ operations=operations,
+ files_to_copy=files_to_copy,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ parent_commit=parent_commit,
+ )
+ commit_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/commit/{revision}"
+
+ def _payload_as_ndjson() -> Iterable[bytes]:
+ for item in commit_payload:
+ yield json.dumps(item).encode()
+ yield b"\n"
+
+ headers = {
+ # See https://github.com/huggingface/huggingface_hub/issues/1085#issuecomment-1265208073
+ "Content-Type": "application/x-ndjson",
+ **headers,
+ }
+ data = b"".join(_payload_as_ndjson())
+ params = {"create_pr": "1"} if create_pr else None
+
+ try:
+ commit_resp = get_session().post(url=commit_url, headers=headers, data=data, params=params)
+ hf_raise_for_status(commit_resp, endpoint_name="commit")
+ except RepositoryNotFoundError as e:
+ e.append_to_message(_CREATE_COMMIT_NO_REPO_ERROR_MESSAGE)
+ raise
+ except EntryNotFoundError as e:
+ if nb_deletions > 0 and "A file with this name doesn't exist" in str(e):
+ e.append_to_message(
+ "\nMake sure to differentiate file and folder paths in delete"
+ " operations with a trailing '/' or using `is_folder=True/False`."
+ )
+ raise
+
+ # Mark additions as committed (cannot be reused in another commit)
+ for addition in additions:
+ addition._is_committed = True
+
+ commit_data = commit_resp.json()
+ return CommitInfo(
+ commit_url=commit_data["commitUrl"],
+ commit_message=commit_message,
+ commit_description=commit_description,
+ oid=commit_data["commitOid"],
+ pr_url=commit_data["pullRequestUrl"] if create_pr else None,
+ )
+
+ def preupload_lfs_files(
+ self,
+ repo_id: str,
+ additions: Iterable[CommitOperationAdd],
+ *,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ num_threads: int = 5,
+ free_memory: bool = True,
+ gitignore_content: Optional[str] = None,
+ ):
+ """Pre-upload LFS files to S3 in preparation on a future commit.
+
+ This method is useful if you are generating the files to upload on-the-fly and you don't want to store them
+ in memory before uploading them all at once.
+
+ > [!WARNING]
+ > This is a power-user method. You shouldn't need to call it directly to make a normal commit.
+ > Use [`create_commit`] directly instead.
+
+ > [!WARNING]
+ > Commit operations will be mutated during the process. In particular, the attached `path_or_fileobj` will be
+ > removed after the upload to save memory (and replaced by an empty `bytes` object). Do not reuse the same
+ > objects except to pass them to [`create_commit`]. If you don't want to remove the attached content from the
+ > commit operation object, pass `free_memory=False`.
+
+ Args:
+ repo_id (`str`):
+ The repository in which you will commit the files, for example: `"username/custom_transformers"`.
+
+ operations (`Iterable` of [`CommitOperationAdd`]):
+ The list of files to upload. Warning: the objects in this list will be mutated to include information
+ relative to the upload. Do not reuse the same objects for multiple commits.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ The type of repository to upload to (e.g. `"model"` -default-, `"dataset"` or `"space"`).
+
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+
+ create_pr (`boolean`, *optional*):
+ Whether or not you plan to create a Pull Request with that commit. Defaults to `False`.
+
+ num_threads (`int`, *optional*):
+ Number of concurrent threads for uploading files. Defaults to 5.
+ Setting it to 2 means at most 2 files will be uploaded concurrently.
+
+ gitignore_content (`str`, *optional*):
+ The content of the `.gitignore` file to know which files should be ignored. The order of priority
+ is to first check if `gitignore_content` is passed, then check if the `.gitignore` file is present
+ in the list of files to commit and finally default to the `.gitignore` file already hosted on the Hub
+ (if any).
+
+ Example:
+ ```py
+ >>> from huggingface_hub import CommitOperationAdd, preupload_lfs_files, create_commit, create_repo
+
+ >>> repo_id = create_repo("test_preupload").repo_id
+
+ # Generate and preupload LFS files one by one
+ >>> operations = [] # List of all `CommitOperationAdd` objects that will be generated
+ >>> for i in range(5):
+ ... content = ... # generate binary content
+ ... addition = CommitOperationAdd(path_in_repo=f"shard_{i}_of_5.bin", path_or_fileobj=content)
+ ... preupload_lfs_files(repo_id, additions=[addition]) # upload + free memory
+ ... operations.append(addition)
+
+ # Create commit
+ >>> create_commit(repo_id, operations=operations, commit_message="Commit all shards")
+ ```
+ """
+ repo_type = repo_type if repo_type is not None else constants.REPO_TYPE_MODEL
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ revision = quote(revision, safe="") if revision is not None else constants.DEFAULT_REVISION
+ create_pr = create_pr if create_pr is not None else False
+ headers = self._build_hf_headers(token=token)
+
+ # Check if a `gitignore` file is being committed to the Hub.
+ additions = list(additions)
+ if gitignore_content is None:
+ for addition in additions:
+ if addition.path_in_repo == ".gitignore":
+ with addition.as_file() as f:
+ gitignore_content = f.read().decode()
+ break
+
+ # Filter out already uploaded files
+ new_additions = [addition for addition in additions if not addition._is_uploaded]
+
+ # Check which new files are LFS
+ # For some items, we might have already fetched the upload mode (in case of upload_large_folder)
+ additions_no_upload_mode = [addition for addition in new_additions if addition._upload_mode is None]
+ if len(additions_no_upload_mode) > 0:
+ try:
+ _fetch_upload_modes(
+ additions=additions_no_upload_mode,
+ repo_type=repo_type,
+ repo_id=repo_id,
+ headers=headers,
+ revision=revision,
+ endpoint=self.endpoint,
+ create_pr=create_pr or False,
+ gitignore_content=gitignore_content,
+ )
+ except RepositoryNotFoundError as e:
+ e.append_to_message(_CREATE_COMMIT_NO_REPO_ERROR_MESSAGE)
+ raise
+
+ # Filter out regular files
+ new_lfs_additions = [addition for addition in new_additions if addition._upload_mode == "lfs"]
+
+ # Filter out files listed in .gitignore
+ new_lfs_additions_to_upload = []
+ for addition in new_lfs_additions:
+ if addition._should_ignore:
+ logger.debug(f"Skipping upload for LFS file '{addition.path_in_repo}' (ignored by gitignore file).")
+ else:
+ new_lfs_additions_to_upload.append(addition)
+ if len(new_lfs_additions) != len(new_lfs_additions_to_upload):
+ logger.info(
+ f"Skipped upload for {len(new_lfs_additions) - len(new_lfs_additions_to_upload)} LFS file(s) "
+ "(ignored by gitignore file)."
+ )
+ # If no LFS files remain to upload, keep previous behavior and log explicitly
+ if len(new_lfs_additions_to_upload) == 0:
+ logger.debug("No LFS files to upload.")
+ return
+ # Prepare upload parameters
+ upload_kwargs = {
+ "additions": new_lfs_additions_to_upload,
+ "repo_type": repo_type,
+ "repo_id": repo_id,
+ "headers": headers,
+ "endpoint": self.endpoint,
+ # If `create_pr`, we don't want to check user permission on the revision as users with read permission
+ # should still be able to create PRs even if they don't have write permission on the target branch of the
+ # PR (i.e. `revision`).
+ "revision": revision if not create_pr else None,
+ }
+ _upload_files(**upload_kwargs, num_threads=num_threads, create_pr=create_pr) # type: ignore [arg-type]
+ for addition in new_lfs_additions_to_upload:
+ addition._is_uploaded = True
+ if free_memory:
+ addition.path_or_fileobj = b""
+
+ @overload
+ def upload_file( # type: ignore
+ self,
+ *,
+ path_or_fileobj: Union[str, Path, bytes, BinaryIO],
+ path_in_repo: str,
+ repo_id: str,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ run_as_future: Literal[False] = ...,
+ ) -> CommitInfo: ...
+
+ @overload
+ def upload_file(
+ self,
+ *,
+ path_or_fileobj: Union[str, Path, bytes, BinaryIO],
+ path_in_repo: str,
+ repo_id: str,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ run_as_future: Literal[True] = ...,
+ ) -> Future[CommitInfo]: ...
+
+ @validate_hf_hub_args
+ @future_compatible
+ def upload_file(
+ self,
+ *,
+ path_or_fileobj: Union[str, Path, bytes, BinaryIO],
+ path_in_repo: str,
+ repo_id: str,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ run_as_future: bool = False,
+ ) -> Union[CommitInfo, Future[CommitInfo]]:
+ """
+ Upload a local file (up to 50 GB) to the given repo. The upload is done
+ through a HTTP post request, and doesn't require git or git-lfs to be
+ installed.
+
+ Args:
+ path_or_fileobj (`str`, `Path`, `bytes`, or `IO`):
+ Path to a file on the local machine or binary data stream /
+ fileobj / buffer.
+ path_in_repo (`str`):
+ Relative filepath in the repo, for example:
+ `"checkpoints/1fec34a/weights.bin"`
+ repo_id (`str`):
+ The repository to which the file will be uploaded, for example:
+ `"username/custom_transformers"`
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit
+ commit_description (`str` *optional*)
+ The description of the generated commit
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`.
+ If `revision` is not set, PR is opened against the `"main"` branch. If
+ `revision` is set and is a branch, PR is opened against this branch. If
+ `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ run_as_future (`bool`, *optional*):
+ Whether or not to run this method in the background. Background jobs are run sequentially without
+ blocking the main thread. Passing `run_as_future=True` will return a [Future](https://docs.python.org/3/library/concurrent.futures.html#future-objects)
+ object. Defaults to `False`.
+
+
+ Returns:
+ [`CommitInfo`] or `Future`:
+ Instance of [`CommitInfo`] containing information about the newly created commit (commit hash, commit
+ url, pr url, commit message,...). If `run_as_future=True` is passed, returns a Future object which will
+ contain the result when executed.
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+
+ > [!WARNING]
+ > `upload_file` assumes that the repo already exists on the Hub. If you get a
+ > Client error 404, please make sure you are authenticated and that `repo_id` and
+ > `repo_type` are set correctly. If repo does not exist, create it first using
+ > [`~hf_api.create_repo`].
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import upload_file
+
+ >>> with open("./local/filepath", "rb") as fobj:
+ ... upload_file(
+ ... path_or_fileobj=fileobj,
+ ... path_in_repo="remote/file/path.h5",
+ ... repo_id="username/my-dataset",
+ ... repo_type="dataset",
+ ... token="my_token",
+ ... )
+ "https://huggingface.co/datasets/username/my-dataset/blob/main/remote/file/path.h5"
+
+ >>> upload_file(
+ ... path_or_fileobj=".\\\\local\\\\file\\\\path",
+ ... path_in_repo="remote/file/path.h5",
+ ... repo_id="username/my-model",
+ ... token="my_token",
+ ... )
+ "https://huggingface.co/username/my-model/blob/main/remote/file/path.h5"
+
+ >>> upload_file(
+ ... path_or_fileobj=".\\\\local\\\\file\\\\path",
+ ... path_in_repo="remote/file/path.h5",
+ ... repo_id="username/my-model",
+ ... token="my_token",
+ ... create_pr=True,
+ ... )
+ "https://huggingface.co/username/my-model/blob/refs%2Fpr%2F1/remote/file/path.h5"
+ ```
+ """
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+
+ commit_message = (
+ commit_message if commit_message is not None else f"Upload {path_in_repo} with huggingface_hub"
+ )
+ operation = CommitOperationAdd(
+ path_or_fileobj=path_or_fileobj,
+ path_in_repo=path_in_repo,
+ )
+
+ commit_info = self.create_commit(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ operations=[operation],
+ commit_message=commit_message,
+ commit_description=commit_description,
+ token=token,
+ revision=revision,
+ create_pr=create_pr,
+ parent_commit=parent_commit,
+ )
+
+ if commit_info.pr_url is not None:
+ revision = quote(_parse_revision_from_pr_url(commit_info.pr_url), safe="")
+ if repo_type in constants.REPO_TYPES_URL_PREFIXES:
+ repo_id = constants.REPO_TYPES_URL_PREFIXES[repo_type] + repo_id
+ revision = revision if revision is not None else constants.DEFAULT_REVISION
+
+ return CommitInfo(
+ commit_url=commit_info.commit_url,
+ commit_message=commit_info.commit_message,
+ commit_description=commit_info.commit_description,
+ oid=commit_info.oid,
+ pr_url=commit_info.pr_url,
+ # Similar to `hf_hub_url` but it's "blob" instead of "resolve"
+ # TODO: remove this in v1.0
+ _url=f"{self.endpoint}/{repo_id}/blob/{revision}/{path_in_repo}",
+ )
+
+ @overload
+ def upload_folder( # type: ignore
+ self,
+ *,
+ repo_id: str,
+ folder_path: Union[str, Path],
+ path_in_repo: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ run_as_future: Literal[False] = ...,
+ ) -> CommitInfo: ...
+
+ @overload
+ def upload_folder( # type: ignore
+ self,
+ *,
+ repo_id: str,
+ folder_path: Union[str, Path],
+ path_in_repo: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ run_as_future: Literal[True] = ...,
+ ) -> Future[CommitInfo]: ...
+
+ @validate_hf_hub_args
+ @future_compatible
+ def upload_folder(
+ self,
+ *,
+ repo_id: str,
+ folder_path: Union[str, Path],
+ path_in_repo: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ run_as_future: bool = False,
+ ) -> Union[CommitInfo, Future[CommitInfo]]:
+ """
+ Upload a local folder to the given repo. The upload is done through a HTTP requests, and doesn't require git or
+ git-lfs to be installed.
+
+ The structure of the folder will be preserved. Files with the same name already present in the repository will
+ be overwritten. Others will be left untouched.
+
+ Use the `allow_patterns` and `ignore_patterns` arguments to specify which files to upload. These parameters
+ accept either a single pattern or a list of patterns. Patterns are Standard Wildcards (globbing patterns) as
+ documented [here](https://tldp.org/LDP/GNU-Linux-Tools-Summary/html/x11655.htm). If both `allow_patterns` and
+ `ignore_patterns` are provided, both constraints apply. By default, all files from the folder are uploaded.
+
+ Use the `delete_patterns` argument to specify remote files you want to delete. Input type is the same as for
+ `allow_patterns` (see above). If `path_in_repo` is also provided, the patterns are matched against paths
+ relative to this folder. For example, `upload_folder(..., path_in_repo="experiment", delete_patterns="logs/*")`
+ will delete any remote file under `./experiment/logs/`. Note that the `.gitattributes` file will not be deleted
+ even if it matches the patterns.
+
+ Any `.git/` folder present in any subdirectory will be ignored. However, please be aware that the `.gitignore`
+ file is not taken into account.
+
+ Uses `HfApi.create_commit` under the hood.
+
+ Args:
+ repo_id (`str`):
+ The repository to which the file will be uploaded, for example:
+ `"username/custom_transformers"`
+ folder_path (`str` or `Path`):
+ Path to the folder to upload on the local file system
+ path_in_repo (`str`, *optional*):
+ Relative path of the directory in the repo, for example:
+ `"checkpoints/1fec34a/results"`. Will default to the root folder of the repository.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit. Defaults to:
+ `f"Upload {path_in_repo} with huggingface_hub"`
+ commit_description (`str` *optional*):
+ The description of the generated commit
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`. If `revision` is not
+ set, PR is opened against the `"main"` branch. If `revision` is set and is a branch, PR is opened
+ against this branch. If `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are uploaded.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not uploaded.
+ delete_patterns (`List[str]` or `str`, *optional*):
+ If provided, remote files matching any of the patterns will be deleted from the repo while committing
+ new files. This is useful if you don't know which files have already been uploaded.
+ Note: to avoid discrepancies the `.gitattributes` file is not deleted even if it matches the pattern.
+ run_as_future (`bool`, *optional*):
+ Whether or not to run this method in the background. Background jobs are run sequentially without
+ blocking the main thread. Passing `run_as_future=True` will return a [Future](https://docs.python.org/3/library/concurrent.futures.html#future-objects)
+ object. Defaults to `False`.
+
+ Returns:
+ [`CommitInfo`] or `Future`:
+ Instance of [`CommitInfo`] containing information about the newly created commit (commit hash, commit
+ url, pr url, commit message,...). If `run_as_future=True` is passed, returns a Future object which will
+ contain the result when executed.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+
+ > [!WARNING]
+ > `upload_folder` assumes that the repo already exists on the Hub. If you get a Client error 404, please make
+ > sure you are authenticated and that `repo_id` and `repo_type` are set correctly. If repo does not exist, create
+ > it first using [`~hf_api.create_repo`].
+
+ > [!TIP]
+ > When dealing with a large folder (thousands of files or hundreds of GB), we recommend using [`~hf_api.upload_large_folder`] instead.
+
+ Example:
+
+ ```python
+ # Upload checkpoints folder except the log files
+ >>> upload_folder(
+ ... folder_path="local/checkpoints",
+ ... path_in_repo="remote/experiment/checkpoints",
+ ... repo_id="username/my-dataset",
+ ... repo_type="datasets",
+ ... token="my_token",
+ ... ignore_patterns="**/logs/*.txt",
+ ... )
+ # "https://huggingface.co/datasets/username/my-dataset/tree/main/remote/experiment/checkpoints"
+
+ # Upload checkpoints folder including logs while deleting existing logs from the repo
+ # Useful if you don't know exactly which log files have already being pushed
+ >>> upload_folder(
+ ... folder_path="local/checkpoints",
+ ... path_in_repo="remote/experiment/checkpoints",
+ ... repo_id="username/my-dataset",
+ ... repo_type="datasets",
+ ... token="my_token",
+ ... delete_patterns="**/logs/*.txt",
+ ... )
+ "https://huggingface.co/datasets/username/my-dataset/tree/main/remote/experiment/checkpoints"
+
+ # Upload checkpoints folder while creating a PR
+ >>> upload_folder(
+ ... folder_path="local/checkpoints",
+ ... path_in_repo="remote/experiment/checkpoints",
+ ... repo_id="username/my-dataset",
+ ... repo_type="datasets",
+ ... token="my_token",
+ ... create_pr=True,
+ ... )
+ "https://huggingface.co/datasets/username/my-dataset/tree/refs%2Fpr%2F1/remote/experiment/checkpoints"
+
+ ```
+ """
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+
+ # By default, upload folder to the root directory in repo.
+ if path_in_repo is None:
+ path_in_repo = ""
+
+ # Do not upload .git folder
+ if ignore_patterns is None:
+ ignore_patterns = []
+ elif isinstance(ignore_patterns, str):
+ ignore_patterns = [ignore_patterns]
+ ignore_patterns += DEFAULT_IGNORE_PATTERNS
+
+ delete_operations = self._prepare_folder_deletions(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=constants.DEFAULT_REVISION if create_pr else revision,
+ token=token,
+ path_in_repo=path_in_repo,
+ delete_patterns=delete_patterns,
+ )
+ add_operations = self._prepare_upload_folder_additions(
+ folder_path,
+ path_in_repo,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ token=token,
+ repo_type=repo_type,
+ )
+
+ # Optimize operations: if some files will be overwritten, we don't need to delete them first
+ if len(add_operations) > 0:
+ added_paths = set(op.path_in_repo for op in add_operations)
+ delete_operations = [
+ delete_op for delete_op in delete_operations if delete_op.path_in_repo not in added_paths
+ ]
+ commit_operations = delete_operations + add_operations
+
+ commit_message = commit_message or "Upload folder using huggingface_hub"
+
+ commit_info = self.create_commit(
+ repo_type=repo_type,
+ repo_id=repo_id,
+ operations=commit_operations,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ token=token,
+ revision=revision,
+ create_pr=create_pr,
+ parent_commit=parent_commit,
+ )
+
+ # Create url to uploaded folder (for legacy return value)
+ if create_pr and commit_info.pr_url is not None:
+ revision = quote(_parse_revision_from_pr_url(commit_info.pr_url), safe="")
+ if repo_type in constants.REPO_TYPES_URL_PREFIXES:
+ repo_id = constants.REPO_TYPES_URL_PREFIXES[repo_type] + repo_id
+ revision = revision if revision is not None else constants.DEFAULT_REVISION
+
+ return CommitInfo(
+ commit_url=commit_info.commit_url,
+ commit_message=commit_info.commit_message,
+ commit_description=commit_info.commit_description,
+ oid=commit_info.oid,
+ pr_url=commit_info.pr_url,
+ # Similar to `hf_hub_url` but it's "tree" instead of "resolve"
+ # TODO: remove this in v1.0
+ _url=f"{self.endpoint}/{repo_id}/tree/{revision}/{path_in_repo}",
+ )
+
+ @validate_hf_hub_args
+ def delete_file(
+ self,
+ path_in_repo: str,
+ repo_id: str,
+ *,
+ token: Union[str, bool, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ ) -> CommitInfo:
+ """
+ Deletes a file in the given repo.
+
+ Args:
+ path_in_repo (`str`):
+ Relative filepath in the repo, for example:
+ `"checkpoints/1fec34a/weights.bin"`
+ repo_id (`str`):
+ The repository from which the file will be deleted, for example:
+ `"username/custom_transformers"`
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if the file is in a dataset or
+ space, `None` or `"model"` if in a model. Default is `None`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit. Defaults to
+ `f"Delete {path_in_repo} with huggingface_hub"`.
+ commit_description (`str` *optional*)
+ The description of the generated commit
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`.
+ If `revision` is not set, PR is opened against the `"main"` branch. If
+ `revision` is set and is a branch, PR is opened against this branch. If
+ `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ > - [`~utils.RevisionNotFoundError`]
+ > If the revision to download from cannot be found.
+ > - [`~utils.EntryNotFoundError`]
+ > If the file to download cannot be found.
+
+ """
+ commit_message = (
+ commit_message if commit_message is not None else f"Delete {path_in_repo} with huggingface_hub"
+ )
+
+ operations = [CommitOperationDelete(path_in_repo=path_in_repo)]
+
+ return self.create_commit(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ token=token,
+ operations=operations,
+ revision=revision,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ create_pr=create_pr,
+ parent_commit=parent_commit,
+ )
+
+ @validate_hf_hub_args
+ def delete_files(
+ self,
+ repo_id: str,
+ delete_patterns: List[str],
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ ) -> CommitInfo:
+ """
+ Delete files from a repository on the Hub.
+
+ If a folder path is provided, the entire folder is deleted as well as
+ all files it contained.
+
+ Args:
+ repo_id (`str`):
+ The repository from which the folder will be deleted, for example:
+ `"username/custom_transformers"`
+ delete_patterns (`List[str]`):
+ List of files or folders to delete. Each string can either be
+ a file path, a folder path or a Unix shell-style wildcard.
+ E.g. `["file.txt", "folder/", "data/*.parquet"]`
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ to the stored token.
+ repo_type (`str`, *optional*):
+ Type of the repo to delete files from. Can be `"model"`,
+ `"dataset"` or `"space"`. Defaults to `"model"`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The summary (first line) of the generated commit. Defaults to
+ `f"Delete files using huggingface_hub"`.
+ commit_description (`str` *optional*)
+ The description of the generated commit.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`.
+ If `revision` is not set, PR is opened against the `"main"` branch. If
+ `revision` is set and is a branch, PR is opened against this branch. If
+ `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ """
+ operations = self._prepare_folder_deletions(
+ repo_id=repo_id, repo_type=repo_type, delete_patterns=delete_patterns, path_in_repo="", revision=revision
+ )
+
+ if commit_message is None:
+ commit_message = f"Delete files {' '.join(delete_patterns)} with huggingface_hub"
+
+ return self.create_commit(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ token=token,
+ operations=operations,
+ revision=revision,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ create_pr=create_pr,
+ parent_commit=parent_commit,
+ )
+
+ @validate_hf_hub_args
+ def delete_folder(
+ self,
+ path_in_repo: str,
+ repo_id: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ ) -> CommitInfo:
+ """
+ Deletes a folder in the given repo.
+
+ Simple wrapper around [`create_commit`] method.
+
+ Args:
+ path_in_repo (`str`):
+ Relative folder path in the repo, for example: `"checkpoints/1fec34a"`.
+ repo_id (`str`):
+ The repository from which the folder will be deleted, for example:
+ `"username/custom_transformers"`
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ to the stored token.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if the folder is in a dataset or
+ space, `None` or `"model"` if in a model. Default is `None`.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit. Defaults to
+ `f"Delete folder {path_in_repo} with huggingface_hub"`.
+ commit_description (`str` *optional*)
+ The description of the generated commit.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request with that commit. Defaults to `False`.
+ If `revision` is not set, PR is opened against the `"main"` branch. If
+ `revision` is set and is a branch, PR is opened against this branch. If
+ `revision` is set and is not a branch name (example: a commit oid), an
+ `RevisionNotFoundError` is returned by the server.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ """
+ return self.create_commit(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ token=token,
+ operations=[CommitOperationDelete(path_in_repo=path_in_repo, is_folder=True)],
+ revision=revision,
+ commit_message=(
+ commit_message if commit_message is not None else f"Delete folder {path_in_repo} with huggingface_hub"
+ ),
+ commit_description=commit_description,
+ create_pr=create_pr,
+ parent_commit=parent_commit,
+ )
+
+ def upload_large_folder(
+ self,
+ repo_id: str,
+ folder_path: Union[str, Path],
+ *,
+ repo_type: str, # Repo type is required!
+ revision: Optional[str] = None,
+ private: Optional[bool] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ num_workers: Optional[int] = None,
+ print_report: bool = True,
+ print_report_every: int = 60,
+ ) -> None:
+ """Upload a large folder to the Hub in the most resilient way possible.
+
+ Several workers are started to upload files in an optimized way. Before being committed to a repo, files must be
+ hashed and be pre-uploaded if they are LFS files. Workers will perform these tasks for each file in the folder.
+ At each step, some metadata information about the upload process is saved in the folder under `.cache/.huggingface/`
+ to be able to resume the process if interrupted. The whole process might result in several commits.
+
+ Args:
+ repo_id (`str`):
+ The repository to which the file will be uploaded.
+ E.g. `"HuggingFaceTB/smollm-corpus"`.
+ folder_path (`str` or `Path`):
+ Path to the folder to upload on the local file system.
+ repo_type (`str`):
+ Type of the repository. Must be one of `"model"`, `"dataset"` or `"space"`.
+ Unlike in all other `HfApi` methods, `repo_type` is explicitly required here. This is to avoid
+ any mistake when uploading a large folder to the Hub, and therefore prevent from having to re-upload
+ everything.
+ revision (`str`, `optional`):
+ The branch to commit to. If not provided, the `main` branch will be used.
+ private (`bool`, `optional`):
+ Whether the repository should be private.
+ If `None` (default), the repo will be public unless the organization's default is private.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are uploaded.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not uploaded.
+ num_workers (`int`, *optional*):
+ Number of workers to start. Defaults to `os.cpu_count() - 2` (minimum 2).
+ A higher number of workers may speed up the process if your machine allows it. However, on machines with a
+ slower connection, it is recommended to keep the number of workers low to ensure better resumability.
+ Indeed, partially uploaded files will have to be completely re-uploaded if the process is interrupted.
+ print_report (`bool`, *optional*):
+ Whether to print a report of the upload progress. Defaults to True.
+ Report is printed to `sys.stdout` every X seconds (60 by defaults) and overwrites the previous report.
+ print_report_every (`int`, *optional*):
+ Frequency at which the report is printed. Defaults to 60 seconds.
+
+ > [!TIP]
+ > A few things to keep in mind:
+ > - Repository limits still apply: https://huggingface.co/docs/hub/repositories-recommendations
+ > - Do not start several processes in parallel.
+ > - You can interrupt and resume the process at any time.
+ > - Do not upload the same folder to several repositories. If you need to do so, you must delete the local `.cache/.huggingface/` folder first.
+
+ > [!WARNING]
+ > While being much more robust to upload large folders, `upload_large_folder` is more limited than [`upload_folder`] feature-wise. In practice:
+ > - you cannot set a custom `path_in_repo`. If you want to upload to a subfolder, you need to set the proper structure locally.
+ > - you cannot set a custom `commit_message` and `commit_description` since multiple commits are created.
+ > - you cannot delete from the repo while uploading. Please make a separate commit first.
+ > - you cannot create a PR directly. Please create a PR first (from the UI or using [`create_pull_request`]) and then commit to it by passing `revision`.
+
+ **Technical details:**
+
+ `upload_large_folder` process is as follow:
+ 1. (Check parameters and setup.)
+ 2. Create repo if missing.
+ 3. List local files to upload.
+ 4. Run validation checks and display warnings if repository limits might be exceeded:
+ - Warns if the total number of files exceeds 100k (recommended limit).
+ - Warns if any folder contains more than 10k files (recommended limit).
+ - Warns about files larger than 20GB (recommended) or 50GB (hard limit).
+ 5. Start workers. Workers can perform the following tasks:
+ - Hash a file.
+ - Get upload mode (regular or LFS) for a list of files.
+ - Pre-upload an LFS file.
+ - Commit a bunch of files.
+ Once a worker finishes a task, it will move on to the next task based on the priority list (see below) until
+ all files are uploaded and committed.
+ 6. While workers are up, regularly print a report to sys.stdout.
+
+ Order of priority:
+ 1. Commit if more than 5 minutes since last commit attempt (and at least 1 file).
+ 2. Commit if at least 150 files are ready to commit.
+ 3. Get upload mode if at least 10 files have been hashed.
+ 4. Pre-upload LFS file if at least 1 file and no worker is pre-uploading.
+ 5. Hash file if at least 1 file and no worker is hashing.
+ 6. Get upload mode if at least 1 file and no worker is getting upload mode.
+ 7. Pre-upload LFS file if at least 1 file (exception: if hf_transfer is enabled, only 1 worker can preupload LFS at a time).
+ 8. Hash file if at least 1 file to hash.
+ 9. Get upload mode if at least 1 file to get upload mode.
+ 10. Commit if at least 1 file to commit and at least 1 min since last commit attempt.
+ 11. Commit if at least 1 file to commit and all other queues are empty.
+
+ Special rules:
+ - If `hf_transfer` is enabled, only 1 LFS uploader at a time. Otherwise the CPU would be bloated by `hf_transfer`.
+ - Only one worker can commit at a time.
+ - If no tasks are available, the worker waits for 10 seconds before checking again.
+ """
+ return upload_large_folder_internal(
+ self,
+ repo_id=repo_id,
+ folder_path=folder_path,
+ repo_type=repo_type,
+ revision=revision,
+ private=private,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ num_workers=num_workers,
+ print_report=print_report,
+ print_report_every=print_report_every,
+ )
+
+ @validate_hf_hub_args
+ def get_hf_file_metadata(
+ self,
+ *,
+ url: str,
+ token: Union[bool, str, None] = None,
+ proxies: Optional[Dict] = None,
+ timeout: Optional[float] = constants.DEFAULT_REQUEST_TIMEOUT,
+ ) -> HfFileMetadata:
+ """Fetch metadata of a file versioned on the Hub for a given url.
+
+ Args:
+ url (`str`):
+ File url, for example returned by [`hf_hub_url`].
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to `requests.request`.
+ timeout (`float`, *optional*, defaults to 10):
+ How many seconds to wait for the server to send metadata before giving up.
+
+ Returns:
+ A [`HfFileMetadata`] object containing metadata such as location, etag, size and commit_hash.
+ """
+ if token is None:
+ # Cannot do `token = token or self.token` as token can be `False`.
+ token = self.token
+
+ return get_hf_file_metadata(
+ url=url,
+ token=token,
+ proxies=proxies,
+ timeout=timeout,
+ library_name=self.library_name,
+ library_version=self.library_version,
+ user_agent=self.user_agent,
+ endpoint=self.endpoint,
+ )
+
+ @validate_hf_hub_args
+ def hf_hub_download(
+ self,
+ repo_id: str,
+ filename: str,
+ *,
+ subfolder: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ cache_dir: Union[str, Path, None] = None,
+ local_dir: Union[str, Path, None] = None,
+ force_download: bool = False,
+ proxies: Optional[Dict] = None,
+ etag_timeout: float = constants.DEFAULT_ETAG_TIMEOUT,
+ token: Union[bool, str, None] = None,
+ local_files_only: bool = False,
+ # Deprecated args
+ resume_download: Optional[bool] = None,
+ force_filename: Optional[str] = None,
+ local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
+ ) -> str:
+ """Download a given file if it's not already present in the local cache.
+
+ The new cache file layout looks like this:
+ - The cache directory contains one subfolder per repo_id (namespaced by repo type)
+ - inside each repo folder:
+ - refs is a list of the latest known revision => commit_hash pairs
+ - blobs contains the actual file blobs (identified by their git-sha or sha256, depending on
+ whether they're LFS files or not)
+ - snapshots contains one subfolder per commit, each "commit" contains the subset of the files
+ that have been resolved at that particular commit. Each filename is a symlink to the blob
+ at that particular commit.
+
+ ```
+ [ 96] .
+ └── [ 160] models--julien-c--EsperBERTo-small
+ ├── [ 160] blobs
+ │ ├── [321M] 403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ │ ├── [ 398] 7cb18dc9bafbfcf74629a4b760af1b160957a83e
+ │ └── [1.4K] d7edf6bd2a681fb0175f7735299831ee1b22b812
+ ├── [ 96] refs
+ │ └── [ 40] main
+ └── [ 128] snapshots
+ ├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f
+ │ ├── [ 52] README.md -> ../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812
+ │ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ └── [ 128] bbc77c8132af1cc5cf678da3f1ddf2de43606d48
+ ├── [ 52] README.md -> ../../blobs/7cb18dc9bafbfcf74629a4b760af1b160957a83e
+ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
+ ```
+
+ If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
+ option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
+ to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
+ cache-system, it's optimized for regularly pulling the latest version of a repository.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ filename (`str`):
+ The name of the file in the repo.
+ subfolder (`str`, *optional*):
+ An optional value corresponding to a folder inside the repository.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+ `None` or `"model"` if downloading from a model. Default is `None`.
+ revision (`str`, *optional*):
+ An optional Git revision id which can be a branch name, a tag, or a
+ commit hash.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_dir (`str` or `Path`, *optional*):
+ If provided, the downloaded file will be placed under this directory.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether the file should be downloaded even if it already exists in
+ the local cache.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to
+ `requests.request`.
+ etag_timeout (`float`, *optional*, defaults to `10`):
+ When fetching ETag, how many seconds to wait for the server to send
+ data before giving up which is passed to `requests.request`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the
+ local cached file if it exists.
+
+ Returns:
+ `str`: Local path of file or if networking is off, last version of file cached on disk.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to download from cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ [`~utils.RevisionNotFoundError`]
+ If the revision to download from cannot be found.
+ [`~utils.EntryNotFoundError`]
+ If the file to download cannot be found.
+ [`~utils.LocalEntryNotFoundError`]
+ If network is disabled or unavailable and file is not found in cache.
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If `token=True` but the token cannot be found.
+ [`OSError`](https://docs.python.org/3/library/exceptions.html#OSError)
+ If ETag cannot be determined.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If some parameter value is invalid.
+ """
+ from .file_download import hf_hub_download
+
+ if token is None:
+ # Cannot do `token = token or self.token` as token can be `False`.
+ token = self.token
+
+ return hf_hub_download(
+ repo_id=repo_id,
+ filename=filename,
+ subfolder=subfolder,
+ repo_type=repo_type,
+ revision=revision,
+ endpoint=self.endpoint,
+ library_name=self.library_name,
+ library_version=self.library_version,
+ cache_dir=cache_dir,
+ local_dir=local_dir,
+ local_dir_use_symlinks=local_dir_use_symlinks,
+ user_agent=self.user_agent,
+ force_download=force_download,
+ force_filename=force_filename,
+ proxies=proxies,
+ etag_timeout=etag_timeout,
+ resume_download=resume_download,
+ token=token,
+ headers=self.headers,
+ local_files_only=local_files_only,
+ )
+
+ @validate_hf_hub_args
+ def snapshot_download(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ cache_dir: Union[str, Path, None] = None,
+ local_dir: Union[str, Path, None] = None,
+ proxies: Optional[Dict] = None,
+ etag_timeout: float = constants.DEFAULT_ETAG_TIMEOUT,
+ force_download: bool = False,
+ token: Union[bool, str, None] = None,
+ local_files_only: bool = False,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ max_workers: int = 8,
+ tqdm_class: Optional[Type[base_tqdm]] = None,
+ # Deprecated args
+ local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
+ resume_download: Optional[bool] = None,
+ ) -> str:
+ """Download repo files.
+
+ Download a whole snapshot of a repo's files at the specified revision. This is useful when you want all files from
+ a repo, because you don't know which ones you will need a priori. All files are nested inside a folder in order
+ to keep their actual filename relative to that folder. You can also filter which files to download using
+ `allow_patterns` and `ignore_patterns`.
+
+ If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
+ option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
+ to store some metadata related to the downloaded files.While this mechanism is not as robust as the main
+ cache-system, it's optimized for regularly pulling the latest version of a repository.
+
+ An alternative would be to clone the repo but this requires git and git-lfs to be installed and properly
+ configured. It is also not possible to filter which files to download when cloning a repository using git.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+ `None` or `"model"` if downloading from a model. Default is `None`.
+ revision (`str`, *optional*):
+ An optional Git revision id which can be a branch name, a tag, or a
+ commit hash.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_dir (`str` or `Path`, *optional*):
+ If provided, the downloaded files will be placed under this directory.
+ proxies (`dict`, *optional*):
+ Dictionary mapping protocol to the URL of the proxy passed to
+ `requests.request`.
+ etag_timeout (`float`, *optional*, defaults to `10`):
+ When fetching ETag, how many seconds to wait for the server to send
+ data before giving up which is passed to `requests.request`.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether the file should be downloaded even if it already exists in the local cache.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the
+ local cached file if it exists.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are downloaded.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not downloaded.
+ max_workers (`int`, *optional*):
+ Number of concurrent threads to download files (1 thread = 1 file download).
+ Defaults to 8.
+ tqdm_class (`tqdm`, *optional*):
+ If provided, overwrites the default behavior for the progress bar. Passed
+ argument must inherit from `tqdm.auto.tqdm` or at least mimic its behavior.
+ Note that the `tqdm_class` is not passed to each individual download.
+ Defaults to the custom HF progress bar that can be disabled by setting
+ `HF_HUB_DISABLE_PROGRESS_BARS` environment variable.
+
+ Returns:
+ `str`: folder path of the repo snapshot.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]
+ If the repository to download from cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ [`~utils.RevisionNotFoundError`]
+ If the revision to download from cannot be found.
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If `token=True` and the token cannot be found.
+ [`OSError`](https://docs.python.org/3/library/exceptions.html#OSError) if
+ ETag cannot be determined.
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ if some parameter value is invalid.
+ """
+ from ._snapshot_download import snapshot_download
+
+ if token is None:
+ # Cannot do `token = token or self.token` as token can be `False`.
+ token = self.token
+
+ return snapshot_download(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ revision=revision,
+ endpoint=self.endpoint,
+ cache_dir=cache_dir,
+ local_dir=local_dir,
+ local_dir_use_symlinks=local_dir_use_symlinks,
+ library_name=self.library_name,
+ library_version=self.library_version,
+ user_agent=self.user_agent,
+ proxies=proxies,
+ etag_timeout=etag_timeout,
+ resume_download=resume_download,
+ force_download=force_download,
+ token=token,
+ local_files_only=local_files_only,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ max_workers=max_workers,
+ tqdm_class=tqdm_class,
+ )
+
+ def get_safetensors_metadata(
+ self,
+ repo_id: str,
+ *,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> SafetensorsRepoMetadata:
+ """
+ Parse metadata for a safetensors repo on the Hub.
+
+ We first check if the repo has a single safetensors file or a sharded safetensors repo. If it's a single
+ safetensors file, we parse the metadata from this file. If it's a sharded safetensors repo, we parse the
+ metadata from the index file and then parse the metadata from each shard.
+
+ To parse metadata from a single safetensors file, use [`parse_safetensors_file_metadata`].
+
+ For more details regarding the safetensors format, check out https://huggingface.co/docs/safetensors/index#format.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if the file is in a dataset or space, `None` or `"model"` if in a
+ model. Default is `None`.
+ revision (`str`, *optional*):
+ The git revision to fetch the file from. Can be a branch name, a tag, or a commit hash. Defaults to the
+ head of the `"main"` branch.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`SafetensorsRepoMetadata`]: information related to safetensors repo.
+
+ Raises:
+ [`NotASafetensorsRepoError`]
+ If the repo is not a safetensors repo i.e. doesn't have either a
+ `model.safetensors` or a `model.safetensors.index.json` file.
+ [`SafetensorsParsingError`]
+ If a safetensors file header couldn't be parsed correctly.
+
+ Example:
+ ```py
+ # Parse repo with single weights file
+ >>> metadata = get_safetensors_metadata("bigscience/bloomz-560m")
+ >>> metadata
+ SafetensorsRepoMetadata(
+ metadata=None,
+ sharded=False,
+ weight_map={'h.0.input_layernorm.bias': 'model.safetensors', ...},
+ files_metadata={'model.safetensors': SafetensorsFileMetadata(...)}
+ )
+ >>> metadata.files_metadata["model.safetensors"].metadata
+ {'format': 'pt'}
+
+ # Parse repo with sharded model
+ >>> metadata = get_safetensors_metadata("bigscience/bloom")
+ Parse safetensors files: 100%|██████████████████████████████████████████| 72/72 [00:12<00:00, 5.78it/s]
+ >>> metadata
+ SafetensorsRepoMetadata(metadata={'total_size': 352494542848}, sharded=True, weight_map={...}, files_metadata={...})
+ >>> len(metadata.files_metadata)
+ 72 # All safetensors files have been fetched
+
+ # Parse repo with sharded model
+ >>> get_safetensors_metadata("runwayml/stable-diffusion-v1-5")
+ NotASafetensorsRepoError: 'runwayml/stable-diffusion-v1-5' is not a safetensors repo. Couldn't find 'model.safetensors.index.json' or 'model.safetensors' files.
+ ```
+ """
+ if self.file_exists( # Single safetensors file => non-sharded model
+ repo_id=repo_id,
+ filename=constants.SAFETENSORS_SINGLE_FILE,
+ repo_type=repo_type,
+ revision=revision,
+ token=token,
+ ):
+ file_metadata = self.parse_safetensors_file_metadata(
+ repo_id=repo_id,
+ filename=constants.SAFETENSORS_SINGLE_FILE,
+ repo_type=repo_type,
+ revision=revision,
+ token=token,
+ )
+ return SafetensorsRepoMetadata(
+ metadata=None,
+ sharded=False,
+ weight_map={
+ tensor_name: constants.SAFETENSORS_SINGLE_FILE for tensor_name in file_metadata.tensors.keys()
+ },
+ files_metadata={constants.SAFETENSORS_SINGLE_FILE: file_metadata},
+ )
+ elif self.file_exists( # Multiple safetensors files => sharded with index
+ repo_id=repo_id,
+ filename=constants.SAFETENSORS_INDEX_FILE,
+ repo_type=repo_type,
+ revision=revision,
+ token=token,
+ ):
+ # Fetch index
+ index_file = self.hf_hub_download(
+ repo_id=repo_id,
+ filename=constants.SAFETENSORS_INDEX_FILE,
+ repo_type=repo_type,
+ revision=revision,
+ token=token,
+ )
+ with open(index_file) as f:
+ index = json.load(f)
+
+ weight_map = index.get("weight_map", {})
+
+ # Fetch metadata per shard
+ files_metadata = {}
+
+ def _parse(filename: str) -> None:
+ files_metadata[filename] = self.parse_safetensors_file_metadata(
+ repo_id=repo_id, filename=filename, repo_type=repo_type, revision=revision, token=token
+ )
+
+ thread_map(
+ _parse,
+ set(weight_map.values()),
+ desc="Parse safetensors files",
+ tqdm_class=hf_tqdm,
+ )
+
+ return SafetensorsRepoMetadata(
+ metadata=index.get("metadata", None),
+ sharded=True,
+ weight_map=weight_map,
+ files_metadata=files_metadata,
+ )
+ else:
+ # Not a safetensors repo
+ raise NotASafetensorsRepoError(
+ f"'{repo_id}' is not a safetensors repo. Couldn't find '{constants.SAFETENSORS_INDEX_FILE}' or '{constants.SAFETENSORS_SINGLE_FILE}' files."
+ )
+
+ def parse_safetensors_file_metadata(
+ self,
+ repo_id: str,
+ filename: str,
+ *,
+ repo_type: Optional[str] = None,
+ revision: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> SafetensorsFileMetadata:
+ """
+ Parse metadata from a safetensors file on the Hub.
+
+ To parse metadata from all safetensors files in a repo at once, use [`get_safetensors_metadata`].
+
+ For more details regarding the safetensors format, check out https://huggingface.co/docs/safetensors/index#format.
+
+ Args:
+ repo_id (`str`):
+ A user or an organization name and a repo name separated by a `/`.
+ filename (`str`):
+ The name of the file in the repo.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if the file is in a dataset or space, `None` or `"model"` if in a
+ model. Default is `None`.
+ revision (`str`, *optional*):
+ The git revision to fetch the file from. Can be a branch name, a tag, or a commit hash. Defaults to the
+ head of the `"main"` branch.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`SafetensorsFileMetadata`]: information related to a safetensors file.
+
+ Raises:
+ [`NotASafetensorsRepoError`]:
+ If the repo is not a safetensors repo i.e. doesn't have either a
+ `model.safetensors` or a `model.safetensors.index.json` file.
+ [`SafetensorsParsingError`]:
+ If a safetensors file header couldn't be parsed correctly.
+ """
+ url = hf_hub_url(
+ repo_id=repo_id, filename=filename, repo_type=repo_type, revision=revision, endpoint=self.endpoint
+ )
+ _headers = self._build_hf_headers(token=token)
+
+ # 1. Fetch first 100kb
+ # Empirically, 97% of safetensors files have a metadata size < 100kb (over the top 1000 models on the Hub).
+ # We assume fetching 100kb is faster than making 2 GET requests. Therefore we always fetch the first 100kb to
+ # avoid the 2nd GET in most cases.
+ # See https://github.com/huggingface/huggingface_hub/pull/1855#discussion_r1404286419.
+ response = get_session().get(url, headers={**_headers, "range": "bytes=0-100000"})
+ hf_raise_for_status(response)
+
+ # 2. Parse metadata size
+ metadata_size = struct.unpack(" constants.SAFETENSORS_MAX_HEADER_LENGTH:
+ raise SafetensorsParsingError(
+ f"Failed to parse safetensors header for '{filename}' (repo '{repo_id}', revision "
+ f"'{revision or constants.DEFAULT_REVISION}'): safetensors header is too big. Maximum supported size is "
+ f"{constants.SAFETENSORS_MAX_HEADER_LENGTH} bytes (got {metadata_size})."
+ )
+
+ # 3.a. Get metadata from payload
+ if metadata_size <= 100000:
+ metadata_as_bytes = response.content[8 : 8 + metadata_size]
+ else: # 3.b. Request full metadata
+ response = get_session().get(url, headers={**_headers, "range": f"bytes=8-{metadata_size + 7}"})
+ hf_raise_for_status(response)
+ metadata_as_bytes = response.content
+
+ # 4. Parse json header
+ try:
+ metadata_as_dict = json.loads(metadata_as_bytes.decode(errors="ignore"))
+ except json.JSONDecodeError as e:
+ raise SafetensorsParsingError(
+ f"Failed to parse safetensors header for '{filename}' (repo '{repo_id}', revision "
+ f"'{revision or constants.DEFAULT_REVISION}'): header is not json-encoded string. Please make sure this is a "
+ "correctly formatted safetensors file."
+ ) from e
+
+ try:
+ return SafetensorsFileMetadata(
+ metadata=metadata_as_dict.get("__metadata__", {}),
+ tensors={
+ key: TensorInfo(
+ dtype=tensor["dtype"],
+ shape=tensor["shape"],
+ data_offsets=tuple(tensor["data_offsets"]), # type: ignore
+ )
+ for key, tensor in metadata_as_dict.items()
+ if key != "__metadata__"
+ },
+ )
+ except (KeyError, IndexError) as e:
+ raise SafetensorsParsingError(
+ f"Failed to parse safetensors header for '{filename}' (repo '{repo_id}', revision "
+ f"'{revision or constants.DEFAULT_REVISION}'): header format not recognized. Please make sure this is a correctly"
+ " formatted safetensors file."
+ ) from e
+
+ @validate_hf_hub_args
+ def create_branch(
+ self,
+ repo_id: str,
+ *,
+ branch: str,
+ revision: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ exist_ok: bool = False,
+ ) -> None:
+ """
+ Create a new branch for a repo on the Hub, starting from the specified revision (defaults to `main`).
+ To find a revision suiting your needs, you can use [`list_repo_refs`] or [`list_repo_commits`].
+
+ Args:
+ repo_id (`str`):
+ The repository in which the branch will be created.
+ Example: `"user/my-cool-model"`.
+
+ branch (`str`):
+ The name of the branch to create.
+
+ revision (`str`, *optional*):
+ The git revision to create the branch from. It can be a branch name or
+ the OID/SHA of a commit, as a hexadecimal string. Defaults to the head
+ of the `"main"` branch.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if creating a branch on a dataset or
+ space, `None` or `"model"` if tagging a model. Default is `None`.
+
+ exist_ok (`bool`, *optional*, defaults to `False`):
+ If `True`, do not raise an error if branch already exists.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+ [`~utils.BadRequestError`]:
+ If invalid reference for a branch. Ex: `refs/pr/5` or 'refs/foo/bar'.
+ [`~utils.HfHubHTTPError`]:
+ If the branch already exists on the repo (error 409) and `exist_ok` is
+ set to `False`.
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ branch = quote(branch, safe="")
+
+ # Prepare request
+ branch_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/branch/{branch}"
+ headers = self._build_hf_headers(token=token)
+ payload = {}
+ if revision is not None:
+ payload["startingPoint"] = revision
+
+ # Create branch
+ response = get_session().post(url=branch_url, headers=headers, json=payload)
+ try:
+ hf_raise_for_status(response)
+ except HfHubHTTPError as e:
+ if exist_ok and e.response.status_code == 409:
+ return
+ elif exist_ok and e.response.status_code == 403:
+ # No write permission on the namespace but branch might already exist
+ try:
+ refs = self.list_repo_refs(repo_id=repo_id, repo_type=repo_type, token=token)
+ for branch_ref in refs.branches:
+ if branch_ref.name == branch:
+ return # Branch already exists => do not raise
+ except HfHubHTTPError:
+ pass # We raise the original error if the branch does not exist
+ raise
+
+ @validate_hf_hub_args
+ def delete_branch(
+ self,
+ repo_id: str,
+ *,
+ branch: str,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> None:
+ """
+ Delete a branch from a repo on the Hub.
+
+ Args:
+ repo_id (`str`):
+ The repository in which a branch will be deleted.
+ Example: `"user/my-cool-model"`.
+
+ branch (`str`):
+ The name of the branch to delete.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if creating a branch on a dataset or
+ space, `None` or `"model"` if tagging a model. Default is `None`.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+ [`~utils.HfHubHTTPError`]:
+ If trying to delete a protected branch. Ex: `main` cannot be deleted.
+ [`~utils.HfHubHTTPError`]:
+ If trying to delete a branch that does not exist.
+
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ branch = quote(branch, safe="")
+
+ # Prepare request
+ branch_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/branch/{branch}"
+ headers = self._build_hf_headers(token=token)
+
+ # Delete branch
+ response = get_session().delete(url=branch_url, headers=headers)
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def create_tag(
+ self,
+ repo_id: str,
+ *,
+ tag: str,
+ tag_message: Optional[str] = None,
+ revision: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ exist_ok: bool = False,
+ ) -> None:
+ """
+ Tag a given commit of a repo on the Hub.
+
+ Args:
+ repo_id (`str`):
+ The repository in which a commit will be tagged.
+ Example: `"user/my-cool-model"`.
+
+ tag (`str`):
+ The name of the tag to create.
+
+ tag_message (`str`, *optional*):
+ The description of the tag to create.
+
+ revision (`str`, *optional*):
+ The git revision to tag. It can be a branch name or the OID/SHA of a
+ commit, as a hexadecimal string. Shorthands (7 first characters) are
+ also supported. Defaults to the head of the `"main"` branch.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if tagging a dataset or
+ space, `None` or `"model"` if tagging a model. Default is
+ `None`.
+
+ exist_ok (`bool`, *optional*, defaults to `False`):
+ If `True`, do not raise an error if tag already exists.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If revision is not found (error 404) on the repo.
+ [`~utils.HfHubHTTPError`]:
+ If the branch already exists on the repo (error 409) and `exist_ok` is
+ set to `False`.
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ revision = quote(revision, safe="") if revision is not None else constants.DEFAULT_REVISION
+
+ # Prepare request
+ tag_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/tag/{revision}"
+ headers = self._build_hf_headers(token=token)
+ payload = {"tag": tag}
+ if tag_message is not None:
+ payload["message"] = tag_message
+
+ # Tag
+ response = get_session().post(url=tag_url, headers=headers, json=payload)
+ try:
+ hf_raise_for_status(response)
+ except HfHubHTTPError as e:
+ if not (e.response.status_code == 409 and exist_ok):
+ raise
+
+ @validate_hf_hub_args
+ def delete_tag(
+ self,
+ repo_id: str,
+ *,
+ tag: str,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> None:
+ """
+ Delete a tag from a repo on the Hub.
+
+ Args:
+ repo_id (`str`):
+ The repository in which a tag will be deleted.
+ Example: `"user/my-cool-model"`.
+
+ tag (`str`):
+ The name of the tag to delete.
+
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if tagging a dataset or space, `None` or
+ `"model"` if tagging a model. Default is `None`.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If repository is not found (error 404): wrong repo_id/repo_type, private
+ but not authenticated or repo does not exist.
+ [`~utils.RevisionNotFoundError`]:
+ If tag is not found.
+ """
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ tag = quote(tag, safe="")
+
+ # Prepare request
+ tag_url = f"{self.endpoint}/api/{repo_type}s/{repo_id}/tag/{tag}"
+ headers = self._build_hf_headers(token=token)
+
+ # Un-tag
+ response = get_session().delete(url=tag_url, headers=headers)
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def get_full_repo_name(
+ self,
+ model_id: str,
+ *,
+ organization: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ):
+ """
+ Returns the repository name for a given model ID and optional
+ organization.
+
+ Args:
+ model_id (`str`):
+ The name of the model.
+ organization (`str`, *optional*):
+ If passed, the repository name will be in the organization
+ namespace instead of the user namespace.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `str`: The repository name in the user's namespace
+ ({username}/{model_id}) if no organization is passed, and under the
+ organization namespace ({organization}/{model_id}) otherwise.
+ """
+ if organization is None:
+ if "/" in model_id:
+ username = model_id.split("/")[0]
+ else:
+ username = self.whoami(token=token)["name"] # type: ignore
+ return f"{username}/{model_id}"
+ else:
+ return f"{organization}/{model_id}"
+
+ @validate_hf_hub_args
+ def get_repo_discussions(
+ self,
+ repo_id: str,
+ *,
+ author: Optional[str] = None,
+ discussion_type: Optional[constants.DiscussionTypeFilter] = None,
+ discussion_status: Optional[constants.DiscussionStatusFilter] = None,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterator[Discussion]:
+ """
+ Fetches Discussions and Pull Requests for the given repo.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ author (`str`, *optional*):
+ Pass a value to filter by discussion author. `None` means no filter.
+ Default is `None`.
+ discussion_type (`str`, *optional*):
+ Set to `"pull_request"` to fetch only pull requests, `"discussion"`
+ to fetch only discussions. Set to `"all"` or `None` to fetch both.
+ Default is `None`.
+ discussion_status (`str`, *optional*):
+ Set to `"open"` (respectively `"closed"`) to fetch only open
+ (respectively closed) discussions. Set to `"all"` or `None`
+ to fetch both.
+ Default is `None`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if fetching from a dataset or
+ space, `None` or `"model"` if fetching from a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterator[Discussion]`: An iterator of [`Discussion`] objects.
+
+ Example:
+ Collecting all discussions of a repo in a list:
+
+ ```python
+ >>> from huggingface_hub import get_repo_discussions
+ >>> discussions_list = list(get_repo_discussions(repo_id="bert-base-uncased"))
+ ```
+
+ Iterating over discussions of a repo:
+
+ ```python
+ >>> from huggingface_hub import get_repo_discussions
+ >>> for discussion in get_repo_discussions(repo_id="bert-base-uncased"):
+ ... print(discussion.num, discussion.title)
+ ```
+ """
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ if discussion_type is not None and discussion_type not in constants.DISCUSSION_TYPES:
+ raise ValueError(f"Invalid discussion_type, must be one of {constants.DISCUSSION_TYPES}")
+ if discussion_status is not None and discussion_status not in constants.DISCUSSION_STATUS:
+ raise ValueError(f"Invalid discussion_status, must be one of {constants.DISCUSSION_STATUS}")
+
+ headers = self._build_hf_headers(token=token)
+ path = f"{self.endpoint}/api/{repo_type}s/{repo_id}/discussions"
+
+ params: Dict[str, Union[str, int]] = {}
+ if discussion_type is not None:
+ params["type"] = discussion_type
+ if discussion_status is not None:
+ params["status"] = discussion_status
+ if author is not None:
+ params["author"] = author
+
+ def _fetch_discussion_page(page_index: int):
+ params["p"] = page_index
+ resp = get_session().get(path, headers=headers, params=params)
+ hf_raise_for_status(resp)
+ paginated_discussions = resp.json()
+ total = paginated_discussions["count"]
+ start = paginated_discussions["start"]
+ discussions = paginated_discussions["discussions"]
+ has_next = (start + len(discussions)) < total
+ return discussions, has_next
+
+ has_next, page_index = True, 0
+
+ while has_next:
+ discussions, has_next = _fetch_discussion_page(page_index=page_index)
+ for discussion in discussions:
+ yield Discussion(
+ title=discussion["title"],
+ num=discussion["num"],
+ author=discussion.get("author", {}).get("name", "deleted"),
+ created_at=parse_datetime(discussion["createdAt"]),
+ status=discussion["status"],
+ repo_id=discussion["repo"]["name"],
+ repo_type=discussion["repo"]["type"],
+ is_pull_request=discussion["isPullRequest"],
+ endpoint=self.endpoint,
+ )
+ page_index = page_index + 1
+
+ @validate_hf_hub_args
+ def get_discussion_details(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ *,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> DiscussionWithDetails:
+ """Fetches a Discussion's / Pull Request 's details from the Hub.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns: [`DiscussionWithDetails`]
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ if not isinstance(discussion_num, int) or discussion_num <= 0:
+ raise ValueError("Invalid discussion_num, must be a positive integer")
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+
+ path = f"{self.endpoint}/api/{repo_type}s/{repo_id}/discussions/{discussion_num}"
+ headers = self._build_hf_headers(token=token)
+ resp = get_session().get(path, params={"diff": "1"}, headers=headers)
+ hf_raise_for_status(resp)
+
+ discussion_details = resp.json()
+ is_pull_request = discussion_details["isPullRequest"]
+
+ target_branch = discussion_details["changes"]["base"] if is_pull_request else None
+ conflicting_files = discussion_details["filesWithConflicts"] if is_pull_request else None
+ merge_commit_oid = discussion_details["changes"].get("mergeCommitId", None) if is_pull_request else None
+
+ return DiscussionWithDetails(
+ title=discussion_details["title"],
+ num=discussion_details["num"],
+ author=discussion_details.get("author", {}).get("name", "deleted"),
+ created_at=parse_datetime(discussion_details["createdAt"]),
+ status=discussion_details["status"],
+ repo_id=discussion_details["repo"]["name"],
+ repo_type=discussion_details["repo"]["type"],
+ is_pull_request=discussion_details["isPullRequest"],
+ events=[deserialize_event(evt) for evt in discussion_details["events"]],
+ conflicting_files=conflicting_files,
+ target_branch=target_branch,
+ merge_commit_oid=merge_commit_oid,
+ diff=discussion_details.get("diff"),
+ endpoint=self.endpoint,
+ )
+
+ @validate_hf_hub_args
+ def create_discussion(
+ self,
+ repo_id: str,
+ title: str,
+ *,
+ token: Union[bool, str, None] = None,
+ description: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ pull_request: bool = False,
+ ) -> DiscussionWithDetails:
+ """Creates a Discussion or Pull Request.
+
+ Pull Requests created programmatically will be in `"draft"` status.
+
+ Creating a Pull Request with changes can also be done at once with [`HfApi.create_commit`].
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ title (`str`):
+ The title of the discussion. It can be up to 200 characters long,
+ and must be at least 3 characters long. Leading and trailing whitespaces
+ will be stripped.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ description (`str`, *optional*):
+ An optional description for the Pull Request.
+ Defaults to `"Discussion opened with the huggingface_hub Python library"`
+ pull_request (`bool`, *optional*):
+ Whether to create a Pull Request or discussion. If `True`, creates a Pull Request.
+ If `False`, creates a discussion. Defaults to `False`.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+
+ Returns: [`DiscussionWithDetails`]
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access."""
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+
+ if description is not None:
+ description = description.strip()
+ description = (
+ description
+ if description
+ else (
+ f"{'Pull Request' if pull_request else 'Discussion'} opened with the"
+ " [huggingface_hub Python"
+ " library](https://huggingface.co/docs/huggingface_hub)"
+ )
+ )
+
+ headers = self._build_hf_headers(token=token)
+ resp = get_session().post(
+ f"{self.endpoint}/api/{repo_type}s/{repo_id}/discussions",
+ json={
+ "title": title.strip(),
+ "description": description,
+ "pullRequest": pull_request,
+ },
+ headers=headers,
+ )
+ hf_raise_for_status(resp)
+ num = resp.json()["num"]
+ return self.get_discussion_details(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=num,
+ token=token,
+ )
+
+ @validate_hf_hub_args
+ def create_pull_request(
+ self,
+ repo_id: str,
+ title: str,
+ *,
+ token: Union[bool, str, None] = None,
+ description: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionWithDetails:
+ """Creates a Pull Request . Pull Requests created programmatically will be in `"draft"` status.
+
+ Creating a Pull Request with changes can also be done at once with [`HfApi.create_commit`];
+
+ This is a wrapper around [`HfApi.create_discussion`].
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ title (`str`):
+ The title of the discussion. It can be up to 200 characters long,
+ and must be at least 3 characters long. Leading and trailing whitespaces
+ will be stripped.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ description (`str`, *optional*):
+ An optional description for the Pull Request.
+ Defaults to `"Discussion opened with the huggingface_hub Python library"`
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+
+ Returns: [`DiscussionWithDetails`]
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access."""
+ return self.create_discussion(
+ repo_id=repo_id,
+ title=title,
+ token=token,
+ description=description,
+ repo_type=repo_type,
+ pull_request=True,
+ )
+
+ def _post_discussion_changes(
+ self,
+ *,
+ repo_id: str,
+ discussion_num: int,
+ resource: str,
+ body: Optional[dict] = None,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> requests.Response:
+ """Internal utility to POST changes to a Discussion or Pull Request"""
+ if not isinstance(discussion_num, int) or discussion_num <= 0:
+ raise ValueError("Invalid discussion_num, must be a positive integer")
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ repo_id = f"{repo_type}s/{repo_id}"
+
+ path = f"{self.endpoint}/api/{repo_id}/discussions/{discussion_num}/{resource}"
+
+ headers = self._build_hf_headers(token=token)
+ resp = requests.post(path, headers=headers, json=body)
+ hf_raise_for_status(resp)
+ return resp
+
+ @validate_hf_hub_args
+ def comment_discussion(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ comment: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionComment:
+ """Creates a new comment on the given Discussion.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ comment (`str`):
+ The content of the comment to create. Comments support markdown formatting.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionComment`]: the newly created comment
+
+
+ Examples:
+ ```python
+
+ >>> comment = \"\"\"
+ ... Hello @otheruser!
+ ...
+ ... # This is a title
+ ...
+ ... **This is bold**, *this is italic* and ~this is strikethrough~
+ ... And [this](http://url) is a link
+ ... \"\"\"
+
+ >>> HfApi().comment_discussion(
+ ... repo_id="username/repo_name",
+ ... discussion_num=34
+ ... comment=comment
+ ... )
+ # DiscussionComment(id='deadbeef0000000', type='comment', ...)
+
+ ```
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ resp = self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource="comment",
+ body={"comment": comment},
+ )
+ return deserialize_event(resp.json()["newMessage"]) # type: ignore
+
+ @validate_hf_hub_args
+ def rename_discussion(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ new_title: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionTitleChange:
+ """Renames a Discussion.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ new_title (`str`):
+ The new title for the discussion
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionTitleChange`]: the title change event
+
+
+ Examples:
+ ```python
+ >>> new_title = "New title, fixing a typo"
+ >>> HfApi().rename_discussion(
+ ... repo_id="username/repo_name",
+ ... discussion_num=34
+ ... new_title=new_title
+ ... )
+ # DiscussionTitleChange(id='deadbeef0000000', type='title-change', ...)
+
+ ```
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ resp = self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource="title",
+ body={"title": new_title},
+ )
+ return deserialize_event(resp.json()["newTitle"]) # type: ignore
+
+ @validate_hf_hub_args
+ def change_discussion_status(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ new_status: Literal["open", "closed"],
+ *,
+ token: Union[bool, str, None] = None,
+ comment: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionStatusChange:
+ """Closes or re-opens a Discussion or Pull Request.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ new_status (`str`):
+ The new status for the discussion, either `"open"` or `"closed"`.
+ comment (`str`, *optional*):
+ An optional comment to post with the status change.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionStatusChange`]: the status change event
+
+
+ Examples:
+ ```python
+ >>> new_title = "New title, fixing a typo"
+ >>> HfApi().rename_discussion(
+ ... repo_id="username/repo_name",
+ ... discussion_num=34
+ ... new_title=new_title
+ ... )
+ # DiscussionStatusChange(id='deadbeef0000000', type='status-change', ...)
+
+ ```
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ if new_status not in ["open", "closed"]:
+ raise ValueError("Invalid status, valid statuses are: 'open' and 'closed'")
+ body: Dict[str, str] = {"status": new_status}
+ if comment and comment.strip():
+ body["comment"] = comment.strip()
+ resp = self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource="status",
+ body=body,
+ )
+ return deserialize_event(resp.json()["newStatus"]) # type: ignore
+
+ @validate_hf_hub_args
+ def merge_pull_request(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ *,
+ token: Union[bool, str, None] = None,
+ comment: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ ):
+ """Merges a Pull Request.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ comment (`str`, *optional*):
+ An optional comment to post with the status change.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionStatusChange`]: the status change event
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource="merge",
+ body={"comment": comment.strip()} if comment and comment.strip() else None,
+ )
+
+ @validate_hf_hub_args
+ def edit_discussion_comment(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ comment_id: str,
+ new_content: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionComment:
+ """Edits a comment on a Discussion / Pull Request.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ comment_id (`str`):
+ The ID of the comment to edit.
+ new_content (`str`):
+ The new content of the comment. Comments support markdown formatting.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionComment`]: the edited comment
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ resp = self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource=f"comment/{comment_id.lower()}/edit",
+ body={"content": new_content},
+ )
+ return deserialize_event(resp.json()["updatedComment"]) # type: ignore
+
+ @validate_hf_hub_args
+ def hide_discussion_comment(
+ self,
+ repo_id: str,
+ discussion_num: int,
+ comment_id: str,
+ *,
+ token: Union[bool, str, None] = None,
+ repo_type: Optional[str] = None,
+ ) -> DiscussionComment:
+ """Hides a comment on a Discussion / Pull Request.
+
+ > [!WARNING]
+ > Hidden comments' content cannot be retrieved anymore. Hiding a comment is irreversible.
+
+ Args:
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ discussion_num (`int`):
+ The number of the Discussion or Pull Request . Must be a strictly positive integer.
+ comment_id (`str`):
+ The ID of the comment to edit.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if uploading to a dataset or
+ space, `None` or `"model"` if uploading to a model. Default is
+ `None`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`DiscussionComment`]: the hidden comment
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the HuggingFace API returned an error
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if some parameter value is invalid
+ > - [`~utils.RepositoryNotFoundError`]
+ > If the repository to download from cannot be found. This may be because it doesn't exist,
+ > or because it is set to `private` and you do not have access.
+ """
+ warnings.warn(
+ "Hidden comments' content cannot be retrieved anymore. Hiding a comment is irreversible.",
+ UserWarning,
+ )
+ resp = self._post_discussion_changes(
+ repo_id=repo_id,
+ repo_type=repo_type,
+ discussion_num=discussion_num,
+ token=token,
+ resource=f"comment/{comment_id.lower()}/hide",
+ )
+ return deserialize_event(resp.json()["updatedComment"]) # type: ignore
+
+ @validate_hf_hub_args
+ def add_space_secret(
+ self,
+ repo_id: str,
+ key: str,
+ value: str,
+ *,
+ description: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """Adds or updates a secret in a Space.
+
+ Secrets allow to set secret keys or tokens to a Space without hardcoding them.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets.
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ key (`str`):
+ Secret key. Example: `"GITHUB_API_KEY"`
+ value (`str`):
+ Secret value. Example: `"your_github_api_key"`.
+ description (`str`, *optional*):
+ Secret description. Example: `"Github API key to access the Github API"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ payload = {"key": key, "value": value}
+ if description is not None:
+ payload["description"] = description
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/secrets",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(r)
+
+ @validate_hf_hub_args
+ def delete_space_secret(self, repo_id: str, key: str, *, token: Union[bool, str, None] = None) -> None:
+ """Deletes a secret from a Space.
+
+ Secrets allow to set secret keys or tokens to a Space without hardcoding them.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets.
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ key (`str`):
+ Secret key. Example: `"GITHUB_API_KEY"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ r = get_session().delete(
+ f"{self.endpoint}/api/spaces/{repo_id}/secrets",
+ headers=self._build_hf_headers(token=token),
+ json={"key": key},
+ )
+ hf_raise_for_status(r)
+
+ @validate_hf_hub_args
+ def get_space_variables(self, repo_id: str, *, token: Union[bool, str, None] = None) -> Dict[str, SpaceVariable]:
+ """Gets all variables from a Space.
+
+ Variables allow to set environment variables to a Space without hardcoding them.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to query. Example: `"bigcode/in-the-stack"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ r = get_session().get(
+ f"{self.endpoint}/api/spaces/{repo_id}/variables",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(r)
+ return {k: SpaceVariable(k, v) for k, v in r.json().items()}
+
+ @validate_hf_hub_args
+ def add_space_variable(
+ self,
+ repo_id: str,
+ key: str,
+ value: str,
+ *,
+ description: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Dict[str, SpaceVariable]:
+ """Adds or updates a variable in a Space.
+
+ Variables allow to set environment variables to a Space without hardcoding them.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ key (`str`):
+ Variable key. Example: `"MODEL_REPO_ID"`
+ value (`str`):
+ Variable value. Example: `"the_model_repo_id"`.
+ description (`str`):
+ Description of the variable. Example: `"Model Repo ID of the implemented model"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ payload = {"key": key, "value": value}
+ if description is not None:
+ payload["description"] = description
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/variables",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(r)
+ return {k: SpaceVariable(k, v) for k, v in r.json().items()}
+
+ @validate_hf_hub_args
+ def delete_space_variable(
+ self, repo_id: str, key: str, *, token: Union[bool, str, None] = None
+ ) -> Dict[str, SpaceVariable]:
+ """Deletes a variable from a Space.
+
+ Variables allow to set environment variables to a Space without hardcoding them.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ key (`str`):
+ Variable key. Example: `"MODEL_REPO_ID"`
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ r = get_session().delete(
+ f"{self.endpoint}/api/spaces/{repo_id}/variables",
+ headers=self._build_hf_headers(token=token),
+ json={"key": key},
+ )
+ hf_raise_for_status(r)
+ return {k: SpaceVariable(k, v) for k, v in r.json().items()}
+
+ @validate_hf_hub_args
+ def get_space_runtime(self, repo_id: str, *, token: Union[bool, str, None] = None) -> SpaceRuntime:
+ """Gets runtime information about a Space.
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ Returns:
+ [`SpaceRuntime`]: Runtime information about a Space including Space stage and hardware.
+ """
+ r = get_session().get(
+ f"{self.endpoint}/api/spaces/{repo_id}/runtime", headers=self._build_hf_headers(token=token)
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ @validate_hf_hub_args
+ def request_space_hardware(
+ self,
+ repo_id: str,
+ hardware: SpaceHardware,
+ *,
+ token: Union[bool, str, None] = None,
+ sleep_time: Optional[int] = None,
+ ) -> SpaceRuntime:
+ """Request new hardware for a Space.
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ hardware (`str` or [`SpaceHardware`]):
+ Hardware on which to run the Space. Example: `"t4-medium"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ sleep_time (`int`, *optional*):
+ Number of seconds of inactivity to wait before a Space is put to sleep. Set to `-1` if you don't want
+ your Space to sleep (default behavior for upgraded hardware). For free hardware, you can't configure
+ the sleep time (value is fixed to 48 hours of inactivity).
+ See https://huggingface.co/docs/hub/spaces-gpus#sleep-time for more details.
+ Returns:
+ [`SpaceRuntime`]: Runtime information about a Space including Space stage and hardware.
+
+ > [!TIP]
+ > It is also possible to request hardware directly when creating the Space repo! See [`create_repo`] for details.
+ """
+ if sleep_time is not None and hardware == SpaceHardware.CPU_BASIC:
+ warnings.warn(
+ "If your Space runs on the default 'cpu-basic' hardware, it will go to sleep if inactive for more"
+ " than 48 hours. This value is not configurable. If you don't want your Space to deactivate or if"
+ " you want to set a custom sleep time, you need to upgrade to a paid Hardware.",
+ UserWarning,
+ )
+ payload: Dict[str, Any] = {"flavor": hardware}
+ if sleep_time is not None:
+ payload["sleepTimeSeconds"] = sleep_time
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/hardware",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ @validate_hf_hub_args
+ def set_space_sleep_time(
+ self, repo_id: str, sleep_time: int, *, token: Union[bool, str, None] = None
+ ) -> SpaceRuntime:
+ """Set a custom sleep time for a Space running on upgraded hardware..
+
+ Your Space will go to sleep after X seconds of inactivity. You are not billed when your Space is in "sleep"
+ mode. If a new visitor lands on your Space, it will "wake it up". Only upgraded hardware can have a
+ configurable sleep time. To know more about the sleep stage, please refer to
+ https://huggingface.co/docs/hub/spaces-gpus#sleep-time.
+
+ Args:
+ repo_id (`str`):
+ ID of the repo to update. Example: `"bigcode/in-the-stack"`.
+ sleep_time (`int`, *optional*):
+ Number of seconds of inactivity to wait before a Space is put to sleep. Set to `-1` if you don't want
+ your Space to pause (default behavior for upgraded hardware). For free hardware, you can't configure
+ the sleep time (value is fixed to 48 hours of inactivity).
+ See https://huggingface.co/docs/hub/spaces-gpus#sleep-time for more details.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ Returns:
+ [`SpaceRuntime`]: Runtime information about a Space including Space stage and hardware.
+
+ > [!TIP]
+ > It is also possible to set a custom sleep time when requesting hardware with [`request_space_hardware`].
+ """
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/sleeptime",
+ headers=self._build_hf_headers(token=token),
+ json={"seconds": sleep_time},
+ )
+ hf_raise_for_status(r)
+ runtime = SpaceRuntime(r.json())
+
+ hardware = runtime.requested_hardware or runtime.hardware
+ if hardware == SpaceHardware.CPU_BASIC:
+ warnings.warn(
+ "If your Space runs on the default 'cpu-basic' hardware, it will go to sleep if inactive for more"
+ " than 48 hours. This value is not configurable. If you don't want your Space to deactivate or if"
+ " you want to set a custom sleep time, you need to upgrade to a paid Hardware.",
+ UserWarning,
+ )
+ return runtime
+
+ @validate_hf_hub_args
+ def pause_space(self, repo_id: str, *, token: Union[bool, str, None] = None) -> SpaceRuntime:
+ """Pause your Space.
+
+ A paused Space stops executing until manually restarted by its owner. This is different from the sleeping
+ state in which free Spaces go after 48h of inactivity. Paused time is not billed to your account, no matter the
+ hardware you've selected. To restart your Space, use [`restart_space`] and go to your Space settings page.
+
+ For more details, please visit [the docs](https://huggingface.co/docs/hub/spaces-gpus#pause).
+
+ Args:
+ repo_id (`str`):
+ ID of the Space to pause. Example: `"Salesforce/BLIP2"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`SpaceRuntime`]: Runtime information about your Space including `stage=PAUSED` and requested hardware.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If your Space is not found (error 404). Most probably wrong repo_id or your space is private but you
+ are not authenticated.
+ [`~utils.HfHubHTTPError`]:
+ 403 Forbidden: only the owner of a Space can pause it. If you want to manage a Space that you don't
+ own, either ask the owner by opening a Discussion or duplicate the Space.
+ [`~utils.BadRequestError`]:
+ If your Space is a static Space. Static Spaces are always running and never billed. If you want to hide
+ a static Space, you can set it to private.
+ """
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/pause", headers=self._build_hf_headers(token=token)
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ @validate_hf_hub_args
+ def restart_space(
+ self, repo_id: str, *, token: Union[bool, str, None] = None, factory_reboot: bool = False
+ ) -> SpaceRuntime:
+ """Restart your Space.
+
+ This is the only way to programmatically restart a Space if you've put it on Pause (see [`pause_space`]). You
+ must be the owner of the Space to restart it. If you are using an upgraded hardware, your account will be
+ billed as soon as the Space is restarted. You can trigger a restart no matter the current state of a Space.
+
+ For more details, please visit [the docs](https://huggingface.co/docs/hub/spaces-gpus#pause).
+
+ Args:
+ repo_id (`str`):
+ ID of the Space to restart. Example: `"Salesforce/BLIP2"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ factory_reboot (`bool`, *optional*):
+ If `True`, the Space will be rebuilt from scratch without caching any requirements.
+
+ Returns:
+ [`SpaceRuntime`]: Runtime information about your Space.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If your Space is not found (error 404). Most probably wrong repo_id or your space is private but you
+ are not authenticated.
+ [`~utils.HfHubHTTPError`]:
+ 403 Forbidden: only the owner of a Space can restart it. If you want to restart a Space that you don't
+ own, either ask the owner by opening a Discussion or duplicate the Space.
+ [`~utils.BadRequestError`]:
+ If your Space is a static Space. Static Spaces are always running and never billed. If you want to hide
+ a static Space, you can set it to private.
+ """
+ params = {}
+ if factory_reboot:
+ params["factory"] = "true"
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/restart", headers=self._build_hf_headers(token=token), params=params
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ @validate_hf_hub_args
+ def duplicate_space(
+ self,
+ from_id: str,
+ to_id: Optional[str] = None,
+ *,
+ private: Optional[bool] = None,
+ token: Union[bool, str, None] = None,
+ exist_ok: bool = False,
+ hardware: Optional[SpaceHardware] = None,
+ storage: Optional[SpaceStorage] = None,
+ sleep_time: Optional[int] = None,
+ secrets: Optional[List[Dict[str, str]]] = None,
+ variables: Optional[List[Dict[str, str]]] = None,
+ ) -> RepoUrl:
+ """Duplicate a Space.
+
+ Programmatically duplicate a Space. The new Space will be created in your account and will be in the same state
+ as the original Space (running or paused). You can duplicate a Space no matter the current state of a Space.
+
+ Args:
+ from_id (`str`):
+ ID of the Space to duplicate. Example: `"pharma/CLIP-Interrogator"`.
+ to_id (`str`, *optional*):
+ ID of the new Space. Example: `"dog/CLIP-Interrogator"`. If not provided, the new Space will have the same
+ name as the original Space, but in your account.
+ private (`bool`, *optional*):
+ Whether the new Space should be private or not. Defaults to the same privacy as the original Space.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ exist_ok (`bool`, *optional*, defaults to `False`):
+ If `True`, do not raise an error if repo already exists.
+ hardware (`SpaceHardware` or `str`, *optional*):
+ Choice of Hardware. Example: `"t4-medium"`. See [`SpaceHardware`] for a complete list.
+ storage (`SpaceStorage` or `str`, *optional*):
+ Choice of persistent storage tier. Example: `"small"`. See [`SpaceStorage`] for a complete list.
+ sleep_time (`int`, *optional*):
+ Number of seconds of inactivity to wait before a Space is put to sleep. Set to `-1` if you don't want
+ your Space to sleep (default behavior for upgraded hardware). For free hardware, you can't configure
+ the sleep time (value is fixed to 48 hours of inactivity).
+ See https://huggingface.co/docs/hub/spaces-gpus#sleep-time for more details.
+ secrets (`List[Dict[str, str]]`, *optional*):
+ A list of secret keys to set in your Space. Each item is in the form `{"key": ..., "value": ..., "description": ...}` where description is optional.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets.
+ variables (`List[Dict[str, str]]`, *optional*):
+ A list of public environment variables to set in your Space. Each item is in the form `{"key": ..., "value": ..., "description": ...}` where description is optional.
+ For more details, see https://huggingface.co/docs/hub/spaces-overview#managing-secrets-and-environment-variables.
+
+ Returns:
+ [`RepoUrl`]: URL to the newly created repo. Value is a subclass of `str` containing
+ attributes like `endpoint`, `repo_type` and `repo_id`.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ If one of `from_id` or `to_id` cannot be found. This may be because it doesn't exist,
+ or because it is set to `private` and you do not have access.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ If the HuggingFace API returned an error
+
+ Example:
+ ```python
+ >>> from huggingface_hub import duplicate_space
+
+ # Duplicate a Space to your account
+ >>> duplicate_space("multimodalart/dreambooth-training")
+ RepoUrl('https://huggingface.co/spaces/nateraw/dreambooth-training',...)
+
+ # Can set custom destination id and visibility flag.
+ >>> duplicate_space("multimodalart/dreambooth-training", to_id="my-dreambooth", private=True)
+ RepoUrl('https://huggingface.co/spaces/nateraw/my-dreambooth',...)
+ ```
+ """
+ # Parse to_id if provided
+ parsed_to_id = RepoUrl(to_id) if to_id is not None else None
+
+ # Infer target repo_id
+ to_namespace = ( # set namespace manually or default to username
+ parsed_to_id.namespace
+ if parsed_to_id is not None and parsed_to_id.namespace is not None
+ else self.whoami(token)["name"]
+ )
+ to_repo_name = parsed_to_id.repo_name if to_id is not None else RepoUrl(from_id).repo_name # type: ignore
+
+ # repository must be a valid repo_id (namespace/repo_name).
+ payload: Dict[str, Any] = {"repository": f"{to_namespace}/{to_repo_name}"}
+
+ keys = ["private", "hardware", "storageTier", "sleepTimeSeconds", "secrets", "variables"]
+ values = [private, hardware, storage, sleep_time, secrets, variables]
+ payload.update({k: v for k, v in zip(keys, values) if v is not None})
+
+ if sleep_time is not None and hardware == SpaceHardware.CPU_BASIC:
+ warnings.warn(
+ "If your Space runs on the default 'cpu-basic' hardware, it will go to sleep if inactive for more"
+ " than 48 hours. This value is not configurable. If you don't want your Space to deactivate or if"
+ " you want to set a custom sleep time, you need to upgrade to a paid Hardware.",
+ UserWarning,
+ )
+
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{from_id}/duplicate",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if exist_ok and err.response.status_code == 409:
+ # Repo already exists and `exist_ok=True`
+ pass
+ else:
+ raise
+
+ return RepoUrl(r.json()["url"], endpoint=self.endpoint)
+
+ @validate_hf_hub_args
+ def request_space_storage(
+ self,
+ repo_id: str,
+ storage: SpaceStorage,
+ *,
+ token: Union[bool, str, None] = None,
+ ) -> SpaceRuntime:
+ """Request persistent storage for a Space.
+
+ Args:
+ repo_id (`str`):
+ ID of the Space to update. Example: `"open-llm-leaderboard/open_llm_leaderboard"`.
+ storage (`str` or [`SpaceStorage`]):
+ Storage tier. Either 'small', 'medium', or 'large'.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ Returns:
+ [`SpaceRuntime`]: Runtime information about a Space including Space stage and hardware.
+
+ > [!TIP]
+ > It is not possible to decrease persistent storage after its granted. To do so, you must delete it
+ > via [`delete_space_storage`].
+ """
+ payload: Dict[str, SpaceStorage] = {"tier": storage}
+ r = get_session().post(
+ f"{self.endpoint}/api/spaces/{repo_id}/storage",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ @validate_hf_hub_args
+ def delete_space_storage(
+ self,
+ repo_id: str,
+ *,
+ token: Union[bool, str, None] = None,
+ ) -> SpaceRuntime:
+ """Delete persistent storage for a Space.
+
+ Args:
+ repo_id (`str`):
+ ID of the Space to update. Example: `"open-llm-leaderboard/open_llm_leaderboard"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ Returns:
+ [`SpaceRuntime`]: Runtime information about a Space including Space stage and hardware.
+ Raises:
+ [`BadRequestError`]
+ If space has no persistent storage.
+
+ """
+ r = get_session().delete(
+ f"{self.endpoint}/api/spaces/{repo_id}/storage",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(r)
+ return SpaceRuntime(r.json())
+
+ #######################
+ # Inference Endpoints #
+ #######################
+
+ def list_inference_endpoints(
+ self, namespace: Optional[str] = None, *, token: Union[bool, str, None] = None
+ ) -> List[InferenceEndpoint]:
+ """Lists all inference endpoints for the given namespace.
+
+ Args:
+ namespace (`str`, *optional*):
+ The namespace to list endpoints for. Defaults to the current user. Set to `"*"` to list all endpoints
+ from all namespaces (i.e. personal namespace and all orgs the user belongs to).
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ List[`InferenceEndpoint`]: A list of all inference endpoints for the given namespace.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> api.list_inference_endpoints()
+ [InferenceEndpoint(name='my-endpoint', ...), ...]
+ ```
+ """
+ # Special case: list all endpoints for all namespaces the user has access to
+ if namespace == "*":
+ user = self.whoami(token=token)
+
+ # List personal endpoints first
+ endpoints: List[InferenceEndpoint] = list_inference_endpoints(namespace=self._get_namespace(token=token))
+
+ # Then list endpoints for all orgs the user belongs to and ignore 401 errors (no billing or no access)
+ for org in user.get("orgs", []):
+ try:
+ endpoints += list_inference_endpoints(namespace=org["name"], token=token)
+ except HfHubHTTPError as error:
+ if error.response.status_code == 401: # Either no billing or user don't have access)
+ logger.debug("Cannot list Inference Endpoints for org '%s': %s", org["name"], error)
+ pass
+
+ return endpoints
+
+ # Normal case: list endpoints for a specific namespace
+ namespace = namespace or self._get_namespace(token=token)
+
+ response = get_session().get(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ return [
+ InferenceEndpoint.from_raw(endpoint, namespace=namespace, token=token)
+ for endpoint in response.json()["items"]
+ ]
+
+ def create_inference_endpoint(
+ self,
+ name: str,
+ *,
+ repository: str,
+ framework: str,
+ accelerator: str,
+ instance_size: str,
+ instance_type: str,
+ region: str,
+ vendor: str,
+ account_id: Optional[str] = None,
+ min_replica: int = 1,
+ max_replica: int = 1,
+ scale_to_zero_timeout: Optional[int] = None,
+ revision: Optional[str] = None,
+ task: Optional[str] = None,
+ custom_image: Optional[Dict] = None,
+ env: Optional[Dict[str, str]] = None,
+ secrets: Optional[Dict[str, str]] = None,
+ type: InferenceEndpointType = InferenceEndpointType.PROTECTED,
+ domain: Optional[str] = None,
+ path: Optional[str] = None,
+ cache_http_responses: Optional[bool] = None,
+ tags: Optional[List[str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> InferenceEndpoint:
+ """Create a new Inference Endpoint.
+
+ Args:
+ name (`str`):
+ The unique name for the new Inference Endpoint.
+ repository (`str`):
+ The name of the model repository associated with the Inference Endpoint (e.g. `"gpt2"`).
+ framework (`str`):
+ The machine learning framework used for the model (e.g. `"custom"`).
+ accelerator (`str`):
+ The hardware accelerator to be used for inference (e.g. `"cpu"`).
+ instance_size (`str`):
+ The size or type of the instance to be used for hosting the model (e.g. `"x4"`).
+ instance_type (`str`):
+ The cloud instance type where the Inference Endpoint will be deployed (e.g. `"intel-icl"`).
+ region (`str`):
+ The cloud region in which the Inference Endpoint will be created (e.g. `"us-east-1"`).
+ vendor (`str`):
+ The cloud provider or vendor where the Inference Endpoint will be hosted (e.g. `"aws"`).
+ account_id (`str`, *optional*):
+ The account ID used to link a VPC to a private Inference Endpoint (if applicable).
+ min_replica (`int`, *optional*):
+ The minimum number of replicas (instances) to keep running for the Inference Endpoint. To enable
+ scaling to zero, set this value to 0 and adjust `scale_to_zero_timeout` accordingly. Defaults to 1.
+ max_replica (`int`, *optional*):
+ The maximum number of replicas (instances) to scale to for the Inference Endpoint. Defaults to 1.
+ scale_to_zero_timeout (`int`, *optional*):
+ The duration in minutes before an inactive endpoint is scaled to zero, or no scaling to zero if
+ set to None and `min_replica` is not 0. Defaults to None.
+ revision (`str`, *optional*):
+ The specific model revision to deploy on the Inference Endpoint (e.g. `"6c0e6080953db56375760c0471a8c5f2929baf11"`).
+ task (`str`, *optional*):
+ The task on which to deploy the model (e.g. `"text-classification"`).
+ custom_image (`Dict`, *optional*):
+ A custom Docker image to use for the Inference Endpoint. This is useful if you want to deploy an
+ Inference Endpoint running on the `text-generation-inference` (TGI) framework (see examples).
+ env (`Dict[str, str]`, *optional*):
+ Non-secret environment variables to inject in the container environment.
+ secrets (`Dict[str, str]`, *optional*):
+ Secret values to inject in the container environment.
+ type ([`InferenceEndpointType]`, *optional*):
+ The type of the Inference Endpoint, which can be `"protected"` (default), `"public"` or `"private"`.
+ domain (`str`, *optional*):
+ The custom domain for the Inference Endpoint deployment, if setup the inference endpoint will be available at this domain (e.g. `"my-new-domain.cool-website.woof"`).
+ path (`str`, *optional*):
+ The custom path to the deployed model, should start with a `/` (e.g. `"/models/google-bert/bert-base-uncased"`).
+ cache_http_responses (`bool`, *optional*):
+ Whether to cache HTTP responses from the Inference Endpoint. Defaults to `False`.
+ tags (`List[str]`, *optional*):
+ A list of tags to associate with the Inference Endpoint.
+ namespace (`str`, *optional*):
+ The namespace where the Inference Endpoint will be created. Defaults to the current user's namespace.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the updated Inference Endpoint.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> endpoint = api.create_inference_endpoint(
+ ... "my-endpoint-name",
+ ... repository="gpt2",
+ ... framework="pytorch",
+ ... task="text-generation",
+ ... accelerator="cpu",
+ ... vendor="aws",
+ ... region="us-east-1",
+ ... type="protected",
+ ... instance_size="x2",
+ ... instance_type="intel-icl",
+ ... )
+ >>> endpoint
+ InferenceEndpoint(name='my-endpoint-name', status="pending",...)
+
+ # Run inference on the endpoint
+ >>> endpoint.client.text_generation(...)
+ "..."
+ ```
+
+ ```python
+ # Start an Inference Endpoint running Zephyr-7b-beta on TGI
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> endpoint = api.create_inference_endpoint(
+ ... "aws-zephyr-7b-beta-0486",
+ ... repository="HuggingFaceH4/zephyr-7b-beta",
+ ... framework="pytorch",
+ ... task="text-generation",
+ ... accelerator="gpu",
+ ... vendor="aws",
+ ... region="us-east-1",
+ ... type="protected",
+ ... instance_size="x1",
+ ... instance_type="nvidia-a10g",
+ ... env={
+ ... "MAX_BATCH_PREFILL_TOKENS": "2048",
+ ... "MAX_INPUT_LENGTH": "1024",
+ ... "MAX_TOTAL_TOKENS": "1512",
+ ... "MODEL_ID": "/repository"
+ ... },
+ ... custom_image={
+ ... "health_route": "/health",
+ ... "url": "ghcr.io/huggingface/text-generation-inference:1.1.0",
+ ... },
+ ... secrets={"MY_SECRET_KEY": "secret_value"},
+ ... tags=["dev", "text-generation"],
+ ... )
+ ```
+
+ ```python
+ # Start an Inference Endpoint running ProsusAI/finbert while scaling to zero in 15 minutes
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> endpoint = api.create_inference_endpoint(
+ ... "finbert-classifier",
+ ... repository="ProsusAI/finbert",
+ ... framework="pytorch",
+ ... task="text-classification",
+ ... min_replica=0,
+ ... scale_to_zero_timeout=15,
+ ... accelerator="cpu",
+ ... vendor="aws",
+ ... region="us-east-1",
+ ... type="protected",
+ ... instance_size="x2",
+ ... instance_type="intel-icl",
+ ... )
+ >>> endpoint.wait(timeout=300)
+ # Run inference on the endpoint
+ >>> endpoint.client.text_generation(...)
+ TextClassificationOutputElement(label='positive', score=0.8983615040779114)
+ ```
+
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ if custom_image is not None:
+ image = (
+ custom_image
+ if next(iter(custom_image)) in constants.INFERENCE_ENDPOINT_IMAGE_KEYS
+ else {"custom": custom_image}
+ )
+ else:
+ image = {"huggingface": {}}
+
+ payload: Dict = {
+ "accountId": account_id,
+ "compute": {
+ "accelerator": accelerator,
+ "instanceSize": instance_size,
+ "instanceType": instance_type,
+ "scaling": {
+ "maxReplica": max_replica,
+ "minReplica": min_replica,
+ "scaleToZeroTimeout": scale_to_zero_timeout,
+ },
+ },
+ "model": {
+ "framework": framework,
+ "repository": repository,
+ "revision": revision,
+ "task": task,
+ "image": image,
+ },
+ "name": name,
+ "provider": {
+ "region": region,
+ "vendor": vendor,
+ },
+ "type": type,
+ }
+ if env:
+ payload["model"]["env"] = env
+ if secrets:
+ payload["model"]["secrets"] = secrets
+ if domain is not None or path is not None:
+ payload["route"] = {}
+ if domain is not None:
+ payload["route"]["domain"] = domain
+ if path is not None:
+ payload["route"]["path"] = path
+ if cache_http_responses is not None:
+ payload["cacheHttpResponses"] = cache_http_responses
+ if tags is not None:
+ payload["tags"] = tags
+
+ response = get_session().post(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(response)
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ @experimental
+ @validate_hf_hub_args
+ def create_inference_endpoint_from_catalog(
+ self,
+ repo_id: str,
+ *,
+ name: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ namespace: Optional[str] = None,
+ ) -> InferenceEndpoint:
+ """Create a new Inference Endpoint from a model in the Hugging Face Inference Catalog.
+
+ The goal of the Inference Catalog is to provide a curated list of models that are optimized for inference
+ and for which default configurations have been tested. See https://endpoints.huggingface.co/catalog for a list
+ of available models in the catalog.
+
+ Args:
+ repo_id (`str`):
+ The ID of the model in the catalog to deploy as an Inference Endpoint.
+ name (`str`, *optional*):
+ The unique name for the new Inference Endpoint. If not provided, a random name will be generated.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ namespace (`str`, *optional*):
+ The namespace where the Inference Endpoint will be created. Defaults to the current user's namespace.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the new Inference Endpoint.
+
+ > [!WARNING]
+ > `create_inference_endpoint_from_catalog` is experimental. Its API is subject to change in the future. Please provide feedback
+ > if you have any suggestions or requests.
+ """
+ token = token or self.token or get_token()
+ payload: Dict = {
+ "namespace": namespace or self._get_namespace(token=token),
+ "repoId": repo_id,
+ }
+ if name is not None:
+ payload["endpointName"] = name
+
+ response = get_session().post(
+ f"{constants.INFERENCE_CATALOG_ENDPOINT}/deploy",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(response)
+ data = response.json()["endpoint"]
+ return InferenceEndpoint.from_raw(data, namespace=data["name"], token=token)
+
+ @experimental
+ @validate_hf_hub_args
+ def list_inference_catalog(self, *, token: Union[bool, str, None] = None) -> List[str]:
+ """List models available in the Hugging Face Inference Catalog.
+
+ The goal of the Inference Catalog is to provide a curated list of models that are optimized for inference
+ and for which default configurations have been tested. See https://endpoints.huggingface.co/catalog for a list
+ of available models in the catalog.
+
+ Use [`create_inference_endpoint_from_catalog`] to deploy a model from the catalog.
+
+ Args:
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+
+ Returns:
+ List[`str`]: A list of model IDs available in the catalog.
+ > [!WARNING]
+ > `list_inference_catalog` is experimental. Its API is subject to change in the future. Please provide feedback
+ > if you have any suggestions or requests.
+ """
+ response = get_session().get(
+ f"{constants.INFERENCE_CATALOG_ENDPOINT}/repo-list",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ return response.json()["models"]
+
+ def get_inference_endpoint(
+ self, name: str, *, namespace: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> InferenceEndpoint:
+ """Get information about an Inference Endpoint.
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to retrieve information about.
+ namespace (`str`, *optional*):
+ The namespace in which the Inference Endpoint is located. Defaults to the current user.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the requested Inference Endpoint.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import HfApi
+ >>> api = HfApi()
+ >>> endpoint = api.get_inference_endpoint("my-text-to-image")
+ >>> endpoint
+ InferenceEndpoint(name='my-text-to-image', ...)
+
+ # Get status
+ >>> endpoint.status
+ 'running'
+ >>> endpoint.url
+ 'https://my-text-to-image.region.vendor.endpoints.huggingface.cloud'
+
+ # Run inference
+ >>> endpoint.client.text_to_image(...)
+ ```
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ response = get_session().get(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ def update_inference_endpoint(
+ self,
+ name: str,
+ *,
+ # Compute update
+ accelerator: Optional[str] = None,
+ instance_size: Optional[str] = None,
+ instance_type: Optional[str] = None,
+ min_replica: Optional[int] = None,
+ max_replica: Optional[int] = None,
+ scale_to_zero_timeout: Optional[int] = None,
+ # Model update
+ repository: Optional[str] = None,
+ framework: Optional[str] = None,
+ revision: Optional[str] = None,
+ task: Optional[str] = None,
+ custom_image: Optional[Dict] = None,
+ env: Optional[Dict[str, str]] = None,
+ secrets: Optional[Dict[str, str]] = None,
+ # Route update
+ domain: Optional[str] = None,
+ path: Optional[str] = None,
+ # Other
+ cache_http_responses: Optional[bool] = None,
+ tags: Optional[List[str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> InferenceEndpoint:
+ """Update an Inference Endpoint.
+
+ This method allows the update of either the compute configuration, the deployed model, the route, or any combination.
+ All arguments are optional but at least one must be provided.
+
+ For convenience, you can also update an Inference Endpoint using [`InferenceEndpoint.update`].
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to update.
+
+ accelerator (`str`, *optional*):
+ The hardware accelerator to be used for inference (e.g. `"cpu"`).
+ instance_size (`str`, *optional*):
+ The size or type of the instance to be used for hosting the model (e.g. `"x4"`).
+ instance_type (`str`, *optional*):
+ The cloud instance type where the Inference Endpoint will be deployed (e.g. `"intel-icl"`).
+ min_replica (`int`, *optional*):
+ The minimum number of replicas (instances) to keep running for the Inference Endpoint.
+ max_replica (`int`, *optional*):
+ The maximum number of replicas (instances) to scale to for the Inference Endpoint.
+ scale_to_zero_timeout (`int`, *optional*):
+ The duration in minutes before an inactive endpoint is scaled to zero.
+
+ repository (`str`, *optional*):
+ The name of the model repository associated with the Inference Endpoint (e.g. `"gpt2"`).
+ framework (`str`, *optional*):
+ The machine learning framework used for the model (e.g. `"custom"`).
+ revision (`str`, *optional*):
+ The specific model revision to deploy on the Inference Endpoint (e.g. `"6c0e6080953db56375760c0471a8c5f2929baf11"`).
+ task (`str`, *optional*):
+ The task on which to deploy the model (e.g. `"text-classification"`).
+ custom_image (`Dict`, *optional*):
+ A custom Docker image to use for the Inference Endpoint. This is useful if you want to deploy an
+ Inference Endpoint running on the `text-generation-inference` (TGI) framework (see examples).
+ env (`Dict[str, str]`, *optional*):
+ Non-secret environment variables to inject in the container environment
+ secrets (`Dict[str, str]`, *optional*):
+ Secret values to inject in the container environment.
+
+ domain (`str`, *optional*):
+ The custom domain for the Inference Endpoint deployment, if setup the inference endpoint will be available at this domain (e.g. `"my-new-domain.cool-website.woof"`).
+ path (`str`, *optional*):
+ The custom path to the deployed model, should start with a `/` (e.g. `"/models/google-bert/bert-base-uncased"`).
+
+ cache_http_responses (`bool`, *optional*):
+ Whether to cache HTTP responses from the Inference Endpoint.
+ tags (`List[str]`, *optional*):
+ A list of tags to associate with the Inference Endpoint.
+
+ namespace (`str`, *optional*):
+ The namespace where the Inference Endpoint will be updated. Defaults to the current user's namespace.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the updated Inference Endpoint.
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ # Populate only the fields that are not None
+ payload: Dict = defaultdict(lambda: defaultdict(dict))
+ if accelerator is not None:
+ payload["compute"]["accelerator"] = accelerator
+ if instance_size is not None:
+ payload["compute"]["instanceSize"] = instance_size
+ if instance_type is not None:
+ payload["compute"]["instanceType"] = instance_type
+ if max_replica is not None:
+ payload["compute"]["scaling"]["maxReplica"] = max_replica
+ if min_replica is not None:
+ payload["compute"]["scaling"]["minReplica"] = min_replica
+ if scale_to_zero_timeout is not None:
+ payload["compute"]["scaling"]["scaleToZeroTimeout"] = scale_to_zero_timeout
+ if repository is not None:
+ payload["model"]["repository"] = repository
+ if framework is not None:
+ payload["model"]["framework"] = framework
+ if revision is not None:
+ payload["model"]["revision"] = revision
+ if task is not None:
+ payload["model"]["task"] = task
+ if custom_image is not None:
+ payload["model"]["image"] = {"custom": custom_image}
+ if env is not None:
+ payload["model"]["env"] = env
+ if secrets is not None:
+ payload["model"]["secrets"] = secrets
+ if domain is not None:
+ payload["route"]["domain"] = domain
+ if path is not None:
+ payload["route"]["path"] = path
+ if cache_http_responses is not None:
+ payload["cacheHttpResponses"] = cache_http_responses
+ if tags is not None:
+ payload["tags"] = tags
+
+ response = get_session().put(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(response)
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ def delete_inference_endpoint(
+ self, name: str, *, namespace: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> None:
+ """Delete an Inference Endpoint.
+
+ This operation is not reversible. If you don't want to be charged for an Inference Endpoint, it is preferable
+ to pause it with [`pause_inference_endpoint`] or scale it to zero with [`scale_to_zero_inference_endpoint`].
+
+ For convenience, you can also delete an Inference Endpoint using [`InferenceEndpoint.delete`].
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to delete.
+ namespace (`str`, *optional*):
+ The namespace in which the Inference Endpoint is located. Defaults to the current user.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ """
+ namespace = namespace or self._get_namespace(token=token)
+ response = get_session().delete(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ def pause_inference_endpoint(
+ self, name: str, *, namespace: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> InferenceEndpoint:
+ """Pause an Inference Endpoint.
+
+ A paused Inference Endpoint will not be charged. It can be resumed at any time using [`resume_inference_endpoint`].
+ This is different than scaling the Inference Endpoint to zero with [`scale_to_zero_inference_endpoint`], which
+ would be automatically restarted when a request is made to it.
+
+ For convenience, you can also pause an Inference Endpoint using [`pause_inference_endpoint`].
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to pause.
+ namespace (`str`, *optional*):
+ The namespace in which the Inference Endpoint is located. Defaults to the current user.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the paused Inference Endpoint.
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ response = get_session().post(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}/pause",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ def resume_inference_endpoint(
+ self,
+ name: str,
+ *,
+ namespace: Optional[str] = None,
+ running_ok: bool = True,
+ token: Union[bool, str, None] = None,
+ ) -> InferenceEndpoint:
+ """Resume an Inference Endpoint.
+
+ For convenience, you can also resume an Inference Endpoint using [`InferenceEndpoint.resume`].
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to resume.
+ namespace (`str`, *optional*):
+ The namespace in which the Inference Endpoint is located. Defaults to the current user.
+ running_ok (`bool`, *optional*):
+ If `True`, the method will not raise an error if the Inference Endpoint is already running. Defaults to
+ `True`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the resumed Inference Endpoint.
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ response = get_session().post(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}/resume",
+ headers=self._build_hf_headers(token=token),
+ )
+ try:
+ hf_raise_for_status(response)
+ except HfHubHTTPError as error:
+ # If already running (and it's ok), then fetch current status and return
+ if running_ok and error.response.status_code == 400 and "already running" in error.response.text:
+ return self.get_inference_endpoint(name, namespace=namespace, token=token)
+ # Otherwise, raise the error
+ raise
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ def scale_to_zero_inference_endpoint(
+ self, name: str, *, namespace: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> InferenceEndpoint:
+ """Scale Inference Endpoint to zero.
+
+ An Inference Endpoint scaled to zero will not be charged. It will be resume on the next request to it, with a
+ cold start delay. This is different than pausing the Inference Endpoint with [`pause_inference_endpoint`], which
+ would require a manual resume with [`resume_inference_endpoint`].
+
+ For convenience, you can also scale an Inference Endpoint to zero using [`InferenceEndpoint.scale_to_zero`].
+
+ Args:
+ name (`str`):
+ The name of the Inference Endpoint to scale to zero.
+ namespace (`str`, *optional*):
+ The namespace in which the Inference Endpoint is located. Defaults to the current user.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`InferenceEndpoint`]: information about the scaled-to-zero Inference Endpoint.
+ """
+ namespace = namespace or self._get_namespace(token=token)
+
+ response = get_session().post(
+ f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}/scale-to-zero",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ return InferenceEndpoint.from_raw(response.json(), namespace=namespace, token=token)
+
+ def _get_namespace(self, token: Union[bool, str, None] = None) -> str:
+ """Get the default namespace for the current user."""
+ me = self.whoami(token=token)
+ if me["type"] == "user":
+ return me["name"]
+ else:
+ raise ValueError(
+ "Cannot determine default namespace. You must provide a 'namespace' as input or be logged in as a"
+ " user."
+ )
+
+ ########################
+ # Collection Endpoints #
+ ########################
+ @validate_hf_hub_args
+ def list_collections(
+ self,
+ *,
+ owner: Union[List[str], str, None] = None,
+ item: Union[List[str], str, None] = None,
+ sort: Optional[Literal["lastModified", "trending", "upvotes"]] = None,
+ limit: Optional[int] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[Collection]:
+ """List collections on the Huggingface Hub, given some filters.
+
+ > [!WARNING]
+ > When listing collections, the item list per collection is truncated to 4 items maximum. To retrieve all items
+ > from a collection, you must use [`get_collection`].
+
+ Args:
+ owner (`List[str]` or `str`, *optional*):
+ Filter by owner's username.
+ item (`List[str]` or `str`, *optional*):
+ Filter collections containing a particular items. Example: `"models/teknium/OpenHermes-2.5-Mistral-7B"`, `"datasets/squad"` or `"papers/2311.12983"`.
+ sort (`Literal["lastModified", "trending", "upvotes"]`, *optional*):
+ Sort collections by last modified, trending or upvotes.
+ limit (`int`, *optional*):
+ Maximum number of collections to be returned.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[Collection]`: an iterable of [`Collection`] objects.
+ """
+ # Construct the API endpoint
+ path = f"{self.endpoint}/api/collections"
+ headers = self._build_hf_headers(token=token)
+ params: Dict = {}
+ if owner is not None:
+ params.update({"owner": owner})
+ if item is not None:
+ params.update({"item": item})
+ if sort is not None:
+ params.update({"sort": sort})
+ if limit is not None:
+ params.update({"limit": limit})
+
+ # Paginate over the results until limit is reached
+ items = paginate(path, headers=headers, params=params)
+ if limit is not None:
+ items = islice(items, limit) # Do not iterate over all pages
+
+ # Parse as Collection and return
+ for position, collection_data in enumerate(items):
+ yield Collection(position=position, **collection_data)
+
+ def get_collection(self, collection_slug: str, *, token: Union[bool, str, None] = None) -> Collection:
+ """Gets information about a Collection on the Hub.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection of the Hub. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns: [`Collection`]
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import get_collection
+ >>> collection = get_collection("TheBloke/recent-models-64f9a55bb3115b4f513ec026")
+ >>> collection.title
+ 'Recent models'
+ >>> len(collection.items)
+ 37
+ >>> collection.items[0]
+ CollectionItem(
+ item_object_id='651446103cd773a050bf64c2',
+ item_id='TheBloke/U-Amethyst-20B-AWQ',
+ item_type='model',
+ position=88,
+ note=None
+ )
+ ```
+ """
+ r = get_session().get(
+ f"{self.endpoint}/api/collections/{collection_slug}", headers=self._build_hf_headers(token=token)
+ )
+ hf_raise_for_status(r)
+ return Collection(**{**r.json(), "endpoint": self.endpoint})
+
+ def create_collection(
+ self,
+ title: str,
+ *,
+ namespace: Optional[str] = None,
+ description: Optional[str] = None,
+ private: bool = False,
+ exists_ok: bool = False,
+ token: Union[bool, str, None] = None,
+ ) -> Collection:
+ """Create a new Collection on the Hub.
+
+ Args:
+ title (`str`):
+ Title of the collection to create. Example: `"Recent models"`.
+ namespace (`str`, *optional*):
+ Namespace of the collection to create (username or org). Will default to the owner name.
+ description (`str`, *optional*):
+ Description of the collection to create.
+ private (`bool`, *optional*):
+ Whether the collection should be private or not. Defaults to `False` (i.e. public collection).
+ exists_ok (`bool`, *optional*):
+ If `True`, do not raise an error if collection already exists.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns: [`Collection`]
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import create_collection
+ >>> collection = create_collection(
+ ... title="ICCV 2023",
+ ... description="Portfolio of models, papers and demos I presented at ICCV 2023",
+ ... )
+ >>> collection.slug
+ "username/iccv-2023-64f9a55bb3115b4f513ec026"
+ ```
+ """
+ if namespace is None:
+ namespace = self.whoami(token)["name"]
+
+ payload = {
+ "title": title,
+ "namespace": namespace,
+ "private": private,
+ }
+ if description is not None:
+ payload["description"] = description
+
+ r = get_session().post(
+ f"{self.endpoint}/api/collections", headers=self._build_hf_headers(token=token), json=payload
+ )
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if exists_ok and err.response.status_code == 409:
+ # Collection already exists and `exists_ok=True`
+ slug = r.json()["slug"]
+ return self.get_collection(slug, token=token)
+ else:
+ raise
+ return Collection(**{**r.json(), "endpoint": self.endpoint})
+
+ def update_collection_metadata(
+ self,
+ collection_slug: str,
+ *,
+ title: Optional[str] = None,
+ description: Optional[str] = None,
+ position: Optional[int] = None,
+ private: Optional[bool] = None,
+ theme: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Collection:
+ """Update metadata of a collection on the Hub.
+
+ All arguments are optional. Only provided metadata will be updated.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection to update. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ title (`str`):
+ Title of the collection to update.
+ description (`str`, *optional*):
+ Description of the collection to update.
+ position (`int`, *optional*):
+ New position of the collection in the list of collections of the user.
+ private (`bool`, *optional*):
+ Whether the collection should be private or not.
+ theme (`str`, *optional*):
+ Theme of the collection on the Hub.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns: [`Collection`]
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import update_collection_metadata
+ >>> collection = update_collection_metadata(
+ ... collection_slug="username/iccv-2023-64f9a55bb3115b4f513ec026",
+ ... title="ICCV Oct. 2023"
+ ... description="Portfolio of models, datasets, papers and demos I presented at ICCV Oct. 2023",
+ ... private=False,
+ ... theme="pink",
+ ... )
+ >>> collection.slug
+ "username/iccv-oct-2023-64f9a55bb3115b4f513ec026"
+ # ^collection slug got updated but not the trailing ID
+ ```
+ """
+ payload = {
+ "position": position,
+ "private": private,
+ "theme": theme,
+ "title": title,
+ "description": description,
+ }
+ r = get_session().patch(
+ f"{self.endpoint}/api/collections/{collection_slug}",
+ headers=self._build_hf_headers(token=token),
+ # Only send not-none values to the API
+ json={key: value for key, value in payload.items() if value is not None},
+ )
+ hf_raise_for_status(r)
+ return Collection(**{**r.json()["data"], "endpoint": self.endpoint})
+
+ def delete_collection(
+ self, collection_slug: str, *, missing_ok: bool = False, token: Union[bool, str, None] = None
+ ) -> None:
+ """Delete a collection on the Hub.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection to delete. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ missing_ok (`bool`, *optional*):
+ If `True`, do not raise an error if collection doesn't exists.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import delete_collection
+ >>> collection = delete_collection("username/useless-collection-64f9a55bb3115b4f513ec026", missing_ok=True)
+ ```
+
+ > [!WARNING]
+ > This is a non-revertible action. A deleted collection cannot be restored.
+ """
+ r = get_session().delete(
+ f"{self.endpoint}/api/collections/{collection_slug}", headers=self._build_hf_headers(token=token)
+ )
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if missing_ok and err.response.status_code == 404:
+ # Collection doesn't exists and `missing_ok=True`
+ return
+ else:
+ raise
+
+ def add_collection_item(
+ self,
+ collection_slug: str,
+ item_id: str,
+ item_type: CollectionItemType_T,
+ *,
+ note: Optional[str] = None,
+ exists_ok: bool = False,
+ token: Union[bool, str, None] = None,
+ ) -> Collection:
+ """Add an item to a collection on the Hub.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection to update. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ item_id (`str`):
+ ID of the item to add to the collection. It can be the ID of a repo on the Hub (e.g. `"facebook/bart-large-mnli"`)
+ or a paper id (e.g. `"2307.09288"`).
+ item_type (`str`):
+ Type of the item to add. Can be one of `"model"`, `"dataset"`, `"space"` or `"paper"`.
+ note (`str`, *optional*):
+ A note to attach to the item in the collection. The maximum size for a note is 500 characters.
+ exists_ok (`bool`, *optional*):
+ If `True`, do not raise an error if item already exists.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns: [`Collection`]
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the item you try to add to the collection does not exist on the Hub.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 409 if the item you try to add to the collection is already in the collection (and exists_ok=False)
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import add_collection_item
+ >>> collection = add_collection_item(
+ ... collection_slug="davanstrien/climate-64f99dc2a5067f6b65531bab",
+ ... item_id="pierre-loic/climate-news-articles",
+ ... item_type="dataset"
+ ... )
+ >>> collection.items[-1].item_id
+ "pierre-loic/climate-news-articles"
+ # ^item got added to the collection on last position
+
+ # Add item with a note
+ >>> add_collection_item(
+ ... collection_slug="davanstrien/climate-64f99dc2a5067f6b65531bab",
+ ... item_id="datasets/climate_fever",
+ ... item_type="dataset"
+ ... note="This dataset adopts the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet."
+ ... )
+ (...)
+ ```
+ """
+ payload: Dict[str, Any] = {"item": {"id": item_id, "type": item_type}}
+ if note is not None:
+ payload["note"] = note
+ r = get_session().post(
+ f"{self.endpoint}/api/collections/{collection_slug}/items",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if exists_ok and err.response.status_code == 409:
+ # Item already exists and `exists_ok=True`
+ return self.get_collection(collection_slug, token=token)
+ else:
+ raise
+ return Collection(**{**r.json(), "endpoint": self.endpoint})
+
+ def update_collection_item(
+ self,
+ collection_slug: str,
+ item_object_id: str,
+ *,
+ note: Optional[str] = None,
+ position: Optional[int] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """Update an item in a collection.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection to update. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ item_object_id (`str`):
+ ID of the item in the collection. This is not the id of the item on the Hub (repo_id or paper id).
+ It must be retrieved from a [`CollectionItem`] object. Example: `collection.items[0].item_object_id`.
+ note (`str`, *optional*):
+ A note to attach to the item in the collection. The maximum size for a note is 500 characters.
+ position (`int`, *optional*):
+ New position of the item in the collection.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import get_collection, update_collection_item
+
+ # Get collection first
+ >>> collection = get_collection("TheBloke/recent-models-64f9a55bb3115b4f513ec026")
+
+ # Update item based on its ID (add note + update position)
+ >>> update_collection_item(
+ ... collection_slug="TheBloke/recent-models-64f9a55bb3115b4f513ec026",
+ ... item_object_id=collection.items[-1].item_object_id,
+ ... note="Newly updated model!"
+ ... position=0,
+ ... )
+ ```
+ """
+ payload = {"position": position, "note": note}
+ r = get_session().patch(
+ f"{self.endpoint}/api/collections/{collection_slug}/items/{item_object_id}",
+ headers=self._build_hf_headers(token=token),
+ # Only send not-none values to the API
+ json={key: value for key, value in payload.items() if value is not None},
+ )
+ hf_raise_for_status(r)
+
+ def delete_collection_item(
+ self,
+ collection_slug: str,
+ item_object_id: str,
+ *,
+ missing_ok: bool = False,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """Delete an item from a collection.
+
+ Args:
+ collection_slug (`str`):
+ Slug of the collection to update. Example: `"TheBloke/recent-models-64f9a55bb3115b4f513ec026"`.
+ item_object_id (`str`):
+ ID of the item in the collection. This is not the id of the item on the Hub (repo_id or paper id).
+ It must be retrieved from a [`CollectionItem`] object. Example: `collection.items[0].item_object_id`.
+ missing_ok (`bool`, *optional*):
+ If `True`, do not raise an error if item doesn't exists.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Example:
+
+ ```py
+ >>> from huggingface_hub import get_collection, delete_collection_item
+
+ # Get collection first
+ >>> collection = get_collection("TheBloke/recent-models-64f9a55bb3115b4f513ec026")
+
+ # Delete item based on its ID
+ >>> delete_collection_item(
+ ... collection_slug="TheBloke/recent-models-64f9a55bb3115b4f513ec026",
+ ... item_object_id=collection.items[-1].item_object_id,
+ ... )
+ ```
+ """
+ r = get_session().delete(
+ f"{self.endpoint}/api/collections/{collection_slug}/items/{item_object_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ try:
+ hf_raise_for_status(r)
+ except HTTPError as err:
+ if missing_ok and err.response.status_code == 404:
+ # Item already deleted and `missing_ok=True`
+ return
+ else:
+ raise
+
+ ##########################
+ # Manage access requests #
+ ##########################
+
+ @validate_hf_hub_args
+ def list_pending_access_requests(
+ self, repo_id: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> List[AccessRequest]:
+ """
+ Get pending access requests for a given gated repo.
+
+ A pending request means the user has requested access to the repo but the request has not been processed yet.
+ If the approval mode is automatic, this list should be empty. Pending requests can be accepted or rejected
+ using [`accept_access_request`] and [`reject_access_request`].
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to get access requests for.
+ repo_type (`str`, *optional*):
+ The type of the repo to get access requests for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[AccessRequest]`: A list of [`AccessRequest`] objects. Each time contains a `username`, `email`,
+ `status` and `timestamp` attribute. If the gated repo has a custom form, the `fields` attribute will
+ be populated with user's answers.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import list_pending_access_requests, accept_access_request
+
+ # List pending requests
+ >>> requests = list_pending_access_requests("meta-llama/Llama-2-7b")
+ >>> len(requests)
+ 411
+ >>> requests[0]
+ [
+ AccessRequest(
+ username='clem',
+ fullname='Clem 🤗',
+ email='***',
+ timestamp=datetime.datetime(2023, 11, 23, 18, 4, 53, 828000, tzinfo=datetime.timezone.utc),
+ status='pending',
+ fields=None,
+ ),
+ ...
+ ]
+
+ # Accept Clem's request
+ >>> accept_access_request("meta-llama/Llama-2-7b", "clem")
+ ```
+ """
+ return self._list_access_requests(repo_id, "pending", repo_type=repo_type, token=token)
+
+ @validate_hf_hub_args
+ def list_accepted_access_requests(
+ self, repo_id: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> List[AccessRequest]:
+ """
+ Get accepted access requests for a given gated repo.
+
+ An accepted request means the user has requested access to the repo and the request has been accepted. The user
+ can download any file of the repo. If the approval mode is automatic, this list should contains by default all
+ requests. Accepted requests can be cancelled or rejected at any time using [`cancel_access_request`] and
+ [`reject_access_request`]. A cancelled request will go back to the pending list while a rejected request will
+ go to the rejected list. In both cases, the user will lose access to the repo.
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to get access requests for.
+ repo_type (`str`, *optional*):
+ The type of the repo to get access requests for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[AccessRequest]`: A list of [`AccessRequest`] objects. Each time contains a `username`, `email`,
+ `status` and `timestamp` attribute. If the gated repo has a custom form, the `fields` attribute will
+ be populated with user's answers.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import list_accepted_access_requests
+
+ >>> requests = list_accepted_access_requests("meta-llama/Llama-2-7b")
+ >>> len(requests)
+ 411
+ >>> requests[0]
+ [
+ AccessRequest(
+ username='clem',
+ fullname='Clem 🤗',
+ email='***',
+ timestamp=datetime.datetime(2023, 11, 23, 18, 4, 53, 828000, tzinfo=datetime.timezone.utc),
+ status='accepted',
+ fields=None,
+ ),
+ ...
+ ]
+ ```
+ """
+ return self._list_access_requests(repo_id, "accepted", repo_type=repo_type, token=token)
+
+ @validate_hf_hub_args
+ def list_rejected_access_requests(
+ self, repo_id: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> List[AccessRequest]:
+ """
+ Get rejected access requests for a given gated repo.
+
+ A rejected request means the user has requested access to the repo and the request has been explicitly rejected
+ by a repo owner (either you or another user from your organization). The user cannot download any file of the
+ repo. Rejected requests can be accepted or cancelled at any time using [`accept_access_request`] and
+ [`cancel_access_request`]. A cancelled request will go back to the pending list while an accepted request will
+ go to the accepted list.
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to get access requests for.
+ repo_type (`str`, *optional*):
+ The type of the repo to get access requests for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[AccessRequest]`: A list of [`AccessRequest`] objects. Each time contains a `username`, `email`,
+ `status` and `timestamp` attribute. If the gated repo has a custom form, the `fields` attribute will
+ be populated with user's answers.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+
+ Example:
+ ```py
+ >>> from huggingface_hub import list_rejected_access_requests
+
+ >>> requests = list_rejected_access_requests("meta-llama/Llama-2-7b")
+ >>> len(requests)
+ 411
+ >>> requests[0]
+ [
+ AccessRequest(
+ username='clem',
+ fullname='Clem 🤗',
+ email='***',
+ timestamp=datetime.datetime(2023, 11, 23, 18, 4, 53, 828000, tzinfo=datetime.timezone.utc),
+ status='rejected',
+ fields=None,
+ ),
+ ...
+ ]
+ ```
+ """
+ return self._list_access_requests(repo_id, "rejected", repo_type=repo_type, token=token)
+
+ def _list_access_requests(
+ self,
+ repo_id: str,
+ status: Literal["accepted", "rejected", "pending"],
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> List[AccessRequest]:
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+
+ response = get_session().get(
+ f"{constants.ENDPOINT}/api/{repo_type}s/{repo_id}/user-access-request/{status}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ return [
+ AccessRequest(
+ username=request["user"]["user"],
+ fullname=request["user"]["fullname"],
+ email=request["user"].get("email"),
+ status=request["status"],
+ timestamp=parse_datetime(request["timestamp"]),
+ fields=request.get("fields"), # only if custom fields in form
+ )
+ for request in response.json()
+ ]
+
+ @validate_hf_hub_args
+ def cancel_access_request(
+ self, repo_id: str, user: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> None:
+ """
+ Cancel an access request from a user for a given gated repo.
+
+ A cancelled request will go back to the pending list and the user will lose access to the repo.
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to cancel access request for.
+ user (`str`):
+ The username of the user which access request should be cancelled.
+ repo_type (`str`, *optional*):
+ The type of the repo to cancel access request for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user does not exist on the Hub.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request cannot be found.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request is already in the pending list.
+ """
+ self._handle_access_request(repo_id, user, "pending", repo_type=repo_type, token=token)
+
+ @validate_hf_hub_args
+ def accept_access_request(
+ self, repo_id: str, user: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> None:
+ """
+ Accept an access request from a user for a given gated repo.
+
+ Once the request is accepted, the user will be able to download any file of the repo and access the community
+ tab. If the approval mode is automatic, you don't have to accept requests manually. An accepted request can be
+ cancelled or rejected at any time using [`cancel_access_request`] and [`reject_access_request`].
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to accept access request for.
+ user (`str`):
+ The username of the user which access request should be accepted.
+ repo_type (`str`, *optional*):
+ The type of the repo to accept access request for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user does not exist on the Hub.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request cannot be found.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request is already in the accepted list.
+ """
+ self._handle_access_request(repo_id, user, "accepted", repo_type=repo_type, token=token)
+
+ @validate_hf_hub_args
+ def reject_access_request(
+ self,
+ repo_id: str,
+ user: str,
+ *,
+ repo_type: Optional[str] = None,
+ rejection_reason: Optional[str],
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Reject an access request from a user for a given gated repo.
+
+ A rejected request will go to the rejected list. The user cannot download any file of the repo. Rejected
+ requests can be accepted or cancelled at any time using [`accept_access_request`] and [`cancel_access_request`].
+ A cancelled request will go back to the pending list while an accepted request will go to the accepted list.
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to reject access request for.
+ user (`str`):
+ The username of the user which access request should be rejected.
+ repo_type (`str`, *optional*):
+ The type of the repo to reject access request for. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ rejection_reason (`str`, *optional*):
+ Optional rejection reason that will be visible to the user (max 200 characters).
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user does not exist on the Hub.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request cannot be found.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user access request is already in the rejected list.
+ """
+ self._handle_access_request(
+ repo_id, user, "rejected", repo_type=repo_type, rejection_reason=rejection_reason, token=token
+ )
+
+ @validate_hf_hub_args
+ def _handle_access_request(
+ self,
+ repo_id: str,
+ user: str,
+ status: Literal["accepted", "rejected", "pending"],
+ repo_type: Optional[str] = None,
+ rejection_reason: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+
+ payload = {"user": user, "status": status}
+
+ if rejection_reason is not None:
+ if status != "rejected":
+ raise ValueError("`rejection_reason` can only be passed when rejecting an access request.")
+ payload["rejectionReason"] = rejection_reason
+
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/{repo_type}s/{repo_id}/user-access-request/handle",
+ headers=self._build_hf_headers(token=token),
+ json=payload,
+ )
+ hf_raise_for_status(response)
+
+ @validate_hf_hub_args
+ def grant_access(
+ self, repo_id: str, user: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> None:
+ """
+ Grant access to a user for a given gated repo.
+
+ Granting access don't require for the user to send an access request by themselves. The user is automatically
+ added to the accepted list meaning they can download the files You can revoke the granted access at any time
+ using [`cancel_access_request`] or [`reject_access_request`].
+
+ For more info about gated repos, see https://huggingface.co/docs/hub/models-gated.
+
+ Args:
+ repo_id (`str`):
+ The id of the repo to grant access to.
+ user (`str`):
+ The username of the user to grant access.
+ repo_type (`str`, *optional*):
+ The type of the repo to grant access to. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the repo is not gated.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 400 if the user already has access to the repo.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 403 if you only have read-only access to the repo. This can be the case if you don't have `write`
+ or `admin` role in the organization the repo belongs to or if you passed a `read` token.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 if the user does not exist on the Hub.
+ """
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/{repo_type}s/{repo_id}/user-access-request/grant",
+ headers=self._build_hf_headers(token=token),
+ json={"user": user},
+ )
+ hf_raise_for_status(response)
+ return response.json()
+
+ ###################
+ # Manage webhooks #
+ ###################
+
+ @validate_hf_hub_args
+ def get_webhook(self, webhook_id: str, *, token: Union[bool, str, None] = None) -> WebhookInfo:
+ """Get a webhook by its id.
+
+ Args:
+ webhook_id (`str`):
+ The unique identifier of the webhook to get.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`WebhookInfo`]:
+ Info about the webhook.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import get_webhook
+ >>> webhook = get_webhook("654bbbc16f2ec14d77f109cc")
+ >>> print(webhook)
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ job=None,
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ secret="my-secret",
+ domains=["repo", "discussion"],
+ disabled=False,
+ )
+ ```
+ """
+ response = get_session().get(
+ f"{constants.ENDPOINT}/api/settings/webhooks/{webhook_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhook_data = response.json()["webhook"]
+
+ watched_items = [WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook_data["watched"]]
+
+ webhook = WebhookInfo(
+ id=webhook_data["id"],
+ url=webhook_data.get("url"),
+ job=JobSpec(**webhook_data["job"]) if webhook_data.get("job") else None,
+ watched=watched_items,
+ domains=webhook_data["domains"],
+ secret=webhook_data.get("secret"),
+ disabled=webhook_data["disabled"],
+ )
+
+ return webhook
+
+ @validate_hf_hub_args
+ def list_webhooks(self, *, token: Union[bool, str, None] = None) -> List[WebhookInfo]:
+ """List all configured webhooks.
+
+ Args:
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `List[WebhookInfo]`:
+ List of webhook info objects.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import list_webhooks
+ >>> webhooks = list_webhooks()
+ >>> len(webhooks)
+ 2
+ >>> webhooks[0]
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ secret="my-secret",
+ domains=["repo", "discussion"],
+ disabled=False,
+ )
+ ```
+ """
+ response = get_session().get(
+ f"{constants.ENDPOINT}/api/settings/webhooks",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhooks_data = response.json()
+
+ return [
+ WebhookInfo(
+ id=webhook["id"],
+ url=webhook.get("url"),
+ job=JobSpec(**webhook["job"]) if webhook.get("job") else None,
+ watched=[WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook["watched"]],
+ domains=webhook["domains"],
+ secret=webhook.get("secret"),
+ disabled=webhook["disabled"],
+ )
+ for webhook in webhooks_data
+ ]
+
+ @validate_hf_hub_args
+ def create_webhook(
+ self,
+ *,
+ url: Optional[str] = None,
+ job_id: Optional[str] = None,
+ watched: List[Union[Dict, WebhookWatchedItem]],
+ domains: Optional[List[constants.WEBHOOK_DOMAIN_T]] = None,
+ secret: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> WebhookInfo:
+ """Create a new webhook.
+
+ The webhook can either send a payload to a URL, or trigger a Job to run on Hugging Face infrastructure.
+ This function should be called with one of `url` or `job_id`, but not both.
+
+ Args:
+ url (`str`):
+ URL to send the payload to.
+ job_id (`str`):
+ ID of the source Job to trigger with the webhook payload in the environment variable WEBHOOK_PAYLOAD.
+ Additional environment variables are available for convenience: WEBHOOK_REPO_ID, WEBHOOK_REPO_TYPE and WEBHOOK_SECRET.
+ watched (`List[WebhookWatchedItem]`):
+ List of [`WebhookWatchedItem`] to be watched by the webhook. It can be users, orgs, models, datasets or spaces.
+ Watched items can also be provided as plain dictionaries.
+ domains (`List[Literal["repo", "discussion"]]`, optional):
+ List of domains to watch. It can be "repo", "discussion" or both.
+ secret (`str`, optional):
+ A secret to sign the payload with.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`WebhookInfo`]:
+ Info about the newly created webhook.
+
+ Example:
+
+ Create a webhook that sends a payload to a URL
+ ```python
+ >>> from huggingface_hub import create_webhook
+ >>> payload = create_webhook(
+ ... watched=[{"type": "user", "name": "julien-c"}, {"type": "org", "name": "HuggingFaceH4"}],
+ ... url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ ... domains=["repo", "discussion"],
+ ... secret="my-secret",
+ ... )
+ >>> print(payload)
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ job=None,
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ domains=["repo", "discussion"],
+ secret="my-secret",
+ disabled=False,
+ )
+ ```
+
+ Run a Job and then create a webhook that triggers this Job
+ ```python
+ >>> from huggingface_hub import create_webhook, run_job
+ >>> job = run_job(
+ ... image="ubuntu",
+ ... command=["bash", "-c", r"echo An event occured in $WEBHOOK_REPO_ID: $WEBHOOK_PAYLOAD"],
+ ... )
+ >>> payload = create_webhook(
+ ... watched=[{"type": "user", "name": "julien-c"}, {"type": "org", "name": "HuggingFaceH4"}],
+ ... job_id=job.id,
+ ... domains=["repo", "discussion"],
+ ... secret="my-secret",
+ ... )
+ >>> print(payload)
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ url=None,
+ job=JobSpec(
+ docker_image='ubuntu',
+ space_id=None,
+ command=['bash', '-c', 'echo An event occured in $WEBHOOK_REPO_ID: $WEBHOOK_PAYLOAD'],
+ arguments=[],
+ environment={},
+ secrets=[],
+ flavor='cpu-basic',
+ timeout=None,
+ tags=None,
+ arch=None
+ ),
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ domains=["repo", "discussion"],
+ secret="my-secret",
+ disabled=False,
+ )
+ ```
+ """
+ watched_dicts = [asdict(item) if isinstance(item, WebhookWatchedItem) else item for item in watched]
+
+ post_webhooks_json = {"watched": watched_dicts, "domains": domains, "secret": secret}
+ if url is not None and job_id is not None:
+ raise ValueError("Set `url` or `job_id` but not both.")
+ elif url is not None:
+ post_webhooks_json["url"] = url
+ elif job_id is not None:
+ post_webhooks_json["jobSourceId"] = job_id
+ else:
+ raise ValueError("Missing argument for webhook: `url` or `job_id`.")
+
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/settings/webhooks",
+ json=post_webhooks_json,
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhook_data = response.json()["webhook"]
+ watched_items = [WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook_data["watched"]]
+
+ webhook = WebhookInfo(
+ id=webhook_data["id"],
+ url=webhook_data.get("url"),
+ job=JobSpec(**webhook_data["job"]) if webhook_data.get("job") else None,
+ watched=watched_items,
+ domains=webhook_data["domains"],
+ secret=webhook_data.get("secret"),
+ disabled=webhook_data["disabled"],
+ )
+
+ return webhook
+
+ @validate_hf_hub_args
+ def update_webhook(
+ self,
+ webhook_id: str,
+ *,
+ url: Optional[str] = None,
+ watched: Optional[List[Union[Dict, WebhookWatchedItem]]] = None,
+ domains: Optional[List[constants.WEBHOOK_DOMAIN_T]] = None,
+ secret: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> WebhookInfo:
+ """Update an existing webhook.
+
+ Args:
+ webhook_id (`str`):
+ The unique identifier of the webhook to be updated.
+ url (`str`, optional):
+ The URL to which the payload will be sent.
+ watched (`List[WebhookWatchedItem]`, optional):
+ List of items to watch. It can be users, orgs, models, datasets, or spaces.
+ Refer to [`WebhookWatchedItem`] for more details. Watched items can also be provided as plain dictionaries.
+ domains (`List[Literal["repo", "discussion"]]`, optional):
+ The domains to watch. This can include "repo", "discussion", or both.
+ secret (`str`, optional):
+ A secret to sign the payload with, providing an additional layer of security.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`WebhookInfo`]:
+ Info about the updated webhook.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import update_webhook
+ >>> updated_payload = update_webhook(
+ ... webhook_id="654bbbc16f2ec14d77f109cc",
+ ... url="https://new.webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ ... watched=[{"type": "user", "name": "julien-c"}, {"type": "org", "name": "HuggingFaceH4"}],
+ ... domains=["repo"],
+ ... secret="my-secret",
+ ... )
+ >>> print(updated_payload)
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ job=None,
+ url="https://new.webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ domains=["repo"],
+ secret="my-secret",
+ disabled=False,
+ ```
+ """
+ if watched is None:
+ watched = []
+ watched_dicts = [asdict(item) if isinstance(item, WebhookWatchedItem) else item for item in watched]
+
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/settings/webhooks/{webhook_id}",
+ json={"watched": watched_dicts, "url": url, "domains": domains, "secret": secret},
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhook_data = response.json()["webhook"]
+
+ watched_items = [WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook_data["watched"]]
+
+ webhook = WebhookInfo(
+ id=webhook_data["id"],
+ url=webhook_data.get("url"),
+ job=JobSpec(**webhook_data["job"]) if webhook_data.get("job") else None,
+ watched=watched_items,
+ domains=webhook_data["domains"],
+ secret=webhook_data.get("secret"),
+ disabled=webhook_data["disabled"],
+ )
+
+ return webhook
+
+ @validate_hf_hub_args
+ def enable_webhook(self, webhook_id: str, *, token: Union[bool, str, None] = None) -> WebhookInfo:
+ """Enable a webhook (makes it "active").
+
+ Args:
+ webhook_id (`str`):
+ The unique identifier of the webhook to enable.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`WebhookInfo`]:
+ Info about the enabled webhook.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import enable_webhook
+ >>> enabled_webhook = enable_webhook("654bbbc16f2ec14d77f109cc")
+ >>> enabled_webhook
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ job=None,
+ url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ domains=["repo", "discussion"],
+ secret="my-secret",
+ disabled=False,
+ )
+ ```
+ """
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/settings/webhooks/{webhook_id}/enable",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhook_data = response.json()["webhook"]
+
+ watched_items = [WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook_data["watched"]]
+
+ webhook = WebhookInfo(
+ id=webhook_data["id"],
+ url=webhook_data.get("url"),
+ job=JobSpec(**webhook_data["job"]) if webhook_data.get("job") else None,
+ watched=watched_items,
+ domains=webhook_data["domains"],
+ secret=webhook_data.get("secret"),
+ disabled=webhook_data["disabled"],
+ )
+
+ return webhook
+
+ @validate_hf_hub_args
+ def disable_webhook(self, webhook_id: str, *, token: Union[bool, str, None] = None) -> WebhookInfo:
+ """Disable a webhook (makes it "disabled").
+
+ Args:
+ webhook_id (`str`):
+ The unique identifier of the webhook to disable.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ [`WebhookInfo`]:
+ Info about the disabled webhook.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import disable_webhook
+ >>> disabled_webhook = disable_webhook("654bbbc16f2ec14d77f109cc")
+ >>> disabled_webhook
+ WebhookInfo(
+ id="654bbbc16f2ec14d77f109cc",
+ url="https://webhook.site/a2176e82-5720-43ee-9e06-f91cb4c91548",
+ jon=None,
+ watched=[WebhookWatchedItem(type="user", name="julien-c"), WebhookWatchedItem(type="org", name="HuggingFaceH4")],
+ domains=["repo", "discussion"],
+ secret="my-secret",
+ disabled=True,
+ )
+ ```
+ """
+ response = get_session().post(
+ f"{constants.ENDPOINT}/api/settings/webhooks/{webhook_id}/disable",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ webhook_data = response.json()["webhook"]
+
+ watched_items = [WebhookWatchedItem(type=item["type"], name=item["name"]) for item in webhook_data["watched"]]
+
+ webhook = WebhookInfo(
+ id=webhook_data["id"],
+ url=webhook_data.get("url"),
+ job=JobSpec(**webhook_data["job"]) if webhook_data.get("job") else None,
+ watched=watched_items,
+ domains=webhook_data["domains"],
+ secret=webhook_data.get("secret"),
+ disabled=webhook_data["disabled"],
+ )
+
+ return webhook
+
+ @validate_hf_hub_args
+ def delete_webhook(self, webhook_id: str, *, token: Union[bool, str, None] = None) -> None:
+ """Delete a webhook.
+
+ Args:
+ webhook_id (`str`):
+ The unique identifier of the webhook to delete.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended
+ method for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `None`
+
+ Example:
+ ```python
+ >>> from huggingface_hub import delete_webhook
+ >>> delete_webhook("654bbbc16f2ec14d77f109cc")
+ ```
+ """
+ response = get_session().delete(
+ f"{constants.ENDPOINT}/api/settings/webhooks/{webhook_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ #############
+ # Internals #
+ #############
+
+ def _build_hf_headers(
+ self,
+ token: Union[bool, str, None] = None,
+ library_name: Optional[str] = None,
+ library_version: Optional[str] = None,
+ user_agent: Union[Dict, str, None] = None,
+ ) -> Dict[str, str]:
+ """
+ Alias for [`build_hf_headers`] that uses the token from [`HfApi`] client
+ when `token` is not provided.
+ """
+ if token is None:
+ # Cannot do `token = token or self.token` as token can be `False`.
+ token = self.token
+ return build_hf_headers(
+ token=token,
+ library_name=library_name or self.library_name,
+ library_version=library_version or self.library_version,
+ user_agent=user_agent or self.user_agent,
+ headers=self.headers,
+ )
+
+ def _prepare_folder_deletions(
+ self,
+ repo_id: str,
+ repo_type: Optional[str],
+ revision: Optional[str],
+ path_in_repo: str,
+ delete_patterns: Optional[Union[List[str], str]],
+ token: Union[bool, str, None] = None,
+ ) -> List[CommitOperationDelete]:
+ """Generate the list of Delete operations for a commit to delete files from a repo.
+
+ List remote files and match them against the `delete_patterns` constraints. Returns a list of [`CommitOperationDelete`]
+ with the matching items.
+
+ Note: `.gitattributes` file is essential to make a repo work properly on the Hub. This file will always be
+ kept even if it matches the `delete_patterns` constraints.
+ """
+ if delete_patterns is None:
+ # If no delete patterns, no need to list and filter remote files
+ return []
+
+ # List remote files
+ filenames = self.list_repo_files(repo_id=repo_id, revision=revision, repo_type=repo_type, token=token)
+
+ # Compute relative path in repo
+ if path_in_repo and path_in_repo not in (".", "./"):
+ path_in_repo = path_in_repo.strip("/") + "/" # harmonize
+ relpath_to_abspath = {
+ file[len(path_in_repo) :]: file for file in filenames if file.startswith(path_in_repo)
+ }
+ else:
+ relpath_to_abspath = {file: file for file in filenames}
+
+ # Apply filter on relative paths and return
+ return [
+ CommitOperationDelete(path_in_repo=relpath_to_abspath[relpath], is_folder=False)
+ for relpath in filter_repo_objects(relpath_to_abspath.keys(), allow_patterns=delete_patterns)
+ if relpath_to_abspath[relpath] != ".gitattributes"
+ ]
+
+ def _prepare_upload_folder_additions(
+ self,
+ folder_path: Union[str, Path],
+ path_in_repo: str,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> List[CommitOperationAdd]:
+ """Generate the list of Add operations for a commit to upload a folder.
+
+ Files not matching the `allow_patterns` (allowlist) and `ignore_patterns` (denylist)
+ constraints are discarded.
+ """
+
+ folder_path = Path(folder_path).expanduser().resolve()
+ if not folder_path.is_dir():
+ raise ValueError(f"Provided path: '{folder_path}' is not a directory")
+
+ # List files from folder
+ relpath_to_abspath = {
+ path.relative_to(folder_path).as_posix(): path
+ for path in sorted(folder_path.glob("**/*")) # sorted to be deterministic
+ if path.is_file()
+ }
+
+ # Filter files
+ # Patterns are applied on the path relative to `folder_path`. `path_in_repo` is prefixed after the filtering.
+ filtered_repo_objects = list(
+ filter_repo_objects(
+ relpath_to_abspath.keys(), allow_patterns=allow_patterns, ignore_patterns=ignore_patterns
+ )
+ )
+
+ prefix = f"{path_in_repo.strip('/')}/" if path_in_repo else ""
+
+ # If updating a README.md file, make sure the metadata format is valid
+ # It's better to fail early than to fail after all the files have been hashed.
+ if "README.md" in filtered_repo_objects:
+ self._validate_yaml(
+ content=relpath_to_abspath["README.md"].read_text(encoding="utf8"),
+ repo_type=repo_type,
+ token=token,
+ )
+ if len(filtered_repo_objects) > 30:
+ log = logger.warning if len(filtered_repo_objects) > 200 else logger.info
+ log(
+ "It seems you are trying to upload a large folder at once. This might take some time and then fail if "
+ "the folder is too large. For such cases, it is recommended to upload in smaller batches or to use "
+ "`HfApi().upload_large_folder(...)`/`hf upload-large-folder` instead. For more details, "
+ "check out https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#upload-a-large-folder."
+ )
+
+ logger.info(f"Start hashing {len(filtered_repo_objects)} files.")
+ operations = [
+ CommitOperationAdd(
+ path_or_fileobj=relpath_to_abspath[relpath], # absolute path on disk
+ path_in_repo=prefix + relpath, # "absolute" path in repo
+ )
+ for relpath in filtered_repo_objects
+ ]
+ logger.info(f"Finished hashing {len(filtered_repo_objects)} files.")
+ return operations
+
+ def _validate_yaml(self, content: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None):
+ """
+ Validate YAML from `README.md`, used before file hashing and upload.
+
+ Args:
+ content (`str`):
+ Content of `README.md` to validate.
+ repo_type (`str`, *optional*):
+ The type of the repo to grant access to. Must be one of `model`, `dataset` or `space`.
+ Defaults to `model`.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Raises:
+ - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ if YAML is invalid
+ """
+ repo_type = repo_type if repo_type is not None else constants.REPO_TYPE_MODEL
+ headers = self._build_hf_headers(token=token)
+
+ response = get_session().post(
+ f"{self.endpoint}/api/validate-yaml",
+ json={"content": content, "repoType": repo_type},
+ headers=headers,
+ )
+ # Handle warnings (example: empty metadata)
+ response_content = response.json()
+ message = "\n".join([f"- {warning.get('message')}" for warning in response_content.get("warnings", [])])
+ if message:
+ warnings.warn(f"Warnings while validating metadata in README.md:\n{message}")
+
+ # Raise on errors
+ try:
+ hf_raise_for_status(response)
+ except BadRequestError as e:
+ errors = response_content.get("errors", [])
+ message = "\n".join([f"- {error.get('message')}" for error in errors])
+ raise ValueError(f"Invalid metadata in README.md.\n{message}") from e
+
+ def get_user_overview(self, username: str, token: Union[bool, str, None] = None) -> User:
+ """
+ Get an overview of a user on the Hub.
+
+ Args:
+ username (`str`):
+ Username of the user to get an overview of.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `User`: A [`User`] object with the user's overview.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the user does not exist on the Hub.
+ """
+ r = get_session().get(
+ f"{constants.ENDPOINT}/api/users/{username}/overview", headers=self._build_hf_headers(token=token)
+ )
+ hf_raise_for_status(r)
+ return User(**r.json())
+
+ @validate_hf_hub_args
+ def get_organization_overview(self, organization: str, token: Union[bool, str, None] = None) -> Organization:
+ """
+ Get an overview of an organization on the Hub.
+
+ Args:
+ organization (`str`):
+ Name of the organization to get an overview of.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved token, which is the recommended method
+ for authentication (see https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Organization`: An [`Organization`] object with the organization's overview.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the organization does not exist on the Hub.
+ """
+ r = get_session().get(
+ f"{constants.ENDPOINT}/api/organizations/{organization}/overview",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(r)
+ return Organization(**r.json())
+
+ def list_organization_members(self, organization: str, token: Union[bool, str, None] = None) -> Iterable[User]:
+ """
+ List of members of an organization on the Hub.
+
+ Args:
+ organization (`str`):
+ Name of the organization to get the members of.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[User]`: A list of [`User`] objects with the members of the organization.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the organization does not exist on the Hub.
+
+ """
+ for member in paginate(
+ path=f"{constants.ENDPOINT}/api/organizations/{organization}/members",
+ params={},
+ headers=self._build_hf_headers(token=token),
+ ):
+ yield User(**member)
+
+ def list_user_followers(self, username: str, token: Union[bool, str, None] = None) -> Iterable[User]:
+ """
+ Get the list of followers of a user on the Hub.
+
+ Args:
+ username (`str`):
+ Username of the user to get the followers of.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[User]`: A list of [`User`] objects with the followers of the user.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the user does not exist on the Hub.
+
+ """
+ for follower in paginate(
+ path=f"{constants.ENDPOINT}/api/users/{username}/followers",
+ params={},
+ headers=self._build_hf_headers(token=token),
+ ):
+ yield User(**follower)
+
+ def list_user_following(self, username: str, token: Union[bool, str, None] = None) -> Iterable[User]:
+ """
+ Get the list of users followed by a user on the Hub.
+
+ Args:
+ username (`str`):
+ Username of the user to get the users followed by.
+ token (`bool` or `str`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[User]`: A list of [`User`] objects with the users followed by the user.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the user does not exist on the Hub.
+
+ """
+ for followed_user in paginate(
+ path=f"{constants.ENDPOINT}/api/users/{username}/following",
+ params={},
+ headers=self._build_hf_headers(token=token),
+ ):
+ yield User(**followed_user)
+
+ def list_papers(
+ self,
+ *,
+ query: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[PaperInfo]:
+ """
+ List daily papers on the Hugging Face Hub given a search query.
+
+ Args:
+ query (`str`, *optional*):
+ A search query string to find papers.
+ If provided, returns papers that match the query.
+ token (Union[bool, str, None], *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+
+ Returns:
+ `Iterable[PaperInfo]`: an iterable of [`huggingface_hub.hf_api.PaperInfo`] objects.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import HfApi
+
+ >>> api = HfApi()
+
+ # List all papers with "attention" in their title
+ >>> api.list_papers(query="attention")
+ ```
+ """
+ path = f"{self.endpoint}/api/papers/search"
+ params = {}
+ if query:
+ params["q"] = query
+ r = get_session().get(
+ path,
+ params=params,
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(r)
+ for paper in r.json():
+ yield PaperInfo(**paper)
+
+ def paper_info(self, id: str) -> PaperInfo:
+ """
+ Get information for a paper on the Hub.
+
+ Args:
+ id (`str`, **optional**):
+ ArXiv id of the paper.
+
+ Returns:
+ `PaperInfo`: A `PaperInfo` object.
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError):
+ HTTP 404 If the paper does not exist on the Hub.
+ """
+ path = f"{self.endpoint}/api/papers/{id}"
+ r = get_session().get(path)
+ hf_raise_for_status(r)
+ return PaperInfo(**r.json())
+
+ def auth_check(
+ self, repo_id: str, *, repo_type: Optional[str] = None, token: Union[bool, str, None] = None
+ ) -> None:
+ """
+ Check if the provided user token has access to a specific repository on the Hugging Face Hub.
+
+ This method verifies whether the user, authenticated via the provided token, has access to the specified
+ repository. If the repository is not found or if the user lacks the required permissions to access it,
+ the method raises an appropriate exception.
+
+ Args:
+ repo_id (`str`):
+ The repository to check for access. Format should be `"user/repo_name"`.
+ Example: `"user/my-cool-model"`.
+
+ repo_type (`str`, *optional*):
+ The type of the repository. Should be one of `"model"`, `"dataset"`, or `"space"`.
+ If not specified, the default is `"model"`.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Raises:
+ [`~utils.RepositoryNotFoundError`]:
+ Raised if the repository does not exist, is private, or the user does not have access. This can
+ occur if the `repo_id` or `repo_type` is incorrect or if the repository is private but the user
+ is not authenticated.
+
+ [`~utils.GatedRepoError`]:
+ Raised if the repository exists but is gated and the user is not authorized to access it.
+
+ Example:
+ Check if the user has access to a repository:
+
+ ```python
+ >>> from huggingface_hub import auth_check
+ >>> from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
+
+ try:
+ auth_check("user/my-cool-model")
+ except GatedRepoError:
+ # Handle gated repository error
+ print("You do not have permission to access this gated repository.")
+ except RepositoryNotFoundError:
+ # Handle repository not found error
+ print("The repository was not found or you do not have access.")
+ ```
+
+ In this example:
+ - If the user has access, the method completes successfully.
+ - If the repository is gated or does not exist, appropriate exceptions are raised, allowing the user
+ to handle them accordingly.
+ """
+ headers = self._build_hf_headers(token=token)
+ if repo_type is None:
+ repo_type = constants.REPO_TYPE_MODEL
+ if repo_type not in constants.REPO_TYPES:
+ raise ValueError(f"Invalid repo type, must be one of {constants.REPO_TYPES}")
+ path = f"{self.endpoint}/api/{repo_type}s/{repo_id}/auth-check"
+ r = get_session().get(path, headers=headers)
+ hf_raise_for_status(r)
+
+ def run_job(
+ self,
+ *,
+ image: str,
+ command: List[str],
+ env: Optional[Dict[str, Any]] = None,
+ secrets: Optional[Dict[str, Any]] = None,
+ flavor: Optional[SpaceHardware] = None,
+ timeout: Optional[Union[int, float, str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> JobInfo:
+ """
+ Run compute Jobs on Hugging Face infrastructure.
+
+ Args:
+ image (`str`):
+ The Docker image to use.
+ Examples: `"ubuntu"`, `"python:3.12"`, `"pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel"`.
+ Example with an image from a Space: `"hf.co/spaces/lhoestq/duckdb"`.
+
+ command (`List[str]`):
+ The command to run. Example: `["echo", "hello"]`.
+
+ env (`Dict[str, Any]`, *optional*):
+ Defines the environment variables for the Job.
+
+ secrets (`Dict[str, Any]`, *optional*):
+ Defines the secret environment variables for the Job.
+
+ flavor (`str`, *optional*):
+ Flavor for the hardware, as in Hugging Face Spaces. See [`SpaceHardware`] for possible values.
+ Defaults to `"cpu-basic"`.
+
+ timeout (`Union[int, float, str]`, *optional*):
+ Max duration for the Job: int/float with s (seconds, default), m (minutes), h (hours) or d (days).
+ Example: `300` or `"5m"` for 5 minutes.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job will be created. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+ Run your first Job:
+
+ ```python
+ >>> from huggingface_hub import run_job
+ >>> run_job(image="python:3.12", command=["python", "-c" ,"print('Hello from HF compute!')"])
+ ```
+
+ Run a GPU Job:
+
+ ```python
+ >>> from huggingface_hub import run_job
+ >>> image = "pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel"
+ >>> command = ["python", "-c", "import torch; print(f"This code ran with the following GPU: {torch.cuda.get_device_name()}")"]
+ >>> run_job(image=image, command=command, flavor="a10g-small")
+ ```
+
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ job_spec = _create_job_spec(
+ image=image,
+ command=command,
+ env=env,
+ secrets=secrets,
+ flavor=flavor,
+ timeout=timeout,
+ )
+ response = get_session().post(
+ f"https://huggingface.co/api/jobs/{namespace}",
+ json=job_spec,
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ job_info = response.json()
+ return JobInfo(**job_info, endpoint=self.endpoint)
+
+ def fetch_job_logs(
+ self,
+ *,
+ job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> Iterable[str]:
+ """
+ Fetch all the logs from a compute Job on Hugging Face infrastructure.
+
+ Args:
+ job_id (`str`):
+ ID of the Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job is running. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import fetch_job_logs, run_job
+ >>> job = run_job(image="python:3.12", command=["python", "-c" ,"print('Hello from HF compute!')"])
+ >>> for log in fetch_job_logs(job.id):
+ ... print(log)
+ Hello from HF compute!
+ ```
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ logging_finished = logging_started = False
+ job_finished = False
+ # - We need to retry because sometimes the /logs doesn't return logs when the job just started.
+ # (for example it can return only two lines: one for "Job started" and one empty line)
+ # - Timeouts can happen in case of build errors
+ # - ChunkedEncodingError can happen in case of stopped logging in the middle of streaming
+ # - Infinite empty log stream can happen in case of build error
+ # (the logs stream is infinite and empty except for the Job started message)
+ # - there is a ": keep-alive" every 30 seconds
+
+ # We don't use http_backoff since we need to check ourselves if ConnectionError.__context__ is a TimeoutError
+ max_retries = 5
+ min_wait_time = 1
+ max_wait_time = 10
+ sleep_time = 0
+ for _ in range(max_retries):
+ time.sleep(sleep_time)
+ sleep_time = min(max_wait_time, max(min_wait_time, sleep_time * 2))
+ try:
+ resp = get_session().get(
+ f"https://huggingface.co/api/jobs/{namespace}/{job_id}/logs",
+ headers=self._build_hf_headers(token=token),
+ stream=True,
+ timeout=120,
+ )
+ log = None
+ for line in resp.iter_lines(chunk_size=1):
+ line = line.decode("utf-8")
+ if line and line.startswith("data: {"):
+ data = json.loads(line[len("data: ") :])
+ # timestamp = data["timestamp"]
+ if not data["data"].startswith("===== Job started"):
+ logging_started = True
+ log = data["data"]
+ yield log
+ logging_finished = logging_started
+ except requests.exceptions.ChunkedEncodingError:
+ # Response ended prematurely
+ break
+ except KeyboardInterrupt:
+ break
+ except requests.exceptions.ConnectionError as err:
+ is_timeout = err.__context__ and isinstance(getattr(err.__context__, "__cause__", None), TimeoutError)
+ if logging_started or not is_timeout:
+ raise
+ if logging_finished or job_finished:
+ break
+ job_status = (
+ get_session()
+ .get(
+ f"https://huggingface.co/api/jobs/{namespace}/{job_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ .json()
+ )
+ if "status" in job_status and job_status["status"]["stage"] not in ("RUNNING", "UPDATING"):
+ job_finished = True
+
+ def list_jobs(
+ self,
+ *,
+ timeout: Optional[int] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> List[JobInfo]:
+ """
+ List compute Jobs on Hugging Face infrastructure.
+
+ Args:
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+
+ namespace (`str`, *optional*):
+ The namespace from where it lists the jobs. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = whoami(token=token)["name"]
+ response = get_session().get(
+ f"{self.endpoint}/api/jobs/{namespace}",
+ headers=self._build_hf_headers(token=token),
+ timeout=timeout,
+ )
+ response.raise_for_status()
+ return [JobInfo(**job_info, endpoint=self.endpoint) for job_info in response.json()]
+
+ def inspect_job(
+ self,
+ *,
+ job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> JobInfo:
+ """
+ Inspect a compute Job on Hugging Face infrastructure.
+
+ Args:
+ job_id (`str`):
+ ID of the Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job is running. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import inspect_job, run_job
+ >>> job = run_job(image="python:3.12", command=["python", "-c" ,"print('Hello from HF compute!')"])
+ >>> inspect_job(job.id)
+ JobInfo(
+ id='68780d00bbe36d38803f645f',
+ created_at=datetime.datetime(2025, 7, 16, 20, 35, 12, 808000, tzinfo=datetime.timezone.utc),
+ docker_image='python:3.12',
+ space_id=None,
+ command=['python', '-c', "print('Hello from HF compute!')"],
+ arguments=[],
+ environment={},
+ secrets={},
+ flavor='cpu-basic',
+ status=JobStatus(stage='RUNNING', message=None)
+ )
+ ```
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ response = get_session().get(
+ f"{self.endpoint}/api/jobs/{namespace}/{job_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ response.raise_for_status()
+ return JobInfo(**response.json(), endpoint=self.endpoint)
+
+ def cancel_job(
+ self,
+ *,
+ job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Cancel a compute Job on Hugging Face infrastructure.
+
+ Args:
+ job_id (`str`):
+ ID of the Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job is running. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ get_session().post(
+ f"{self.endpoint}/api/jobs/{namespace}/{job_id}/cancel",
+ headers=self._build_hf_headers(token=token),
+ ).raise_for_status()
+
+ @experimental
+ def run_uv_job(
+ self,
+ script: str,
+ *,
+ script_args: Optional[List[str]] = None,
+ dependencies: Optional[List[str]] = None,
+ python: Optional[str] = None,
+ image: Optional[str] = None,
+ env: Optional[Dict[str, Any]] = None,
+ secrets: Optional[Dict[str, Any]] = None,
+ flavor: Optional[SpaceHardware] = None,
+ timeout: Optional[Union[int, float, str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ _repo: Optional[str] = None,
+ ) -> JobInfo:
+ """
+ Run a UV script Job on Hugging Face infrastructure.
+
+ Args:
+ script (`str`):
+ Path or URL of the UV script, or a command.
+
+ script_args (`List[str]`, *optional*)
+ Arguments to pass to the script or command.
+
+ dependencies (`List[str]`, *optional*)
+ Dependencies to use to run the UV script.
+
+ python (`str`, *optional*)
+ Use a specific Python version. Default is 3.12.
+
+ image (`str`, *optional*, defaults to "ghcr.io/astral-sh/uv:python3.12-bookworm"):
+ Use a custom Docker image with `uv` installed.
+
+ env (`Dict[str, Any]`, *optional*):
+ Defines the environment variables for the Job.
+
+ secrets (`Dict[str, Any]`, *optional*):
+ Defines the secret environment variables for the Job.
+
+ flavor (`str`, *optional*):
+ Flavor for the hardware, as in Hugging Face Spaces. See [`SpaceHardware`] for possible values.
+ Defaults to `"cpu-basic"`.
+
+ timeout (`Union[int, float, str]`, *optional*):
+ Max duration for the Job: int/float with s (seconds, default), m (minutes), h (hours) or d (days).
+ Example: `300` or `"5m"` for 5 minutes.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job will be created. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+
+ Run a script from a URL:
+
+ ```python
+ >>> from huggingface_hub import run_uv_job
+ >>> script = "https://raw.githubusercontent.com/huggingface/trl/refs/heads/main/trl/scripts/sft.py"
+ >>> script_args = ["--model_name_or_path", "Qwen/Qwen2-0.5B", "--dataset_name", "trl-lib/Capybara", "--push_to_hub"]
+ >>> run_uv_job(script, script_args=script_args, dependencies=["trl"], flavor="a10g-small")
+ ```
+
+ Run a local script:
+
+ ```python
+ >>> from huggingface_hub import run_uv_job
+ >>> script = "my_sft.py"
+ >>> script_args = ["--model_name_or_path", "Qwen/Qwen2-0.5B", "--dataset_name", "trl-lib/Capybara", "--push_to_hub"]
+ >>> run_uv_job(script, script_args=script_args, dependencies=["trl"], flavor="a10g-small")
+ ```
+
+ Run a command:
+
+ ```python
+ >>> from huggingface_hub import run_uv_job
+ >>> script = "lighteval"
+ >>> script_args= ["endpoint", "inference-providers", "model_name=openai/gpt-oss-20b,provider=auto", "lighteval|gsm8k|0|0"]
+ >>> run_uv_job(script, script_args=script_args, dependencies=["lighteval"], flavor="a10g-small")
+ ```
+ """
+ image = image or "ghcr.io/astral-sh/uv:python3.12-bookworm"
+ env = env or {}
+ secrets = secrets or {}
+
+ # Build command
+ command, env, secrets = self._create_uv_command_env_and_secrets(
+ script=script,
+ script_args=script_args,
+ dependencies=dependencies,
+ python=python,
+ env=env,
+ secrets=secrets,
+ namespace=namespace,
+ token=token,
+ _repo=_repo,
+ )
+ # Create RunCommand args
+ return self.run_job(
+ image=image,
+ command=command,
+ env=env,
+ secrets=secrets,
+ flavor=flavor,
+ timeout=timeout,
+ namespace=namespace,
+ token=token,
+ )
+
+ def create_scheduled_job(
+ self,
+ *,
+ image: str,
+ command: List[str],
+ schedule: str,
+ suspend: Optional[bool] = None,
+ concurrency: Optional[bool] = None,
+ env: Optional[Dict[str, Any]] = None,
+ secrets: Optional[Dict[str, Any]] = None,
+ flavor: Optional[SpaceHardware] = None,
+ timeout: Optional[Union[int, float, str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> ScheduledJobInfo:
+ """
+ Create scheduled compute Jobs on Hugging Face infrastructure.
+
+ Args:
+ image (`str`):
+ The Docker image to use.
+ Examples: `"ubuntu"`, `"python:3.12"`, `"pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel"`.
+ Example with an image from a Space: `"hf.co/spaces/lhoestq/duckdb"`.
+
+ command (`List[str]`):
+ The command to run. Example: `["echo", "hello"]`.
+
+ schedule (`str`):
+ One of "@annually", "@yearly", "@monthly", "@weekly", "@daily", "@hourly", or a
+ CRON schedule expression (e.g., '0 9 * * 1' for 9 AM every Monday).
+
+ suspend (`bool`, *optional*):
+ If True, the scheduled Job is suspended (paused). Defaults to False.
+
+ concurrency (`bool`, *optional*):
+ If True, multiple instances of this Job can run concurrently. Defaults to False.
+
+ env (`Dict[str, Any]`, *optional*):
+ Defines the environment variables for the Job.
+
+ secrets (`Dict[str, Any]`, *optional*):
+ Defines the secret environment variables for the Job.
+
+ flavor (`str`, *optional*):
+ Flavor for the hardware, as in Hugging Face Spaces. See [`SpaceHardware`] for possible values.
+ Defaults to `"cpu-basic"`.
+
+ timeout (`Union[int, float, str]`, *optional*):
+ Max duration for the Job: int/float with s (seconds, default), m (minutes), h (hours) or d (days).
+ Example: `300` or `"5m"` for 5 minutes.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job will be created. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+ Create your first scheduled Job:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_job
+ >>> create_scheduled_job(image="python:3.12", command=["python", "-c" ,"print('Hello from HF compute!')"], schedule="@hourly")
+ ```
+
+ Use a CRON schedule expression:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_job
+ >>> create_scheduled_job(image="python:3.12", command=["python", "-c" ,"print('this runs every 5min')"], schedule="*/5 * * * *")
+ ```
+
+ Create a scheduled GPU Job:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_job
+ >>> image = "pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel"
+ >>> command = ["python", "-c", "import torch; print(f"This code ran with the following GPU: {torch.cuda.get_device_name()}")"]
+ >>> create_scheduled_job(image, command, flavor="a10g-small", schedule="@hourly")
+ ```
+
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+
+ # prepare payload to send to HF Jobs API
+ job_spec = _create_job_spec(
+ image=image,
+ command=command,
+ env=env,
+ secrets=secrets,
+ flavor=flavor,
+ timeout=timeout,
+ )
+ input_json: Dict[str, Any] = {
+ "jobSpec": job_spec,
+ "schedule": schedule,
+ }
+ if concurrency is not None:
+ input_json["concurrency"] = concurrency
+ if suspend is not None:
+ input_json["suspend"] = suspend
+ response = get_session().post(
+ f"https://huggingface.co/api/scheduled-jobs/{namespace}",
+ json=input_json,
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ scheduled_job_info = response.json()
+ return ScheduledJobInfo(**scheduled_job_info)
+
+ def list_scheduled_jobs(
+ self,
+ *,
+ timeout: Optional[int] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> List[ScheduledJobInfo]:
+ """
+ List scheduled compute Jobs on Hugging Face infrastructure.
+
+ Args:
+ timeout (`float`, *optional*):
+ Whether to set a timeout for the request to the Hub.
+
+ namespace (`str`, *optional*):
+ The namespace from where it lists the jobs. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ response = get_session().get(
+ f"{self.endpoint}/api/scheduled-jobs/{namespace}",
+ headers=self._build_hf_headers(token=token),
+ timeout=timeout,
+ )
+ hf_raise_for_status(response)
+ return [ScheduledJobInfo(**scheduled_job_info) for scheduled_job_info in response.json()]
+
+ def inspect_scheduled_job(
+ self,
+ *,
+ scheduled_job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> ScheduledJobInfo:
+ """
+ Inspect a scheduled compute Job on Hugging Face infrastructure.
+
+ Args:
+ scheduled_job_id (`str`):
+ ID of the scheduled Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the scheduled Job is. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import inspect_job, create_scheduled_job
+ >>> scheduled_job = create_scheduled_job(image="python:3.12", command=["python", "-c" ,"print('Hello from HF compute!')"], schedule="@hourly")
+ >>> inspect_scheduled_job(scheduled_job.id)
+ ```
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ response = get_session().get(
+ f"{self.endpoint}/api/scheduled-jobs/{namespace}/{scheduled_job_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+ return ScheduledJobInfo(**response.json())
+
+ def delete_scheduled_job(
+ self,
+ *,
+ scheduled_job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Delete a scheduled compute Job on Hugging Face infrastructure.
+
+ Args:
+ scheduled_job_id (`str`):
+ ID of the scheduled Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the scheduled Job is. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ response = get_session().delete(
+ f"{self.endpoint}/api/scheduled-jobs/{namespace}/{scheduled_job_id}",
+ headers=self._build_hf_headers(token=token),
+ )
+ hf_raise_for_status(response)
+
+ def suspend_scheduled_job(
+ self,
+ *,
+ scheduled_job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Suspend (pause) a scheduled compute Job on Hugging Face infrastructure.
+
+ Args:
+ scheduled_job_id (`str`):
+ ID of the scheduled Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the scheduled Job is. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ get_session().post(
+ f"{self.endpoint}/api/scheduled-jobs/{namespace}/{scheduled_job_id}/suspend",
+ headers=self._build_hf_headers(token=token),
+ ).raise_for_status()
+
+ def resume_scheduled_job(
+ self,
+ *,
+ scheduled_job_id: str,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ ) -> None:
+ """
+ Resume (unpause) a scheduled compute Job on Hugging Face infrastructure.
+
+ Args:
+ scheduled_job_id (`str`):
+ ID of the scheduled Job.
+
+ namespace (`str`, *optional*):
+ The namespace where the scheduled Job is. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+ """
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+ get_session().post(
+ f"{self.endpoint}/api/scheduled-jobs/{namespace}/{scheduled_job_id}/resume",
+ headers=self._build_hf_headers(token=token),
+ ).raise_for_status()
+
+ @experimental
+ def create_scheduled_uv_job(
+ self,
+ script: str,
+ *,
+ script_args: Optional[List[str]] = None,
+ schedule: str,
+ suspend: Optional[bool] = None,
+ concurrency: Optional[bool] = None,
+ dependencies: Optional[List[str]] = None,
+ python: Optional[str] = None,
+ image: Optional[str] = None,
+ env: Optional[Dict[str, Any]] = None,
+ secrets: Optional[Dict[str, Any]] = None,
+ flavor: Optional[SpaceHardware] = None,
+ timeout: Optional[Union[int, float, str]] = None,
+ namespace: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ _repo: Optional[str] = None,
+ ) -> ScheduledJobInfo:
+ """
+ Run a UV script Job on Hugging Face infrastructure.
+
+ Args:
+ script (`str`):
+ Path or URL of the UV script, or a command.
+
+ script_args (`List[str]`, *optional*)
+ Arguments to pass to the script, or a command.
+
+ schedule (`str`):
+ One of "@annually", "@yearly", "@monthly", "@weekly", "@daily", "@hourly", or a
+ CRON schedule expression (e.g., '0 9 * * 1' for 9 AM every Monday).
+
+ suspend (`bool`, *optional*):
+ If True, the scheduled Job is suspended (paused). Defaults to False.
+
+ concurrency (`bool`, *optional*):
+ If True, multiple instances of this Job can run concurrently. Defaults to False.
+
+ dependencies (`List[str]`, *optional*)
+ Dependencies to use to run the UV script.
+
+ python (`str`, *optional*)
+ Use a specific Python version. Default is 3.12.
+
+ image (`str`, *optional*, defaults to "ghcr.io/astral-sh/uv:python3.12-bookworm"):
+ Use a custom Docker image with `uv` installed.
+
+ env (`Dict[str, Any]`, *optional*):
+ Defines the environment variables for the Job.
+
+ secrets (`Dict[str, Any]`, *optional*):
+ Defines the secret environment variables for the Job.
+
+ flavor (`str`, *optional*):
+ Flavor for the hardware, as in Hugging Face Spaces. See [`SpaceHardware`] for possible values.
+ Defaults to `"cpu-basic"`.
+
+ timeout (`Union[int, float, str]`, *optional*):
+ Max duration for the Job: int/float with s (seconds, default), m (minutes), h (hours) or d (days).
+ Example: `300` or `"5m"` for 5 minutes.
+
+ namespace (`str`, *optional*):
+ The namespace where the Job will be created. Defaults to the current user's namespace.
+
+ token `(Union[bool, str, None]`, *optional*):
+ A valid user access token. If not provided, the locally saved token will be used, which is the
+ recommended authentication method. Set to `False` to disable authentication.
+ Refer to: https://huggingface.co/docs/huggingface_hub/quick-start#authentication.
+
+ Example:
+
+ Schedule a script from a URL:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_uv_job
+ >>> script = "https://raw.githubusercontent.com/huggingface/trl/refs/heads/main/trl/scripts/sft.py"
+ >>> script_args = ["--model_name_or_path", "Qwen/Qwen2-0.5B", "--dataset_name", "trl-lib/Capybara", "--push_to_hub"]
+ >>> create_scheduled_uv_job(script, script_args=script_args, dependencies=["trl"], flavor="a10g-small", schedule="@weekly")
+ ```
+
+ Schedule a local script:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_uv_job
+ >>> script = "my_sft.py"
+ >>> script_args = ["--model_name_or_path", "Qwen/Qwen2-0.5B", "--dataset_name", "trl-lib/Capybara", "--push_to_hub"]
+ >>> create_scheduled_uv_job(script, script_args=script_args, dependencies=["trl"], flavor="a10g-small", schedule="@weekly")
+ ```
+
+ Schedule a command:
+
+ ```python
+ >>> from huggingface_hub import create_scheduled_uv_job
+ >>> script = "lighteval"
+ >>> script_args= ["endpoint", "inference-providers", "model_name=openai/gpt-oss-20b,provider=auto", "lighteval|gsm8k|0|0"]
+ >>> create_scheduled_uv_job(script, script_args=script_args, dependencies=["lighteval"], flavor="a10g-small", schedule="@weekly")
+ ```
+ """
+ image = image or "ghcr.io/astral-sh/uv:python3.12-bookworm"
+ # Build command
+ command, env, secrets = self._create_uv_command_env_and_secrets(
+ script=script,
+ script_args=script_args,
+ dependencies=dependencies,
+ python=python,
+ env=env,
+ secrets=secrets,
+ namespace=namespace,
+ token=token,
+ _repo=_repo,
+ )
+ # Create RunCommand args
+ return self.create_scheduled_job(
+ image=image,
+ command=command,
+ schedule=schedule,
+ suspend=suspend,
+ concurrency=concurrency,
+ env=env,
+ secrets=secrets,
+ flavor=flavor,
+ timeout=timeout,
+ namespace=namespace,
+ token=token,
+ )
+
+ def _create_uv_command_env_and_secrets(
+ self,
+ *,
+ script: str,
+ script_args: Optional[List[str]],
+ dependencies: Optional[List[str]],
+ python: Optional[str],
+ env: Optional[Dict[str, Any]],
+ secrets: Optional[Dict[str, Any]],
+ namespace: Optional[str],
+ token: Union[bool, str, None],
+ _repo: Optional[str],
+ ) -> Tuple[List[str], Dict[str, Any], Dict[str, Any]]:
+ env = env or {}
+ secrets = secrets or {}
+
+ # Build command
+ uv_args = []
+ if dependencies:
+ for dependency in dependencies:
+ uv_args += ["--with", dependency]
+ if python:
+ uv_args += ["--python", python]
+ script_args = script_args or []
+
+ if namespace is None:
+ namespace = self.whoami(token=token)["name"]
+
+ is_url = script.startswith("http://") or script.startswith("https://")
+ if is_url or not Path(script).is_file():
+ # Direct URL execution or command - no upload needed
+ command = ["uv", "run"] + uv_args + [script] + script_args
+ else:
+ # Local file - upload to HF
+ script_path = Path(script)
+ filename = script_path.name
+ # Parse repo
+ if _repo:
+ repo_id = _repo
+ if "/" not in repo_id:
+ repo_id = f"{namespace}/{repo_id}"
+ else:
+ repo_id = f"{namespace}/hf-cli-jobs-uv-run-scripts"
+
+ # Create repo if needed
+ try:
+ self.repo_info(repo_id, repo_type="dataset")
+ logger.debug(f"Using existing repository: {repo_id}")
+ except RepositoryNotFoundError:
+ logger.info(f"Creating repository: {repo_id}")
+ create_repo(repo_id, repo_type="dataset", private=True, exist_ok=True)
+
+ # Upload script
+ logger.info(f"Uploading {script_path.name} to {repo_id}...")
+ with open(script_path, "r") as f:
+ script_content = f.read()
+
+ commit_hash = self.upload_file(
+ path_or_fileobj=script_content.encode(),
+ path_in_repo=filename,
+ repo_id=repo_id,
+ repo_type="dataset",
+ ).oid
+
+ script_url = f"{self.endpoint}/datasets/{repo_id}/resolve/{commit_hash}/{filename}"
+ repo_url = f"{self.endpoint}/datasets/{repo_id}"
+
+ logger.debug(f"✓ Script uploaded to: {repo_url}/blob/main/{filename}")
+
+ # Create and upload minimal README
+ timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S UTC")
+ readme_content = dedent(
+ f"""
+ ---
+ tags:
+ - hf-cli-jobs-uv-script
+ - ephemeral
+ viewer: false
+ ---
+
+ # UV Script: {filename}
+
+ Executed via `hf jobs uv run` on {timestamp}
+
+ ## Run this script
+
+ ```bash
+ hf jobs uv run {filename}
+ ```
+
+ ---
+ *Created with [hf jobs](https://huggingface.co/docs/huggingface_hub/main/en/guides/jobs)*
+ """
+ )
+ self.upload_file(
+ path_or_fileobj=readme_content.encode(),
+ path_in_repo="README.md",
+ repo_id=repo_id,
+ repo_type="dataset",
+ )
+
+ secrets["UV_SCRIPT_HF_TOKEN"] = token or self.token or get_token()
+ env["UV_SCRIPT_URL"] = script_url
+
+ pre_command = (
+ dedent(
+ """
+ import urllib.request
+ import os
+ from pathlib import Path
+ o = urllib.request.build_opener()
+ o.addheaders = [("Authorization", "Bearer " + os.environ["UV_SCRIPT_HF_TOKEN"])]
+ Path("/tmp/script.py").write_bytes(o.open(os.environ["UV_SCRIPT_URL"]).read())
+ """
+ )
+ .strip()
+ .replace('"', r"\"")
+ .split("\n")
+ )
+ pre_command = ["python", "-c", '"' + "; ".join(pre_command) + '"']
+ command = ["uv", "run"] + uv_args + ["/tmp/script.py"] + script_args
+ command = ["bash", "-c", " ".join(pre_command) + " && " + " ".join(command)]
+ return command, env, secrets
+
+
+def _parse_revision_from_pr_url(pr_url: str) -> str:
+ """Safely parse revision number from a PR url.
+
+ Example:
+ ```py
+ >>> _parse_revision_from_pr_url("https://huggingface.co/bigscience/bloom/discussions/2")
+ "refs/pr/2"
+ ```
+ """
+ re_match = re.match(_REGEX_DISCUSSION_URL, pr_url)
+ if re_match is None:
+ raise RuntimeError(f"Unexpected response from the hub, expected a Pull Request URL but got: '{pr_url}'")
+ return f"refs/pr/{re_match[1]}"
+
+
+api = HfApi()
+
+whoami = api.whoami
+auth_check = api.auth_check
+get_token_permission = api.get_token_permission
+
+list_models = api.list_models
+model_info = api.model_info
+
+list_datasets = api.list_datasets
+dataset_info = api.dataset_info
+
+list_spaces = api.list_spaces
+space_info = api.space_info
+
+list_papers = api.list_papers
+paper_info = api.paper_info
+
+repo_exists = api.repo_exists
+revision_exists = api.revision_exists
+file_exists = api.file_exists
+repo_info = api.repo_info
+list_repo_files = api.list_repo_files
+list_repo_refs = api.list_repo_refs
+list_repo_commits = api.list_repo_commits
+list_repo_tree = api.list_repo_tree
+get_paths_info = api.get_paths_info
+
+get_model_tags = api.get_model_tags
+get_dataset_tags = api.get_dataset_tags
+
+create_commit = api.create_commit
+create_repo = api.create_repo
+delete_repo = api.delete_repo
+update_repo_visibility = api.update_repo_visibility
+update_repo_settings = api.update_repo_settings
+move_repo = api.move_repo
+upload_file = api.upload_file
+upload_folder = api.upload_folder
+delete_file = api.delete_file
+delete_folder = api.delete_folder
+delete_files = api.delete_files
+upload_large_folder = api.upload_large_folder
+preupload_lfs_files = api.preupload_lfs_files
+create_branch = api.create_branch
+delete_branch = api.delete_branch
+create_tag = api.create_tag
+delete_tag = api.delete_tag
+get_full_repo_name = api.get_full_repo_name
+
+# Danger-zone API
+super_squash_history = api.super_squash_history
+list_lfs_files = api.list_lfs_files
+permanently_delete_lfs_files = api.permanently_delete_lfs_files
+
+# Safetensors helpers
+get_safetensors_metadata = api.get_safetensors_metadata
+parse_safetensors_file_metadata = api.parse_safetensors_file_metadata
+
+# Background jobs
+run_as_future = api.run_as_future
+
+# Activity API
+list_liked_repos = api.list_liked_repos
+list_repo_likers = api.list_repo_likers
+unlike = api.unlike
+
+# Community API
+get_discussion_details = api.get_discussion_details
+get_repo_discussions = api.get_repo_discussions
+create_discussion = api.create_discussion
+create_pull_request = api.create_pull_request
+change_discussion_status = api.change_discussion_status
+comment_discussion = api.comment_discussion
+edit_discussion_comment = api.edit_discussion_comment
+rename_discussion = api.rename_discussion
+merge_pull_request = api.merge_pull_request
+
+# Space API
+add_space_secret = api.add_space_secret
+delete_space_secret = api.delete_space_secret
+get_space_variables = api.get_space_variables
+add_space_variable = api.add_space_variable
+delete_space_variable = api.delete_space_variable
+get_space_runtime = api.get_space_runtime
+request_space_hardware = api.request_space_hardware
+set_space_sleep_time = api.set_space_sleep_time
+pause_space = api.pause_space
+restart_space = api.restart_space
+duplicate_space = api.duplicate_space
+request_space_storage = api.request_space_storage
+delete_space_storage = api.delete_space_storage
+
+# Inference Endpoint API
+list_inference_endpoints = api.list_inference_endpoints
+create_inference_endpoint = api.create_inference_endpoint
+get_inference_endpoint = api.get_inference_endpoint
+update_inference_endpoint = api.update_inference_endpoint
+delete_inference_endpoint = api.delete_inference_endpoint
+pause_inference_endpoint = api.pause_inference_endpoint
+resume_inference_endpoint = api.resume_inference_endpoint
+scale_to_zero_inference_endpoint = api.scale_to_zero_inference_endpoint
+create_inference_endpoint_from_catalog = api.create_inference_endpoint_from_catalog
+list_inference_catalog = api.list_inference_catalog
+
+# Collections API
+get_collection = api.get_collection
+list_collections = api.list_collections
+create_collection = api.create_collection
+update_collection_metadata = api.update_collection_metadata
+delete_collection = api.delete_collection
+add_collection_item = api.add_collection_item
+update_collection_item = api.update_collection_item
+delete_collection_item = api.delete_collection_item
+delete_collection_item = api.delete_collection_item
+
+# Access requests API
+list_pending_access_requests = api.list_pending_access_requests
+list_accepted_access_requests = api.list_accepted_access_requests
+list_rejected_access_requests = api.list_rejected_access_requests
+cancel_access_request = api.cancel_access_request
+accept_access_request = api.accept_access_request
+reject_access_request = api.reject_access_request
+grant_access = api.grant_access
+
+# Webhooks API
+create_webhook = api.create_webhook
+disable_webhook = api.disable_webhook
+delete_webhook = api.delete_webhook
+enable_webhook = api.enable_webhook
+get_webhook = api.get_webhook
+list_webhooks = api.list_webhooks
+update_webhook = api.update_webhook
+
+
+# User API
+get_user_overview = api.get_user_overview
+get_organization_overview = api.get_organization_overview
+list_organization_members = api.list_organization_members
+list_user_followers = api.list_user_followers
+list_user_following = api.list_user_following
+
+# Jobs API
+run_job = api.run_job
+fetch_job_logs = api.fetch_job_logs
+list_jobs = api.list_jobs
+inspect_job = api.inspect_job
+cancel_job = api.cancel_job
+run_uv_job = api.run_uv_job
+create_scheduled_job = api.create_scheduled_job
+list_scheduled_jobs = api.list_scheduled_jobs
+inspect_scheduled_job = api.inspect_scheduled_job
+delete_scheduled_job = api.delete_scheduled_job
+suspend_scheduled_job = api.suspend_scheduled_job
+resume_scheduled_job = api.resume_scheduled_job
+create_scheduled_uv_job = api.create_scheduled_uv_job
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py
new file mode 100644
index 0000000000000000000000000000000000000000..a29d38a92ee4ddc9348e2575769ca36de6ceab08
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py
@@ -0,0 +1,1150 @@
+import os
+import re
+import tempfile
+from collections import deque
+from dataclasses import dataclass, field
+from datetime import datetime
+from itertools import chain
+from pathlib import Path
+from typing import Any, Dict, Iterator, List, NoReturn, Optional, Tuple, Union
+from urllib.parse import quote, unquote
+
+import fsspec
+from fsspec.callbacks import _DEFAULT_CALLBACK, NoOpCallback, TqdmCallback
+from fsspec.utils import isfilelike
+from requests import Response
+
+from . import constants
+from ._commit_api import CommitOperationCopy, CommitOperationDelete
+from .errors import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError
+from .file_download import hf_hub_url, http_get
+from .hf_api import HfApi, LastCommitInfo, RepoFile
+from .utils import HFValidationError, hf_raise_for_status, http_backoff
+
+
+# Regex used to match special revisions with "/" in them (see #1710)
+SPECIAL_REFS_REVISION_REGEX = re.compile(
+ r"""
+ (^refs\/convert\/\w+) # `refs/convert/parquet` revisions
+ |
+ (^refs\/pr\/\d+) # PR revisions
+ """,
+ re.VERBOSE,
+)
+
+
+@dataclass
+class HfFileSystemResolvedPath:
+ """Data structure containing information about a resolved Hugging Face file system path."""
+
+ repo_type: str
+ repo_id: str
+ revision: str
+ path_in_repo: str
+ # The part placed after '@' in the initial path. It can be a quoted or unquoted refs revision.
+ # Used to reconstruct the unresolved path to return to the user.
+ _raw_revision: Optional[str] = field(default=None, repr=False)
+
+ def unresolve(self) -> str:
+ repo_path = constants.REPO_TYPES_URL_PREFIXES.get(self.repo_type, "") + self.repo_id
+ if self._raw_revision:
+ return f"{repo_path}@{self._raw_revision}/{self.path_in_repo}".rstrip("/")
+ elif self.revision != constants.DEFAULT_REVISION:
+ return f"{repo_path}@{safe_revision(self.revision)}/{self.path_in_repo}".rstrip("/")
+ else:
+ return f"{repo_path}/{self.path_in_repo}".rstrip("/")
+
+
+class HfFileSystem(fsspec.AbstractFileSystem):
+ """
+ Access a remote Hugging Face Hub repository as if were a local file system.
+
+ > [!WARNING]
+ > [`HfFileSystem`] provides fsspec compatibility, which is useful for libraries that require it (e.g., reading
+ > Hugging Face datasets directly with `pandas`). However, it introduces additional overhead due to this compatibility
+ > layer. For better performance and reliability, it's recommended to use `HfApi` methods when possible.
+
+ Args:
+ token (`str` or `bool`, *optional*):
+ A valid user access token (string). Defaults to the locally saved
+ token, which is the recommended method for authentication (see
+ https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+ To disable authentication, pass `False`.
+ endpoint (`str`, *optional*):
+ Endpoint of the Hub. Defaults to .
+ Usage:
+
+ ```python
+ >>> from huggingface_hub import HfFileSystem
+
+ >>> fs = HfFileSystem()
+
+ >>> # List files
+ >>> fs.glob("my-username/my-model/*.bin")
+ ['my-username/my-model/pytorch_model.bin']
+ >>> fs.ls("datasets/my-username/my-dataset", detail=False)
+ ['datasets/my-username/my-dataset/.gitattributes', 'datasets/my-username/my-dataset/README.md', 'datasets/my-username/my-dataset/data.json']
+
+ >>> # Read/write files
+ >>> with fs.open("my-username/my-model/pytorch_model.bin") as f:
+ ... data = f.read()
+ >>> with fs.open("my-username/my-model/pytorch_model.bin", "wb") as f:
+ ... f.write(data)
+ ```
+ """
+
+ root_marker = ""
+ protocol = "hf"
+
+ def __init__(
+ self,
+ *args,
+ endpoint: Optional[str] = None,
+ token: Union[bool, str, None] = None,
+ block_size: Optional[int] = None,
+ **storage_options,
+ ):
+ super().__init__(*args, **storage_options)
+ self.endpoint = endpoint or constants.ENDPOINT
+ self.token = token
+ self._api = HfApi(endpoint=endpoint, token=token)
+ self.block_size = block_size
+ # Maps (repo_type, repo_id, revision) to a 2-tuple with:
+ # * the 1st element indicating whether the repositoy and the revision exist
+ # * the 2nd element being the exception raised if the repository or revision doesn't exist
+ self._repo_and_revision_exists_cache: Dict[
+ Tuple[str, str, Optional[str]], Tuple[bool, Optional[Exception]]
+ ] = {}
+ # Maps parent directory path to path infos
+ self.dircache: Dict[str, List[Dict[str, Any]]] = {}
+
+ def _repo_and_revision_exist(
+ self, repo_type: str, repo_id: str, revision: Optional[str]
+ ) -> Tuple[bool, Optional[Exception]]:
+ if (repo_type, repo_id, revision) not in self._repo_and_revision_exists_cache:
+ try:
+ self._api.repo_info(
+ repo_id, revision=revision, repo_type=repo_type, timeout=constants.HF_HUB_ETAG_TIMEOUT
+ )
+ except (RepositoryNotFoundError, HFValidationError) as e:
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = False, e
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = False, e
+ except RevisionNotFoundError as e:
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = False, e
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = True, None
+ else:
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = True, None
+ self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = True, None
+ return self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)]
+
+ def resolve_path(self, path: str, revision: Optional[str] = None) -> HfFileSystemResolvedPath:
+ """
+ Resolve a Hugging Face file system path into its components.
+
+ Args:
+ path (`str`):
+ Path to resolve.
+ revision (`str`, *optional*):
+ The revision of the repo to resolve. Defaults to the revision specified in the path.
+
+ Returns:
+ [`HfFileSystemResolvedPath`]: Resolved path information containing `repo_type`, `repo_id`, `revision` and `path_in_repo`.
+
+ Raises:
+ `ValueError`:
+ If path contains conflicting revision information.
+ `NotImplementedError`:
+ If trying to list repositories.
+ """
+
+ def _align_revision_in_path_with_revision(
+ revision_in_path: Optional[str], revision: Optional[str]
+ ) -> Optional[str]:
+ if revision is not None:
+ if revision_in_path is not None and revision_in_path != revision:
+ raise ValueError(
+ f'Revision specified in path ("{revision_in_path}") and in `revision` argument ("{revision}")'
+ " are not the same."
+ )
+ else:
+ revision = revision_in_path
+ return revision
+
+ path = self._strip_protocol(path)
+ if not path:
+ # can't list repositories at root
+ raise NotImplementedError("Access to repositories lists is not implemented.")
+ elif path.split("/")[0] + "/" in constants.REPO_TYPES_URL_PREFIXES.values():
+ if "/" not in path:
+ # can't list repositories at the repository type level
+ raise NotImplementedError("Access to repositories lists is not implemented.")
+ repo_type, path = path.split("/", 1)
+ repo_type = constants.REPO_TYPES_MAPPING[repo_type]
+ else:
+ repo_type = constants.REPO_TYPE_MODEL
+ if path.count("/") > 0:
+ if "@" in path:
+ repo_id, revision_in_path = path.split("@", 1)
+ if "/" in revision_in_path:
+ match = SPECIAL_REFS_REVISION_REGEX.search(revision_in_path)
+ if match is not None and revision in (None, match.group()):
+ # Handle `refs/convert/parquet` and PR revisions separately
+ path_in_repo = SPECIAL_REFS_REVISION_REGEX.sub("", revision_in_path).lstrip("/")
+ revision_in_path = match.group()
+ else:
+ revision_in_path, path_in_repo = revision_in_path.split("/", 1)
+ else:
+ path_in_repo = ""
+ revision = _align_revision_in_path_with_revision(unquote(revision_in_path), revision)
+ repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
+ if not repo_and_revision_exist:
+ _raise_file_not_found(path, err)
+ else:
+ revision_in_path = None
+ repo_id_with_namespace = "/".join(path.split("/")[:2])
+ path_in_repo_with_namespace = "/".join(path.split("/")[2:])
+ repo_id_without_namespace = path.split("/")[0]
+ path_in_repo_without_namespace = "/".join(path.split("/")[1:])
+ repo_id = repo_id_with_namespace
+ path_in_repo = path_in_repo_with_namespace
+ repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
+ if not repo_and_revision_exist:
+ if isinstance(err, (RepositoryNotFoundError, HFValidationError)):
+ repo_id = repo_id_without_namespace
+ path_in_repo = path_in_repo_without_namespace
+ repo_and_revision_exist, _ = self._repo_and_revision_exist(repo_type, repo_id, revision)
+ if not repo_and_revision_exist:
+ _raise_file_not_found(path, err)
+ else:
+ _raise_file_not_found(path, err)
+ else:
+ repo_id = path
+ path_in_repo = ""
+ if "@" in path:
+ repo_id, revision_in_path = path.split("@", 1)
+ revision = _align_revision_in_path_with_revision(unquote(revision_in_path), revision)
+ else:
+ revision_in_path = None
+ repo_and_revision_exist, _ = self._repo_and_revision_exist(repo_type, repo_id, revision)
+ if not repo_and_revision_exist:
+ raise NotImplementedError("Access to repositories lists is not implemented.")
+
+ revision = revision if revision is not None else constants.DEFAULT_REVISION
+ return HfFileSystemResolvedPath(repo_type, repo_id, revision, path_in_repo, _raw_revision=revision_in_path)
+
+ def invalidate_cache(self, path: Optional[str] = None) -> None:
+ """
+ Clear the cache for a given path.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.invalidate_cache).
+
+ Args:
+ path (`str`, *optional*):
+ Path to clear from cache. If not provided, clear the entire cache.
+
+ """
+ if not path:
+ self.dircache.clear()
+ self._repo_and_revision_exists_cache.clear()
+ else:
+ resolved_path = self.resolve_path(path)
+ path = resolved_path.unresolve()
+ while path:
+ self.dircache.pop(path, None)
+ path = self._parent(path)
+
+ # Only clear repo cache if path is to repo root
+ if not resolved_path.path_in_repo:
+ self._repo_and_revision_exists_cache.pop((resolved_path.repo_type, resolved_path.repo_id, None), None)
+ self._repo_and_revision_exists_cache.pop(
+ (resolved_path.repo_type, resolved_path.repo_id, resolved_path.revision), None
+ )
+
+ def _open(
+ self,
+ path: str,
+ mode: str = "rb",
+ revision: Optional[str] = None,
+ block_size: Optional[int] = None,
+ **kwargs,
+ ) -> "HfFileSystemFile":
+ block_size = block_size if block_size is not None else self.block_size
+ if block_size is not None:
+ kwargs["block_size"] = block_size
+ if "a" in mode:
+ raise NotImplementedError("Appending to remote files is not yet supported.")
+ if block_size == 0:
+ return HfFileSystemStreamFile(self, path, mode=mode, revision=revision, **kwargs)
+ else:
+ return HfFileSystemFile(self, path, mode=mode, revision=revision, **kwargs)
+
+ def _rm(self, path: str, revision: Optional[str] = None, **kwargs) -> None:
+ resolved_path = self.resolve_path(path, revision=revision)
+ self._api.delete_file(
+ path_in_repo=resolved_path.path_in_repo,
+ repo_id=resolved_path.repo_id,
+ token=self.token,
+ repo_type=resolved_path.repo_type,
+ revision=resolved_path.revision,
+ commit_message=kwargs.get("commit_message"),
+ commit_description=kwargs.get("commit_description"),
+ )
+ self.invalidate_cache(path=resolved_path.unresolve())
+
+ def rm(
+ self,
+ path: str,
+ recursive: bool = False,
+ maxdepth: Optional[int] = None,
+ revision: Optional[str] = None,
+ **kwargs,
+ ) -> None:
+ """
+ Delete files from a repository.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.rm).
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.delete_file()` for better performance.
+
+ Args:
+ path (`str`):
+ Path to delete.
+ recursive (`bool`, *optional*):
+ If True, delete directory and all its contents. Defaults to False.
+ maxdepth (`int`, *optional*):
+ Maximum number of subdirectories to visit when deleting recursively.
+ revision (`str`, *optional*):
+ The git revision to delete from.
+
+ """
+ resolved_path = self.resolve_path(path, revision=revision)
+ paths = self.expand_path(path, recursive=recursive, maxdepth=maxdepth, revision=revision)
+ paths_in_repo = [self.resolve_path(path).path_in_repo for path in paths if not self.isdir(path)]
+ operations = [CommitOperationDelete(path_in_repo=path_in_repo) for path_in_repo in paths_in_repo]
+ commit_message = f"Delete {path} "
+ commit_message += "recursively " if recursive else ""
+ commit_message += f"up to depth {maxdepth} " if maxdepth is not None else ""
+ # TODO: use `commit_description` to list all the deleted paths?
+ self._api.create_commit(
+ repo_id=resolved_path.repo_id,
+ repo_type=resolved_path.repo_type,
+ token=self.token,
+ operations=operations,
+ revision=resolved_path.revision,
+ commit_message=kwargs.get("commit_message", commit_message),
+ commit_description=kwargs.get("commit_description"),
+ )
+ self.invalidate_cache(path=resolved_path.unresolve())
+
+ def ls(
+ self, path: str, detail: bool = True, refresh: bool = False, revision: Optional[str] = None, **kwargs
+ ) -> List[Union[str, Dict[str, Any]]]:
+ """
+ List the contents of a directory.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.ls).
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.list_repo_tree()` for better performance.
+
+ Args:
+ path (`str`):
+ Path to the directory.
+ detail (`bool`, *optional*):
+ If True, returns a list of dictionaries containing file information. If False,
+ returns a list of file paths. Defaults to True.
+ refresh (`bool`, *optional*):
+ If True, bypass the cache and fetch the latest data. Defaults to False.
+ revision (`str`, *optional*):
+ The git revision to list from.
+
+ Returns:
+ `List[Union[str, Dict[str, Any]]]`: List of file paths (if detail=False) or list of file information
+ dictionaries (if detail=True).
+ """
+ resolved_path = self.resolve_path(path, revision=revision)
+ path = resolved_path.unresolve()
+ try:
+ out = self._ls_tree(path, refresh=refresh, revision=revision, **kwargs)
+ except EntryNotFoundError:
+ # Path could be a file
+ if not resolved_path.path_in_repo:
+ _raise_file_not_found(path, None)
+ out = self._ls_tree(self._parent(path), refresh=refresh, revision=revision, **kwargs)
+ out = [o for o in out if o["name"] == path]
+ if len(out) == 0:
+ _raise_file_not_found(path, None)
+ return out if detail else [o["name"] for o in out]
+
+ def _ls_tree(
+ self,
+ path: str,
+ recursive: bool = False,
+ refresh: bool = False,
+ revision: Optional[str] = None,
+ expand_info: bool = False,
+ maxdepth: Optional[int] = None,
+ ):
+ resolved_path = self.resolve_path(path, revision=revision)
+ path = resolved_path.unresolve()
+ root_path = HfFileSystemResolvedPath(
+ resolved_path.repo_type,
+ resolved_path.repo_id,
+ resolved_path.revision,
+ path_in_repo="",
+ _raw_revision=resolved_path._raw_revision,
+ ).unresolve()
+
+ out = []
+ if path in self.dircache and not refresh:
+ cached_path_infos = self.dircache[path]
+ out.extend(cached_path_infos)
+ dirs_not_in_dircache = []
+ if recursive:
+ # Use BFS to traverse the cache and build the "recursive "output
+ # (The Hub uses a so-called "tree first" strategy for the tree endpoint but we sort the output to follow the spec so the result is (eventually) the same)
+ depth = 2
+ dirs_to_visit = deque(
+ [(depth, path_info) for path_info in cached_path_infos if path_info["type"] == "directory"]
+ )
+ while dirs_to_visit:
+ depth, dir_info = dirs_to_visit.popleft()
+ if maxdepth is None or depth <= maxdepth:
+ if dir_info["name"] not in self.dircache:
+ dirs_not_in_dircache.append(dir_info["name"])
+ else:
+ cached_path_infos = self.dircache[dir_info["name"]]
+ out.extend(cached_path_infos)
+ dirs_to_visit.extend(
+ [
+ (depth + 1, path_info)
+ for path_info in cached_path_infos
+ if path_info["type"] == "directory"
+ ]
+ )
+
+ dirs_not_expanded = []
+ if expand_info:
+ # Check if there are directories with non-expanded entries
+ dirs_not_expanded = [self._parent(o["name"]) for o in out if o["last_commit"] is None]
+
+ if (recursive and dirs_not_in_dircache) or (expand_info and dirs_not_expanded):
+ # If the dircache is incomplete, find the common path of the missing and non-expanded entries
+ # and extend the output with the result of `_ls_tree(common_path, recursive=True)`
+ common_prefix = os.path.commonprefix(dirs_not_in_dircache + dirs_not_expanded)
+ # Get the parent directory if the common prefix itself is not a directory
+ common_path = (
+ common_prefix.rstrip("/")
+ if common_prefix.endswith("/")
+ or common_prefix == root_path
+ or common_prefix in chain(dirs_not_in_dircache, dirs_not_expanded)
+ else self._parent(common_prefix)
+ )
+ if maxdepth is not None:
+ common_path_depth = common_path[len(path) :].count("/")
+ maxdepth -= common_path_depth
+ out = [o for o in out if not o["name"].startswith(common_path + "/")]
+ for cached_path in list(self.dircache):
+ if cached_path.startswith(common_path + "/"):
+ self.dircache.pop(cached_path, None)
+ self.dircache.pop(common_path, None)
+ out.extend(
+ self._ls_tree(
+ common_path,
+ recursive=recursive,
+ refresh=True,
+ revision=revision,
+ expand_info=expand_info,
+ maxdepth=maxdepth,
+ )
+ )
+ else:
+ tree = self._api.list_repo_tree(
+ resolved_path.repo_id,
+ resolved_path.path_in_repo,
+ recursive=recursive,
+ expand=expand_info,
+ revision=resolved_path.revision,
+ repo_type=resolved_path.repo_type,
+ )
+ for path_info in tree:
+ cache_path = root_path + "/" + path_info.path
+ if isinstance(path_info, RepoFile):
+ cache_path_info = {
+ "name": cache_path,
+ "size": path_info.size,
+ "type": "file",
+ "blob_id": path_info.blob_id,
+ "lfs": path_info.lfs,
+ "last_commit": path_info.last_commit,
+ "security": path_info.security,
+ }
+ else:
+ cache_path_info = {
+ "name": cache_path,
+ "size": 0,
+ "type": "directory",
+ "tree_id": path_info.tree_id,
+ "last_commit": path_info.last_commit,
+ }
+ parent_path = self._parent(cache_path_info["name"])
+ self.dircache.setdefault(parent_path, []).append(cache_path_info)
+ depth = cache_path[len(path) :].count("/")
+ if maxdepth is None or depth <= maxdepth:
+ out.append(cache_path_info)
+ return out
+
+ def walk(self, path: str, *args, **kwargs) -> Iterator[Tuple[str, List[str], List[str]]]:
+ """
+ Return all files below the given path.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.walk).
+
+ Args:
+ path (`str`):
+ Root path to list files from.
+
+ Returns:
+ `Iterator[Tuple[str, List[str], List[str]]]`: An iterator of (path, list of directory names, list of file names) tuples.
+ """
+ path = self.resolve_path(path, revision=kwargs.get("revision")).unresolve()
+ yield from super().walk(path, *args, **kwargs)
+
+ def glob(self, path: str, **kwargs) -> List[str]:
+ """
+ Find files by glob-matching.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.glob).
+
+ Args:
+ path (`str`):
+ Path pattern to match.
+
+ Returns:
+ `List[str]`: List of paths matching the pattern.
+ """
+ path = self.resolve_path(path, revision=kwargs.get("revision")).unresolve()
+ return super().glob(path, **kwargs)
+
+ def find(
+ self,
+ path: str,
+ maxdepth: Optional[int] = None,
+ withdirs: bool = False,
+ detail: bool = False,
+ refresh: bool = False,
+ revision: Optional[str] = None,
+ **kwargs,
+ ) -> Union[List[str], Dict[str, Dict[str, Any]]]:
+ """
+ List all files below path.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.find).
+
+ Args:
+ path (`str`):
+ Root path to list files from.
+ maxdepth (`int`, *optional*):
+ Maximum depth to descend into subdirectories.
+ withdirs (`bool`, *optional*):
+ Include directory paths in the output. Defaults to False.
+ detail (`bool`, *optional*):
+ If True, returns a dict mapping paths to file information. Defaults to False.
+ refresh (`bool`, *optional*):
+ If True, bypass the cache and fetch the latest data. Defaults to False.
+ revision (`str`, *optional*):
+ The git revision to list from.
+
+ Returns:
+ `Union[List[str], Dict[str, Dict[str, Any]]]`: List of paths or dict of file information.
+ """
+ if maxdepth is not None and maxdepth < 1:
+ raise ValueError("maxdepth must be at least 1")
+ resolved_path = self.resolve_path(path, revision=revision)
+ path = resolved_path.unresolve()
+ try:
+ out = self._ls_tree(
+ path, recursive=True, refresh=refresh, revision=resolved_path.revision, maxdepth=maxdepth, **kwargs
+ )
+ except EntryNotFoundError:
+ # Path could be a file
+ try:
+ if self.info(path, revision=revision, **kwargs)["type"] == "file":
+ out = {path: {}}
+ else:
+ out = {}
+ except FileNotFoundError:
+ out = {}
+ else:
+ if not withdirs:
+ out = [o for o in out if o["type"] != "directory"]
+ else:
+ # If `withdirs=True`, include the directory itself to be consistent with the spec
+ path_info = self.info(path, revision=resolved_path.revision, **kwargs)
+ out = [path_info] + out if path_info["type"] == "directory" else out
+ out = {o["name"]: o for o in out}
+ names = sorted(out)
+ if not detail:
+ return names
+ else:
+ return {name: out[name] for name in names}
+
+ def cp_file(self, path1: str, path2: str, revision: Optional[str] = None, **kwargs) -> None:
+ """
+ Copy a file within or between repositories.
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.upload_file()` for better performance.
+
+ Args:
+ path1 (`str`):
+ Source path to copy from.
+ path2 (`str`):
+ Destination path to copy to.
+ revision (`str`, *optional*):
+ The git revision to copy from.
+
+ """
+ resolved_path1 = self.resolve_path(path1, revision=revision)
+ resolved_path2 = self.resolve_path(path2, revision=revision)
+
+ same_repo = (
+ resolved_path1.repo_type == resolved_path2.repo_type and resolved_path1.repo_id == resolved_path2.repo_id
+ )
+
+ if same_repo:
+ commit_message = f"Copy {path1} to {path2}"
+ self._api.create_commit(
+ repo_id=resolved_path1.repo_id,
+ repo_type=resolved_path1.repo_type,
+ revision=resolved_path2.revision,
+ commit_message=kwargs.get("commit_message", commit_message),
+ commit_description=kwargs.get("commit_description", ""),
+ operations=[
+ CommitOperationCopy(
+ src_path_in_repo=resolved_path1.path_in_repo,
+ path_in_repo=resolved_path2.path_in_repo,
+ src_revision=resolved_path1.revision,
+ )
+ ],
+ )
+ else:
+ with self.open(path1, "rb", revision=resolved_path1.revision) as f:
+ content = f.read()
+ commit_message = f"Copy {path1} to {path2}"
+ self._api.upload_file(
+ path_or_fileobj=content,
+ path_in_repo=resolved_path2.path_in_repo,
+ repo_id=resolved_path2.repo_id,
+ token=self.token,
+ repo_type=resolved_path2.repo_type,
+ revision=resolved_path2.revision,
+ commit_message=kwargs.get("commit_message", commit_message),
+ commit_description=kwargs.get("commit_description"),
+ )
+ self.invalidate_cache(path=resolved_path1.unresolve())
+ self.invalidate_cache(path=resolved_path2.unresolve())
+
+ def modified(self, path: str, **kwargs) -> datetime:
+ """
+ Get the last modified time of a file.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.modified).
+
+ Args:
+ path (`str`):
+ Path to the file.
+
+ Returns:
+ `datetime`: Last commit date of the file.
+ """
+ info = self.info(path, **{**kwargs, "expand_info": True})
+ return info["last_commit"]["date"]
+
+ def info(self, path: str, refresh: bool = False, revision: Optional[str] = None, **kwargs) -> Dict[str, Any]:
+ """
+ Get information about a file or directory.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.info).
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.get_paths_info()` or `HfApi.repo_info()` for better performance.
+
+ Args:
+ path (`str`):
+ Path to get info for.
+ refresh (`bool`, *optional*):
+ If True, bypass the cache and fetch the latest data. Defaults to False.
+ revision (`str`, *optional*):
+ The git revision to get info from.
+
+ Returns:
+ `Dict[str, Any]`: Dictionary containing file information (type, size, commit info, etc.).
+
+ """
+ resolved_path = self.resolve_path(path, revision=revision)
+ path = resolved_path.unresolve()
+ expand_info = kwargs.get(
+ "expand_info", False
+ ) # don't expose it as a parameter in the public API to follow the spec
+ if not resolved_path.path_in_repo:
+ # Path is the root directory
+ out = {
+ "name": path,
+ "size": 0,
+ "type": "directory",
+ "last_commit": None,
+ }
+ if expand_info:
+ last_commit = self._api.list_repo_commits(
+ resolved_path.repo_id, repo_type=resolved_path.repo_type, revision=resolved_path.revision
+ )[-1]
+ out = {
+ **out,
+ "tree_id": None, # TODO: tree_id of the root directory?
+ "last_commit": LastCommitInfo(
+ oid=last_commit.commit_id, title=last_commit.title, date=last_commit.created_at
+ ),
+ }
+ else:
+ out = None
+ parent_path = self._parent(path)
+ if not expand_info and parent_path not in self.dircache:
+ # Fill the cache with cheap call
+ self.ls(parent_path)
+ if parent_path in self.dircache:
+ # Check if the path is in the cache
+ out1 = [o for o in self.dircache[parent_path] if o["name"] == path]
+ if not out1:
+ _raise_file_not_found(path, None)
+ out = out1[0]
+ if refresh or out is None or (expand_info and out and out["last_commit"] is None):
+ paths_info = self._api.get_paths_info(
+ resolved_path.repo_id,
+ resolved_path.path_in_repo,
+ expand=expand_info,
+ revision=resolved_path.revision,
+ repo_type=resolved_path.repo_type,
+ )
+ if not paths_info:
+ _raise_file_not_found(path, None)
+ path_info = paths_info[0]
+ root_path = HfFileSystemResolvedPath(
+ resolved_path.repo_type,
+ resolved_path.repo_id,
+ resolved_path.revision,
+ path_in_repo="",
+ _raw_revision=resolved_path._raw_revision,
+ ).unresolve()
+ if isinstance(path_info, RepoFile):
+ out = {
+ "name": root_path + "/" + path_info.path,
+ "size": path_info.size,
+ "type": "file",
+ "blob_id": path_info.blob_id,
+ "lfs": path_info.lfs,
+ "last_commit": path_info.last_commit,
+ "security": path_info.security,
+ }
+ else:
+ out = {
+ "name": root_path + "/" + path_info.path,
+ "size": 0,
+ "type": "directory",
+ "tree_id": path_info.tree_id,
+ "last_commit": path_info.last_commit,
+ }
+ if not expand_info:
+ out = {k: out[k] for k in ["name", "size", "type"]}
+ assert out is not None
+ return out
+
+ def exists(self, path, **kwargs):
+ """
+ Check if a file exists.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.exists).
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.file_exists()` for better performance.
+
+ Args:
+ path (`str`):
+ Path to check.
+
+ Returns:
+ `bool`: True if file exists, False otherwise.
+ """
+ try:
+ if kwargs.get("refresh", False):
+ self.invalidate_cache(path)
+
+ self.info(path, **kwargs)
+ return True
+ except: # noqa: E722
+ return False
+
+ def isdir(self, path):
+ """
+ Check if a path is a directory.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.isdir).
+
+ Args:
+ path (`str`):
+ Path to check.
+
+ Returns:
+ `bool`: True if path is a directory, False otherwise.
+ """
+ try:
+ return self.info(path)["type"] == "directory"
+ except OSError:
+ return False
+
+ def isfile(self, path):
+ """
+ Check if a path is a file.
+
+ For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.isfile).
+
+ Args:
+ path (`str`):
+ Path to check.
+
+ Returns:
+ `bool`: True if path is a file, False otherwise.
+ """
+ try:
+ return self.info(path)["type"] == "file"
+ except: # noqa: E722
+ return False
+
+ def url(self, path: str) -> str:
+ """
+ Get the HTTP URL of the given path.
+
+ Args:
+ path (`str`):
+ Path to get URL for.
+
+ Returns:
+ `str`: HTTP URL to access the file or directory on the Hub.
+ """
+ resolved_path = self.resolve_path(path)
+ url = hf_hub_url(
+ resolved_path.repo_id,
+ resolved_path.path_in_repo,
+ repo_type=resolved_path.repo_type,
+ revision=resolved_path.revision,
+ endpoint=self.endpoint,
+ )
+ if self.isdir(path):
+ url = url.replace("/resolve/", "/tree/", 1)
+ return url
+
+ def get_file(self, rpath, lpath, callback=_DEFAULT_CALLBACK, outfile=None, **kwargs) -> None:
+ """
+ Copy single remote file to local.
+
+ > [!WARNING]
+ > Note: When possible, use `HfApi.hf_hub_download()` for better performance.
+
+ Args:
+ rpath (`str`):
+ Remote path to download from.
+ lpath (`str`):
+ Local path to download to.
+ callback (`Callback`, *optional*):
+ Optional callback to track download progress. Defaults to no callback.
+ outfile (`IO`, *optional*):
+ Optional file-like object to write to. If provided, `lpath` is ignored.
+
+ """
+ revision = kwargs.get("revision")
+ unhandled_kwargs = set(kwargs.keys()) - {"revision"}
+ if not isinstance(callback, (NoOpCallback, TqdmCallback)) or len(unhandled_kwargs) > 0:
+ # for now, let's not handle custom callbacks
+ # and let's not handle custom kwargs
+ return super().get_file(rpath, lpath, callback=callback, outfile=outfile, **kwargs)
+
+ # Taken from https://github.com/fsspec/filesystem_spec/blob/47b445ae4c284a82dd15e0287b1ffc410e8fc470/fsspec/spec.py#L883
+ if isfilelike(lpath):
+ outfile = lpath
+ elif self.isdir(rpath):
+ os.makedirs(lpath, exist_ok=True)
+ return None
+
+ if isinstance(lpath, (str, Path)): # otherwise, let's assume it's a file-like object
+ os.makedirs(os.path.dirname(lpath), exist_ok=True)
+
+ # Open file if not already open
+ close_file = False
+ if outfile is None:
+ outfile = open(lpath, "wb")
+ close_file = True
+ initial_pos = outfile.tell()
+
+ # Custom implementation of `get_file` to use `http_get`.
+ resolve_remote_path = self.resolve_path(rpath, revision=revision)
+ expected_size = self.info(rpath, revision=revision)["size"]
+ callback.set_size(expected_size)
+ try:
+ http_get(
+ url=hf_hub_url(
+ repo_id=resolve_remote_path.repo_id,
+ revision=resolve_remote_path.revision,
+ filename=resolve_remote_path.path_in_repo,
+ repo_type=resolve_remote_path.repo_type,
+ endpoint=self.endpoint,
+ ),
+ temp_file=outfile, # type: ignore[arg-type]
+ displayed_filename=rpath,
+ expected_size=expected_size,
+ resume_size=0,
+ headers=self._api._build_hf_headers(),
+ _tqdm_bar=callback.tqdm if isinstance(callback, TqdmCallback) else None,
+ )
+ outfile.seek(initial_pos)
+ finally:
+ # Close file only if we opened it ourselves
+ if close_file:
+ outfile.close()
+
+ @property
+ def transaction(self):
+ """A context within which files are committed together upon exit
+
+ Requires the file class to implement `.commit()` and `.discard()`
+ for the normal and exception cases.
+ """
+ # Taken from https://github.com/fsspec/filesystem_spec/blob/3fbb6fee33b46cccb015607630843dea049d3243/fsspec/spec.py#L231
+ # See https://github.com/huggingface/huggingface_hub/issues/1733
+ raise NotImplementedError("Transactional commits are not supported.")
+
+ def start_transaction(self):
+ """Begin write transaction for deferring files, non-context version"""
+ # Taken from https://github.com/fsspec/filesystem_spec/blob/3fbb6fee33b46cccb015607630843dea049d3243/fsspec/spec.py#L241
+ # See https://github.com/huggingface/huggingface_hub/issues/1733
+ raise NotImplementedError("Transactional commits are not supported.")
+
+ def __reduce__(self):
+ # re-populate the instance cache at HfFileSystem._cache and re-populate the cache attributes of every instance
+ return make_instance, (
+ type(self),
+ self.storage_args,
+ self.storage_options,
+ {
+ "dircache": self.dircache,
+ "_repo_and_revision_exists_cache": self._repo_and_revision_exists_cache,
+ },
+ )
+
+
+class HfFileSystemFile(fsspec.spec.AbstractBufferedFile):
+ def __init__(self, fs: HfFileSystem, path: str, revision: Optional[str] = None, **kwargs):
+ try:
+ self.resolved_path = fs.resolve_path(path, revision=revision)
+ except FileNotFoundError as e:
+ if "w" in kwargs.get("mode", ""):
+ raise FileNotFoundError(
+ f"{e}.\nMake sure the repository and revision exist before writing data."
+ ) from e
+ raise
+ super().__init__(fs, self.resolved_path.unresolve(), **kwargs)
+ self.fs: HfFileSystem
+
+ def __del__(self):
+ if not hasattr(self, "resolved_path"):
+ # Means that the constructor failed. Nothing to do.
+ return
+ return super().__del__()
+
+ def _fetch_range(self, start: int, end: int) -> bytes:
+ headers = {
+ "range": f"bytes={start}-{end - 1}",
+ **self.fs._api._build_hf_headers(),
+ }
+ url = hf_hub_url(
+ repo_id=self.resolved_path.repo_id,
+ revision=self.resolved_path.revision,
+ filename=self.resolved_path.path_in_repo,
+ repo_type=self.resolved_path.repo_type,
+ endpoint=self.fs.endpoint,
+ )
+ r = http_backoff("GET", url, headers=headers, timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT)
+ hf_raise_for_status(r)
+ return r.content
+
+ def _initiate_upload(self) -> None:
+ self.temp_file = tempfile.NamedTemporaryFile(prefix="hffs-", delete=False)
+
+ def _upload_chunk(self, final: bool = False) -> None:
+ self.buffer.seek(0)
+ block = self.buffer.read()
+ self.temp_file.write(block)
+ if final:
+ self.temp_file.close()
+ self.fs._api.upload_file(
+ path_or_fileobj=self.temp_file.name,
+ path_in_repo=self.resolved_path.path_in_repo,
+ repo_id=self.resolved_path.repo_id,
+ token=self.fs.token,
+ repo_type=self.resolved_path.repo_type,
+ revision=self.resolved_path.revision,
+ commit_message=self.kwargs.get("commit_message"),
+ commit_description=self.kwargs.get("commit_description"),
+ )
+ os.remove(self.temp_file.name)
+ self.fs.invalidate_cache(
+ path=self.resolved_path.unresolve(),
+ )
+
+ def read(self, length=-1):
+ """Read remote file.
+
+ If `length` is not provided or is -1, the entire file is downloaded and read. On POSIX systems and if
+ `hf_transfer` is not enabled, the file is loaded in memory directly. Otherwise, the file is downloaded to a
+ temporary file and read from there.
+ """
+ if self.mode == "rb" and (length is None or length == -1) and self.loc == 0:
+ with self.fs.open(self.path, "rb", block_size=0) as f: # block_size=0 enables fast streaming
+ out = f.read()
+ self.loc += len(out)
+ return out
+ return super().read(length)
+
+ def url(self) -> str:
+ return self.fs.url(self.path)
+
+
+class HfFileSystemStreamFile(fsspec.spec.AbstractBufferedFile):
+ def __init__(
+ self,
+ fs: HfFileSystem,
+ path: str,
+ mode: str = "rb",
+ revision: Optional[str] = None,
+ block_size: int = 0,
+ cache_type: str = "none",
+ **kwargs,
+ ):
+ if block_size != 0:
+ raise ValueError(f"HfFileSystemStreamFile only supports block_size=0 but got {block_size}")
+ if cache_type != "none":
+ raise ValueError(f"HfFileSystemStreamFile only supports cache_type='none' but got {cache_type}")
+ if "w" in mode:
+ raise ValueError(f"HfFileSystemStreamFile only supports reading but got mode='{mode}'")
+ try:
+ self.resolved_path = fs.resolve_path(path, revision=revision)
+ except FileNotFoundError as e:
+ if "w" in kwargs.get("mode", ""):
+ raise FileNotFoundError(
+ f"{e}.\nMake sure the repository and revision exist before writing data."
+ ) from e
+ # avoid an unnecessary .info() call to instantiate .details
+ self.details = {"name": self.resolved_path.unresolve(), "size": None}
+ super().__init__(
+ fs, self.resolved_path.unresolve(), mode=mode, block_size=block_size, cache_type=cache_type, **kwargs
+ )
+ self.response: Optional[Response] = None
+ self.fs: HfFileSystem
+
+ def seek(self, loc: int, whence: int = 0):
+ if loc == 0 and whence == 1:
+ return
+ if loc == self.loc and whence == 0:
+ return
+ raise ValueError("Cannot seek streaming HF file")
+
+ def read(self, length: int = -1):
+ read_args = (length,) if length >= 0 else ()
+ if self.response is None:
+ url = hf_hub_url(
+ repo_id=self.resolved_path.repo_id,
+ revision=self.resolved_path.revision,
+ filename=self.resolved_path.path_in_repo,
+ repo_type=self.resolved_path.repo_type,
+ endpoint=self.fs.endpoint,
+ )
+ self.response = http_backoff(
+ "GET",
+ url,
+ headers=self.fs._api._build_hf_headers(),
+ stream=True,
+ timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT,
+ )
+ hf_raise_for_status(self.response)
+ try:
+ self.response.raw.decode_content = True
+ out = self.response.raw.read(*read_args)
+ except Exception:
+ self.response.close()
+
+ # Retry by recreating the connection
+ url = hf_hub_url(
+ repo_id=self.resolved_path.repo_id,
+ revision=self.resolved_path.revision,
+ filename=self.resolved_path.path_in_repo,
+ repo_type=self.resolved_path.repo_type,
+ endpoint=self.fs.endpoint,
+ )
+ self.response = http_backoff(
+ "GET",
+ url,
+ headers={"Range": "bytes=%d-" % self.loc, **self.fs._api._build_hf_headers()},
+ stream=True,
+ timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT,
+ )
+ hf_raise_for_status(self.response)
+ try:
+ self.response.raw.decode_content = True
+ out = self.response.raw.read(*read_args)
+ except Exception:
+ self.response.close()
+ raise
+ self.loc += len(out)
+ return out
+
+ def url(self) -> str:
+ return self.fs.url(self.path)
+
+ def __del__(self):
+ if not hasattr(self, "resolved_path"):
+ # Means that the constructor failed. Nothing to do.
+ return
+ return super().__del__()
+
+ def __reduce__(self):
+ return reopen, (self.fs, self.path, self.mode, self.blocksize, self.cache.name)
+
+
+def safe_revision(revision: str) -> str:
+ return revision if SPECIAL_REFS_REVISION_REGEX.match(revision) else safe_quote(revision)
+
+
+def safe_quote(s: str) -> str:
+ return quote(s, safe="")
+
+
+def _raise_file_not_found(path: str, err: Optional[Exception]) -> NoReturn:
+ msg = path
+ if isinstance(err, RepositoryNotFoundError):
+ msg = f"{path} (repository not found)"
+ elif isinstance(err, RevisionNotFoundError):
+ msg = f"{path} (revision not found)"
+ elif isinstance(err, HFValidationError):
+ msg = f"{path} (invalid repository id)"
+ raise FileNotFoundError(msg) from err
+
+
+def reopen(fs: HfFileSystem, path: str, mode: str, block_size: int, cache_type: str):
+ return fs.open(path, mode=mode, block_size=block_size, cache_type=cache_type)
+
+
+def make_instance(cls, args, kwargs, instance_cache_attributes_dict):
+ fs = cls(*args, **kwargs)
+ for attr, cached_value in instance_cache_attributes_dict.items():
+ setattr(fs, attr, cached_value)
+ return fs
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hub_mixin.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hub_mixin.py
new file mode 100644
index 0000000000000000000000000000000000000000..9fa702ceda97318a817cb1a325223e26a78e2710
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/hub_mixin.py
@@ -0,0 +1,853 @@
+import inspect
+import json
+import os
+from dataclasses import Field, asdict, dataclass, is_dataclass
+from pathlib import Path
+from typing import Any, Callable, ClassVar, Dict, List, Optional, Protocol, Tuple, Type, TypeVar, Union
+
+import packaging.version
+
+from . import constants
+from .errors import EntryNotFoundError, HfHubHTTPError
+from .file_download import hf_hub_download
+from .hf_api import HfApi
+from .repocard import ModelCard, ModelCardData
+from .utils import (
+ SoftTemporaryDirectory,
+ is_jsonable,
+ is_safetensors_available,
+ is_simple_optional_type,
+ is_torch_available,
+ logging,
+ unwrap_simple_optional_type,
+ validate_hf_hub_args,
+)
+
+
+if is_torch_available():
+ import torch # type: ignore
+
+if is_safetensors_available():
+ import safetensors
+ from safetensors.torch import load_model as load_model_as_safetensor
+ from safetensors.torch import save_model as save_model_as_safetensor
+
+
+logger = logging.get_logger(__name__)
+
+
+# Type alias for dataclass instances, copied from https://github.com/python/typeshed/blob/9f28171658b9ca6c32a7cb93fbb99fc92b17858b/stdlib/_typeshed/__init__.pyi#L349
+class DataclassInstance(Protocol):
+ __dataclass_fields__: ClassVar[Dict[str, Field]]
+
+
+# Generic variable that is either ModelHubMixin or a subclass thereof
+T = TypeVar("T", bound="ModelHubMixin")
+# Generic variable to represent an args type
+ARGS_T = TypeVar("ARGS_T")
+ENCODER_T = Callable[[ARGS_T], Any]
+DECODER_T = Callable[[Any], ARGS_T]
+CODER_T = Tuple[ENCODER_T, DECODER_T]
+
+
+DEFAULT_MODEL_CARD = """
+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+{{ card_data }}
+---
+
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Code: {{ repo_url | default("[More Information Needed]", true) }}
+- Paper: {{ paper_url | default("[More Information Needed]", true) }}
+- Docs: {{ docs_url | default("[More Information Needed]", true) }}
+"""
+
+
+@dataclass
+class MixinInfo:
+ model_card_template: str
+ model_card_data: ModelCardData
+ docs_url: Optional[str] = None
+ paper_url: Optional[str] = None
+ repo_url: Optional[str] = None
+
+
+class ModelHubMixin:
+ """
+ A generic mixin to integrate ANY machine learning framework with the Hub.
+
+ To integrate your framework, your model class must inherit from this class. Custom logic for saving/loading models
+ have to be overwritten in [`_from_pretrained`] and [`_save_pretrained`]. [`PyTorchModelHubMixin`] is a good example
+ of mixin integration with the Hub. Check out our [integration guide](../guides/integrations) for more instructions.
+
+ When inheriting from [`ModelHubMixin`], you can define class-level attributes. These attributes are not passed to
+ `__init__` but to the class definition itself. This is useful to define metadata about the library integrating
+ [`ModelHubMixin`].
+
+ For more details on how to integrate the mixin with your library, checkout the [integration guide](../guides/integrations).
+
+ Args:
+ repo_url (`str`, *optional*):
+ URL of the library repository. Used to generate model card.
+ paper_url (`str`, *optional*):
+ URL of the library paper. Used to generate model card.
+ docs_url (`str`, *optional*):
+ URL of the library documentation. Used to generate model card.
+ model_card_template (`str`, *optional*):
+ Template of the model card. Used to generate model card. Defaults to a generic template.
+ language (`str` or `List[str]`, *optional*):
+ Language supported by the library. Used to generate model card.
+ library_name (`str`, *optional*):
+ Name of the library integrating ModelHubMixin. Used to generate model card.
+ license (`str`, *optional*):
+ License of the library integrating ModelHubMixin. Used to generate model card.
+ E.g: "apache-2.0"
+ license_name (`str`, *optional*):
+ Name of the library integrating ModelHubMixin. Used to generate model card.
+ Only used if `license` is set to `other`.
+ E.g: "coqui-public-model-license".
+ license_link (`str`, *optional*):
+ URL to the license of the library integrating ModelHubMixin. Used to generate model card.
+ Only used if `license` is set to `other` and `license_name` is set.
+ E.g: "https://coqui.ai/cpml".
+ pipeline_tag (`str`, *optional*):
+ Tag of the pipeline. Used to generate model card. E.g. "text-classification".
+ tags (`List[str]`, *optional*):
+ Tags to be added to the model card. Used to generate model card. E.g. ["computer-vision"]
+ coders (`Dict[Type, Tuple[Callable, Callable]]`, *optional*):
+ Dictionary of custom types and their encoders/decoders. Used to encode/decode arguments that are not
+ jsonable by default. E.g dataclasses, argparse.Namespace, OmegaConf, etc.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub import ModelHubMixin
+
+ # Inherit from ModelHubMixin
+ >>> class MyCustomModel(
+ ... ModelHubMixin,
+ ... library_name="my-library",
+ ... tags=["computer-vision"],
+ ... repo_url="https://github.com/huggingface/my-cool-library",
+ ... paper_url="https://arxiv.org/abs/2304.12244",
+ ... docs_url="https://huggingface.co/docs/my-cool-library",
+ ... # ^ optional metadata to generate model card
+ ... ):
+ ... def __init__(self, size: int = 512, device: str = "cpu"):
+ ... # define how to initialize your model
+ ... super().__init__()
+ ... ...
+ ...
+ ... def _save_pretrained(self, save_directory: Path) -> None:
+ ... # define how to serialize your model
+ ... ...
+ ...
+ ... @classmethod
+ ... def from_pretrained(
+ ... cls: Type[T],
+ ... pretrained_model_name_or_path: Union[str, Path],
+ ... *,
+ ... force_download: bool = False,
+ ... resume_download: Optional[bool] = None,
+ ... proxies: Optional[Dict] = None,
+ ... token: Optional[Union[str, bool]] = None,
+ ... cache_dir: Optional[Union[str, Path]] = None,
+ ... local_files_only: bool = False,
+ ... revision: Optional[str] = None,
+ ... **model_kwargs,
+ ... ) -> T:
+ ... # define how to deserialize your model
+ ... ...
+
+ >>> model = MyCustomModel(size=256, device="gpu")
+
+ # Save model weights to local directory
+ >>> model.save_pretrained("my-awesome-model")
+
+ # Push model weights to the Hub
+ >>> model.push_to_hub("my-awesome-model")
+
+ # Download and initialize weights from the Hub
+ >>> reloaded_model = MyCustomModel.from_pretrained("username/my-awesome-model")
+ >>> reloaded_model.size
+ 256
+
+ # Model card has been correctly populated
+ >>> from huggingface_hub import ModelCard
+ >>> card = ModelCard.load("username/my-awesome-model")
+ >>> card.data.tags
+ ["x-custom-tag", "pytorch_model_hub_mixin", "model_hub_mixin"]
+ >>> card.data.library_name
+ "my-library"
+ ```
+ """
+
+ _hub_mixin_config: Optional[Union[dict, DataclassInstance]] = None
+ # ^ optional config attribute automatically set in `from_pretrained`
+ _hub_mixin_info: MixinInfo
+ # ^ information about the library integrating ModelHubMixin (used to generate model card)
+ _hub_mixin_inject_config: bool # whether `_from_pretrained` expects `config` or not
+ _hub_mixin_init_parameters: Dict[str, inspect.Parameter] # __init__ parameters
+ _hub_mixin_jsonable_default_values: Dict[str, Any] # default values for __init__ parameters
+ _hub_mixin_jsonable_custom_types: Tuple[Type, ...] # custom types that can be encoded/decoded
+ _hub_mixin_coders: Dict[Type, CODER_T] # encoders/decoders for custom types
+ # ^ internal values to handle config
+
+ def __init_subclass__(
+ cls,
+ *,
+ # Generic info for model card
+ repo_url: Optional[str] = None,
+ paper_url: Optional[str] = None,
+ docs_url: Optional[str] = None,
+ # Model card template
+ model_card_template: str = DEFAULT_MODEL_CARD,
+ # Model card metadata
+ language: Optional[List[str]] = None,
+ library_name: Optional[str] = None,
+ license: Optional[str] = None,
+ license_name: Optional[str] = None,
+ license_link: Optional[str] = None,
+ pipeline_tag: Optional[str] = None,
+ tags: Optional[List[str]] = None,
+ # How to encode/decode arguments with custom type into a JSON config?
+ coders: Optional[
+ Dict[Type, CODER_T]
+ # Key is a type.
+ # Value is a tuple (encoder, decoder).
+ # Example: {MyCustomType: (lambda x: x.value, lambda data: MyCustomType(data))}
+ ] = None,
+ ) -> None:
+ """Inspect __init__ signature only once when subclassing + handle modelcard."""
+ super().__init_subclass__()
+
+ # Will be reused when creating modelcard
+ tags = tags or []
+ tags.append("model_hub_mixin")
+
+ # Initialize MixinInfo if not existent
+ info = MixinInfo(model_card_template=model_card_template, model_card_data=ModelCardData())
+
+ # If parent class has a MixinInfo, inherit from it as a copy
+ if hasattr(cls, "_hub_mixin_info"):
+ # Inherit model card template from parent class if not explicitly set
+ if model_card_template == DEFAULT_MODEL_CARD:
+ info.model_card_template = cls._hub_mixin_info.model_card_template
+
+ # Inherit from parent model card data
+ info.model_card_data = ModelCardData(**cls._hub_mixin_info.model_card_data.to_dict())
+
+ # Inherit other info
+ info.docs_url = cls._hub_mixin_info.docs_url
+ info.paper_url = cls._hub_mixin_info.paper_url
+ info.repo_url = cls._hub_mixin_info.repo_url
+ cls._hub_mixin_info = info
+
+ # Update MixinInfo with metadata
+ if model_card_template is not None and model_card_template != DEFAULT_MODEL_CARD:
+ info.model_card_template = model_card_template
+ if repo_url is not None:
+ info.repo_url = repo_url
+ if paper_url is not None:
+ info.paper_url = paper_url
+ if docs_url is not None:
+ info.docs_url = docs_url
+ if language is not None:
+ info.model_card_data.language = language
+ if library_name is not None:
+ info.model_card_data.library_name = library_name
+ if license is not None:
+ info.model_card_data.license = license
+ if license_name is not None:
+ info.model_card_data.license_name = license_name
+ if license_link is not None:
+ info.model_card_data.license_link = license_link
+ if pipeline_tag is not None:
+ info.model_card_data.pipeline_tag = pipeline_tag
+ if tags is not None:
+ normalized_tags = list(tags)
+ if info.model_card_data.tags is not None:
+ info.model_card_data.tags.extend(normalized_tags)
+ else:
+ info.model_card_data.tags = normalized_tags
+
+ if info.model_card_data.tags is not None:
+ info.model_card_data.tags = sorted(set(info.model_card_data.tags))
+
+ # Handle encoders/decoders for args
+ cls._hub_mixin_coders = coders or {}
+ cls._hub_mixin_jsonable_custom_types = tuple(cls._hub_mixin_coders.keys())
+
+ # Inspect __init__ signature to handle config
+ cls._hub_mixin_init_parameters = dict(inspect.signature(cls.__init__).parameters)
+ cls._hub_mixin_jsonable_default_values = {
+ param.name: cls._encode_arg(param.default)
+ for param in cls._hub_mixin_init_parameters.values()
+ if param.default is not inspect.Parameter.empty and cls._is_jsonable(param.default)
+ }
+ cls._hub_mixin_inject_config = "config" in inspect.signature(cls._from_pretrained).parameters
+
+ def __new__(cls: Type[T], *args, **kwargs) -> T:
+ """Create a new instance of the class and handle config.
+
+ 3 cases:
+ - If `self._hub_mixin_config` is already set, do nothing.
+ - If `config` is passed as a dataclass, set it as `self._hub_mixin_config`.
+ - Otherwise, build `self._hub_mixin_config` from default values and passed values.
+ """
+ instance = super().__new__(cls)
+
+ # If `config` is already set, return early
+ if instance._hub_mixin_config is not None:
+ return instance
+
+ # Infer passed values
+ passed_values = {
+ **{
+ key: value
+ for key, value in zip(
+ # [1:] to skip `self` parameter
+ list(cls._hub_mixin_init_parameters)[1:],
+ args,
+ )
+ },
+ **kwargs,
+ }
+
+ # If config passed as dataclass => set it and return early
+ if is_dataclass(passed_values.get("config")):
+ instance._hub_mixin_config = passed_values["config"]
+ return instance
+
+ # Otherwise, build config from default + passed values
+ init_config = {
+ # default values
+ **cls._hub_mixin_jsonable_default_values,
+ # passed values
+ **{
+ key: cls._encode_arg(value) # Encode custom types as jsonable value
+ for key, value in passed_values.items()
+ if instance._is_jsonable(value) # Only if jsonable or we have a custom encoder
+ },
+ }
+ passed_config = init_config.pop("config", {})
+
+ # Populate `init_config` with provided config
+ if isinstance(passed_config, dict):
+ init_config.update(passed_config)
+
+ # Set `config` attribute and return
+ if init_config != {}:
+ instance._hub_mixin_config = init_config
+ return instance
+
+ @classmethod
+ def _is_jsonable(cls, value: Any) -> bool:
+ """Check if a value is JSON serializable."""
+ if is_dataclass(value):
+ return True
+ if isinstance(value, cls._hub_mixin_jsonable_custom_types):
+ return True
+ return is_jsonable(value)
+
+ @classmethod
+ def _encode_arg(cls, arg: Any) -> Any:
+ """Encode an argument into a JSON serializable format."""
+ if is_dataclass(arg):
+ return asdict(arg) # type: ignore[arg-type]
+ for type_, (encoder, _) in cls._hub_mixin_coders.items():
+ if isinstance(arg, type_):
+ if arg is None:
+ return None
+ return encoder(arg)
+ return arg
+
+ @classmethod
+ def _decode_arg(cls, expected_type: Type[ARGS_T], value: Any) -> Optional[ARGS_T]:
+ """Decode a JSON serializable value into an argument."""
+ if is_simple_optional_type(expected_type):
+ if value is None:
+ return None
+ expected_type = unwrap_simple_optional_type(expected_type)
+ # Dataclass => handle it
+ if is_dataclass(expected_type):
+ return _load_dataclass(expected_type, value) # type: ignore[return-value]
+ # Otherwise => check custom decoders
+ for type_, (_, decoder) in cls._hub_mixin_coders.items():
+ if inspect.isclass(expected_type) and issubclass(expected_type, type_):
+ return decoder(value)
+ # Otherwise => don't decode
+ return value
+
+ def save_pretrained(
+ self,
+ save_directory: Union[str, Path],
+ *,
+ config: Optional[Union[dict, DataclassInstance]] = None,
+ repo_id: Optional[str] = None,
+ push_to_hub: bool = False,
+ model_card_kwargs: Optional[Dict[str, Any]] = None,
+ **push_to_hub_kwargs,
+ ) -> Optional[str]:
+ """
+ Save weights in local directory.
+
+ Args:
+ save_directory (`str` or `Path`):
+ Path to directory in which the model weights and configuration will be saved.
+ config (`dict` or `DataclassInstance`, *optional*):
+ Model configuration specified as a key/value dictionary or a dataclass instance.
+ push_to_hub (`bool`, *optional*, defaults to `False`):
+ Whether or not to push your model to the Huggingface Hub after saving it.
+ repo_id (`str`, *optional*):
+ ID of your repository on the Hub. Used only if `push_to_hub=True`. Will default to the folder name if
+ not provided.
+ model_card_kwargs (`Dict[str, Any]`, *optional*):
+ Additional arguments passed to the model card template to customize the model card.
+ push_to_hub_kwargs:
+ Additional key word arguments passed along to the [`~ModelHubMixin.push_to_hub`] method.
+ Returns:
+ `str` or `None`: url of the commit on the Hub if `push_to_hub=True`, `None` otherwise.
+ """
+ save_directory = Path(save_directory)
+ save_directory.mkdir(parents=True, exist_ok=True)
+
+ # Remove config.json if already exists. After `_save_pretrained` we don't want to overwrite config.json
+ # as it might have been saved by the custom `_save_pretrained` already. However we do want to overwrite
+ # an existing config.json if it was not saved by `_save_pretrained`.
+ config_path = save_directory / constants.CONFIG_NAME
+ config_path.unlink(missing_ok=True)
+
+ # save model weights/files (framework-specific)
+ self._save_pretrained(save_directory)
+
+ # save config (if provided and if not serialized yet in `_save_pretrained`)
+ if config is None:
+ config = self._hub_mixin_config
+ if config is not None:
+ if is_dataclass(config):
+ config = asdict(config) # type: ignore[arg-type]
+ if not config_path.exists():
+ config_str = json.dumps(config, sort_keys=True, indent=2)
+ config_path.write_text(config_str)
+
+ # save model card
+ model_card_path = save_directory / "README.md"
+ model_card_kwargs = model_card_kwargs if model_card_kwargs is not None else {}
+ if not model_card_path.exists(): # do not overwrite if already exists
+ self.generate_model_card(**model_card_kwargs).save(save_directory / "README.md")
+
+ # push to the Hub if required
+ if push_to_hub:
+ kwargs = push_to_hub_kwargs.copy() # soft-copy to avoid mutating input
+ if config is not None: # kwarg for `push_to_hub`
+ kwargs["config"] = config
+ if repo_id is None:
+ repo_id = save_directory.name # Defaults to `save_directory` name
+ return self.push_to_hub(repo_id=repo_id, model_card_kwargs=model_card_kwargs, **kwargs)
+ return None
+
+ def _save_pretrained(self, save_directory: Path) -> None:
+ """
+ Overwrite this method in subclass to define how to save your model.
+ Check out our [integration guide](../guides/integrations) for instructions.
+
+ Args:
+ save_directory (`str` or `Path`):
+ Path to directory in which the model weights and configuration will be saved.
+ """
+ raise NotImplementedError
+
+ @classmethod
+ @validate_hf_hub_args
+ def from_pretrained(
+ cls: Type[T],
+ pretrained_model_name_or_path: Union[str, Path],
+ *,
+ force_download: bool = False,
+ resume_download: Optional[bool] = None,
+ proxies: Optional[Dict] = None,
+ token: Optional[Union[str, bool]] = None,
+ cache_dir: Optional[Union[str, Path]] = None,
+ local_files_only: bool = False,
+ revision: Optional[str] = None,
+ **model_kwargs,
+ ) -> T:
+ """
+ Download a model from the Huggingface Hub and instantiate it.
+
+ Args:
+ pretrained_model_name_or_path (`str`, `Path`):
+ - Either the `model_id` (string) of a model hosted on the Hub, e.g. `bigscience/bloom`.
+ - Or a path to a `directory` containing model weights saved using
+ [`~transformers.PreTrainedModel.save_pretrained`], e.g., `../path/to/my_model_directory/`.
+ revision (`str`, *optional*):
+ Revision of the model on the Hub. Can be a branch name, a git tag or any commit id.
+ Defaults to the latest commit on `main` branch.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether to force (re-)downloading the model weights and configuration files from the Hub, overriding
+ the existing cache.
+ proxies (`Dict[str, str]`, *optional*):
+ A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
+ 'http://hostname': 'foo.bar:4012'}`. The proxies are used on every request.
+ token (`str` or `bool`, *optional*):
+ The token to use as HTTP bearer authorization for remote files. By default, it will use the token
+ cached when running `hf auth login`.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the local cached file if it exists.
+ model_kwargs (`Dict`, *optional*):
+ Additional kwargs to pass to the model during initialization.
+ """
+ model_id = str(pretrained_model_name_or_path)
+ config_file: Optional[str] = None
+ if os.path.isdir(model_id):
+ if constants.CONFIG_NAME in os.listdir(model_id):
+ config_file = os.path.join(model_id, constants.CONFIG_NAME)
+ else:
+ logger.warning(f"{constants.CONFIG_NAME} not found in {Path(model_id).resolve()}")
+ else:
+ try:
+ config_file = hf_hub_download(
+ repo_id=model_id,
+ filename=constants.CONFIG_NAME,
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ token=token,
+ local_files_only=local_files_only,
+ )
+ except HfHubHTTPError as e:
+ logger.info(f"{constants.CONFIG_NAME} not found on the HuggingFace Hub: {str(e)}")
+
+ # Read config
+ config = None
+ if config_file is not None:
+ with open(config_file, "r", encoding="utf-8") as f:
+ config = json.load(f)
+
+ # Decode custom types in config
+ for key, value in config.items():
+ if key in cls._hub_mixin_init_parameters:
+ expected_type = cls._hub_mixin_init_parameters[key].annotation
+ if expected_type is not inspect.Parameter.empty:
+ config[key] = cls._decode_arg(expected_type, value)
+
+ # Populate model_kwargs from config
+ for param in cls._hub_mixin_init_parameters.values():
+ if param.name not in model_kwargs and param.name in config:
+ model_kwargs[param.name] = config[param.name]
+
+ # Check if `config` argument was passed at init
+ if "config" in cls._hub_mixin_init_parameters and "config" not in model_kwargs:
+ # Decode `config` argument if it was passed
+ config_annotation = cls._hub_mixin_init_parameters["config"].annotation
+ config = cls._decode_arg(config_annotation, config)
+
+ # Forward config to model initialization
+ model_kwargs["config"] = config
+
+ # Inject config if `**kwargs` are expected
+ if is_dataclass(cls):
+ for key in cls.__dataclass_fields__:
+ if key not in model_kwargs and key in config:
+ model_kwargs[key] = config[key]
+ elif any(param.kind == inspect.Parameter.VAR_KEYWORD for param in cls._hub_mixin_init_parameters.values()):
+ for key, value in config.items():
+ if key not in model_kwargs:
+ model_kwargs[key] = value
+
+ # Finally, also inject if `_from_pretrained` expects it
+ if cls._hub_mixin_inject_config and "config" not in model_kwargs:
+ model_kwargs["config"] = config
+
+ instance = cls._from_pretrained(
+ model_id=str(model_id),
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ local_files_only=local_files_only,
+ token=token,
+ **model_kwargs,
+ )
+
+ # Implicitly set the config as instance attribute if not already set by the class
+ # This way `config` will be available when calling `save_pretrained` or `push_to_hub`.
+ if config is not None and (getattr(instance, "_hub_mixin_config", None) in (None, {})):
+ instance._hub_mixin_config = config
+
+ return instance
+
+ @classmethod
+ def _from_pretrained(
+ cls: Type[T],
+ *,
+ model_id: str,
+ revision: Optional[str],
+ cache_dir: Optional[Union[str, Path]],
+ force_download: bool,
+ proxies: Optional[Dict],
+ resume_download: Optional[bool],
+ local_files_only: bool,
+ token: Optional[Union[str, bool]],
+ **model_kwargs,
+ ) -> T:
+ """Overwrite this method in subclass to define how to load your model from pretrained.
+
+ Use [`hf_hub_download`] or [`snapshot_download`] to download files from the Hub before loading them. Most
+ args taken as input can be directly passed to those 2 methods. If needed, you can add more arguments to this
+ method using "model_kwargs". For example [`PyTorchModelHubMixin._from_pretrained`] takes as input a `map_location`
+ parameter to set on which device the model should be loaded.
+
+ Check out our [integration guide](../guides/integrations) for more instructions.
+
+ Args:
+ model_id (`str`):
+ ID of the model to load from the Huggingface Hub (e.g. `bigscience/bloom`).
+ revision (`str`, *optional*):
+ Revision of the model on the Hub. Can be a branch name, a git tag or any commit id. Defaults to the
+ latest commit on `main` branch.
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether to force (re-)downloading the model weights and configuration files from the Hub, overriding
+ the existing cache.
+ proxies (`Dict[str, str]`, *optional*):
+ A dictionary of proxy servers to use by protocol or endpoint (e.g., `{'http': 'foo.bar:3128',
+ 'http://hostname': 'foo.bar:4012'}`).
+ token (`str` or `bool`, *optional*):
+ The token to use as HTTP bearer authorization for remote files. By default, it will use the token
+ cached when running `hf auth login`.
+ cache_dir (`str`, `Path`, *optional*):
+ Path to the folder where cached files are stored.
+ local_files_only (`bool`, *optional*, defaults to `False`):
+ If `True`, avoid downloading the file and return the path to the local cached file if it exists.
+ model_kwargs:
+ Additional keyword arguments passed along to the [`~ModelHubMixin._from_pretrained`] method.
+ """
+ raise NotImplementedError
+
+ @validate_hf_hub_args
+ def push_to_hub(
+ self,
+ repo_id: str,
+ *,
+ config: Optional[Union[dict, DataclassInstance]] = None,
+ commit_message: str = "Push model using huggingface_hub.",
+ private: Optional[bool] = None,
+ token: Optional[str] = None,
+ branch: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ model_card_kwargs: Optional[Dict[str, Any]] = None,
+ ) -> str:
+ """
+ Upload model checkpoint to the Hub.
+
+ Use `allow_patterns` and `ignore_patterns` to precisely filter which files should be pushed to the hub. Use
+ `delete_patterns` to delete existing remote files in the same commit. See [`upload_folder`] reference for more
+ details.
+
+ Args:
+ repo_id (`str`):
+ ID of the repository to push to (example: `"username/my-model"`).
+ config (`dict` or `DataclassInstance`, *optional*):
+ Model configuration specified as a key/value dictionary or a dataclass instance.
+ commit_message (`str`, *optional*):
+ Message to commit while pushing.
+ private (`bool`, *optional*):
+ Whether the repository created should be private.
+ If `None` (default), the repo will be public unless the organization's default is private.
+ token (`str`, *optional*):
+ The token to use as HTTP bearer authorization for remote files. By default, it will use the token
+ cached when running `hf auth login`.
+ branch (`str`, *optional*):
+ The git branch on which to push the model. This defaults to `"main"`.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request from `branch` with that commit. Defaults to `False`.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are pushed.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not pushed.
+ delete_patterns (`List[str]` or `str`, *optional*):
+ If provided, remote files matching any of the patterns will be deleted from the repo.
+ model_card_kwargs (`Dict[str, Any]`, *optional*):
+ Additional arguments passed to the model card template to customize the model card.
+
+ Returns:
+ The url of the commit of your model in the given repository.
+ """
+ api = HfApi(token=token)
+ repo_id = api.create_repo(repo_id=repo_id, private=private, exist_ok=True).repo_id
+
+ # Push the files to the repo in a single commit
+ with SoftTemporaryDirectory() as tmp:
+ saved_path = Path(tmp) / repo_id
+ self.save_pretrained(saved_path, config=config, model_card_kwargs=model_card_kwargs)
+ return api.upload_folder(
+ repo_id=repo_id,
+ repo_type="model",
+ folder_path=saved_path,
+ commit_message=commit_message,
+ revision=branch,
+ create_pr=create_pr,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ delete_patterns=delete_patterns,
+ )
+
+ def generate_model_card(self, *args, **kwargs) -> ModelCard:
+ card = ModelCard.from_template(
+ card_data=self._hub_mixin_info.model_card_data,
+ template_str=self._hub_mixin_info.model_card_template,
+ repo_url=self._hub_mixin_info.repo_url,
+ paper_url=self._hub_mixin_info.paper_url,
+ docs_url=self._hub_mixin_info.docs_url,
+ **kwargs,
+ )
+ return card
+
+
+class PyTorchModelHubMixin(ModelHubMixin):
+ """
+ Implementation of [`ModelHubMixin`] to provide model Hub upload/download capabilities to PyTorch models. The model
+ is set in evaluation mode by default using `model.eval()` (dropout modules are deactivated). To train the model,
+ you should first set it back in training mode with `model.train()`.
+
+ See [`ModelHubMixin`] for more details on how to use the mixin.
+
+ Example:
+
+ ```python
+ >>> import torch
+ >>> import torch.nn as nn
+ >>> from huggingface_hub import PyTorchModelHubMixin
+
+ >>> class MyModel(
+ ... nn.Module,
+ ... PyTorchModelHubMixin,
+ ... library_name="keras-nlp",
+ ... repo_url="https://github.com/keras-team/keras-nlp",
+ ... paper_url="https://arxiv.org/abs/2304.12244",
+ ... docs_url="https://keras.io/keras_nlp/",
+ ... # ^ optional metadata to generate model card
+ ... ):
+ ... def __init__(self, hidden_size: int = 512, vocab_size: int = 30000, output_size: int = 4):
+ ... super().__init__()
+ ... self.param = nn.Parameter(torch.rand(hidden_size, vocab_size))
+ ... self.linear = nn.Linear(output_size, vocab_size)
+
+ ... def forward(self, x):
+ ... return self.linear(x + self.param)
+ >>> model = MyModel(hidden_size=256)
+
+ # Save model weights to local directory
+ >>> model.save_pretrained("my-awesome-model")
+
+ # Push model weights to the Hub
+ >>> model.push_to_hub("my-awesome-model")
+
+ # Download and initialize weights from the Hub
+ >>> model = MyModel.from_pretrained("username/my-awesome-model")
+ >>> model.hidden_size
+ 256
+ ```
+ """
+
+ def __init_subclass__(cls, *args, tags: Optional[List[str]] = None, **kwargs) -> None:
+ tags = tags or []
+ tags.append("pytorch_model_hub_mixin")
+ kwargs["tags"] = tags
+ return super().__init_subclass__(*args, **kwargs)
+
+ def _save_pretrained(self, save_directory: Path) -> None:
+ """Save weights from a Pytorch model to a local directory."""
+ model_to_save = self.module if hasattr(self, "module") else self # type: ignore
+ save_model_as_safetensor(model_to_save, str(save_directory / constants.SAFETENSORS_SINGLE_FILE)) # type: ignore [arg-type]
+
+ @classmethod
+ def _from_pretrained(
+ cls,
+ *,
+ model_id: str,
+ revision: Optional[str],
+ cache_dir: Optional[Union[str, Path]],
+ force_download: bool,
+ proxies: Optional[Dict],
+ resume_download: Optional[bool],
+ local_files_only: bool,
+ token: Union[str, bool, None],
+ map_location: str = "cpu",
+ strict: bool = False,
+ **model_kwargs,
+ ):
+ """Load Pytorch pretrained weights and return the loaded model."""
+ model = cls(**model_kwargs)
+ if os.path.isdir(model_id):
+ print("Loading weights from local directory")
+ model_file = os.path.join(model_id, constants.SAFETENSORS_SINGLE_FILE)
+ return cls._load_as_safetensor(model, model_file, map_location, strict)
+ else:
+ try:
+ model_file = hf_hub_download(
+ repo_id=model_id,
+ filename=constants.SAFETENSORS_SINGLE_FILE,
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ token=token,
+ local_files_only=local_files_only,
+ )
+ return cls._load_as_safetensor(model, model_file, map_location, strict)
+ except EntryNotFoundError:
+ model_file = hf_hub_download(
+ repo_id=model_id,
+ filename=constants.PYTORCH_WEIGHTS_NAME,
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ token=token,
+ local_files_only=local_files_only,
+ )
+ return cls._load_as_pickle(model, model_file, map_location, strict)
+
+ @classmethod
+ def _load_as_pickle(cls, model: T, model_file: str, map_location: str, strict: bool) -> T:
+ state_dict = torch.load(model_file, map_location=torch.device(map_location), weights_only=True)
+ model.load_state_dict(state_dict, strict=strict) # type: ignore
+ model.eval() # type: ignore
+ return model
+
+ @classmethod
+ def _load_as_safetensor(cls, model: T, model_file: str, map_location: str, strict: bool) -> T:
+ if packaging.version.parse(safetensors.__version__) < packaging.version.parse("0.4.3"): # type: ignore [attr-defined]
+ load_model_as_safetensor(model, model_file, strict=strict) # type: ignore [arg-type]
+ if map_location != "cpu":
+ logger.warning(
+ "Loading model weights on other devices than 'cpu' is not supported natively in your version of safetensors."
+ " This means that the model is loaded on 'cpu' first and then copied to the device."
+ " This leads to a slower loading time."
+ " Please update safetensors to version 0.4.3 or above for improved performance."
+ )
+ model.to(map_location) # type: ignore [attr-defined]
+ else:
+ safetensors.torch.load_model(model, model_file, strict=strict, device=map_location) # type: ignore [arg-type]
+ return model
+
+
+def _load_dataclass(datacls: Type[DataclassInstance], data: dict) -> DataclassInstance:
+ """Load a dataclass instance from a dictionary.
+
+ Fields not expected by the dataclass are ignored.
+ """
+ return datacls(**{k: v for k, v in data.items() if k in datacls.__dataclass_fields__})
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/inference_api.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/inference_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..f895fcc61c3867838b013ecd3f6789cbc010b5b3
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/inference_api.py
@@ -0,0 +1,217 @@
+import io
+from typing import Any, Dict, List, Optional, Union
+
+from . import constants
+from .hf_api import HfApi
+from .utils import build_hf_headers, get_session, is_pillow_available, logging, validate_hf_hub_args
+from .utils._deprecation import _deprecate_method
+
+
+logger = logging.get_logger(__name__)
+
+
+ALL_TASKS = [
+ # NLP
+ "text-classification",
+ "token-classification",
+ "table-question-answering",
+ "question-answering",
+ "zero-shot-classification",
+ "translation",
+ "summarization",
+ "conversational",
+ "feature-extraction",
+ "text-generation",
+ "text2text-generation",
+ "fill-mask",
+ "sentence-similarity",
+ # Audio
+ "text-to-speech",
+ "automatic-speech-recognition",
+ "audio-to-audio",
+ "audio-classification",
+ "voice-activity-detection",
+ # Computer vision
+ "image-classification",
+ "object-detection",
+ "image-segmentation",
+ "text-to-image",
+ "image-to-image",
+ # Others
+ "tabular-classification",
+ "tabular-regression",
+]
+
+
+class InferenceApi:
+ """Client to configure requests and make calls to the HuggingFace Inference API.
+
+ Example:
+
+ ```python
+ >>> from huggingface_hub.inference_api import InferenceApi
+
+ >>> # Mask-fill example
+ >>> inference = InferenceApi("bert-base-uncased")
+ >>> inference(inputs="The goal of life is [MASK].")
+ [{'sequence': 'the goal of life is life.', 'score': 0.10933292657136917, 'token': 2166, 'token_str': 'life'}]
+
+ >>> # Question Answering example
+ >>> inference = InferenceApi("deepset/roberta-base-squad2")
+ >>> inputs = {
+ ... "question": "What's my name?",
+ ... "context": "My name is Clara and I live in Berkeley.",
+ ... }
+ >>> inference(inputs)
+ {'score': 0.9326569437980652, 'start': 11, 'end': 16, 'answer': 'Clara'}
+
+ >>> # Zero-shot example
+ >>> inference = InferenceApi("typeform/distilbert-base-uncased-mnli")
+ >>> inputs = "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!"
+ >>> params = {"candidate_labels": ["refund", "legal", "faq"]}
+ >>> inference(inputs, params)
+ {'sequence': 'Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!', 'labels': ['refund', 'faq', 'legal'], 'scores': [0.9378499388694763, 0.04914155602455139, 0.013008488342165947]}
+
+ >>> # Overriding configured task
+ >>> inference = InferenceApi("bert-base-uncased", task="feature-extraction")
+
+ >>> # Text-to-image
+ >>> inference = InferenceApi("stabilityai/stable-diffusion-2-1")
+ >>> inference("cat")
+
+
+ >>> # Return as raw response to parse the output yourself
+ >>> inference = InferenceApi("mio/amadeus")
+ >>> response = inference("hello world", raw_response=True)
+ >>> response.headers
+ {"Content-Type": "audio/flac", ...}
+ >>> response.content # raw bytes from server
+ b'(...)'
+ ```
+ """
+
+ @validate_hf_hub_args
+ @_deprecate_method(
+ version="1.0",
+ message=(
+ "`InferenceApi` client is deprecated in favor of the more feature-complete `InferenceClient`. Check out"
+ " this guide to learn how to convert your script to use it:"
+ " https://huggingface.co/docs/huggingface_hub/guides/inference#legacy-inferenceapi-client."
+ ),
+ )
+ def __init__(
+ self,
+ repo_id: str,
+ task: Optional[str] = None,
+ token: Optional[str] = None,
+ gpu: bool = False,
+ ):
+ """Inits headers and API call information.
+
+ Args:
+ repo_id (``str``):
+ Id of repository (e.g. `user/bert-base-uncased`).
+ task (``str``, `optional`, defaults ``None``):
+ Whether to force a task instead of using task specified in the
+ repository.
+ token (`str`, `optional`):
+ The API token to use as HTTP bearer authorization. This is not
+ the authentication token. You can find the token in
+ https://huggingface.co/settings/token. Alternatively, you can
+ find both your organizations and personal API tokens using
+ `HfApi().whoami(token)`.
+ gpu (`bool`, `optional`, defaults `False`):
+ Whether to use GPU instead of CPU for inference(requires Startup
+ plan at least).
+ """
+ self.options = {"wait_for_model": True, "use_gpu": gpu}
+ self.headers = build_hf_headers(token=token)
+
+ # Configure task
+ model_info = HfApi(token=token).model_info(repo_id=repo_id)
+ if not model_info.pipeline_tag and not task:
+ raise ValueError(
+ "Task not specified in the repository. Please add it to the model card"
+ " using pipeline_tag"
+ " (https://huggingface.co/docs#how-is-a-models-type-of-inference-api-and-widget-determined)"
+ )
+
+ if task and task != model_info.pipeline_tag:
+ if task not in ALL_TASKS:
+ raise ValueError(f"Invalid task {task}. Make sure it's valid.")
+
+ logger.warning(
+ "You're using a different task than the one specified in the"
+ " repository. Be sure to know what you're doing :)"
+ )
+ self.task = task
+ else:
+ assert model_info.pipeline_tag is not None, "Pipeline tag cannot be None"
+ self.task = model_info.pipeline_tag
+
+ self.api_url = f"{constants.INFERENCE_ENDPOINT}/pipeline/{self.task}/{repo_id}"
+
+ def __repr__(self):
+ # Do not add headers to repr to avoid leaking token.
+ return f"InferenceAPI(api_url='{self.api_url}', task='{self.task}', options={self.options})"
+
+ def __call__(
+ self,
+ inputs: Optional[Union[str, Dict, List[str], List[List[str]]]] = None,
+ params: Optional[Dict] = None,
+ data: Optional[bytes] = None,
+ raw_response: bool = False,
+ ) -> Any:
+ """Make a call to the Inference API.
+
+ Args:
+ inputs (`str` or `Dict` or `List[str]` or `List[List[str]]`, *optional*):
+ Inputs for the prediction.
+ params (`Dict`, *optional*):
+ Additional parameters for the models. Will be sent as `parameters` in the
+ payload.
+ data (`bytes`, *optional*):
+ Bytes content of the request. In this case, leave `inputs` and `params` empty.
+ raw_response (`bool`, defaults to `False`):
+ If `True`, the raw `Response` object is returned. You can parse its content
+ as preferred. By default, the content is parsed into a more practical format
+ (json dictionary or PIL Image for example).
+ """
+ # Build payload
+ payload: Dict[str, Any] = {
+ "options": self.options,
+ }
+ if inputs:
+ payload["inputs"] = inputs
+ if params:
+ payload["parameters"] = params
+
+ # Make API call
+ response = get_session().post(self.api_url, headers=self.headers, json=payload, data=data)
+
+ # Let the user handle the response
+ if raw_response:
+ return response
+
+ # By default, parse the response for the user.
+ content_type = response.headers.get("Content-Type") or ""
+ if content_type.startswith("image"):
+ if not is_pillow_available():
+ raise ImportError(
+ f"Task '{self.task}' returned as image but Pillow is not installed."
+ " Please install it (`pip install Pillow`) or pass"
+ " `raw_response=True` to get the raw `Response` object and parse"
+ " the image by yourself."
+ )
+
+ from PIL import Image
+
+ return Image.open(io.BytesIO(response.content))
+ elif content_type == "application/json":
+ return response.json()
+ else:
+ raise NotImplementedError(
+ f"{content_type} output type is not implemented yet. You can pass"
+ " `raw_response=True` to get the raw `Response` object and parse the"
+ " output by yourself."
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/keras_mixin.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/keras_mixin.py
new file mode 100644
index 0000000000000000000000000000000000000000..c284947c1d3c25da421b90e902683054830788d3
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/keras_mixin.py
@@ -0,0 +1,497 @@
+import collections.abc as collections
+import json
+import os
+import warnings
+from functools import wraps
+from pathlib import Path
+from shutil import copytree
+from typing import Any, Dict, List, Optional, Union
+
+from huggingface_hub import ModelHubMixin, snapshot_download
+from huggingface_hub.utils import (
+ get_tf_version,
+ is_graphviz_available,
+ is_pydot_available,
+ is_tf_available,
+ yaml_dump,
+)
+
+from . import constants
+from .hf_api import HfApi
+from .utils import SoftTemporaryDirectory, logging, validate_hf_hub_args
+from .utils._typing import CallableT
+
+
+logger = logging.get_logger(__name__)
+
+keras = None
+if is_tf_available():
+ # Depending on which version of TensorFlow is installed, we need to import
+ # keras from the correct location.
+ # See https://github.com/tensorflow/tensorflow/releases/tag/v2.16.1.
+ # Note: saving a keras model only works with Keras<3.0.
+ try:
+ import tf_keras as keras # type: ignore
+ except ImportError:
+ import tensorflow as tf # type: ignore
+
+ keras = tf.keras
+
+
+def _requires_keras_2_model(fn: CallableT) -> CallableT:
+ # Wrapper to raise if user tries to save a Keras 3.x model
+ @wraps(fn)
+ def _inner(model, *args, **kwargs):
+ if not hasattr(model, "history"): # hacky way to check if model is Keras 2.x
+ raise NotImplementedError(
+ f"Cannot use '{fn.__name__}': Keras 3.x is not supported."
+ " Please save models manually and upload them using `upload_folder` or `hf upload`."
+ )
+ return fn(model, *args, **kwargs)
+
+ return _inner # type: ignore [return-value]
+
+
+def _flatten_dict(dictionary, parent_key=""):
+ """Flatten a nested dictionary.
+ Reference: https://stackoverflow.com/a/6027615/10319735
+
+ Args:
+ dictionary (`dict`):
+ The nested dictionary to be flattened.
+ parent_key (`str`):
+ The parent key to be prefixed to the children keys.
+ Necessary for recursing over the nested dictionary.
+
+ Returns:
+ The flattened dictionary.
+ """
+ items = []
+ for key, value in dictionary.items():
+ new_key = f"{parent_key}.{key}" if parent_key else key
+ if isinstance(value, collections.MutableMapping):
+ items.extend(
+ _flatten_dict(
+ value,
+ new_key,
+ ).items()
+ )
+ else:
+ items.append((new_key, value))
+ return dict(items)
+
+
+def _create_hyperparameter_table(model):
+ """Parse hyperparameter dictionary into a markdown table."""
+ table = None
+ if model.optimizer is not None:
+ optimizer_params = model.optimizer.get_config()
+ # flatten the configuration
+ optimizer_params = _flatten_dict(optimizer_params)
+ optimizer_params["training_precision"] = keras.mixed_precision.global_policy().name
+ table = "| Hyperparameters | Value |\n| :-- | :-- |\n"
+ for key, value in optimizer_params.items():
+ table += f"| {key} | {value} |\n"
+ return table
+
+
+def _plot_network(model, save_directory):
+ keras.utils.plot_model(
+ model,
+ to_file=f"{save_directory}/model.png",
+ show_shapes=False,
+ show_dtype=False,
+ show_layer_names=True,
+ rankdir="TB",
+ expand_nested=False,
+ dpi=96,
+ layer_range=None,
+ )
+
+
+def _create_model_card(
+ model,
+ repo_dir: Path,
+ plot_model: bool = True,
+ metadata: Optional[dict] = None,
+):
+ """
+ Creates a model card for the repository.
+
+ Do not overwrite an existing README.md file.
+ """
+ readme_path = repo_dir / "README.md"
+ if readme_path.exists():
+ return
+
+ hyperparameters = _create_hyperparameter_table(model)
+ if plot_model and is_graphviz_available() and is_pydot_available():
+ _plot_network(model, repo_dir)
+ if metadata is None:
+ metadata = {}
+ metadata["library_name"] = "keras"
+ model_card: str = "---\n"
+ model_card += yaml_dump(metadata, default_flow_style=False)
+ model_card += "---\n"
+ model_card += "\n## Model description\n\nMore information needed\n"
+ model_card += "\n## Intended uses & limitations\n\nMore information needed\n"
+ model_card += "\n## Training and evaluation data\n\nMore information needed\n"
+ if hyperparameters is not None:
+ model_card += "\n## Training procedure\n"
+ model_card += "\n### Training hyperparameters\n"
+ model_card += "\nThe following hyperparameters were used during training:\n\n"
+ model_card += hyperparameters
+ model_card += "\n"
+ if plot_model and os.path.exists(f"{repo_dir}/model.png"):
+ model_card += "\n ## Model Plot\n"
+ model_card += "\n"
+ model_card += "\nView Model Plot\n"
+ path_to_plot = "./model.png"
+ model_card += f"\n\n"
+ model_card += "\n"
+
+ readme_path.write_text(model_card)
+
+
+@_requires_keras_2_model
+def save_pretrained_keras(
+ model,
+ save_directory: Union[str, Path],
+ config: Optional[Dict[str, Any]] = None,
+ include_optimizer: bool = False,
+ plot_model: bool = True,
+ tags: Optional[Union[list, str]] = None,
+ **model_save_kwargs,
+):
+ """
+ Saves a Keras model to save_directory in SavedModel format. Use this if
+ you're using the Functional or Sequential APIs.
+
+ Args:
+ model (`Keras.Model`):
+ The [Keras
+ model](https://www.tensorflow.org/api_docs/python/tf/keras/Model)
+ you'd like to save. The model must be compiled and built.
+ save_directory (`str` or `Path`):
+ Specify directory in which you want to save the Keras model.
+ config (`dict`, *optional*):
+ Configuration object to be saved alongside the model weights.
+ include_optimizer(`bool`, *optional*, defaults to `False`):
+ Whether or not to include optimizer in serialization.
+ plot_model (`bool`, *optional*, defaults to `True`):
+ Setting this to `True` will plot the model and put it in the model
+ card. Requires graphviz and pydot to be installed.
+ tags (Union[`str`,`list`], *optional*):
+ List of tags that are related to model or string of a single tag. See example tags
+ [here](https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1).
+ model_save_kwargs(`dict`, *optional*):
+ model_save_kwargs will be passed to
+ [`tf.keras.models.save_model()`](https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model).
+ """
+ if keras is None:
+ raise ImportError("Called a Tensorflow-specific function but could not import it.")
+
+ if not model.built:
+ raise ValueError("Model should be built before trying to save")
+
+ save_directory = Path(save_directory)
+ save_directory.mkdir(parents=True, exist_ok=True)
+
+ # saving config
+ if config:
+ if not isinstance(config, dict):
+ raise RuntimeError(f"Provided config to save_pretrained_keras should be a dict. Got: '{type(config)}'")
+
+ with (save_directory / constants.CONFIG_NAME).open("w") as f:
+ json.dump(config, f)
+
+ metadata = {}
+ if isinstance(tags, list):
+ metadata["tags"] = tags
+ elif isinstance(tags, str):
+ metadata["tags"] = [tags]
+
+ task_name = model_save_kwargs.pop("task_name", None)
+ if task_name is not None:
+ warnings.warn(
+ "`task_name` input argument is deprecated. Pass `tags` instead.",
+ FutureWarning,
+ )
+ if "tags" in metadata:
+ metadata["tags"].append(task_name)
+ else:
+ metadata["tags"] = [task_name]
+
+ if model.history is not None:
+ if model.history.history != {}:
+ path = save_directory / "history.json"
+ if path.exists():
+ warnings.warn(
+ "`history.json` file already exists, it will be overwritten by the history of this version.",
+ UserWarning,
+ )
+ with path.open("w", encoding="utf-8") as f:
+ json.dump(model.history.history, f, indent=2, sort_keys=True)
+
+ _create_model_card(model, save_directory, plot_model, metadata)
+ keras.models.save_model(model, save_directory, include_optimizer=include_optimizer, **model_save_kwargs)
+
+
+def from_pretrained_keras(*args, **kwargs) -> "KerasModelHubMixin":
+ r"""
+ Instantiate a pretrained Keras model from a pre-trained model from the Hub.
+ The model is expected to be in `SavedModel` format.
+
+ Args:
+ pretrained_model_name_or_path (`str` or `os.PathLike`):
+ Can be either:
+ - A string, the `model id` of a pretrained model hosted inside a
+ model repo on huggingface.co. Valid model ids can be located
+ at the root-level, like `bert-base-uncased`, or namespaced
+ under a user or organization name, like
+ `dbmdz/bert-base-german-cased`.
+ - You can add `revision` by appending `@` at the end of model_id
+ simply like this: `dbmdz/bert-base-german-cased@main` Revision
+ is the specific model version to use. It can be a branch name,
+ a tag name, or a commit id, since we use a git-based system
+ for storing models and other artifacts on huggingface.co, so
+ `revision` can be any identifier allowed by git.
+ - A path to a `directory` containing model weights saved using
+ [`~transformers.PreTrainedModel.save_pretrained`], e.g.,
+ `./my_model_directory/`.
+ - `None` if you are both providing the configuration and state
+ dictionary (resp. with keyword arguments `config` and
+ `state_dict`).
+ force_download (`bool`, *optional*, defaults to `False`):
+ Whether to force the (re-)download of the model weights and
+ configuration files, overriding the cached versions if they exist.
+ proxies (`Dict[str, str]`, *optional*):
+ A dictionary of proxy servers to use by protocol or endpoint, e.g.,
+ `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}`. The
+ proxies are used on each request.
+ token (`str` or `bool`, *optional*):
+ The token to use as HTTP bearer authorization for remote files. If
+ `True`, will use the token generated when running `transformers-cli
+ login` (stored in `~/.huggingface`).
+ cache_dir (`Union[str, os.PathLike]`, *optional*):
+ Path to a directory in which a downloaded pretrained model
+ configuration should be cached if the standard cache should not be
+ used.
+ local_files_only(`bool`, *optional*, defaults to `False`):
+ Whether to only look at local files (i.e., do not try to download
+ the model).
+ model_kwargs (`Dict`, *optional*):
+ model_kwargs will be passed to the model during initialization
+
+ > [!TIP]
+ > Passing `token=True` is required when you want to use a private
+ > model.
+ """
+ return KerasModelHubMixin.from_pretrained(*args, **kwargs)
+
+
+@validate_hf_hub_args
+@_requires_keras_2_model
+def push_to_hub_keras(
+ model,
+ repo_id: str,
+ *,
+ config: Optional[dict] = None,
+ commit_message: str = "Push Keras model using huggingface_hub.",
+ private: Optional[bool] = None,
+ api_endpoint: Optional[str] = None,
+ token: Optional[str] = None,
+ branch: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ allow_patterns: Optional[Union[List[str], str]] = None,
+ ignore_patterns: Optional[Union[List[str], str]] = None,
+ delete_patterns: Optional[Union[List[str], str]] = None,
+ log_dir: Optional[str] = None,
+ include_optimizer: bool = False,
+ tags: Optional[Union[list, str]] = None,
+ plot_model: bool = True,
+ **model_save_kwargs,
+):
+ """
+ Upload model checkpoint to the Hub.
+
+ Use `allow_patterns` and `ignore_patterns` to precisely filter which files should be pushed to the hub. Use
+ `delete_patterns` to delete existing remote files in the same commit. See [`upload_folder`] reference for more
+ details.
+
+ Args:
+ model (`Keras.Model`):
+ The [Keras model](`https://www.tensorflow.org/api_docs/python/tf/keras/Model`) you'd like to push to the
+ Hub. The model must be compiled and built.
+ repo_id (`str`):
+ ID of the repository to push to (example: `"username/my-model"`).
+ commit_message (`str`, *optional*, defaults to "Add Keras model"):
+ Message to commit while pushing.
+ private (`bool`, *optional*):
+ Whether the repository created should be private.
+ If `None` (default), the repo will be public unless the organization's default is private.
+ api_endpoint (`str`, *optional*):
+ The API endpoint to use when pushing the model to the hub.
+ token (`str`, *optional*):
+ The token to use as HTTP bearer authorization for remote files. If
+ not set, will use the token set when logging in with
+ `hf auth login` (stored in `~/.huggingface`).
+ branch (`str`, *optional*):
+ The git branch on which to push the model. This defaults to
+ the default branch as specified in your repository, which
+ defaults to `"main"`.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request from `branch` with that commit.
+ Defaults to `False`.
+ config (`dict`, *optional*):
+ Configuration object to be saved alongside the model weights.
+ allow_patterns (`List[str]` or `str`, *optional*):
+ If provided, only files matching at least one pattern are pushed.
+ ignore_patterns (`List[str]` or `str`, *optional*):
+ If provided, files matching any of the patterns are not pushed.
+ delete_patterns (`List[str]` or `str`, *optional*):
+ If provided, remote files matching any of the patterns will be deleted from the repo.
+ log_dir (`str`, *optional*):
+ TensorBoard logging directory to be pushed. The Hub automatically
+ hosts and displays a TensorBoard instance if log files are included
+ in the repository.
+ include_optimizer (`bool`, *optional*, defaults to `False`):
+ Whether or not to include optimizer during serialization.
+ tags (Union[`list`, `str`], *optional*):
+ List of tags that are related to model or string of a single tag. See example tags
+ [here](https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1).
+ plot_model (`bool`, *optional*, defaults to `True`):
+ Setting this to `True` will plot the model and put it in the model
+ card. Requires graphviz and pydot to be installed.
+ model_save_kwargs(`dict`, *optional*):
+ model_save_kwargs will be passed to
+ [`tf.keras.models.save_model()`](https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model).
+
+ Returns:
+ The url of the commit of your model in the given repository.
+ """
+ api = HfApi(endpoint=api_endpoint)
+ repo_id = api.create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True).repo_id
+
+ # Push the files to the repo in a single commit
+ with SoftTemporaryDirectory() as tmp:
+ saved_path = Path(tmp) / repo_id
+ save_pretrained_keras(
+ model,
+ saved_path,
+ config=config,
+ include_optimizer=include_optimizer,
+ tags=tags,
+ plot_model=plot_model,
+ **model_save_kwargs,
+ )
+
+ # If `log_dir` provided, delete remote logs and upload new ones
+ if log_dir is not None:
+ delete_patterns = (
+ []
+ if delete_patterns is None
+ else (
+ [delete_patterns] # convert `delete_patterns` to a list
+ if isinstance(delete_patterns, str)
+ else delete_patterns
+ )
+ )
+ delete_patterns.append("logs/*")
+ copytree(log_dir, saved_path / "logs")
+
+ return api.upload_folder(
+ repo_type="model",
+ repo_id=repo_id,
+ folder_path=saved_path,
+ commit_message=commit_message,
+ token=token,
+ revision=branch,
+ create_pr=create_pr,
+ allow_patterns=allow_patterns,
+ ignore_patterns=ignore_patterns,
+ delete_patterns=delete_patterns,
+ )
+
+
+class KerasModelHubMixin(ModelHubMixin):
+ """
+ Implementation of [`ModelHubMixin`] to provide model Hub upload/download
+ capabilities to Keras models.
+
+
+ ```python
+ >>> import tensorflow as tf
+ >>> from huggingface_hub import KerasModelHubMixin
+
+
+ >>> class MyModel(tf.keras.Model, KerasModelHubMixin):
+ ... def __init__(self, **kwargs):
+ ... super().__init__()
+ ... self.config = kwargs.pop("config", None)
+ ... self.dummy_inputs = ...
+ ... self.layer = ...
+
+ ... def call(self, *args):
+ ... return ...
+
+
+ >>> # Initialize and compile the model as you normally would
+ >>> model = MyModel()
+ >>> model.compile(...)
+ >>> # Build the graph by training it or passing dummy inputs
+ >>> _ = model(model.dummy_inputs)
+ >>> # Save model weights to local directory
+ >>> model.save_pretrained("my-awesome-model")
+ >>> # Push model weights to the Hub
+ >>> model.push_to_hub("my-awesome-model")
+ >>> # Download and initialize weights from the Hub
+ >>> model = MyModel.from_pretrained("username/super-cool-model")
+ ```
+ """
+
+ def _save_pretrained(self, save_directory):
+ save_pretrained_keras(self, save_directory)
+
+ @classmethod
+ def _from_pretrained(
+ cls,
+ model_id,
+ revision,
+ cache_dir,
+ force_download,
+ proxies,
+ resume_download,
+ local_files_only,
+ token,
+ config: Optional[Dict[str, Any]] = None,
+ **model_kwargs,
+ ):
+ """Here we just call [`from_pretrained_keras`] function so both the mixin and
+ functional APIs stay in sync.
+
+ TODO - Some args above aren't used since we are calling
+ snapshot_download instead of hf_hub_download.
+ """
+ if keras is None:
+ raise ImportError("Called a TensorFlow-specific function but could not import it.")
+
+ # Root is either a local filepath matching model_id or a cached snapshot
+ if not os.path.isdir(model_id):
+ storage_folder = snapshot_download(
+ repo_id=model_id,
+ revision=revision,
+ cache_dir=cache_dir,
+ library_name="keras",
+ library_version=get_tf_version(),
+ )
+ else:
+ storage_folder = model_id
+
+ # TODO: change this in a future PR. We are not returning a KerasModelHubMixin instance here...
+ model = keras.models.load_model(storage_folder)
+
+ # For now, we add a new attribute, config, to store the config loaded from the hub/a local dir.
+ model.config = config
+
+ return model
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/lfs.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/lfs.py
new file mode 100644
index 0000000000000000000000000000000000000000..40b6ad087ca6bd33874433439a2c4f5b23d100c5
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/lfs.py
@@ -0,0 +1,466 @@
+# coding=utf-8
+# Copyright 2019-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Git LFS related type definitions and utilities"""
+
+import inspect
+import io
+import re
+import warnings
+from dataclasses import dataclass
+from math import ceil
+from os.path import getsize
+from pathlib import Path
+from typing import TYPE_CHECKING, BinaryIO, Dict, Iterable, List, Optional, Tuple, TypedDict
+from urllib.parse import unquote
+
+from huggingface_hub import constants
+
+from .utils import (
+ build_hf_headers,
+ fix_hf_endpoint_in_url,
+ get_session,
+ hf_raise_for_status,
+ http_backoff,
+ logging,
+ tqdm,
+ validate_hf_hub_args,
+)
+from .utils._lfs import SliceFileObj
+from .utils.sha import sha256, sha_fileobj
+from .utils.tqdm import is_tqdm_disabled
+
+
+if TYPE_CHECKING:
+ from ._commit_api import CommitOperationAdd
+
+logger = logging.get_logger(__name__)
+
+OID_REGEX = re.compile(r"^[0-9a-f]{40}$")
+
+LFS_MULTIPART_UPLOAD_COMMAND = "lfs-multipart-upload"
+
+LFS_HEADERS = {
+ "Accept": "application/vnd.git-lfs+json",
+ "Content-Type": "application/vnd.git-lfs+json",
+}
+
+
+@dataclass
+class UploadInfo:
+ """
+ Dataclass holding required information to determine whether a blob
+ should be uploaded to the hub using the LFS protocol or the regular protocol
+
+ Args:
+ sha256 (`bytes`):
+ SHA256 hash of the blob
+ size (`int`):
+ Size in bytes of the blob
+ sample (`bytes`):
+ First 512 bytes of the blob
+ """
+
+ sha256: bytes
+ size: int
+ sample: bytes
+
+ @classmethod
+ def from_path(cls, path: str):
+ size = getsize(path)
+ with io.open(path, "rb") as file:
+ sample = file.peek(512)[:512]
+ sha = sha_fileobj(file)
+ return cls(size=size, sha256=sha, sample=sample)
+
+ @classmethod
+ def from_bytes(cls, data: bytes):
+ sha = sha256(data).digest()
+ return cls(size=len(data), sample=data[:512], sha256=sha)
+
+ @classmethod
+ def from_fileobj(cls, fileobj: BinaryIO):
+ sample = fileobj.read(512)
+ fileobj.seek(0, io.SEEK_SET)
+ sha = sha_fileobj(fileobj)
+ size = fileobj.tell()
+ fileobj.seek(0, io.SEEK_SET)
+ return cls(size=size, sha256=sha, sample=sample)
+
+
+@validate_hf_hub_args
+def post_lfs_batch_info(
+ upload_infos: Iterable[UploadInfo],
+ token: Optional[str],
+ repo_type: str,
+ repo_id: str,
+ revision: Optional[str] = None,
+ endpoint: Optional[str] = None,
+ headers: Optional[Dict[str, str]] = None,
+ transfers: Optional[List[str]] = None,
+) -> Tuple[List[dict], List[dict], Optional[str]]:
+ """
+ Requests the LFS batch endpoint to retrieve upload instructions
+
+ Learn more: https://github.com/git-lfs/git-lfs/blob/main/docs/api/batch.md
+
+ Args:
+ upload_infos (`Iterable` of `UploadInfo`):
+ `UploadInfo` for the files that are being uploaded, typically obtained
+ from `CommitOperationAdd.upload_info`
+ repo_type (`str`):
+ Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+ repo_id (`str`):
+ A namespace (user or an organization) and a repo name separated
+ by a `/`.
+ revision (`str`, *optional*):
+ The git revision to upload to.
+ headers (`dict`, *optional*):
+ Additional headers to include in the request
+ transfers (`list`, *optional*):
+ List of transfer methods to use. Defaults to ["basic", "multipart"].
+
+ Returns:
+ `LfsBatchInfo`: 3-tuple:
+ - First element is the list of upload instructions from the server
+ - Second element is a list of errors, if any
+ - Third element is the chosen transfer adapter if provided by the server (e.g. "basic", "multipart", "xet")
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If an argument is invalid or the server response is malformed.
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ If the server returned an error.
+ """
+ endpoint = endpoint if endpoint is not None else constants.ENDPOINT
+ url_prefix = ""
+ if repo_type in constants.REPO_TYPES_URL_PREFIXES:
+ url_prefix = constants.REPO_TYPES_URL_PREFIXES[repo_type]
+ batch_url = f"{endpoint}/{url_prefix}{repo_id}.git/info/lfs/objects/batch"
+ payload: Dict = {
+ "operation": "upload",
+ "transfers": transfers if transfers is not None else ["basic", "multipart"],
+ "objects": [
+ {
+ "oid": upload.sha256.hex(),
+ "size": upload.size,
+ }
+ for upload in upload_infos
+ ],
+ "hash_algo": "sha256",
+ }
+ if revision is not None:
+ payload["ref"] = {"name": unquote(revision)} # revision has been previously 'quoted'
+
+ headers = {
+ **LFS_HEADERS,
+ **build_hf_headers(token=token),
+ **(headers or {}),
+ }
+ resp = get_session().post(batch_url, headers=headers, json=payload)
+ hf_raise_for_status(resp)
+ batch_info = resp.json()
+
+ objects = batch_info.get("objects", None)
+ if not isinstance(objects, list):
+ raise ValueError("Malformed response from server")
+
+ chosen_transfer = batch_info.get("transfer")
+ chosen_transfer = chosen_transfer if isinstance(chosen_transfer, str) else None
+
+ return (
+ [_validate_batch_actions(obj) for obj in objects if "error" not in obj],
+ [_validate_batch_error(obj) for obj in objects if "error" in obj],
+ chosen_transfer,
+ )
+
+
+class PayloadPartT(TypedDict):
+ partNumber: int
+ etag: str
+
+
+class CompletionPayloadT(TypedDict):
+ """Payload that will be sent to the Hub when uploading multi-part."""
+
+ oid: str
+ parts: List[PayloadPartT]
+
+
+def lfs_upload(
+ operation: "CommitOperationAdd",
+ lfs_batch_action: Dict,
+ token: Optional[str] = None,
+ headers: Optional[Dict[str, str]] = None,
+ endpoint: Optional[str] = None,
+) -> None:
+ """
+ Handles uploading a given object to the Hub with the LFS protocol.
+
+ Can be a No-op if the content of the file is already present on the hub large file storage.
+
+ Args:
+ operation (`CommitOperationAdd`):
+ The add operation triggering this upload.
+ lfs_batch_action (`dict`):
+ Upload instructions from the LFS batch endpoint for this object. See [`~utils.lfs.post_lfs_batch_info`] for
+ more details.
+ headers (`dict`, *optional*):
+ Headers to include in the request, including authentication and user agent headers.
+
+ Raises:
+ [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ If `lfs_batch_action` is improperly formatted
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ If the upload resulted in an error
+ """
+ # 0. If LFS file is already present, skip upload
+ _validate_batch_actions(lfs_batch_action)
+ actions = lfs_batch_action.get("actions")
+ if actions is None:
+ # The file was already uploaded
+ logger.debug(f"Content of file {operation.path_in_repo} is already present upstream - skipping upload")
+ return
+
+ # 1. Validate server response (check required keys in dict)
+ upload_action = lfs_batch_action["actions"]["upload"]
+ _validate_lfs_action(upload_action)
+ verify_action = lfs_batch_action["actions"].get("verify")
+ if verify_action is not None:
+ _validate_lfs_action(verify_action)
+
+ # 2. Upload file (either single part or multi-part)
+ header = upload_action.get("header", {})
+ chunk_size = header.get("chunk_size")
+ upload_url = fix_hf_endpoint_in_url(upload_action["href"], endpoint=endpoint)
+ if chunk_size is not None:
+ try:
+ chunk_size = int(chunk_size)
+ except (ValueError, TypeError):
+ raise ValueError(
+ f"Malformed response from LFS batch endpoint: `chunk_size` should be an integer. Got '{chunk_size}'."
+ )
+ _upload_multi_part(operation=operation, header=header, chunk_size=chunk_size, upload_url=upload_url)
+ else:
+ _upload_single_part(operation=operation, upload_url=upload_url)
+
+ # 3. Verify upload went well
+ if verify_action is not None:
+ _validate_lfs_action(verify_action)
+ verify_url = fix_hf_endpoint_in_url(verify_action["href"], endpoint)
+ verify_resp = get_session().post(
+ verify_url,
+ headers=build_hf_headers(token=token, headers=headers),
+ json={"oid": operation.upload_info.sha256.hex(), "size": operation.upload_info.size},
+ )
+ hf_raise_for_status(verify_resp)
+ logger.debug(f"{operation.path_in_repo}: Upload successful")
+
+
+def _validate_lfs_action(lfs_action: dict):
+ """validates response from the LFS batch endpoint"""
+ if not (
+ isinstance(lfs_action.get("href"), str)
+ and (lfs_action.get("header") is None or isinstance(lfs_action.get("header"), dict))
+ ):
+ raise ValueError("lfs_action is improperly formatted")
+ return lfs_action
+
+
+def _validate_batch_actions(lfs_batch_actions: dict):
+ """validates response from the LFS batch endpoint"""
+ if not (isinstance(lfs_batch_actions.get("oid"), str) and isinstance(lfs_batch_actions.get("size"), int)):
+ raise ValueError("lfs_batch_actions is improperly formatted")
+
+ upload_action = lfs_batch_actions.get("actions", {}).get("upload")
+ verify_action = lfs_batch_actions.get("actions", {}).get("verify")
+ if upload_action is not None:
+ _validate_lfs_action(upload_action)
+ if verify_action is not None:
+ _validate_lfs_action(verify_action)
+ return lfs_batch_actions
+
+
+def _validate_batch_error(lfs_batch_error: dict):
+ """validates response from the LFS batch endpoint"""
+ if not (isinstance(lfs_batch_error.get("oid"), str) and isinstance(lfs_batch_error.get("size"), int)):
+ raise ValueError("lfs_batch_error is improperly formatted")
+ error_info = lfs_batch_error.get("error")
+ if not (
+ isinstance(error_info, dict)
+ and isinstance(error_info.get("message"), str)
+ and isinstance(error_info.get("code"), int)
+ ):
+ raise ValueError("lfs_batch_error is improperly formatted")
+ return lfs_batch_error
+
+
+def _upload_single_part(operation: "CommitOperationAdd", upload_url: str) -> None:
+ """
+ Uploads `fileobj` as a single PUT HTTP request (basic LFS transfer protocol)
+
+ Args:
+ upload_url (`str`):
+ The URL to PUT the file to.
+ fileobj:
+ The file-like object holding the data to upload.
+
+ Returns: `requests.Response`
+
+ Raises:
+ [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ If the upload resulted in an error.
+ """
+ with operation.as_file(with_tqdm=True) as fileobj:
+ # S3 might raise a transient 500 error -> let's retry if that happens
+ response = http_backoff("PUT", upload_url, data=fileobj)
+ hf_raise_for_status(response)
+
+
+def _upload_multi_part(operation: "CommitOperationAdd", header: Dict, chunk_size: int, upload_url: str) -> None:
+ """
+ Uploads file using HF multipart LFS transfer protocol.
+ """
+ # 1. Get upload URLs for each part
+ sorted_parts_urls = _get_sorted_parts_urls(header=header, upload_info=operation.upload_info, chunk_size=chunk_size)
+
+ # 2. Upload parts (either with hf_transfer or in pure Python)
+ use_hf_transfer = constants.HF_HUB_ENABLE_HF_TRANSFER
+ if (
+ constants.HF_HUB_ENABLE_HF_TRANSFER
+ and not isinstance(operation.path_or_fileobj, str)
+ and not isinstance(operation.path_or_fileobj, Path)
+ ):
+ warnings.warn(
+ "hf_transfer is enabled but does not support uploading from bytes or BinaryIO, falling back to regular"
+ " upload"
+ )
+ use_hf_transfer = False
+
+ response_headers = (
+ _upload_parts_hf_transfer(operation=operation, sorted_parts_urls=sorted_parts_urls, chunk_size=chunk_size)
+ if use_hf_transfer
+ else _upload_parts_iteratively(operation=operation, sorted_parts_urls=sorted_parts_urls, chunk_size=chunk_size)
+ )
+
+ # 3. Send completion request
+ completion_res = get_session().post(
+ upload_url,
+ json=_get_completion_payload(response_headers, operation.upload_info.sha256.hex()),
+ headers=LFS_HEADERS,
+ )
+ hf_raise_for_status(completion_res)
+
+
+def _get_sorted_parts_urls(header: Dict, upload_info: UploadInfo, chunk_size: int) -> List[str]:
+ sorted_part_upload_urls = [
+ upload_url
+ for _, upload_url in sorted(
+ [
+ (int(part_num, 10), upload_url)
+ for part_num, upload_url in header.items()
+ if part_num.isdigit() and len(part_num) > 0
+ ],
+ key=lambda t: t[0],
+ )
+ ]
+ num_parts = len(sorted_part_upload_urls)
+ if num_parts != ceil(upload_info.size / chunk_size):
+ raise ValueError("Invalid server response to upload large LFS file")
+ return sorted_part_upload_urls
+
+
+def _get_completion_payload(response_headers: List[Dict], oid: str) -> CompletionPayloadT:
+ parts: List[PayloadPartT] = []
+ for part_number, header in enumerate(response_headers):
+ etag = header.get("etag")
+ if etag is None or etag == "":
+ raise ValueError(f"Invalid etag (`{etag}`) returned for part {part_number + 1}")
+ parts.append(
+ {
+ "partNumber": part_number + 1,
+ "etag": etag,
+ }
+ )
+ return {"oid": oid, "parts": parts}
+
+
+def _upload_parts_iteratively(
+ operation: "CommitOperationAdd", sorted_parts_urls: List[str], chunk_size: int
+) -> List[Dict]:
+ headers = []
+ with operation.as_file(with_tqdm=True) as fileobj:
+ for part_idx, part_upload_url in enumerate(sorted_parts_urls):
+ with SliceFileObj(
+ fileobj,
+ seek_from=chunk_size * part_idx,
+ read_limit=chunk_size,
+ ) as fileobj_slice:
+ # S3 might raise a transient 500 error -> let's retry if that happens
+ part_upload_res = http_backoff("PUT", part_upload_url, data=fileobj_slice)
+ hf_raise_for_status(part_upload_res)
+ headers.append(part_upload_res.headers)
+ return headers # type: ignore
+
+
+def _upload_parts_hf_transfer(
+ operation: "CommitOperationAdd", sorted_parts_urls: List[str], chunk_size: int
+) -> List[Dict]:
+ # Upload file using an external Rust-based package. Upload is faster but support less features (no progress bars).
+ try:
+ from hf_transfer import multipart_upload
+ except ImportError:
+ raise ValueError(
+ "Fast uploading using 'hf_transfer' is enabled (HF_HUB_ENABLE_HF_TRANSFER=1) but 'hf_transfer' package is"
+ " not available in your environment. Try `pip install hf_transfer`."
+ )
+
+ supports_callback = "callback" in inspect.signature(multipart_upload).parameters
+ if not supports_callback:
+ warnings.warn(
+ "You are using an outdated version of `hf_transfer`. Consider upgrading to latest version to enable progress bars using `pip install -U hf_transfer`."
+ )
+
+ total = operation.upload_info.size
+ desc = operation.path_in_repo
+ if len(desc) > 40:
+ desc = f"(…){desc[-40:]}"
+
+ with tqdm(
+ unit="B",
+ unit_scale=True,
+ total=total,
+ initial=0,
+ desc=desc,
+ disable=is_tqdm_disabled(logger.getEffectiveLevel()),
+ name="huggingface_hub.lfs_upload",
+ ) as progress:
+ try:
+ output = multipart_upload(
+ file_path=operation.path_or_fileobj,
+ parts_urls=sorted_parts_urls,
+ chunk_size=chunk_size,
+ max_files=128,
+ parallel_failures=127, # could be removed
+ max_retries=5,
+ **({"callback": progress.update} if supports_callback else {}),
+ )
+ except Exception as e:
+ raise RuntimeError(
+ "An error occurred while uploading using `hf_transfer`. Consider disabling HF_HUB_ENABLE_HF_TRANSFER for"
+ " better error handling."
+ ) from e
+ if not supports_callback:
+ progress.update(total)
+ return output
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard.py
new file mode 100644
index 0000000000000000000000000000000000000000..357935c3f1831df2afc86a30f82f10fa8039a225
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard.py
@@ -0,0 +1,827 @@
+import os
+import re
+from pathlib import Path
+from typing import Any, Dict, Literal, Optional, Type, Union
+
+import requests
+import yaml
+
+from huggingface_hub.file_download import hf_hub_download
+from huggingface_hub.hf_api import upload_file
+from huggingface_hub.repocard_data import (
+ CardData,
+ DatasetCardData,
+ EvalResult,
+ ModelCardData,
+ SpaceCardData,
+ eval_results_to_model_index,
+ model_index_to_eval_results,
+)
+from huggingface_hub.utils import get_session, is_jinja_available, yaml_dump
+
+from . import constants
+from .errors import EntryNotFoundError
+from .utils import SoftTemporaryDirectory, logging, validate_hf_hub_args
+
+
+logger = logging.get_logger(__name__)
+
+
+TEMPLATE_MODELCARD_PATH = Path(__file__).parent / "templates" / "modelcard_template.md"
+TEMPLATE_DATASETCARD_PATH = Path(__file__).parent / "templates" / "datasetcard_template.md"
+
+# exact same regex as in the Hub server. Please keep in sync.
+# See https://github.com/huggingface/moon-landing/blob/main/server/lib/ViewMarkdown.ts#L18
+REGEX_YAML_BLOCK = re.compile(r"^(\s*---[\r\n]+)([\S\s]*?)([\r\n]+---(\r\n|\n|$))")
+
+
+class RepoCard:
+ card_data_class = CardData
+ default_template_path = TEMPLATE_MODELCARD_PATH
+ repo_type = "model"
+
+ def __init__(self, content: str, ignore_metadata_errors: bool = False):
+ """Initialize a RepoCard from string content. The content should be a
+ Markdown file with a YAML block at the beginning and a Markdown body.
+
+ Args:
+ content (`str`): The content of the Markdown file.
+
+ Example:
+ ```python
+ >>> from huggingface_hub.repocard import RepoCard
+ >>> text = '''
+ ... ---
+ ... language: en
+ ... license: mit
+ ... ---
+ ...
+ ... # My repo
+ ... '''
+ >>> card = RepoCard(text)
+ >>> card.data.to_dict()
+ {'language': 'en', 'license': 'mit'}
+ >>> card.text
+ '\\n# My repo\\n'
+
+ ```
+ > [!TIP]
+ > Raises the following error:
+ >
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > when the content of the repo card metadata is not a dictionary.
+ """
+
+ # Set the content of the RepoCard, as well as underlying .data and .text attributes.
+ # See the `content` property setter for more details.
+ self.ignore_metadata_errors = ignore_metadata_errors
+ self.content = content
+
+ @property
+ def content(self):
+ """The content of the RepoCard, including the YAML block and the Markdown body."""
+ line_break = _detect_line_ending(self._content) or "\n"
+ return f"---{line_break}{self.data.to_yaml(line_break=line_break, original_order=self._original_order)}{line_break}---{line_break}{self.text}"
+
+ @content.setter
+ def content(self, content: str):
+ """Set the content of the RepoCard."""
+ self._content = content
+
+ match = REGEX_YAML_BLOCK.search(content)
+ if match:
+ # Metadata found in the YAML block
+ yaml_block = match.group(2)
+ self.text = content[match.end() :]
+ data_dict = yaml.safe_load(yaml_block)
+
+ if data_dict is None:
+ data_dict = {}
+
+ # The YAML block's data should be a dictionary
+ if not isinstance(data_dict, dict):
+ raise ValueError("repo card metadata block should be a dict")
+ else:
+ # Model card without metadata... create empty metadata
+ logger.warning("Repo card metadata block was not found. Setting CardData to empty.")
+ data_dict = {}
+ self.text = content
+
+ self.data = self.card_data_class(**data_dict, ignore_metadata_errors=self.ignore_metadata_errors)
+ self._original_order = list(data_dict.keys())
+
+ def __str__(self):
+ return self.content
+
+ def save(self, filepath: Union[Path, str]):
+ r"""Save a RepoCard to a file.
+
+ Args:
+ filepath (`Union[Path, str]`): Filepath to the markdown file to save.
+
+ Example:
+ ```python
+ >>> from huggingface_hub.repocard import RepoCard
+ >>> card = RepoCard("---\nlanguage: en\n---\n# This is a test repo card")
+ >>> card.save("/tmp/test.md")
+
+ ```
+ """
+ filepath = Path(filepath)
+ filepath.parent.mkdir(parents=True, exist_ok=True)
+ # Preserve newlines as in the existing file.
+ with open(filepath, mode="w", newline="", encoding="utf-8") as f:
+ f.write(str(self))
+
+ @classmethod
+ def load(
+ cls,
+ repo_id_or_path: Union[str, Path],
+ repo_type: Optional[str] = None,
+ token: Optional[str] = None,
+ ignore_metadata_errors: bool = False,
+ ):
+ """Initialize a RepoCard from a Hugging Face Hub repo's README.md or a local filepath.
+
+ Args:
+ repo_id_or_path (`Union[str, Path]`):
+ The repo ID associated with a Hugging Face Hub repo or a local filepath.
+ repo_type (`str`, *optional*):
+ The type of Hugging Face repo to push to. Defaults to None, which will use use "model". Other options
+ are "dataset" and "space". Not used when loading from a local filepath. If this is called from a child
+ class, the default value will be the child class's `repo_type`.
+ token (`str`, *optional*):
+ Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token.
+ ignore_metadata_errors (`str`):
+ If True, errors while parsing the metadata section will be ignored. Some information might be lost during
+ the process. Use it at your own risk.
+
+ Returns:
+ [`huggingface_hub.repocard.RepoCard`]: The RepoCard (or subclass) initialized from the repo's
+ README.md file or filepath.
+
+ Example:
+ ```python
+ >>> from huggingface_hub.repocard import RepoCard
+ >>> card = RepoCard.load("nateraw/food")
+ >>> assert card.data.tags == ["generated_from_trainer", "image-classification", "pytorch"]
+
+ ```
+ """
+
+ if Path(repo_id_or_path).is_file():
+ card_path = Path(repo_id_or_path)
+ elif isinstance(repo_id_or_path, str):
+ card_path = Path(
+ hf_hub_download(
+ repo_id_or_path,
+ constants.REPOCARD_NAME,
+ repo_type=repo_type or cls.repo_type,
+ token=token,
+ )
+ )
+ else:
+ raise ValueError(f"Cannot load RepoCard: path not found on disk ({repo_id_or_path}).")
+
+ # Preserve newlines in the existing file.
+ with card_path.open(mode="r", newline="", encoding="utf-8") as f:
+ return cls(f.read(), ignore_metadata_errors=ignore_metadata_errors)
+
+ def validate(self, repo_type: Optional[str] = None):
+ """Validates card against Hugging Face Hub's card validation logic.
+ Using this function requires access to the internet, so it is only called
+ internally by [`huggingface_hub.repocard.RepoCard.push_to_hub`].
+
+ Args:
+ repo_type (`str`, *optional*, defaults to "model"):
+ The type of Hugging Face repo to push to. Options are "model", "dataset", and "space".
+ If this function is called from a child class, the default will be the child class's `repo_type`.
+
+ > [!TIP]
+ > Raises the following errors:
+ >
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if the card fails validation checks.
+ > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+ > if the request to the Hub API fails for any other reason.
+ """
+
+ # If repo type is provided, otherwise, use the repo type of the card.
+ repo_type = repo_type or self.repo_type
+
+ body = {
+ "repoType": repo_type,
+ "content": str(self),
+ }
+ headers = {"Accept": "text/plain"}
+
+ try:
+ r = get_session().post("https://huggingface.co/api/validate-yaml", body, headers=headers)
+ r.raise_for_status()
+ except requests.exceptions.HTTPError as exc:
+ if r.status_code == 400:
+ raise ValueError(r.text)
+ else:
+ raise exc
+
+ def push_to_hub(
+ self,
+ repo_id: str,
+ token: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: Optional[bool] = None,
+ parent_commit: Optional[str] = None,
+ ):
+ """Push a RepoCard to a Hugging Face Hub repo.
+
+ Args:
+ repo_id (`str`):
+ The repo ID of the Hugging Face Hub repo to push to. Example: "nateraw/food".
+ token (`str`, *optional*):
+ Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to
+ the stored token.
+ repo_type (`str`, *optional*, defaults to "model"):
+ The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this
+ function is called by a child class, it will default to the child class's `repo_type`.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit.
+ commit_description (`str`, *optional*)
+ The description of the generated commit.
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the `"main"` branch.
+ create_pr (`bool`, *optional*):
+ Whether or not to create a Pull Request with this commit. Defaults to `False`.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ Returns:
+ `str`: URL of the commit which updated the card metadata.
+ """
+
+ # If repo type is provided, otherwise, use the repo type of the card.
+ repo_type = repo_type or self.repo_type
+
+ # Validate card before pushing to hub
+ self.validate(repo_type=repo_type)
+
+ with SoftTemporaryDirectory() as tmpdir:
+ tmp_path = Path(tmpdir) / constants.REPOCARD_NAME
+ tmp_path.write_text(str(self), encoding="utf-8")
+ url = upload_file(
+ path_or_fileobj=str(tmp_path),
+ path_in_repo=constants.REPOCARD_NAME,
+ repo_id=repo_id,
+ token=token,
+ repo_type=repo_type,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ create_pr=create_pr,
+ revision=revision,
+ parent_commit=parent_commit,
+ )
+ return url
+
+ @classmethod
+ def from_template(
+ cls,
+ card_data: CardData,
+ template_path: Optional[str] = None,
+ template_str: Optional[str] = None,
+ **template_kwargs,
+ ):
+ """Initialize a RepoCard from a template. By default, it uses the default template.
+
+ Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+ Args:
+ card_data (`huggingface_hub.CardData`):
+ A huggingface_hub.CardData instance containing the metadata you want to include in the YAML
+ header of the repo card on the Hugging Face Hub.
+ template_path (`str`, *optional*):
+ A path to a markdown file with optional Jinja template variables that can be filled
+ in with `template_kwargs`. Defaults to the default template.
+
+ Returns:
+ [`huggingface_hub.repocard.RepoCard`]: A RepoCard instance with the specified card data and content from the
+ template.
+ """
+ if is_jinja_available():
+ import jinja2
+ else:
+ raise ImportError(
+ "Using RepoCard.from_template requires Jinja2 to be installed. Please"
+ " install it with `pip install Jinja2`."
+ )
+
+ kwargs = card_data.to_dict().copy()
+ kwargs.update(template_kwargs) # Template_kwargs have priority
+
+ if template_path is not None:
+ template_str = Path(template_path).read_text()
+ if template_str is None:
+ template_str = Path(cls.default_template_path).read_text()
+ template = jinja2.Template(template_str)
+ content = template.render(card_data=card_data.to_yaml(), **kwargs)
+ return cls(content)
+
+
+class ModelCard(RepoCard):
+ card_data_class = ModelCardData
+ default_template_path = TEMPLATE_MODELCARD_PATH
+ repo_type = "model"
+
+ @classmethod
+ def from_template( # type: ignore # violates Liskov property but easier to use
+ cls,
+ card_data: ModelCardData,
+ template_path: Optional[str] = None,
+ template_str: Optional[str] = None,
+ **template_kwargs,
+ ):
+ """Initialize a ModelCard from a template. By default, it uses the default template, which can be found here:
+ https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md
+
+ Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+ Args:
+ card_data (`huggingface_hub.ModelCardData`):
+ A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML
+ header of the model card on the Hugging Face Hub.
+ template_path (`str`, *optional*):
+ A path to a markdown file with optional Jinja template variables that can be filled
+ in with `template_kwargs`. Defaults to the default template.
+
+ Returns:
+ [`huggingface_hub.ModelCard`]: A ModelCard instance with the specified card data and content from the
+ template.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import ModelCard, ModelCardData, EvalResult
+
+ >>> # Using the Default Template
+ >>> card_data = ModelCardData(
+ ... language='en',
+ ... license='mit',
+ ... library_name='timm',
+ ... tags=['image-classification', 'resnet'],
+ ... datasets=['beans'],
+ ... metrics=['accuracy'],
+ ... )
+ >>> card = ModelCard.from_template(
+ ... card_data,
+ ... model_description='This model does x + y...'
+ ... )
+
+ >>> # Including Evaluation Results
+ >>> card_data = ModelCardData(
+ ... language='en',
+ ... tags=['image-classification', 'resnet'],
+ ... eval_results=[
+ ... EvalResult(
+ ... task_type='image-classification',
+ ... dataset_type='beans',
+ ... dataset_name='Beans',
+ ... metric_type='accuracy',
+ ... metric_value=0.9,
+ ... ),
+ ... ],
+ ... model_name='my-cool-model',
+ ... )
+ >>> card = ModelCard.from_template(card_data)
+
+ >>> # Using a Custom Template
+ >>> card_data = ModelCardData(
+ ... language='en',
+ ... tags=['image-classification', 'resnet']
+ ... )
+ >>> card = ModelCard.from_template(
+ ... card_data=card_data,
+ ... template_path='./src/huggingface_hub/templates/modelcard_template.md',
+ ... custom_template_var='custom value', # will be replaced in template if it exists
+ ... )
+
+ ```
+ """
+ return super().from_template(card_data, template_path, template_str, **template_kwargs)
+
+
+class DatasetCard(RepoCard):
+ card_data_class = DatasetCardData
+ default_template_path = TEMPLATE_DATASETCARD_PATH
+ repo_type = "dataset"
+
+ @classmethod
+ def from_template( # type: ignore # violates Liskov property but easier to use
+ cls,
+ card_data: DatasetCardData,
+ template_path: Optional[str] = None,
+ template_str: Optional[str] = None,
+ **template_kwargs,
+ ):
+ """Initialize a DatasetCard from a template. By default, it uses the default template, which can be found here:
+ https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md
+
+ Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+ Args:
+ card_data (`huggingface_hub.DatasetCardData`):
+ A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML
+ header of the dataset card on the Hugging Face Hub.
+ template_path (`str`, *optional*):
+ A path to a markdown file with optional Jinja template variables that can be filled
+ in with `template_kwargs`. Defaults to the default template.
+
+ Returns:
+ [`huggingface_hub.DatasetCard`]: A DatasetCard instance with the specified card data and content from the
+ template.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import DatasetCard, DatasetCardData
+
+ >>> # Using the Default Template
+ >>> card_data = DatasetCardData(
+ ... language='en',
+ ... license='mit',
+ ... annotations_creators='crowdsourced',
+ ... task_categories=['text-classification'],
+ ... task_ids=['sentiment-classification', 'text-scoring'],
+ ... multilinguality='monolingual',
+ ... pretty_name='My Text Classification Dataset',
+ ... )
+ >>> card = DatasetCard.from_template(
+ ... card_data,
+ ... pretty_name=card_data.pretty_name,
+ ... )
+
+ >>> # Using a Custom Template
+ >>> card_data = DatasetCardData(
+ ... language='en',
+ ... license='mit',
+ ... )
+ >>> card = DatasetCard.from_template(
+ ... card_data=card_data,
+ ... template_path='./src/huggingface_hub/templates/datasetcard_template.md',
+ ... custom_template_var='custom value', # will be replaced in template if it exists
+ ... )
+
+ ```
+ """
+ return super().from_template(card_data, template_path, template_str, **template_kwargs)
+
+
+class SpaceCard(RepoCard):
+ card_data_class = SpaceCardData
+ default_template_path = TEMPLATE_MODELCARD_PATH
+ repo_type = "space"
+
+
+def _detect_line_ending(content: str) -> Literal["\r", "\n", "\r\n", None]: # noqa: F722
+ """Detect the line ending of a string. Used by RepoCard to avoid making huge diff on newlines.
+
+ Uses same implementation as in Hub server, keep it in sync.
+
+ Returns:
+ str: The detected line ending of the string.
+ """
+ cr = content.count("\r")
+ lf = content.count("\n")
+ crlf = content.count("\r\n")
+ if cr + lf == 0:
+ return None
+ if crlf == cr and crlf == lf:
+ return "\r\n"
+ if cr > lf:
+ return "\r"
+ else:
+ return "\n"
+
+
+def metadata_load(local_path: Union[str, Path]) -> Optional[Dict]:
+ content = Path(local_path).read_text()
+ match = REGEX_YAML_BLOCK.search(content)
+ if match:
+ yaml_block = match.group(2)
+ data = yaml.safe_load(yaml_block)
+ if data is None or isinstance(data, dict):
+ return data
+ raise ValueError("repo card metadata block should be a dict")
+ else:
+ return None
+
+
+def metadata_save(local_path: Union[str, Path], data: Dict) -> None:
+ """
+ Save the metadata dict in the upper YAML part Trying to preserve newlines as
+ in the existing file. Docs about open() with newline="" parameter:
+ https://docs.python.org/3/library/functions.html?highlight=open#open Does
+ not work with "^M" linebreaks, which are replaced by \n
+ """
+ line_break = "\n"
+ content = ""
+ # try to detect existing newline character
+ if os.path.exists(local_path):
+ with open(local_path, "r", newline="", encoding="utf8") as readme:
+ content = readme.read()
+ if isinstance(readme.newlines, tuple):
+ line_break = readme.newlines[0]
+ elif isinstance(readme.newlines, str):
+ line_break = readme.newlines
+
+ # creates a new file if it not
+ with open(local_path, "w", newline="", encoding="utf8") as readme:
+ data_yaml = yaml_dump(data, sort_keys=False, line_break=line_break)
+ # sort_keys: keep dict order
+ match = REGEX_YAML_BLOCK.search(content)
+ if match:
+ output = content[: match.start()] + f"---{line_break}{data_yaml}---{line_break}" + content[match.end() :]
+ else:
+ output = f"---{line_break}{data_yaml}---{line_break}{content}"
+
+ readme.write(output)
+ readme.close()
+
+
+def metadata_eval_result(
+ *,
+ model_pretty_name: str,
+ task_pretty_name: str,
+ task_id: str,
+ metrics_pretty_name: str,
+ metrics_id: str,
+ metrics_value: Any,
+ dataset_pretty_name: str,
+ dataset_id: str,
+ metrics_config: Optional[str] = None,
+ metrics_verified: bool = False,
+ dataset_config: Optional[str] = None,
+ dataset_split: Optional[str] = None,
+ dataset_revision: Optional[str] = None,
+ metrics_verification_token: Optional[str] = None,
+) -> Dict:
+ """
+ Creates a metadata dict with the result from a model evaluated on a dataset.
+
+ Args:
+ model_pretty_name (`str`):
+ The name of the model in natural language.
+ task_pretty_name (`str`):
+ The name of a task in natural language.
+ task_id (`str`):
+ Example: automatic-speech-recognition. A task id.
+ metrics_pretty_name (`str`):
+ A name for the metric in natural language. Example: Test WER.
+ metrics_id (`str`):
+ Example: wer. A metric id from https://hf.co/metrics.
+ metrics_value (`Any`):
+ The value from the metric. Example: 20.0 or "20.0 ± 1.2".
+ dataset_pretty_name (`str`):
+ The name of the dataset in natural language.
+ dataset_id (`str`):
+ Example: common_voice. A dataset id from https://hf.co/datasets.
+ metrics_config (`str`, *optional*):
+ The name of the metric configuration used in `load_metric()`.
+ Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
+ metrics_verified (`bool`, *optional*, defaults to `False`):
+ Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
+ dataset_config (`str`, *optional*):
+ Example: fr. The name of the dataset configuration used in `load_dataset()`.
+ dataset_split (`str`, *optional*):
+ Example: test. The name of the dataset split used in `load_dataset()`.
+ dataset_revision (`str`, *optional*):
+ Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision
+ used in `load_dataset()`.
+ metrics_verification_token (`bool`, *optional*):
+ A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
+
+ Returns:
+ `dict`: a metadata dict with the result from a model evaluated on a dataset.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import metadata_eval_result
+ >>> results = metadata_eval_result(
+ ... model_pretty_name="RoBERTa fine-tuned on ReactionGIF",
+ ... task_pretty_name="Text Classification",
+ ... task_id="text-classification",
+ ... metrics_pretty_name="Accuracy",
+ ... metrics_id="accuracy",
+ ... metrics_value=0.2662102282047272,
+ ... dataset_pretty_name="ReactionJPEG",
+ ... dataset_id="julien-c/reactionjpeg",
+ ... dataset_config="default",
+ ... dataset_split="test",
+ ... )
+ >>> results == {
+ ... 'model-index': [
+ ... {
+ ... 'name': 'RoBERTa fine-tuned on ReactionGIF',
+ ... 'results': [
+ ... {
+ ... 'task': {
+ ... 'type': 'text-classification',
+ ... 'name': 'Text Classification'
+ ... },
+ ... 'dataset': {
+ ... 'name': 'ReactionJPEG',
+ ... 'type': 'julien-c/reactionjpeg',
+ ... 'config': 'default',
+ ... 'split': 'test'
+ ... },
+ ... 'metrics': [
+ ... {
+ ... 'type': 'accuracy',
+ ... 'value': 0.2662102282047272,
+ ... 'name': 'Accuracy',
+ ... 'verified': False
+ ... }
+ ... ]
+ ... }
+ ... ]
+ ... }
+ ... ]
+ ... }
+ True
+
+ ```
+ """
+
+ return {
+ "model-index": eval_results_to_model_index(
+ model_name=model_pretty_name,
+ eval_results=[
+ EvalResult(
+ task_name=task_pretty_name,
+ task_type=task_id,
+ metric_name=metrics_pretty_name,
+ metric_type=metrics_id,
+ metric_value=metrics_value,
+ dataset_name=dataset_pretty_name,
+ dataset_type=dataset_id,
+ metric_config=metrics_config,
+ verified=metrics_verified,
+ verify_token=metrics_verification_token,
+ dataset_config=dataset_config,
+ dataset_split=dataset_split,
+ dataset_revision=dataset_revision,
+ )
+ ],
+ )
+ }
+
+
+@validate_hf_hub_args
+def metadata_update(
+ repo_id: str,
+ metadata: Dict,
+ *,
+ repo_type: Optional[str] = None,
+ overwrite: bool = False,
+ token: Optional[str] = None,
+ commit_message: Optional[str] = None,
+ commit_description: Optional[str] = None,
+ revision: Optional[str] = None,
+ create_pr: bool = False,
+ parent_commit: Optional[str] = None,
+) -> str:
+ """
+ Updates the metadata in the README.md of a repository on the Hugging Face Hub.
+ If the README.md file doesn't exist yet, a new one is created with metadata and an
+ the default ModelCard or DatasetCard template. For `space` repo, an error is thrown
+ as a Space cannot exist without a `README.md` file.
+
+ Args:
+ repo_id (`str`):
+ The name of the repository.
+ metadata (`dict`):
+ A dictionary containing the metadata to be updated.
+ repo_type (`str`, *optional*):
+ Set to `"dataset"` or `"space"` if updating to a dataset or space,
+ `None` or `"model"` if updating to a model. Default is `None`.
+ overwrite (`bool`, *optional*, defaults to `False`):
+ If set to `True` an existing field can be overwritten, otherwise
+ attempting to overwrite an existing field will cause an error.
+ token (`str`, *optional*):
+ The Hugging Face authentication token.
+ commit_message (`str`, *optional*):
+ The summary / title / first line of the generated commit. Defaults to
+ `f"Update metadata with huggingface_hub"`
+ commit_description (`str` *optional*)
+ The description of the generated commit
+ revision (`str`, *optional*):
+ The git revision to commit from. Defaults to the head of the
+ `"main"` branch.
+ create_pr (`boolean`, *optional*):
+ Whether or not to create a Pull Request from `revision` with that commit.
+ Defaults to `False`.
+ parent_commit (`str`, *optional*):
+ The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+ If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+ If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+ Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+ especially useful if the repo is updated / committed to concurrently.
+ Returns:
+ `str`: URL of the commit which updated the card metadata.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import metadata_update
+ >>> metadata = {'model-index': [{'name': 'RoBERTa fine-tuned on ReactionGIF',
+ ... 'results': [{'dataset': {'name': 'ReactionGIF',
+ ... 'type': 'julien-c/reactiongif'},
+ ... 'metrics': [{'name': 'Recall',
+ ... 'type': 'recall',
+ ... 'value': 0.7762102282047272}],
+ ... 'task': {'name': 'Text Classification',
+ ... 'type': 'text-classification'}}]}]}
+ >>> url = metadata_update("hf-internal-testing/reactiongif-roberta-card", metadata)
+
+ ```
+ """
+ commit_message = commit_message if commit_message is not None else "Update metadata with huggingface_hub"
+
+ # Card class given repo_type
+ card_class: Type[RepoCard]
+ if repo_type is None or repo_type == "model":
+ card_class = ModelCard
+ elif repo_type == "dataset":
+ card_class = DatasetCard
+ elif repo_type == "space":
+ card_class = RepoCard
+ else:
+ raise ValueError(f"Unknown repo_type: {repo_type}")
+
+ # Either load repo_card from the Hub or create an empty one.
+ # NOTE: Will not create the repo if it doesn't exist.
+ try:
+ card = card_class.load(repo_id, token=token, repo_type=repo_type)
+ except EntryNotFoundError:
+ if repo_type == "space":
+ raise ValueError("Cannot update metadata on a Space that doesn't contain a `README.md` file.")
+
+ # Initialize a ModelCard or DatasetCard from default template and no data.
+ # Cast to the concrete expected card type to satisfy type checkers.
+ card = card_class.from_template(CardData()) # type: ignore[return-value]
+
+ for key, value in metadata.items():
+ if key == "model-index":
+ # if the new metadata doesn't include a name, either use existing one or repo name
+ if "name" not in value[0]:
+ value[0]["name"] = getattr(card, "model_name", repo_id)
+ model_name, new_results = model_index_to_eval_results(value)
+ if card.data.eval_results is None:
+ card.data.eval_results = new_results
+ card.data.model_name = model_name
+ else:
+ existing_results = card.data.eval_results
+
+ # Iterate over new results
+ # Iterate over existing results
+ # If both results describe the same metric but value is different:
+ # If overwrite=True: overwrite the metric value
+ # Else: raise ValueError
+ # Else: append new result to existing ones.
+ for new_result in new_results:
+ result_found = False
+ for existing_result in existing_results:
+ if new_result.is_equal_except_value(existing_result):
+ if new_result != existing_result and not overwrite:
+ raise ValueError(
+ "You passed a new value for the existing metric"
+ f" 'name: {new_result.metric_name}, type: "
+ f"{new_result.metric_type}'. Set `overwrite=True`"
+ " to overwrite existing metrics."
+ )
+ result_found = True
+ existing_result.metric_value = new_result.metric_value
+ if existing_result.verified is True:
+ existing_result.verify_token = new_result.verify_token
+ if not result_found:
+ card.data.eval_results.append(new_result)
+ else:
+ # Any metadata that is not a result metric
+ if card.data.get(key) is not None and not overwrite and card.data.get(key) != value:
+ raise ValueError(
+ f"You passed a new value for the existing meta data field '{key}'."
+ " Set `overwrite=True` to overwrite existing metadata."
+ )
+ else:
+ card.data[key] = value
+
+ return card.push_to_hub(
+ repo_id,
+ token=token,
+ repo_type=repo_type,
+ commit_message=commit_message,
+ commit_description=commit_description,
+ create_pr=create_pr,
+ revision=revision,
+ parent_commit=parent_commit,
+ )
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard_data.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..62215f2274e482d4ed69a1d6deeafdf34fc5a6a4
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repocard_data.py
@@ -0,0 +1,770 @@
+import copy
+from collections import defaultdict
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional, Tuple, Union
+
+from huggingface_hub.utils import logging, yaml_dump
+
+
+logger = logging.get_logger(__name__)
+
+
+@dataclass
+class EvalResult:
+ """
+ Flattened representation of individual evaluation results found in model-index of Model Cards.
+
+ For more information on the model-index spec, see https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1.
+
+ Args:
+ task_type (`str`):
+ The task identifier. Example: "image-classification".
+ dataset_type (`str`):
+ The dataset identifier. Example: "common_voice". Use dataset id from https://hf.co/datasets.
+ dataset_name (`str`):
+ A pretty name for the dataset. Example: "Common Voice (French)".
+ metric_type (`str`):
+ The metric identifier. Example: "wer". Use metric id from https://hf.co/metrics.
+ metric_value (`Any`):
+ The metric value. Example: 0.9 or "20.0 ± 1.2".
+ task_name (`str`, *optional*):
+ A pretty name for the task. Example: "Speech Recognition".
+ dataset_config (`str`, *optional*):
+ The name of the dataset configuration used in `load_dataset()`.
+ Example: fr in `load_dataset("common_voice", "fr")`. See the `datasets` docs for more info:
+ https://hf.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name
+ dataset_split (`str`, *optional*):
+ The split used in `load_dataset()`. Example: "test".
+ dataset_revision (`str`, *optional*):
+ The revision (AKA Git Sha) of the dataset used in `load_dataset()`.
+ Example: 5503434ddd753f426f4b38109466949a1217c2bb
+ dataset_args (`Dict[str, Any]`, *optional*):
+ The arguments passed during `Metric.compute()`. Example for `bleu`: `{"max_order": 4}`
+ metric_name (`str`, *optional*):
+ A pretty name for the metric. Example: "Test WER".
+ metric_config (`str`, *optional*):
+ The name of the metric configuration used in `load_metric()`.
+ Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
+ See the `datasets` docs for more info: https://huggingface.co/docs/datasets/v2.1.0/en/loading#load-configurations
+ metric_args (`Dict[str, Any]`, *optional*):
+ The arguments passed during `Metric.compute()`. Example for `bleu`: max_order: 4
+ verified (`bool`, *optional*):
+ Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
+ verify_token (`str`, *optional*):
+ A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
+ source_name (`str`, *optional*):
+ The name of the source of the evaluation result. Example: "Open LLM Leaderboard".
+ source_url (`str`, *optional*):
+ The URL of the source of the evaluation result. Example: "https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard".
+ """
+
+ # Required
+
+ # The task identifier
+ # Example: automatic-speech-recognition
+ task_type: str
+
+ # The dataset identifier
+ # Example: common_voice. Use dataset id from https://hf.co/datasets
+ dataset_type: str
+
+ # A pretty name for the dataset.
+ # Example: Common Voice (French)
+ dataset_name: str
+
+ # The metric identifier
+ # Example: wer. Use metric id from https://hf.co/metrics
+ metric_type: str
+
+ # Value of the metric.
+ # Example: 20.0 or "20.0 ± 1.2"
+ metric_value: Any
+
+ # Optional
+
+ # A pretty name for the task.
+ # Example: Speech Recognition
+ task_name: Optional[str] = None
+
+ # The name of the dataset configuration used in `load_dataset()`.
+ # Example: fr in `load_dataset("common_voice", "fr")`.
+ # See the `datasets` docs for more info:
+ # https://huggingface.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name
+ dataset_config: Optional[str] = None
+
+ # The split used in `load_dataset()`.
+ # Example: test
+ dataset_split: Optional[str] = None
+
+ # The revision (AKA Git Sha) of the dataset used in `load_dataset()`.
+ # Example: 5503434ddd753f426f4b38109466949a1217c2bb
+ dataset_revision: Optional[str] = None
+
+ # The arguments passed during `Metric.compute()`.
+ # Example for `bleu`: max_order: 4
+ dataset_args: Optional[Dict[str, Any]] = None
+
+ # A pretty name for the metric.
+ # Example: Test WER
+ metric_name: Optional[str] = None
+
+ # The name of the metric configuration used in `load_metric()`.
+ # Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
+ # See the `datasets` docs for more info: https://huggingface.co/docs/datasets/v2.1.0/en/loading#load-configurations
+ metric_config: Optional[str] = None
+
+ # The arguments passed during `Metric.compute()`.
+ # Example for `bleu`: max_order: 4
+ metric_args: Optional[Dict[str, Any]] = None
+
+ # Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
+ verified: Optional[bool] = None
+
+ # A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
+ verify_token: Optional[str] = None
+
+ # The name of the source of the evaluation result.
+ # Example: Open LLM Leaderboard
+ source_name: Optional[str] = None
+
+ # The URL of the source of the evaluation result.
+ # Example: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard
+ source_url: Optional[str] = None
+
+ @property
+ def unique_identifier(self) -> tuple:
+ """Returns a tuple that uniquely identifies this evaluation."""
+ return (
+ self.task_type,
+ self.dataset_type,
+ self.dataset_config,
+ self.dataset_split,
+ self.dataset_revision,
+ )
+
+ def is_equal_except_value(self, other: "EvalResult") -> bool:
+ """
+ Return True if `self` and `other` describe exactly the same metric but with a
+ different value.
+ """
+ for key, _ in self.__dict__.items():
+ if key == "metric_value":
+ continue
+ # For metrics computed by Hugging Face's evaluation service, `verify_token` is derived from `metric_value`,
+ # so we exclude it here in the comparison.
+ if key != "verify_token" and getattr(self, key) != getattr(other, key):
+ return False
+ return True
+
+ def __post_init__(self) -> None:
+ if self.source_name is not None and self.source_url is None:
+ raise ValueError("If `source_name` is provided, `source_url` must also be provided.")
+
+
+@dataclass
+class CardData:
+ """Structure containing metadata from a RepoCard.
+
+ [`CardData`] is the parent class of [`ModelCardData`] and [`DatasetCardData`].
+
+ Metadata can be exported as a dictionary or YAML. Export can be customized to alter the representation of the data
+ (example: flatten evaluation results). `CardData` behaves as a dictionary (can get, pop, set values) but do not
+ inherit from `dict` to allow this export step.
+ """
+
+ def __init__(self, ignore_metadata_errors: bool = False, **kwargs):
+ self.__dict__.update(kwargs)
+
+ def to_dict(self):
+ """Converts CardData to a dict.
+
+ Returns:
+ `dict`: CardData represented as a dictionary ready to be dumped to a YAML
+ block for inclusion in a README.md file.
+ """
+
+ data_dict = copy.deepcopy(self.__dict__)
+ self._to_dict(data_dict)
+ return {key: value for key, value in data_dict.items() if value is not None}
+
+ def _to_dict(self, data_dict):
+ """Use this method in child classes to alter the dict representation of the data. Alter the dict in-place.
+
+ Args:
+ data_dict (`dict`): The raw dict representation of the card data.
+ """
+ pass
+
+ def to_yaml(self, line_break=None, original_order: Optional[List[str]] = None) -> str:
+ """Dumps CardData to a YAML block for inclusion in a README.md file.
+
+ Args:
+ line_break (str, *optional*):
+ The line break to use when dumping to yaml.
+
+ Returns:
+ `str`: CardData represented as a YAML block.
+ """
+ if original_order:
+ self.__dict__ = {
+ k: self.__dict__[k]
+ for k in original_order + list(set(self.__dict__.keys()) - set(original_order))
+ if k in self.__dict__
+ }
+ return yaml_dump(self.to_dict(), sort_keys=False, line_break=line_break).strip()
+
+ def __repr__(self):
+ return repr(self.__dict__)
+
+ def __str__(self):
+ return self.to_yaml()
+
+ def get(self, key: str, default: Any = None) -> Any:
+ """Get value for a given metadata key."""
+ value = self.__dict__.get(key)
+ return default if value is None else value
+
+ def pop(self, key: str, default: Any = None) -> Any:
+ """Pop value for a given metadata key."""
+ return self.__dict__.pop(key, default)
+
+ def __getitem__(self, key: str) -> Any:
+ """Get value for a given metadata key."""
+ return self.__dict__[key]
+
+ def __setitem__(self, key: str, value: Any) -> None:
+ """Set value for a given metadata key."""
+ self.__dict__[key] = value
+
+ def __contains__(self, key: str) -> bool:
+ """Check if a given metadata key is set."""
+ return key in self.__dict__
+
+ def __len__(self) -> int:
+ """Return the number of metadata keys set."""
+ return len(self.__dict__)
+
+
+def _validate_eval_results(
+ eval_results: Optional[Union[EvalResult, List[EvalResult]]],
+ model_name: Optional[str],
+) -> List[EvalResult]:
+ if eval_results is None:
+ return []
+ if isinstance(eval_results, EvalResult):
+ eval_results = [eval_results]
+ if not isinstance(eval_results, list) or not all(isinstance(r, EvalResult) for r in eval_results):
+ raise ValueError(
+ f"`eval_results` should be of type `EvalResult` or a list of `EvalResult`, got {type(eval_results)}."
+ )
+ if model_name is None:
+ raise ValueError("Passing `eval_results` requires `model_name` to be set.")
+ return eval_results
+
+
+class ModelCardData(CardData):
+ """Model Card Metadata that is used by Hugging Face Hub when included at the top of your README.md
+
+ Args:
+ base_model (`str` or `List[str]`, *optional*):
+ The identifier of the base model from which the model derives. This is applicable for example if your model is a
+ fine-tune or adapter of an existing model. The value must be the ID of a model on the Hub (or a list of IDs
+ if your model derives from multiple models). Defaults to None.
+ datasets (`Union[str, List[str]]`, *optional*):
+ Dataset or list of datasets that were used to train this model. Should be a dataset ID
+ found on https://hf.co/datasets. Defaults to None.
+ eval_results (`Union[List[EvalResult], EvalResult]`, *optional*):
+ List of `huggingface_hub.EvalResult` that define evaluation results of the model. If provided,
+ `model_name` is used to as a name on PapersWithCode's leaderboards. Defaults to `None`.
+ language (`Union[str, List[str]]`, *optional*):
+ Language of model's training data or metadata. It must be an ISO 639-1, 639-2 or
+ 639-3 code (two/three letters), or a special value like "code", "multilingual". Defaults to `None`.
+ library_name (`str`, *optional*):
+ Name of library used by this model. Example: keras or any library from
+ https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries.ts.
+ Defaults to None.
+ license (`str`, *optional*):
+ License of this model. Example: apache-2.0 or any license from
+ https://huggingface.co/docs/hub/repositories-licenses. Defaults to None.
+ license_name (`str`, *optional*):
+ Name of the license of this model. Defaults to None. To be used in conjunction with `license_link`.
+ Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a name. In that case, use `license` instead.
+ license_link (`str`, *optional*):
+ Link to the license of this model. Defaults to None. To be used in conjunction with `license_name`.
+ Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a link. In that case, use `license` instead.
+ metrics (`List[str]`, *optional*):
+ List of metrics used to evaluate this model. Should be a metric name that can be found
+ at https://hf.co/metrics. Example: 'accuracy'. Defaults to None.
+ model_name (`str`, *optional*):
+ A name for this model. It is used along with
+ `eval_results` to construct the `model-index` within the card's metadata. The name
+ you supply here is what will be used on PapersWithCode's leaderboards. If None is provided
+ then the repo name is used as a default. Defaults to None.
+ pipeline_tag (`str`, *optional*):
+ The pipeline tag associated with the model. Example: "text-classification".
+ tags (`List[str]`, *optional*):
+ List of tags to add to your model that can be used when filtering on the Hugging
+ Face Hub. Defaults to None.
+ ignore_metadata_errors (`str`):
+ If True, errors while parsing the metadata section will be ignored. Some information might be lost during
+ the process. Use it at your own risk.
+ kwargs (`dict`, *optional*):
+ Additional metadata that will be added to the model card. Defaults to None.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import ModelCardData
+ >>> card_data = ModelCardData(
+ ... language="en",
+ ... license="mit",
+ ... library_name="timm",
+ ... tags=['image-classification', 'resnet'],
+ ... )
+ >>> card_data.to_dict()
+ {'language': 'en', 'license': 'mit', 'library_name': 'timm', 'tags': ['image-classification', 'resnet']}
+
+ ```
+ """
+
+ def __init__(
+ self,
+ *,
+ base_model: Optional[Union[str, List[str]]] = None,
+ datasets: Optional[Union[str, List[str]]] = None,
+ eval_results: Optional[List[EvalResult]] = None,
+ language: Optional[Union[str, List[str]]] = None,
+ library_name: Optional[str] = None,
+ license: Optional[str] = None,
+ license_name: Optional[str] = None,
+ license_link: Optional[str] = None,
+ metrics: Optional[List[str]] = None,
+ model_name: Optional[str] = None,
+ pipeline_tag: Optional[str] = None,
+ tags: Optional[List[str]] = None,
+ ignore_metadata_errors: bool = False,
+ **kwargs,
+ ):
+ self.base_model = base_model
+ self.datasets = datasets
+ self.eval_results = eval_results
+ self.language = language
+ self.library_name = library_name
+ self.license = license
+ self.license_name = license_name
+ self.license_link = license_link
+ self.metrics = metrics
+ self.model_name = model_name
+ self.pipeline_tag = pipeline_tag
+ self.tags = _to_unique_list(tags)
+
+ model_index = kwargs.pop("model-index", None)
+ if model_index:
+ try:
+ model_name, eval_results = model_index_to_eval_results(model_index)
+ self.model_name = model_name
+ self.eval_results = eval_results
+ except (KeyError, TypeError) as error:
+ if ignore_metadata_errors:
+ logger.warning("Invalid model-index. Not loading eval results into CardData.")
+ else:
+ raise ValueError(
+ f"Invalid `model_index` in metadata cannot be parsed: {error.__class__} {error}. Pass"
+ " `ignore_metadata_errors=True` to ignore this error while loading a Model Card. Warning:"
+ " some information will be lost. Use it at your own risk."
+ )
+
+ super().__init__(**kwargs)
+
+ if self.eval_results:
+ try:
+ self.eval_results = _validate_eval_results(self.eval_results, self.model_name)
+ except Exception as e:
+ if ignore_metadata_errors:
+ logger.warning(f"Failed to validate eval_results: {e}. Not loading eval results into CardData.")
+ else:
+ raise ValueError(f"Failed to validate eval_results: {e}") from e
+
+ def _to_dict(self, data_dict):
+ """Format the internal data dict. In this case, we convert eval results to a valid model index"""
+ if self.eval_results is not None:
+ data_dict["model-index"] = eval_results_to_model_index(self.model_name, self.eval_results)
+ del data_dict["eval_results"], data_dict["model_name"]
+
+
+class DatasetCardData(CardData):
+ """Dataset Card Metadata that is used by Hugging Face Hub when included at the top of your README.md
+
+ Args:
+ language (`List[str]`, *optional*):
+ Language of dataset's data or metadata. It must be an ISO 639-1, 639-2 or
+ 639-3 code (two/three letters), or a special value like "code", "multilingual".
+ license (`Union[str, List[str]]`, *optional*):
+ License(s) of this dataset. Example: apache-2.0 or any license from
+ https://huggingface.co/docs/hub/repositories-licenses.
+ annotations_creators (`Union[str, List[str]]`, *optional*):
+ How the annotations for the dataset were created.
+ Options are: 'found', 'crowdsourced', 'expert-generated', 'machine-generated', 'no-annotation', 'other'.
+ language_creators (`Union[str, List[str]]`, *optional*):
+ How the text-based data in the dataset was created.
+ Options are: 'found', 'crowdsourced', 'expert-generated', 'machine-generated', 'other'
+ multilinguality (`Union[str, List[str]]`, *optional*):
+ Whether the dataset is multilingual.
+ Options are: 'monolingual', 'multilingual', 'translation', 'other'.
+ size_categories (`Union[str, List[str]]`, *optional*):
+ The number of examples in the dataset. Options are: 'n<1K', '1K1T', and 'other'.
+ source_datasets (`List[str]]`, *optional*):
+ Indicates whether the dataset is an original dataset or extended from another existing dataset.
+ Options are: 'original' and 'extended'.
+ task_categories (`Union[str, List[str]]`, *optional*):
+ What categories of task does the dataset support?
+ task_ids (`Union[str, List[str]]`, *optional*):
+ What specific tasks does the dataset support?
+ paperswithcode_id (`str`, *optional*):
+ ID of the dataset on PapersWithCode.
+ pretty_name (`str`, *optional*):
+ A more human-readable name for the dataset. (ex. "Cats vs. Dogs")
+ train_eval_index (`Dict`, *optional*):
+ A dictionary that describes the necessary spec for doing evaluation on the Hub.
+ If not provided, it will be gathered from the 'train-eval-index' key of the kwargs.
+ config_names (`Union[str, List[str]]`, *optional*):
+ A list of the available dataset configs for the dataset.
+ """
+
+ def __init__(
+ self,
+ *,
+ language: Optional[Union[str, List[str]]] = None,
+ license: Optional[Union[str, List[str]]] = None,
+ annotations_creators: Optional[Union[str, List[str]]] = None,
+ language_creators: Optional[Union[str, List[str]]] = None,
+ multilinguality: Optional[Union[str, List[str]]] = None,
+ size_categories: Optional[Union[str, List[str]]] = None,
+ source_datasets: Optional[List[str]] = None,
+ task_categories: Optional[Union[str, List[str]]] = None,
+ task_ids: Optional[Union[str, List[str]]] = None,
+ paperswithcode_id: Optional[str] = None,
+ pretty_name: Optional[str] = None,
+ train_eval_index: Optional[Dict] = None,
+ config_names: Optional[Union[str, List[str]]] = None,
+ ignore_metadata_errors: bool = False,
+ **kwargs,
+ ):
+ self.annotations_creators = annotations_creators
+ self.language_creators = language_creators
+ self.language = language
+ self.license = license
+ self.multilinguality = multilinguality
+ self.size_categories = size_categories
+ self.source_datasets = source_datasets
+ self.task_categories = task_categories
+ self.task_ids = task_ids
+ self.paperswithcode_id = paperswithcode_id
+ self.pretty_name = pretty_name
+ self.config_names = config_names
+
+ # TODO - maybe handle this similarly to EvalResult?
+ self.train_eval_index = train_eval_index or kwargs.pop("train-eval-index", None)
+ super().__init__(**kwargs)
+
+ def _to_dict(self, data_dict):
+ data_dict["train-eval-index"] = data_dict.pop("train_eval_index")
+
+
+class SpaceCardData(CardData):
+ """Space Card Metadata that is used by Hugging Face Hub when included at the top of your README.md
+
+ To get an exhaustive reference of Spaces configuration, please visit https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference.
+
+ Args:
+ title (`str`, *optional*)
+ Title of the Space.
+ sdk (`str`, *optional*)
+ SDK of the Space (one of `gradio`, `streamlit`, `docker`, or `static`).
+ sdk_version (`str`, *optional*)
+ Version of the used SDK (if Gradio/Streamlit sdk).
+ python_version (`str`, *optional*)
+ Python version used in the Space (if Gradio/Streamlit sdk).
+ app_file (`str`, *optional*)
+ Path to your main application file (which contains either gradio or streamlit Python code, or static html code).
+ Path is relative to the root of the repository.
+ app_port (`str`, *optional*)
+ Port on which your application is running. Used only if sdk is `docker`.
+ license (`str`, *optional*)
+ License of this model. Example: apache-2.0 or any license from
+ https://huggingface.co/docs/hub/repositories-licenses.
+ duplicated_from (`str`, *optional*)
+ ID of the original Space if this is a duplicated Space.
+ models (List[`str`], *optional*)
+ List of models related to this Space. Should be a dataset ID found on https://hf.co/models.
+ datasets (`List[str]`, *optional*)
+ List of datasets related to this Space. Should be a dataset ID found on https://hf.co/datasets.
+ tags (`List[str]`, *optional*)
+ List of tags to add to your Space that can be used when filtering on the Hub.
+ ignore_metadata_errors (`str`):
+ If True, errors while parsing the metadata section will be ignored. Some information might be lost during
+ the process. Use it at your own risk.
+ kwargs (`dict`, *optional*):
+ Additional metadata that will be added to the space card.
+
+ Example:
+ ```python
+ >>> from huggingface_hub import SpaceCardData
+ >>> card_data = SpaceCardData(
+ ... title="Dreambooth Training",
+ ... license="mit",
+ ... sdk="gradio",
+ ... duplicated_from="multimodalart/dreambooth-training"
+ ... )
+ >>> card_data.to_dict()
+ {'title': 'Dreambooth Training', 'sdk': 'gradio', 'license': 'mit', 'duplicated_from': 'multimodalart/dreambooth-training'}
+ ```
+ """
+
+ def __init__(
+ self,
+ *,
+ title: Optional[str] = None,
+ sdk: Optional[str] = None,
+ sdk_version: Optional[str] = None,
+ python_version: Optional[str] = None,
+ app_file: Optional[str] = None,
+ app_port: Optional[int] = None,
+ license: Optional[str] = None,
+ duplicated_from: Optional[str] = None,
+ models: Optional[List[str]] = None,
+ datasets: Optional[List[str]] = None,
+ tags: Optional[List[str]] = None,
+ ignore_metadata_errors: bool = False,
+ **kwargs,
+ ):
+ self.title = title
+ self.sdk = sdk
+ self.sdk_version = sdk_version
+ self.python_version = python_version
+ self.app_file = app_file
+ self.app_port = app_port
+ self.license = license
+ self.duplicated_from = duplicated_from
+ self.models = models
+ self.datasets = datasets
+ self.tags = _to_unique_list(tags)
+ super().__init__(**kwargs)
+
+
+def model_index_to_eval_results(model_index: List[Dict[str, Any]]) -> Tuple[str, List[EvalResult]]:
+ """Takes in a model index and returns the model name and a list of `huggingface_hub.EvalResult` objects.
+
+ A detailed spec of the model index can be found here:
+ https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+
+ Args:
+ model_index (`List[Dict[str, Any]]`):
+ A model index data structure, likely coming from a README.md file on the
+ Hugging Face Hub.
+
+ Returns:
+ model_name (`str`):
+ The name of the model as found in the model index. This is used as the
+ identifier for the model on leaderboards like PapersWithCode.
+ eval_results (`List[EvalResult]`):
+ A list of `huggingface_hub.EvalResult` objects containing the metrics
+ reported in the provided model_index.
+
+ Example:
+ ```python
+ >>> from huggingface_hub.repocard_data import model_index_to_eval_results
+ >>> # Define a minimal model index
+ >>> model_index = [
+ ... {
+ ... "name": "my-cool-model",
+ ... "results": [
+ ... {
+ ... "task": {
+ ... "type": "image-classification"
+ ... },
+ ... "dataset": {
+ ... "type": "beans",
+ ... "name": "Beans"
+ ... },
+ ... "metrics": [
+ ... {
+ ... "type": "accuracy",
+ ... "value": 0.9
+ ... }
+ ... ]
+ ... }
+ ... ]
+ ... }
+ ... ]
+ >>> model_name, eval_results = model_index_to_eval_results(model_index)
+ >>> model_name
+ 'my-cool-model'
+ >>> eval_results[0].task_type
+ 'image-classification'
+ >>> eval_results[0].metric_type
+ 'accuracy'
+
+ ```
+ """
+
+ eval_results = []
+ for elem in model_index:
+ name = elem["name"]
+ results = elem["results"]
+ for result in results:
+ task_type = result["task"]["type"]
+ task_name = result["task"].get("name")
+ dataset_type = result["dataset"]["type"]
+ dataset_name = result["dataset"]["name"]
+ dataset_config = result["dataset"].get("config")
+ dataset_split = result["dataset"].get("split")
+ dataset_revision = result["dataset"].get("revision")
+ dataset_args = result["dataset"].get("args")
+ source_name = result.get("source", {}).get("name")
+ source_url = result.get("source", {}).get("url")
+
+ for metric in result["metrics"]:
+ metric_type = metric["type"]
+ metric_value = metric["value"]
+ metric_name = metric.get("name")
+ metric_args = metric.get("args")
+ metric_config = metric.get("config")
+ verified = metric.get("verified")
+ verify_token = metric.get("verifyToken")
+
+ eval_result = EvalResult(
+ task_type=task_type, # Required
+ dataset_type=dataset_type, # Required
+ dataset_name=dataset_name, # Required
+ metric_type=metric_type, # Required
+ metric_value=metric_value, # Required
+ task_name=task_name,
+ dataset_config=dataset_config,
+ dataset_split=dataset_split,
+ dataset_revision=dataset_revision,
+ dataset_args=dataset_args,
+ metric_name=metric_name,
+ metric_args=metric_args,
+ metric_config=metric_config,
+ verified=verified,
+ verify_token=verify_token,
+ source_name=source_name,
+ source_url=source_url,
+ )
+ eval_results.append(eval_result)
+ return name, eval_results
+
+
+def _remove_none(obj):
+ """
+ Recursively remove `None` values from a dict. Borrowed from: https://stackoverflow.com/a/20558778
+ """
+ if isinstance(obj, (list, tuple, set)):
+ return type(obj)(_remove_none(x) for x in obj if x is not None)
+ elif isinstance(obj, dict):
+ return type(obj)((_remove_none(k), _remove_none(v)) for k, v in obj.items() if k is not None and v is not None)
+ else:
+ return obj
+
+
+def eval_results_to_model_index(model_name: str, eval_results: List[EvalResult]) -> List[Dict[str, Any]]:
+ """Takes in given model name and list of `huggingface_hub.EvalResult` and returns a
+ valid model-index that will be compatible with the format expected by the
+ Hugging Face Hub.
+
+ Args:
+ model_name (`str`):
+ Name of the model (ex. "my-cool-model"). This is used as the identifier
+ for the model on leaderboards like PapersWithCode.
+ eval_results (`List[EvalResult]`):
+ List of `huggingface_hub.EvalResult` objects containing the metrics to be
+ reported in the model-index.
+
+ Returns:
+ model_index (`List[Dict[str, Any]]`): The eval_results converted to a model-index.
+
+ Example:
+ ```python
+ >>> from huggingface_hub.repocard_data import eval_results_to_model_index, EvalResult
+ >>> # Define minimal eval_results
+ >>> eval_results = [
+ ... EvalResult(
+ ... task_type="image-classification", # Required
+ ... dataset_type="beans", # Required
+ ... dataset_name="Beans", # Required
+ ... metric_type="accuracy", # Required
+ ... metric_value=0.9, # Required
+ ... )
+ ... ]
+ >>> eval_results_to_model_index("my-cool-model", eval_results)
+ [{'name': 'my-cool-model', 'results': [{'task': {'type': 'image-classification'}, 'dataset': {'name': 'Beans', 'type': 'beans'}, 'metrics': [{'type': 'accuracy', 'value': 0.9}]}]}]
+
+ ```
+ """
+
+ # Metrics are reported on a unique task-and-dataset basis.
+ # Here, we make a map of those pairs and the associated EvalResults.
+ task_and_ds_types_map: Dict[Any, List[EvalResult]] = defaultdict(list)
+ for eval_result in eval_results:
+ task_and_ds_types_map[eval_result.unique_identifier].append(eval_result)
+
+ # Use the map from above to generate the model index data.
+ model_index_data = []
+ for results in task_and_ds_types_map.values():
+ # All items from `results` share same metadata
+ sample_result = results[0]
+ data = {
+ "task": {
+ "type": sample_result.task_type,
+ "name": sample_result.task_name,
+ },
+ "dataset": {
+ "name": sample_result.dataset_name,
+ "type": sample_result.dataset_type,
+ "config": sample_result.dataset_config,
+ "split": sample_result.dataset_split,
+ "revision": sample_result.dataset_revision,
+ "args": sample_result.dataset_args,
+ },
+ "metrics": [
+ {
+ "type": result.metric_type,
+ "value": result.metric_value,
+ "name": result.metric_name,
+ "config": result.metric_config,
+ "args": result.metric_args,
+ "verified": result.verified,
+ "verifyToken": result.verify_token,
+ }
+ for result in results
+ ],
+ }
+ if sample_result.source_url is not None:
+ source = {
+ "url": sample_result.source_url,
+ }
+ if sample_result.source_name is not None:
+ source["name"] = sample_result.source_name
+ data["source"] = source
+ model_index_data.append(data)
+
+ # TODO - Check if there cases where this list is longer than one?
+ # Finally, the model index itself is list of dicts.
+ model_index = [
+ {
+ "name": model_name,
+ "results": model_index_data,
+ }
+ ]
+ return _remove_none(model_index)
+
+
+def _to_unique_list(tags: Optional[List[str]]) -> Optional[List[str]]:
+ if tags is None:
+ return tags
+ unique_tags = [] # make tags unique + keep order explicitly
+ for tag in tags:
+ if tag not in unique_tags:
+ unique_tags.append(tag)
+ return unique_tags
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repository.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repository.py
new file mode 100644
index 0000000000000000000000000000000000000000..56e2bce619dff404476f95343fb039a0dae9fc56
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/huggingface_hub/repository.py
@@ -0,0 +1,1471 @@
+import atexit
+import os
+import re
+import subprocess
+import threading
+import time
+from contextlib import contextmanager
+from pathlib import Path
+from typing import Callable, Dict, Iterator, List, Optional, Tuple, TypedDict, Union
+from urllib.parse import urlparse
+
+from huggingface_hub import constants
+from huggingface_hub.repocard import metadata_load, metadata_save
+
+from .hf_api import HfApi, repo_type_and_id_from_hf_id
+from .lfs import LFS_MULTIPART_UPLOAD_COMMAND
+from .utils import (
+ SoftTemporaryDirectory,
+ get_token,
+ logging,
+ run_subprocess,
+ tqdm,
+ validate_hf_hub_args,
+)
+from .utils._deprecation import _deprecate_method
+
+
+logger = logging.get_logger(__name__)
+
+
+class CommandInProgress:
+ """
+ Utility to follow commands launched asynchronously.
+ """
+
+ def __init__(
+ self,
+ title: str,
+ is_done_method: Callable,
+ status_method: Callable,
+ process: subprocess.Popen,
+ post_method: Optional[Callable] = None,
+ ):
+ self.title = title
+ self._is_done = is_done_method
+ self._status = status_method
+ self._process = process
+ self._stderr = ""
+ self._stdout = ""
+ self._post_method = post_method
+
+ @property
+ def is_done(self) -> bool:
+ """
+ Whether the process is done.
+ """
+ result = self._is_done()
+
+ if result and self._post_method is not None:
+ self._post_method()
+ self._post_method = None
+
+ return result
+
+ @property
+ def status(self) -> int:
+ """
+ The exit code/status of the current action. Will return `0` if the
+ command has completed successfully, and a number between 1 and 255 if
+ the process errored-out.
+
+ Will return -1 if the command is still ongoing.
+ """
+ return self._status()
+
+ @property
+ def failed(self) -> bool:
+ """
+ Whether the process errored-out.
+ """
+ return self.status > 0
+
+ @property
+ def stderr(self) -> str:
+ """
+ The current output message on the standard error.
+ """
+ if self._process.stderr is not None:
+ self._stderr += self._process.stderr.read()
+ return self._stderr
+
+ @property
+ def stdout(self) -> str:
+ """
+ The current output message on the standard output.
+ """
+ if self._process.stdout is not None:
+ self._stdout += self._process.stdout.read()
+ return self._stdout
+
+ def __repr__(self):
+ status = self.status
+
+ if status == -1:
+ status = "running"
+
+ return (
+ f"[{self.title} command, status code: {status},"
+ f" {'in progress.' if not self.is_done else 'finished.'} PID:"
+ f" {self._process.pid}]"
+ )
+
+
+def is_git_repo(folder: Union[str, Path]) -> bool:
+ """
+ Check if the folder is the root or part of a git repository
+
+ Args:
+ folder (`str`):
+ The folder in which to run the command.
+
+ Returns:
+ `bool`: `True` if the repository is part of a repository, `False`
+ otherwise.
+ """
+ folder_exists = os.path.exists(os.path.join(folder, ".git"))
+ git_branch = subprocess.run("git branch".split(), cwd=folder, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+ return folder_exists and git_branch.returncode == 0
+
+
+def is_local_clone(folder: Union[str, Path], remote_url: str) -> bool:
+ """
+ Check if the folder is a local clone of the remote_url
+
+ Args:
+ folder (`str` or `Path`):
+ The folder in which to run the command.
+ remote_url (`str`):
+ The url of a git repository.
+
+ Returns:
+ `bool`: `True` if the repository is a local clone of the remote
+ repository specified, `False` otherwise.
+ """
+ if not is_git_repo(folder):
+ return False
+
+ remotes = run_subprocess("git remote -v", folder).stdout
+
+ # Remove token for the test with remotes.
+ remote_url = re.sub(r"https://.*@", "https://", remote_url)
+ remotes = [re.sub(r"https://.*@", "https://", remote) for remote in remotes.split()]
+ return remote_url in remotes
+
+
+def is_tracked_with_lfs(filename: Union[str, Path]) -> bool:
+ """
+ Check if the file passed is tracked with git-lfs.
+
+ Args:
+ filename (`str` or `Path`):
+ The filename to check.
+
+ Returns:
+ `bool`: `True` if the file passed is tracked with git-lfs, `False`
+ otherwise.
+ """
+ folder = Path(filename).parent
+ filename = Path(filename).name
+
+ try:
+ p = run_subprocess("git check-attr -a".split() + [filename], folder)
+ attributes = p.stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ if not is_git_repo(folder):
+ return False
+ else:
+ raise OSError(exc.stderr)
+
+ if len(attributes) == 0:
+ return False
+
+ found_lfs_tag = {"diff": False, "merge": False, "filter": False}
+
+ for attribute in attributes.split("\n"):
+ for tag in found_lfs_tag.keys():
+ if tag in attribute and "lfs" in attribute:
+ found_lfs_tag[tag] = True
+
+ return all(found_lfs_tag.values())
+
+
+def is_git_ignored(filename: Union[str, Path]) -> bool:
+ """
+ Check if file is git-ignored. Supports nested .gitignore files.
+
+ Args:
+ filename (`str` or `Path`):
+ The filename to check.
+
+ Returns:
+ `bool`: `True` if the file passed is ignored by `git`, `False`
+ otherwise.
+ """
+ folder = Path(filename).parent
+ filename = Path(filename).name
+
+ try:
+ p = run_subprocess("git check-ignore".split() + [filename], folder, check=False)
+ # Will return exit code 1 if not gitignored
+ is_ignored = not bool(p.returncode)
+ except subprocess.CalledProcessError as exc:
+ raise OSError(exc.stderr)
+
+ return is_ignored
+
+
+def is_binary_file(filename: Union[str, Path]) -> bool:
+ """
+ Check if file is a binary file.
+
+ Args:
+ filename (`str` or `Path`):
+ The filename to check.
+
+ Returns:
+ `bool`: `True` if the file passed is a binary file, `False` otherwise.
+ """
+ try:
+ with open(filename, "rb") as f:
+ content = f.read(10 * (1024**2)) # Read a maximum of 10MB
+
+ # Code sample taken from the following stack overflow thread
+ # https://stackoverflow.com/questions/898669/how-can-i-detect-if-a-file-is-binary-non-text-in-python/7392391#7392391
+ text_chars = bytearray({7, 8, 9, 10, 12, 13, 27} | set(range(0x20, 0x100)) - {0x7F})
+ return bool(content.translate(None, text_chars))
+ except UnicodeDecodeError:
+ return True
+
+
+def files_to_be_staged(pattern: str = ".", folder: Union[str, Path, None] = None) -> List[str]:
+ """
+ Returns a list of filenames that are to be staged.
+
+ Args:
+ pattern (`str` or `Path`):
+ The pattern of filenames to check. Put `.` to get all files.
+ folder (`str` or `Path`):
+ The folder in which to run the command.
+
+ Returns:
+ `List[str]`: List of files that are to be staged.
+ """
+ try:
+ p = run_subprocess("git ls-files --exclude-standard -mo".split() + [pattern], folder)
+ if len(p.stdout.strip()):
+ files = p.stdout.strip().split("\n")
+ else:
+ files = []
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ return files
+
+
+def is_tracked_upstream(folder: Union[str, Path]) -> bool:
+ """
+ Check if the current checked-out branch is tracked upstream.
+
+ Args:
+ folder (`str` or `Path`):
+ The folder in which to run the command.
+
+ Returns:
+ `bool`: `True` if the current checked-out branch is tracked upstream,
+ `False` otherwise.
+ """
+ try:
+ run_subprocess("git rev-parse --symbolic-full-name --abbrev-ref @{u}", folder)
+ return True
+ except subprocess.CalledProcessError as exc:
+ if "HEAD" in exc.stderr:
+ raise OSError("No branch checked out")
+
+ return False
+
+
+def commits_to_push(folder: Union[str, Path], upstream: Optional[str] = None) -> int:
+ """
+ Check the number of commits that would be pushed upstream
+
+ Args:
+ folder (`str` or `Path`):
+ The folder in which to run the command.
+ upstream (`str`, *optional*):
+ The name of the upstream repository with which the comparison should be
+ made.
+
+ Returns:
+ `int`: Number of commits that would be pushed upstream were a `git
+ push` to proceed.
+ """
+ try:
+ result = run_subprocess(f"git cherry -v {upstream or ''}", folder)
+ return len(result.stdout.split("\n")) - 1
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+
+class PbarT(TypedDict):
+ # Used to store an opened progress bar in `_lfs_log_progress`
+ bar: tqdm
+ past_bytes: int
+
+
+@contextmanager
+def _lfs_log_progress():
+ """
+ This is a context manager that will log the Git LFS progress of cleaning,
+ smudging, pulling and pushing.
+ """
+
+ if logger.getEffectiveLevel() >= logging.ERROR:
+ try:
+ yield
+ except Exception:
+ pass
+ return
+
+ def output_progress(stopping_event: threading.Event):
+ """
+ To be launched as a separate thread with an event meaning it should stop
+ the tail.
+ """
+ # Key is tuple(state, filename), value is a dict(tqdm bar and a previous value)
+ pbars: Dict[Tuple[str, str], PbarT] = {}
+
+ def close_pbars():
+ for pbar in pbars.values():
+ pbar["bar"].update(pbar["bar"].total - pbar["past_bytes"])
+ pbar["bar"].refresh()
+ pbar["bar"].close()
+
+ def tail_file(filename) -> Iterator[str]:
+ """
+ Creates a generator to be iterated through, which will return each
+ line one by one. Will stop tailing the file if the stopping_event is
+ set.
+ """
+ with open(filename, "r") as file:
+ current_line = ""
+ while True:
+ if stopping_event.is_set():
+ close_pbars()
+ break
+
+ line_bit = file.readline()
+ if line_bit is not None and not len(line_bit.strip()) == 0:
+ current_line += line_bit
+ if current_line.endswith("\n"):
+ yield current_line
+ current_line = ""
+ else:
+ time.sleep(1)
+
+ # If the file isn't created yet, wait for a few seconds before trying again.
+ # Can be interrupted with the stopping_event.
+ while not os.path.exists(os.environ["GIT_LFS_PROGRESS"]):
+ if stopping_event.is_set():
+ close_pbars()
+ return
+
+ time.sleep(2)
+
+ for line in tail_file(os.environ["GIT_LFS_PROGRESS"]):
+ try:
+ state, file_progress, byte_progress, filename = line.split()
+ except ValueError as error:
+ # Try/except to ease debugging. See https://github.com/huggingface/huggingface_hub/issues/1373.
+ raise ValueError(f"Cannot unpack LFS progress line:\n{line}") from error
+ description = f"{state.capitalize()} file {filename}"
+
+ current_bytes, total_bytes = byte_progress.split("/")
+ current_bytes_int = int(current_bytes)
+ total_bytes_int = int(total_bytes)
+
+ pbar = pbars.get((state, filename))
+ if pbar is None:
+ # Initialize progress bar
+ pbars[(state, filename)] = {
+ "bar": tqdm(
+ desc=description,
+ initial=current_bytes_int,
+ total=total_bytes_int,
+ unit="B",
+ unit_scale=True,
+ unit_divisor=1024,
+ name="huggingface_hub.lfs_upload",
+ ),
+ "past_bytes": int(current_bytes),
+ }
+ else:
+ # Update progress bar
+ pbar["bar"].update(current_bytes_int - pbar["past_bytes"])
+ pbar["past_bytes"] = current_bytes_int
+
+ current_lfs_progress_value = os.environ.get("GIT_LFS_PROGRESS", "")
+
+ with SoftTemporaryDirectory() as tmpdir:
+ os.environ["GIT_LFS_PROGRESS"] = os.path.join(tmpdir, "lfs_progress")
+ logger.debug(f"Following progress in {os.environ['GIT_LFS_PROGRESS']}")
+
+ exit_event = threading.Event()
+ x = threading.Thread(target=output_progress, args=(exit_event,), daemon=True)
+ x.start()
+
+ try:
+ yield
+ finally:
+ exit_event.set()
+ x.join()
+
+ os.environ["GIT_LFS_PROGRESS"] = current_lfs_progress_value
+
+
+class Repository:
+ """
+ Helper class to wrap the git and git-lfs commands.
+
+ The aim is to facilitate interacting with huggingface.co hosted model or
+ dataset repos, though not a lot here (if any) is actually specific to
+ huggingface.co.
+
+ > [!WARNING]
+ > [`Repository`] is deprecated in favor of the http-based alternatives implemented in
+ > [`HfApi`]. Given its large adoption in legacy code, the complete removal of
+ > [`Repository`] will only happen in release `v1.0`. For more details, please read
+ > https://huggingface.co/docs/huggingface_hub/concepts/git_vs_http.
+ """
+
+ command_queue: List[CommandInProgress]
+
+ @validate_hf_hub_args
+ @_deprecate_method(
+ version="1.0",
+ message=(
+ "Please prefer the http-based alternatives instead. Given its large adoption in legacy code, the complete"
+ " removal is only planned on next major release.\nFor more details, please read"
+ " https://huggingface.co/docs/huggingface_hub/concepts/git_vs_http."
+ ),
+ )
+ def __init__(
+ self,
+ local_dir: Union[str, Path],
+ clone_from: Optional[str] = None,
+ repo_type: Optional[str] = None,
+ token: Union[bool, str] = True,
+ git_user: Optional[str] = None,
+ git_email: Optional[str] = None,
+ revision: Optional[str] = None,
+ skip_lfs_files: bool = False,
+ client: Optional[HfApi] = None,
+ ):
+ """
+ Instantiate a local clone of a git repo.
+
+ If `clone_from` is set, the repo will be cloned from an existing remote repository.
+ If the remote repo does not exist, a `EnvironmentError` exception will be thrown.
+ Please create the remote repo first using [`create_repo`].
+
+ `Repository` uses the local git credentials by default. If explicitly set, the `token`
+ or the `git_user`/`git_email` pair will be used instead.
+
+ Args:
+ local_dir (`str` or `Path`):
+ path (e.g. `'my_trained_model/'`) to the local directory, where
+ the `Repository` will be initialized.
+ clone_from (`str`, *optional*):
+ Either a repository url or `repo_id`.
+ Example:
+ - `"https://huggingface.co/philschmid/playground-tests"`
+ - `"philschmid/playground-tests"`
+ repo_type (`str`, *optional*):
+ To set when cloning a repo from a repo_id. Default is model.
+ token (`bool` or `str`, *optional*):
+ A valid authentication token (see https://huggingface.co/settings/token).
+ If `None` or `True` and machine is logged in (through `hf auth login`
+ or [`~huggingface_hub.login`]), token will be retrieved from the cache.
+ If `False`, token is not sent in the request header.
+ git_user (`str`, *optional*):
+ will override the `git config user.name` for committing and
+ pushing files to the hub.
+ git_email (`str`, *optional*):
+ will override the `git config user.email` for committing and
+ pushing files to the hub.
+ revision (`str`, *optional*):
+ Revision to checkout after initializing the repository. If the
+ revision doesn't exist, a branch will be created with that
+ revision name from the default branch's current HEAD.
+ skip_lfs_files (`bool`, *optional*, defaults to `False`):
+ whether to skip git-LFS files or not.
+ client (`HfApi`, *optional*):
+ Instance of [`HfApi`] to use when calling the HF Hub API. A new
+ instance will be created if this is left to `None`.
+
+ Raises:
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If the remote repository set in `clone_from` does not exist.
+ """
+ if isinstance(local_dir, Path):
+ local_dir = str(local_dir)
+ os.makedirs(local_dir, exist_ok=True)
+ self.local_dir = os.path.join(os.getcwd(), local_dir)
+ self._repo_type = repo_type
+ self.command_queue = []
+ self.skip_lfs_files = skip_lfs_files
+ self.client = client if client is not None else HfApi()
+
+ self.check_git_versions()
+
+ if isinstance(token, str):
+ self.huggingface_token: Optional[str] = token
+ elif token is False:
+ self.huggingface_token = None
+ else:
+ # if `True` -> explicit use of the cached token
+ # if `None` -> implicit use of the cached token
+ self.huggingface_token = get_token()
+
+ if clone_from is not None:
+ self.clone_from(repo_url=clone_from)
+ else:
+ if is_git_repo(self.local_dir):
+ logger.debug("[Repository] is a valid git repo")
+ else:
+ raise ValueError("If not specifying `clone_from`, you need to pass Repository a valid git clone.")
+
+ if self.huggingface_token is not None and (git_email is None or git_user is None):
+ user = self.client.whoami(self.huggingface_token)
+
+ if git_email is None:
+ git_email = user.get("email")
+
+ if git_user is None:
+ git_user = user.get("fullname")
+
+ if git_user is not None or git_email is not None:
+ self.git_config_username_and_email(git_user, git_email)
+
+ self.lfs_enable_largefiles()
+ self.git_credential_helper_store()
+
+ if revision is not None:
+ self.git_checkout(revision, create_branch_ok=True)
+
+ # This ensures that all commands exit before exiting the Python runtime.
+ # This will ensure all pushes register on the hub, even if other errors happen in subsequent operations.
+ atexit.register(self.wait_for_commands)
+
+ @property
+ def current_branch(self) -> str:
+ """
+ Returns the current checked out branch.
+
+ Returns:
+ `str`: Current checked out branch.
+ """
+ try:
+ result = run_subprocess("git rev-parse --abbrev-ref HEAD", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ return result
+
+ def check_git_versions(self):
+ """
+ Checks that `git` and `git-lfs` can be run.
+
+ Raises:
+ [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ If `git` or `git-lfs` are not installed.
+ """
+ try:
+ git_version = run_subprocess("git --version", self.local_dir).stdout.strip()
+ except FileNotFoundError:
+ raise EnvironmentError("Looks like you do not have git installed, please install.")
+
+ try:
+ lfs_version = run_subprocess("git-lfs --version", self.local_dir).stdout.strip()
+ except FileNotFoundError:
+ raise EnvironmentError(
+ "Looks like you do not have git-lfs installed, please install."
+ " You can install from https://git-lfs.github.com/."
+ " Then run `git lfs install` (you only have to do this once)."
+ )
+ logger.info(git_version + "\n" + lfs_version)
+
+ @validate_hf_hub_args
+ def clone_from(self, repo_url: str, token: Union[bool, str, None] = None):
+ """
+ Clone from a remote. If the folder already exists, will try to clone the
+ repository within it.
+
+ If this folder is a git repository with linked history, will try to
+ update the repository.
+
+ Args:
+ repo_url (`str`):
+ The URL from which to clone the repository
+ token (`Union[str, bool]`, *optional*):
+ Whether to use the authentication token. It can be:
+ - a string which is the token itself
+ - `False`, which would not use the authentication token
+ - `True`, which would fetch the authentication token from the
+ local folder and use it (you should be logged in for this to
+ work).
+ - `None`, which would retrieve the value of
+ `self.huggingface_token`.
+
+ > [!TIP]
+ > Raises the following error:
+ >
+ > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+ > if an organization token (starts with "api_org") is passed. Use must use
+ > your own personal access token (see https://hf.co/settings/tokens).
+ >
+ > - [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+ > if you are trying to clone the repository in a non-empty folder, or if the
+ > `git` operations raise errors.
+ """
+ token = (
+ token # str -> use it
+ if isinstance(token, str)
+ else (
+ None # `False` -> explicit no token
+ if token is False
+ else self.huggingface_token # `None` or `True` -> use default
+ )
+ )
+ if token is not None and token.startswith("api_org"):
+ raise ValueError(
+ "You must use your personal access token, not an Organization token"
+ " (see https://hf.co/settings/tokens)."
+ )
+
+ hub_url = self.client.endpoint
+ if hub_url in repo_url or ("http" not in repo_url and len(repo_url.split("/")) <= 2):
+ repo_type, namespace, repo_name = repo_type_and_id_from_hf_id(repo_url, hub_url=hub_url)
+ repo_id = f"{namespace}/{repo_name}" if namespace is not None else repo_name
+
+ if repo_type is not None:
+ self._repo_type = repo_type
+
+ repo_url = hub_url + "/"
+
+ if self._repo_type in constants.REPO_TYPES_URL_PREFIXES:
+ repo_url += constants.REPO_TYPES_URL_PREFIXES[self._repo_type]
+
+ if token is not None:
+ # Add token in git url when provided
+ scheme = urlparse(repo_url).scheme
+ repo_url = repo_url.replace(f"{scheme}://", f"{scheme}://user:{token}@")
+
+ repo_url += repo_id
+
+ # For error messages, it's cleaner to show the repo url without the token.
+ clean_repo_url = re.sub(r"(https?)://.*@", r"\1://", repo_url)
+ try:
+ run_subprocess("git lfs install", self.local_dir)
+
+ # checks if repository is initialized in a empty repository or in one with files
+ if len(os.listdir(self.local_dir)) == 0:
+ logger.warning(f"Cloning {clean_repo_url} into local empty directory.")
+
+ with _lfs_log_progress():
+ env = os.environ.copy()
+
+ if self.skip_lfs_files:
+ env.update({"GIT_LFS_SKIP_SMUDGE": "1"})
+
+ run_subprocess(
+ # 'git lfs clone' is deprecated (will display a warning in the terminal)
+ # but we still use it as it provides a nicer UX when downloading large
+ # files (shows progress).
+ f"{'git clone' if self.skip_lfs_files else 'git lfs clone'} {repo_url} .",
+ self.local_dir,
+ env=env,
+ )
+ else:
+ # Check if the folder is the root of a git repository
+ if not is_git_repo(self.local_dir):
+ raise EnvironmentError(
+ "Tried to clone a repository in a non-empty folder that isn't"
+ f" a git repository ('{self.local_dir}'). If you really want to"
+ f" do this, do it manually:\n cd {self.local_dir} && git init"
+ " && git remote add origin && git pull origin main\n or clone"
+ " repo to a new folder and move your existing files there"
+ " afterwards."
+ )
+
+ if is_local_clone(self.local_dir, repo_url):
+ logger.warning(
+ f"{self.local_dir} is already a clone of {clean_repo_url}."
+ " Make sure you pull the latest changes with"
+ " `repo.git_pull()`."
+ )
+ else:
+ output = run_subprocess("git remote get-url origin", self.local_dir, check=False)
+
+ error_msg = (
+ f"Tried to clone {clean_repo_url} in an unrelated git"
+ " repository.\nIf you believe this is an error, please add"
+ f" a remote with the following URL: {clean_repo_url}."
+ )
+ if output.returncode == 0:
+ clean_local_remote_url = re.sub(r"https://.*@", "https://", output.stdout)
+ error_msg += f"\nLocal path has its origin defined as: {clean_local_remote_url}"
+ raise EnvironmentError(error_msg)
+
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_config_username_and_email(self, git_user: Optional[str] = None, git_email: Optional[str] = None):
+ """
+ Sets git username and email (only in the current repo).
+
+ Args:
+ git_user (`str`, *optional*):
+ The username to register through `git`.
+ git_email (`str`, *optional*):
+ The email to register through `git`.
+ """
+ try:
+ if git_user is not None:
+ run_subprocess("git config user.name".split() + [git_user], self.local_dir)
+
+ if git_email is not None:
+ run_subprocess(f"git config user.email {git_email}".split(), self.local_dir)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_credential_helper_store(self):
+ """
+ Sets the git credential helper to `store`
+ """
+ try:
+ run_subprocess("git config credential.helper store", self.local_dir)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_head_hash(self) -> str:
+ """
+ Get commit sha on top of HEAD.
+
+ Returns:
+ `str`: The current checked out commit SHA.
+ """
+ try:
+ p = run_subprocess("git rev-parse HEAD", self.local_dir)
+ return p.stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_remote_url(self) -> str:
+ """
+ Get URL to origin remote.
+
+ Returns:
+ `str`: The URL of the `origin` remote.
+ """
+ try:
+ p = run_subprocess("git config --get remote.origin.url", self.local_dir)
+ url = p.stdout.strip()
+ # Strip basic auth info.
+ return re.sub(r"https://.*@", "https://", url)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_head_commit_url(self) -> str:
+ """
+ Get URL to last commit on HEAD. We assume it's been pushed, and the url
+ scheme is the same one as for GitHub or HuggingFace.
+
+ Returns:
+ `str`: The URL to the current checked-out commit.
+ """
+ sha = self.git_head_hash()
+ url = self.git_remote_url()
+ if url.endswith("/"):
+ url = url[:-1]
+ return f"{url}/commit/{sha}"
+
+ def list_deleted_files(self) -> List[str]:
+ """
+ Returns a list of the files that are deleted in the working directory or
+ index.
+
+ Returns:
+ `List[str]`: A list of files that have been deleted in the working
+ directory or index.
+ """
+ try:
+ git_status = run_subprocess("git status -s", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ if len(git_status) == 0:
+ return []
+
+ # Receives a status like the following
+ # D .gitignore
+ # D new_file.json
+ # AD new_file1.json
+ # ?? new_file2.json
+ # ?? new_file4.json
+
+ # Strip each line of whitespaces
+ modified_files_statuses = [status.strip() for status in git_status.split("\n")]
+
+ # Only keep files that are deleted using the D prefix
+ deleted_files_statuses = [status for status in modified_files_statuses if "D" in status.split()[0]]
+
+ # Remove the D prefix and strip to keep only the relevant filename
+ deleted_files = [status.split()[-1].strip() for status in deleted_files_statuses]
+
+ return deleted_files
+
+ def lfs_track(self, patterns: Union[str, List[str]], filename: bool = False):
+ """
+ Tell git-lfs to track files according to a pattern.
+
+ Setting the `filename` argument to `True` will treat the arguments as
+ literal filenames, not as patterns. Any special glob characters in the
+ filename will be escaped when writing to the `.gitattributes` file.
+
+ Args:
+ patterns (`Union[str, List[str]]`):
+ The pattern, or list of patterns, to track with git-lfs.
+ filename (`bool`, *optional*, defaults to `False`):
+ Whether to use the patterns as literal filenames.
+ """
+ if isinstance(patterns, str):
+ patterns = [patterns]
+ try:
+ for pattern in patterns:
+ run_subprocess(
+ f"git lfs track {'--filename' if filename else ''} {pattern}",
+ self.local_dir,
+ )
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def lfs_untrack(self, patterns: Union[str, List[str]]):
+ """
+ Tell git-lfs to untrack those files.
+
+ Args:
+ patterns (`Union[str, List[str]]`):
+ The pattern, or list of patterns, to untrack with git-lfs.
+ """
+ if isinstance(patterns, str):
+ patterns = [patterns]
+ try:
+ for pattern in patterns:
+ run_subprocess("git lfs untrack".split() + [pattern], self.local_dir)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def lfs_enable_largefiles(self):
+ """
+ HF-specific. This enables upload support of files >5GB.
+ """
+ try:
+ lfs_config = "git config lfs.customtransfer.multipart"
+ run_subprocess(f"{lfs_config}.path hf", self.local_dir)
+ run_subprocess(
+ f"{lfs_config}.args {LFS_MULTIPART_UPLOAD_COMMAND}",
+ self.local_dir,
+ )
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def auto_track_binary_files(self, pattern: str = ".") -> List[str]:
+ """
+ Automatically track binary files with git-lfs.
+
+ Args:
+ pattern (`str`, *optional*, defaults to "."):
+ The pattern with which to track files that are binary.
+
+ Returns:
+ `List[str]`: List of filenames that are now tracked due to being
+ binary files
+ """
+ files_to_be_tracked_with_lfs = []
+
+ deleted_files = self.list_deleted_files()
+
+ for filename in files_to_be_staged(pattern, folder=self.local_dir):
+ if filename in deleted_files:
+ continue
+
+ path_to_file = os.path.join(os.getcwd(), self.local_dir, filename)
+
+ if not (is_tracked_with_lfs(path_to_file) or is_git_ignored(path_to_file)):
+ size_in_mb = os.path.getsize(path_to_file) / (1024 * 1024)
+
+ if size_in_mb >= 10:
+ logger.warning(
+ "Parsing a large file to check if binary or not. Tracking large"
+ " files using `repository.auto_track_large_files` is"
+ " recommended so as to not load the full file in memory."
+ )
+
+ is_binary = is_binary_file(path_to_file)
+
+ if is_binary:
+ self.lfs_track(filename)
+ files_to_be_tracked_with_lfs.append(filename)
+
+ # Cleanup the .gitattributes if files were deleted
+ self.lfs_untrack(deleted_files)
+
+ return files_to_be_tracked_with_lfs
+
+ def auto_track_large_files(self, pattern: str = ".") -> List[str]:
+ """
+ Automatically track large files (files that weigh more than 10MBs) with
+ git-lfs.
+
+ Args:
+ pattern (`str`, *optional*, defaults to "."):
+ The pattern with which to track files that are above 10MBs.
+
+ Returns:
+ `List[str]`: List of filenames that are now tracked due to their
+ size.
+ """
+ files_to_be_tracked_with_lfs = []
+
+ deleted_files = self.list_deleted_files()
+
+ for filename in files_to_be_staged(pattern, folder=self.local_dir):
+ if filename in deleted_files:
+ continue
+
+ path_to_file = os.path.join(os.getcwd(), self.local_dir, filename)
+ size_in_mb = os.path.getsize(path_to_file) / (1024 * 1024)
+
+ if size_in_mb >= 10 and not is_tracked_with_lfs(path_to_file) and not is_git_ignored(path_to_file):
+ self.lfs_track(filename)
+ files_to_be_tracked_with_lfs.append(filename)
+
+ # Cleanup the .gitattributes if files were deleted
+ self.lfs_untrack(deleted_files)
+
+ return files_to_be_tracked_with_lfs
+
+ def lfs_prune(self, recent=False):
+ """
+ git lfs prune
+
+ Args:
+ recent (`bool`, *optional*, defaults to `False`):
+ Whether to prune files even if they were referenced by recent
+ commits. See the following
+ [link](https://github.com/git-lfs/git-lfs/blob/f3d43f0428a84fc4f1e5405b76b5a73ec2437e65/docs/man/git-lfs-prune.1.ronn#recent-files)
+ for more information.
+ """
+ try:
+ with _lfs_log_progress():
+ result = run_subprocess(f"git lfs prune {'--recent' if recent else ''}", self.local_dir)
+ logger.info(result.stdout)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_pull(self, rebase: bool = False, lfs: bool = False):
+ """
+ git pull
+
+ Args:
+ rebase (`bool`, *optional*, defaults to `False`):
+ Whether to rebase the current branch on top of the upstream
+ branch after fetching.
+ lfs (`bool`, *optional*, defaults to `False`):
+ Whether to fetch the LFS files too. This option only changes the
+ behavior when a repository was cloned without fetching the LFS
+ files; calling `repo.git_pull(lfs=True)` will then fetch the LFS
+ file from the remote repository.
+ """
+ command = "git pull" if not lfs else "git lfs pull"
+ if rebase:
+ command += " --rebase"
+ try:
+ with _lfs_log_progress():
+ result = run_subprocess(command, self.local_dir)
+ logger.info(result.stdout)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_add(self, pattern: str = ".", auto_lfs_track: bool = False):
+ """
+ git add
+
+ Setting the `auto_lfs_track` parameter to `True` will automatically
+ track files that are larger than 10MB with `git-lfs`.
+
+ Args:
+ pattern (`str`, *optional*, defaults to "."):
+ The pattern with which to add files to staging.
+ auto_lfs_track (`bool`, *optional*, defaults to `False`):
+ Whether to automatically track large and binary files with
+ git-lfs. Any file over 10MB in size, or in binary format, will
+ be automatically tracked.
+ """
+ if auto_lfs_track:
+ # Track files according to their size (>=10MB)
+ tracked_files = self.auto_track_large_files(pattern)
+
+ # Read the remaining files and track them if they're binary
+ tracked_files.extend(self.auto_track_binary_files(pattern))
+
+ if tracked_files:
+ logger.warning(
+ f"Adding files tracked by Git LFS: {tracked_files}. This may take a"
+ " bit of time if the files are large."
+ )
+
+ try:
+ result = run_subprocess("git add -v".split() + [pattern], self.local_dir)
+ logger.info(f"Adding to index:\n{result.stdout}\n")
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def git_commit(self, commit_message: str = "commit files to HF hub"):
+ """
+ git commit
+
+ Args:
+ commit_message (`str`, *optional*, defaults to "commit files to HF hub"):
+ The message attributed to the commit.
+ """
+ try:
+ result = run_subprocess("git commit -v -m".split() + [commit_message], self.local_dir)
+ logger.info(f"Committed:\n{result.stdout}\n")
+ except subprocess.CalledProcessError as exc:
+ if len(exc.stderr) > 0:
+ raise EnvironmentError(exc.stderr)
+ else:
+ raise EnvironmentError(exc.stdout)
+
+ def git_push(
+ self,
+ upstream: Optional[str] = None,
+ blocking: bool = True,
+ auto_lfs_prune: bool = False,
+ ) -> Union[str, Tuple[str, CommandInProgress]]:
+ """
+ git push
+
+ If used without setting `blocking`, will return url to commit on remote
+ repo. If used with `blocking=True`, will return a tuple containing the
+ url to commit and the command object to follow for information about the
+ process.
+
+ Args:
+ upstream (`str`, *optional*):
+ Upstream to which this should push. If not specified, will push
+ to the lastly defined upstream or to the default one (`origin
+ main`).
+ blocking (`bool`, *optional*, defaults to `True`):
+ Whether the function should return only when the push has
+ finished. Setting this to `False` will return an
+ `CommandInProgress` object which has an `is_done` property. This
+ property will be set to `True` when the push is finished.
+ auto_lfs_prune (`bool`, *optional*, defaults to `False`):
+ Whether to automatically prune files once they have been pushed
+ to the remote.
+ """
+ command = "git push"
+
+ if upstream:
+ command += f" --set-upstream {upstream}"
+
+ number_of_commits = commits_to_push(self.local_dir, upstream)
+
+ if number_of_commits > 1:
+ logger.warning(f"Several commits ({number_of_commits}) will be pushed upstream.")
+ if blocking:
+ logger.warning("The progress bars may be unreliable.")
+
+ try:
+ with _lfs_log_progress():
+ process = subprocess.Popen(
+ command.split(),
+ stderr=subprocess.PIPE,
+ stdout=subprocess.PIPE,
+ encoding="utf-8",
+ cwd=self.local_dir,
+ )
+
+ if blocking:
+ stdout, stderr = process.communicate()
+ return_code = process.poll()
+ process.kill()
+
+ if len(stderr):
+ logger.warning(stderr)
+
+ if return_code:
+ raise subprocess.CalledProcessError(return_code, process.args, output=stdout, stderr=stderr)
+
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ if not blocking:
+
+ def status_method():
+ status = process.poll()
+ if status is None:
+ return -1
+ else:
+ return status
+
+ command_in_progress = CommandInProgress(
+ "push",
+ is_done_method=lambda: process.poll() is not None,
+ status_method=status_method,
+ process=process,
+ post_method=self.lfs_prune if auto_lfs_prune else None,
+ )
+
+ self.command_queue.append(command_in_progress)
+
+ return self.git_head_commit_url(), command_in_progress
+
+ if auto_lfs_prune:
+ self.lfs_prune()
+
+ return self.git_head_commit_url()
+
+ def git_checkout(self, revision: str, create_branch_ok: bool = False):
+ """
+ git checkout a given revision
+
+ Specifying `create_branch_ok` to `True` will create the branch to the
+ given revision if that revision doesn't exist.
+
+ Args:
+ revision (`str`):
+ The revision to checkout.
+ create_branch_ok (`str`, *optional*, defaults to `False`):
+ Whether creating a branch named with the `revision` passed at
+ the current checked-out reference if `revision` isn't an
+ existing revision is allowed.
+ """
+ try:
+ result = run_subprocess(f"git checkout {revision}", self.local_dir)
+ logger.warning(f"Checked out {revision} from {self.current_branch}.")
+ logger.warning(result.stdout)
+ except subprocess.CalledProcessError as exc:
+ if not create_branch_ok:
+ raise EnvironmentError(exc.stderr)
+ else:
+ try:
+ result = run_subprocess(f"git checkout -b {revision}", self.local_dir)
+ logger.warning(
+ f"Revision `{revision}` does not exist. Created and checked out branch `{revision}`."
+ )
+ logger.warning(result.stdout)
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def tag_exists(self, tag_name: str, remote: Optional[str] = None) -> bool:
+ """
+ Check if a tag exists or not.
+
+ Args:
+ tag_name (`str`):
+ The name of the tag to check.
+ remote (`str`, *optional*):
+ Whether to check if the tag exists on a remote. This parameter
+ should be the identifier of the remote.
+
+ Returns:
+ `bool`: Whether the tag exists.
+ """
+ if remote:
+ try:
+ result = run_subprocess(f"git ls-remote origin refs/tags/{tag_name}", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ return len(result) != 0
+ else:
+ try:
+ git_tags = run_subprocess("git tag", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ git_tags = git_tags.split("\n")
+ return tag_name in git_tags
+
+ def delete_tag(self, tag_name: str, remote: Optional[str] = None) -> bool:
+ """
+ Delete a tag, both local and remote, if it exists
+
+ Args:
+ tag_name (`str`):
+ The tag name to delete.
+ remote (`str`, *optional*):
+ The remote on which to delete the tag.
+
+ Returns:
+ `bool`: `True` if deleted, `False` if the tag didn't exist.
+ If remote is not passed, will just be updated locally
+ """
+ delete_locally = True
+ delete_remotely = True
+
+ if not self.tag_exists(tag_name):
+ delete_locally = False
+
+ if not self.tag_exists(tag_name, remote=remote):
+ delete_remotely = False
+
+ if delete_locally:
+ try:
+ run_subprocess(["git", "tag", "-d", tag_name], self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ if remote and delete_remotely:
+ try:
+ run_subprocess(f"git push {remote} --delete {tag_name}", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ return True
+
+ def add_tag(self, tag_name: str, message: Optional[str] = None, remote: Optional[str] = None):
+ """
+ Add a tag at the current head and push it
+
+ If remote is None, will just be updated locally
+
+ If no message is provided, the tag will be lightweight. if a message is
+ provided, the tag will be annotated.
+
+ Args:
+ tag_name (`str`):
+ The name of the tag to be added.
+ message (`str`, *optional*):
+ The message that accompanies the tag. The tag will turn into an
+ annotated tag if a message is passed.
+ remote (`str`, *optional*):
+ The remote on which to add the tag.
+ """
+ if message:
+ tag_args = ["git", "tag", "-a", tag_name, "-m", message]
+ else:
+ tag_args = ["git", "tag", tag_name]
+
+ try:
+ run_subprocess(tag_args, self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ if remote:
+ try:
+ run_subprocess(f"git push {remote} {tag_name}", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ def is_repo_clean(self) -> bool:
+ """
+ Return whether or not the git status is clean or not
+
+ Returns:
+ `bool`: `True` if the git status is clean, `False` otherwise.
+ """
+ try:
+ git_status = run_subprocess("git status --porcelain", self.local_dir).stdout.strip()
+ except subprocess.CalledProcessError as exc:
+ raise EnvironmentError(exc.stderr)
+
+ return len(git_status) == 0
+
+ def push_to_hub(
+ self,
+ commit_message: str = "commit files to HF hub",
+ blocking: bool = True,
+ clean_ok: bool = True,
+ auto_lfs_prune: bool = False,
+ ) -> Union[None, str, Tuple[str, CommandInProgress]]:
+ """
+ Helper to add, commit, and push files to remote repository on the
+ HuggingFace Hub. Will automatically track large files (>10MB).
+
+ Args:
+ commit_message (`str`):
+ Message to use for the commit.
+ blocking (`bool`, *optional*, defaults to `True`):
+ Whether the function should return only when the `git push` has
+ finished.
+ clean_ok (`bool`, *optional*, defaults to `True`):
+ If True, this function will return None if the repo is
+ untouched. Default behavior is to fail because the git command
+ fails.
+ auto_lfs_prune (`bool`, *optional*, defaults to `False`):
+ Whether to automatically prune files once they have been pushed
+ to the remote.
+ """
+ if clean_ok and self.is_repo_clean():
+ logger.info("Repo currently clean. Ignoring push_to_hub")
+ return None
+ self.git_add(auto_lfs_track=True)
+ self.git_commit(commit_message)
+ return self.git_push(
+ upstream=f"origin {self.current_branch}",
+ blocking=blocking,
+ auto_lfs_prune=auto_lfs_prune,
+ )
+
+ @contextmanager
+ def commit(
+ self,
+ commit_message: str,
+ branch: Optional[str] = None,
+ track_large_files: bool = True,
+ blocking: bool = True,
+ auto_lfs_prune: bool = False,
+ ):
+ """
+ Context manager utility to handle committing to a repository. This
+ automatically tracks large files (>10Mb) with git-lfs. Set the
+ `track_large_files` argument to `False` if you wish to ignore that
+ behavior.
+
+ Args:
+ commit_message (`str`):
+ Message to use for the commit.
+ branch (`str`, *optional*):
+ The branch on which the commit will appear. This branch will be
+ checked-out before any operation.
+ track_large_files (`bool`, *optional*, defaults to `True`):
+ Whether to automatically track large files or not. Will do so by
+ default.
+ blocking (`bool`, *optional*, defaults to `True`):
+ Whether the function should return only when the `git push` has
+ finished.
+ auto_lfs_prune (`bool`, defaults to `True`):
+ Whether to automatically prune files once they have been pushed
+ to the remote.
+
+ Examples:
+
+ ```python
+ >>> with Repository(
+ ... "text-files",
+ ... clone_from="/text-files",
+ ... token=True,
+ >>> ).commit("My first file :)"):
+ ... with open("file.txt", "w+") as f:
+ ... f.write(json.dumps({"hey": 8}))
+
+ >>> import torch
+
+ >>> model = torch.nn.Transformer()
+ >>> with Repository(
+ ... "torch-model",
+ ... clone_from="/torch-model",
+ ... token=True,
+ >>> ).commit("My cool model :)"):
+ ... torch.save(model.state_dict(), "model.pt")
+ ```
+
+ """
+
+ files_to_stage = files_to_be_staged(".", folder=self.local_dir)
+
+ if len(files_to_stage):
+ files_in_msg = str(files_to_stage[:5])[:-1] + ", ...]" if len(files_to_stage) > 5 else str(files_to_stage)
+ logger.error(
+ "There exists some updated files in the local repository that are not"
+ f" committed: {files_in_msg}. This may lead to errors if checking out"
+ " a branch. These files and their modifications will be added to the"
+ " current commit."
+ )
+
+ if branch is not None:
+ self.git_checkout(branch, create_branch_ok=True)
+
+ if is_tracked_upstream(self.local_dir):
+ logger.warning("Pulling changes ...")
+ self.git_pull(rebase=True)
+ else:
+ logger.warning(f"The current branch has no upstream branch. Will push to 'origin {self.current_branch}'")
+
+ current_working_directory = os.getcwd()
+ os.chdir(os.path.join(current_working_directory, self.local_dir))
+
+ try:
+ yield self
+ finally:
+ self.git_add(auto_lfs_track=track_large_files)
+
+ try:
+ self.git_commit(commit_message)
+ except OSError as e:
+ # If no changes are detected, there is nothing to commit.
+ if "nothing to commit" not in str(e):
+ raise e
+
+ try:
+ self.git_push(
+ upstream=f"origin {self.current_branch}",
+ blocking=blocking,
+ auto_lfs_prune=auto_lfs_prune,
+ )
+ except OSError as e:
+ # If no changes are detected, there is nothing to commit.
+ if "could not read Username" in str(e):
+ raise OSError("Couldn't authenticate user for push. Did you set `token` to `True`?") from e
+ else:
+ raise e
+
+ os.chdir(current_working_directory)
+
+ def repocard_metadata_load(self) -> Optional[Dict]:
+ filepath = os.path.join(self.local_dir, constants.REPOCARD_NAME)
+ if os.path.isfile(filepath):
+ return metadata_load(filepath)
+ return None
+
+ def repocard_metadata_save(self, data: Dict) -> None:
+ return metadata_save(os.path.join(self.local_dir, constants.REPOCARD_NAME), data)
+
+ @property
+ def commands_failed(self):
+ """
+ Returns the asynchronous commands that failed.
+ """
+ return [c for c in self.command_queue if c.status > 0]
+
+ @property
+ def commands_in_progress(self):
+ """
+ Returns the asynchronous commands that are currently in progress.
+ """
+ return [c for c in self.command_queue if not c.is_done]
+
+ def wait_for_commands(self):
+ """
+ Blocking method: blocks all subsequent execution until all commands have
+ been processed.
+ """
+ index = 0
+ for command_failed in self.commands_failed:
+ logger.error(f"The {command_failed.title} command with PID {command_failed._process.pid} failed.")
+ logger.error(command_failed.stderr)
+
+ while self.commands_in_progress:
+ if index % 10 == 0:
+ logger.warning(
+ f"Waiting for the following commands to finish before shutting down: {self.commands_in_progress}."
+ )
+
+ index += 1
+
+ time.sleep(1)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..cfdc030a751b089fc7e38fc88093b791605d501d
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/__init__.py
@@ -0,0 +1,45 @@
+from .core import (
+ IDNABidiError,
+ IDNAError,
+ InvalidCodepoint,
+ InvalidCodepointContext,
+ alabel,
+ check_bidi,
+ check_hyphen_ok,
+ check_initial_combiner,
+ check_label,
+ check_nfc,
+ decode,
+ encode,
+ ulabel,
+ uts46_remap,
+ valid_contextj,
+ valid_contexto,
+ valid_label_length,
+ valid_string_length,
+)
+from .intranges import intranges_contain
+from .package_data import __version__
+
+__all__ = [
+ "__version__",
+ "IDNABidiError",
+ "IDNAError",
+ "InvalidCodepoint",
+ "InvalidCodepointContext",
+ "alabel",
+ "check_bidi",
+ "check_hyphen_ok",
+ "check_initial_combiner",
+ "check_label",
+ "check_nfc",
+ "decode",
+ "encode",
+ "intranges_contain",
+ "ulabel",
+ "uts46_remap",
+ "valid_contextj",
+ "valid_contexto",
+ "valid_label_length",
+ "valid_string_length",
+]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/codec.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/codec.py
new file mode 100644
index 0000000000000000000000000000000000000000..913abfd6a23ce547f84de2adc41221012f1007d6
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/codec.py
@@ -0,0 +1,122 @@
+import codecs
+import re
+from typing import Any, Optional, Tuple
+
+from .core import IDNAError, alabel, decode, encode, ulabel
+
+_unicode_dots_re = re.compile("[\u002e\u3002\uff0e\uff61]")
+
+
+class Codec(codecs.Codec):
+ def encode(self, data: str, errors: str = "strict") -> Tuple[bytes, int]:
+ if errors != "strict":
+ raise IDNAError('Unsupported error handling "{}"'.format(errors))
+
+ if not data:
+ return b"", 0
+
+ return encode(data), len(data)
+
+ def decode(self, data: bytes, errors: str = "strict") -> Tuple[str, int]:
+ if errors != "strict":
+ raise IDNAError('Unsupported error handling "{}"'.format(errors))
+
+ if not data:
+ return "", 0
+
+ return decode(data), len(data)
+
+
+class IncrementalEncoder(codecs.BufferedIncrementalEncoder):
+ def _buffer_encode(self, data: str, errors: str, final: bool) -> Tuple[bytes, int]:
+ if errors != "strict":
+ raise IDNAError('Unsupported error handling "{}"'.format(errors))
+
+ if not data:
+ return b"", 0
+
+ labels = _unicode_dots_re.split(data)
+ trailing_dot = b""
+ if labels:
+ if not labels[-1]:
+ trailing_dot = b"."
+ del labels[-1]
+ elif not final:
+ # Keep potentially unfinished label until the next call
+ del labels[-1]
+ if labels:
+ trailing_dot = b"."
+
+ result = []
+ size = 0
+ for label in labels:
+ result.append(alabel(label))
+ if size:
+ size += 1
+ size += len(label)
+
+ # Join with U+002E
+ result_bytes = b".".join(result) + trailing_dot
+ size += len(trailing_dot)
+ return result_bytes, size
+
+
+class IncrementalDecoder(codecs.BufferedIncrementalDecoder):
+ def _buffer_decode(self, data: Any, errors: str, final: bool) -> Tuple[str, int]:
+ if errors != "strict":
+ raise IDNAError('Unsupported error handling "{}"'.format(errors))
+
+ if not data:
+ return ("", 0)
+
+ if not isinstance(data, str):
+ data = str(data, "ascii")
+
+ labels = _unicode_dots_re.split(data)
+ trailing_dot = ""
+ if labels:
+ if not labels[-1]:
+ trailing_dot = "."
+ del labels[-1]
+ elif not final:
+ # Keep potentially unfinished label until the next call
+ del labels[-1]
+ if labels:
+ trailing_dot = "."
+
+ result = []
+ size = 0
+ for label in labels:
+ result.append(ulabel(label))
+ if size:
+ size += 1
+ size += len(label)
+
+ result_str = ".".join(result) + trailing_dot
+ size += len(trailing_dot)
+ return (result_str, size)
+
+
+class StreamWriter(Codec, codecs.StreamWriter):
+ pass
+
+
+class StreamReader(Codec, codecs.StreamReader):
+ pass
+
+
+def search_function(name: str) -> Optional[codecs.CodecInfo]:
+ if name != "idna2008":
+ return None
+ return codecs.CodecInfo(
+ name=name,
+ encode=Codec().encode,
+ decode=Codec().decode,
+ incrementalencoder=IncrementalEncoder,
+ incrementaldecoder=IncrementalDecoder,
+ streamwriter=StreamWriter,
+ streamreader=StreamReader,
+ )
+
+
+codecs.register(search_function)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/compat.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..1df9f2a70e6815908f2784e88897a9a359eef84c
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/compat.py
@@ -0,0 +1,15 @@
+from typing import Any, Union
+
+from .core import decode, encode
+
+
+def ToASCII(label: str) -> bytes:
+ return encode(label)
+
+
+def ToUnicode(label: Union[bytes, bytearray]) -> str:
+ return decode(label)
+
+
+def nameprep(s: Any) -> None:
+ raise NotImplementedError("IDNA 2008 does not utilise nameprep protocol")
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/core.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/core.py
new file mode 100644
index 0000000000000000000000000000000000000000..9115f123f0274832af5ba1cf3c5481cc5353eecd
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/core.py
@@ -0,0 +1,437 @@
+import bisect
+import re
+import unicodedata
+from typing import Optional, Union
+
+from . import idnadata
+from .intranges import intranges_contain
+
+_virama_combining_class = 9
+_alabel_prefix = b"xn--"
+_unicode_dots_re = re.compile("[\u002e\u3002\uff0e\uff61]")
+
+
+class IDNAError(UnicodeError):
+ """Base exception for all IDNA-encoding related problems"""
+
+ pass
+
+
+class IDNABidiError(IDNAError):
+ """Exception when bidirectional requirements are not satisfied"""
+
+ pass
+
+
+class InvalidCodepoint(IDNAError):
+ """Exception when a disallowed or unallocated codepoint is used"""
+
+ pass
+
+
+class InvalidCodepointContext(IDNAError):
+ """Exception when the codepoint is not valid in the context it is used"""
+
+ pass
+
+
+def _combining_class(cp: int) -> int:
+ v = unicodedata.combining(chr(cp))
+ if v == 0:
+ if not unicodedata.name(chr(cp)):
+ raise ValueError("Unknown character in unicodedata")
+ return v
+
+
+def _is_script(cp: str, script: str) -> bool:
+ return intranges_contain(ord(cp), idnadata.scripts[script])
+
+
+def _punycode(s: str) -> bytes:
+ return s.encode("punycode")
+
+
+def _unot(s: int) -> str:
+ return "U+{:04X}".format(s)
+
+
+def valid_label_length(label: Union[bytes, str]) -> bool:
+ if len(label) > 63:
+ return False
+ return True
+
+
+def valid_string_length(label: Union[bytes, str], trailing_dot: bool) -> bool:
+ if len(label) > (254 if trailing_dot else 253):
+ return False
+ return True
+
+
+def check_bidi(label: str, check_ltr: bool = False) -> bool:
+ # Bidi rules should only be applied if string contains RTL characters
+ bidi_label = False
+ for idx, cp in enumerate(label, 1):
+ direction = unicodedata.bidirectional(cp)
+ if direction == "":
+ # String likely comes from a newer version of Unicode
+ raise IDNABidiError("Unknown directionality in label {} at position {}".format(repr(label), idx))
+ if direction in ["R", "AL", "AN"]:
+ bidi_label = True
+ if not bidi_label and not check_ltr:
+ return True
+
+ # Bidi rule 1
+ direction = unicodedata.bidirectional(label[0])
+ if direction in ["R", "AL"]:
+ rtl = True
+ elif direction == "L":
+ rtl = False
+ else:
+ raise IDNABidiError("First codepoint in label {} must be directionality L, R or AL".format(repr(label)))
+
+ valid_ending = False
+ number_type: Optional[str] = None
+ for idx, cp in enumerate(label, 1):
+ direction = unicodedata.bidirectional(cp)
+
+ if rtl:
+ # Bidi rule 2
+ if direction not in [
+ "R",
+ "AL",
+ "AN",
+ "EN",
+ "ES",
+ "CS",
+ "ET",
+ "ON",
+ "BN",
+ "NSM",
+ ]:
+ raise IDNABidiError("Invalid direction for codepoint at position {} in a right-to-left label".format(idx))
+ # Bidi rule 3
+ if direction in ["R", "AL", "EN", "AN"]:
+ valid_ending = True
+ elif direction != "NSM":
+ valid_ending = False
+ # Bidi rule 4
+ if direction in ["AN", "EN"]:
+ if not number_type:
+ number_type = direction
+ else:
+ if number_type != direction:
+ raise IDNABidiError("Can not mix numeral types in a right-to-left label")
+ else:
+ # Bidi rule 5
+ if direction not in ["L", "EN", "ES", "CS", "ET", "ON", "BN", "NSM"]:
+ raise IDNABidiError("Invalid direction for codepoint at position {} in a left-to-right label".format(idx))
+ # Bidi rule 6
+ if direction in ["L", "EN"]:
+ valid_ending = True
+ elif direction != "NSM":
+ valid_ending = False
+
+ if not valid_ending:
+ raise IDNABidiError("Label ends with illegal codepoint directionality")
+
+ return True
+
+
+def check_initial_combiner(label: str) -> bool:
+ if unicodedata.category(label[0])[0] == "M":
+ raise IDNAError("Label begins with an illegal combining character")
+ return True
+
+
+def check_hyphen_ok(label: str) -> bool:
+ if label[2:4] == "--":
+ raise IDNAError("Label has disallowed hyphens in 3rd and 4th position")
+ if label[0] == "-" or label[-1] == "-":
+ raise IDNAError("Label must not start or end with a hyphen")
+ return True
+
+
+def check_nfc(label: str) -> None:
+ if unicodedata.normalize("NFC", label) != label:
+ raise IDNAError("Label must be in Normalization Form C")
+
+
+def valid_contextj(label: str, pos: int) -> bool:
+ cp_value = ord(label[pos])
+
+ if cp_value == 0x200C:
+ if pos > 0:
+ if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
+ return True
+
+ ok = False
+ for i in range(pos - 1, -1, -1):
+ joining_type = idnadata.joining_types.get(ord(label[i]))
+ if joining_type == ord("T"):
+ continue
+ elif joining_type in [ord("L"), ord("D")]:
+ ok = True
+ break
+ else:
+ break
+
+ if not ok:
+ return False
+
+ ok = False
+ for i in range(pos + 1, len(label)):
+ joining_type = idnadata.joining_types.get(ord(label[i]))
+ if joining_type == ord("T"):
+ continue
+ elif joining_type in [ord("R"), ord("D")]:
+ ok = True
+ break
+ else:
+ break
+ return ok
+
+ if cp_value == 0x200D:
+ if pos > 0:
+ if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
+ return True
+ return False
+
+ else:
+ return False
+
+
+def valid_contexto(label: str, pos: int, exception: bool = False) -> bool:
+ cp_value = ord(label[pos])
+
+ if cp_value == 0x00B7:
+ if 0 < pos < len(label) - 1:
+ if ord(label[pos - 1]) == 0x006C and ord(label[pos + 1]) == 0x006C:
+ return True
+ return False
+
+ elif cp_value == 0x0375:
+ if pos < len(label) - 1 and len(label) > 1:
+ return _is_script(label[pos + 1], "Greek")
+ return False
+
+ elif cp_value == 0x05F3 or cp_value == 0x05F4:
+ if pos > 0:
+ return _is_script(label[pos - 1], "Hebrew")
+ return False
+
+ elif cp_value == 0x30FB:
+ for cp in label:
+ if cp == "\u30fb":
+ continue
+ if _is_script(cp, "Hiragana") or _is_script(cp, "Katakana") or _is_script(cp, "Han"):
+ return True
+ return False
+
+ elif 0x660 <= cp_value <= 0x669:
+ for cp in label:
+ if 0x6F0 <= ord(cp) <= 0x06F9:
+ return False
+ return True
+
+ elif 0x6F0 <= cp_value <= 0x6F9:
+ for cp in label:
+ if 0x660 <= ord(cp) <= 0x0669:
+ return False
+ return True
+
+ return False
+
+
+def check_label(label: Union[str, bytes, bytearray]) -> None:
+ if isinstance(label, (bytes, bytearray)):
+ label = label.decode("utf-8")
+ if len(label) == 0:
+ raise IDNAError("Empty Label")
+
+ check_nfc(label)
+ check_hyphen_ok(label)
+ check_initial_combiner(label)
+
+ for pos, cp in enumerate(label):
+ cp_value = ord(cp)
+ if intranges_contain(cp_value, idnadata.codepoint_classes["PVALID"]):
+ continue
+ elif intranges_contain(cp_value, idnadata.codepoint_classes["CONTEXTJ"]):
+ try:
+ if not valid_contextj(label, pos):
+ raise InvalidCodepointContext(
+ "Joiner {} not allowed at position {} in {}".format(_unot(cp_value), pos + 1, repr(label))
+ )
+ except ValueError:
+ raise IDNAError(
+ "Unknown codepoint adjacent to joiner {} at position {} in {}".format(
+ _unot(cp_value), pos + 1, repr(label)
+ )
+ )
+ elif intranges_contain(cp_value, idnadata.codepoint_classes["CONTEXTO"]):
+ if not valid_contexto(label, pos):
+ raise InvalidCodepointContext(
+ "Codepoint {} not allowed at position {} in {}".format(_unot(cp_value), pos + 1, repr(label))
+ )
+ else:
+ raise InvalidCodepoint(
+ "Codepoint {} at position {} of {} not allowed".format(_unot(cp_value), pos + 1, repr(label))
+ )
+
+ check_bidi(label)
+
+
+def alabel(label: str) -> bytes:
+ try:
+ label_bytes = label.encode("ascii")
+ ulabel(label_bytes)
+ if not valid_label_length(label_bytes):
+ raise IDNAError("Label too long")
+ return label_bytes
+ except UnicodeEncodeError:
+ pass
+
+ check_label(label)
+ label_bytes = _alabel_prefix + _punycode(label)
+
+ if not valid_label_length(label_bytes):
+ raise IDNAError("Label too long")
+
+ return label_bytes
+
+
+def ulabel(label: Union[str, bytes, bytearray]) -> str:
+ if not isinstance(label, (bytes, bytearray)):
+ try:
+ label_bytes = label.encode("ascii")
+ except UnicodeEncodeError:
+ check_label(label)
+ return label
+ else:
+ label_bytes = label
+
+ label_bytes = label_bytes.lower()
+ if label_bytes.startswith(_alabel_prefix):
+ label_bytes = label_bytes[len(_alabel_prefix) :]
+ if not label_bytes:
+ raise IDNAError("Malformed A-label, no Punycode eligible content found")
+ if label_bytes.decode("ascii")[-1] == "-":
+ raise IDNAError("A-label must not end with a hyphen")
+ else:
+ check_label(label_bytes)
+ return label_bytes.decode("ascii")
+
+ try:
+ label = label_bytes.decode("punycode")
+ except UnicodeError:
+ raise IDNAError("Invalid A-label")
+ check_label(label)
+ return label
+
+
+def uts46_remap(domain: str, std3_rules: bool = True, transitional: bool = False) -> str:
+ """Re-map the characters in the string according to UTS46 processing."""
+ from .uts46data import uts46data
+
+ output = ""
+
+ for pos, char in enumerate(domain):
+ code_point = ord(char)
+ try:
+ uts46row = uts46data[code_point if code_point < 256 else bisect.bisect_left(uts46data, (code_point, "Z")) - 1]
+ status = uts46row[1]
+ replacement: Optional[str] = None
+ if len(uts46row) == 3:
+ replacement = uts46row[2]
+ if (
+ status == "V"
+ or (status == "D" and not transitional)
+ or (status == "3" and not std3_rules and replacement is None)
+ ):
+ output += char
+ elif replacement is not None and (
+ status == "M" or (status == "3" and not std3_rules) or (status == "D" and transitional)
+ ):
+ output += replacement
+ elif status != "I":
+ raise IndexError()
+ except IndexError:
+ raise InvalidCodepoint(
+ "Codepoint {} not allowed at position {} in {}".format(_unot(code_point), pos + 1, repr(domain))
+ )
+
+ return unicodedata.normalize("NFC", output)
+
+
+def encode(
+ s: Union[str, bytes, bytearray],
+ strict: bool = False,
+ uts46: bool = False,
+ std3_rules: bool = False,
+ transitional: bool = False,
+) -> bytes:
+ if not isinstance(s, str):
+ try:
+ s = str(s, "ascii")
+ except UnicodeDecodeError:
+ raise IDNAError("should pass a unicode string to the function rather than a byte string.")
+ if uts46:
+ s = uts46_remap(s, std3_rules, transitional)
+ trailing_dot = False
+ result = []
+ if strict:
+ labels = s.split(".")
+ else:
+ labels = _unicode_dots_re.split(s)
+ if not labels or labels == [""]:
+ raise IDNAError("Empty domain")
+ if labels[-1] == "":
+ del labels[-1]
+ trailing_dot = True
+ for label in labels:
+ s = alabel(label)
+ if s:
+ result.append(s)
+ else:
+ raise IDNAError("Empty label")
+ if trailing_dot:
+ result.append(b"")
+ s = b".".join(result)
+ if not valid_string_length(s, trailing_dot):
+ raise IDNAError("Domain too long")
+ return s
+
+
+def decode(
+ s: Union[str, bytes, bytearray],
+ strict: bool = False,
+ uts46: bool = False,
+ std3_rules: bool = False,
+) -> str:
+ try:
+ if not isinstance(s, str):
+ s = str(s, "ascii")
+ except UnicodeDecodeError:
+ raise IDNAError("Invalid ASCII in A-label")
+ if uts46:
+ s = uts46_remap(s, std3_rules, False)
+ trailing_dot = False
+ result = []
+ if not strict:
+ labels = _unicode_dots_re.split(s)
+ else:
+ labels = s.split(".")
+ if not labels or labels == [""]:
+ raise IDNAError("Empty domain")
+ if not labels[-1]:
+ del labels[-1]
+ trailing_dot = True
+ for label in labels:
+ s = ulabel(label)
+ if s:
+ result.append(s)
+ else:
+ raise IDNAError("Empty label")
+ if trailing_dot:
+ result.append("")
+ return ".".join(result)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/idnadata.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/idnadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..4be6004622efcdc36a8d15efc0ac3e138a4bae02
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/idnadata.py
@@ -0,0 +1,4243 @@
+# This file is automatically generated by tools/idna-data
+
+__version__ = "15.1.0"
+scripts = {
+ "Greek": (
+ 0x37000000374,
+ 0x37500000378,
+ 0x37A0000037E,
+ 0x37F00000380,
+ 0x38400000385,
+ 0x38600000387,
+ 0x3880000038B,
+ 0x38C0000038D,
+ 0x38E000003A2,
+ 0x3A3000003E2,
+ 0x3F000000400,
+ 0x1D2600001D2B,
+ 0x1D5D00001D62,
+ 0x1D6600001D6B,
+ 0x1DBF00001DC0,
+ 0x1F0000001F16,
+ 0x1F1800001F1E,
+ 0x1F2000001F46,
+ 0x1F4800001F4E,
+ 0x1F5000001F58,
+ 0x1F5900001F5A,
+ 0x1F5B00001F5C,
+ 0x1F5D00001F5E,
+ 0x1F5F00001F7E,
+ 0x1F8000001FB5,
+ 0x1FB600001FC5,
+ 0x1FC600001FD4,
+ 0x1FD600001FDC,
+ 0x1FDD00001FF0,
+ 0x1FF200001FF5,
+ 0x1FF600001FFF,
+ 0x212600002127,
+ 0xAB650000AB66,
+ 0x101400001018F,
+ 0x101A0000101A1,
+ 0x1D2000001D246,
+ ),
+ "Han": (
+ 0x2E8000002E9A,
+ 0x2E9B00002EF4,
+ 0x2F0000002FD6,
+ 0x300500003006,
+ 0x300700003008,
+ 0x30210000302A,
+ 0x30380000303C,
+ 0x340000004DC0,
+ 0x4E000000A000,
+ 0xF9000000FA6E,
+ 0xFA700000FADA,
+ 0x16FE200016FE4,
+ 0x16FF000016FF2,
+ 0x200000002A6E0,
+ 0x2A7000002B73A,
+ 0x2B7400002B81E,
+ 0x2B8200002CEA2,
+ 0x2CEB00002EBE1,
+ 0x2EBF00002EE5E,
+ 0x2F8000002FA1E,
+ 0x300000003134B,
+ 0x31350000323B0,
+ ),
+ "Hebrew": (
+ 0x591000005C8,
+ 0x5D0000005EB,
+ 0x5EF000005F5,
+ 0xFB1D0000FB37,
+ 0xFB380000FB3D,
+ 0xFB3E0000FB3F,
+ 0xFB400000FB42,
+ 0xFB430000FB45,
+ 0xFB460000FB50,
+ ),
+ "Hiragana": (
+ 0x304100003097,
+ 0x309D000030A0,
+ 0x1B0010001B120,
+ 0x1B1320001B133,
+ 0x1B1500001B153,
+ 0x1F2000001F201,
+ ),
+ "Katakana": (
+ 0x30A1000030FB,
+ 0x30FD00003100,
+ 0x31F000003200,
+ 0x32D0000032FF,
+ 0x330000003358,
+ 0xFF660000FF70,
+ 0xFF710000FF9E,
+ 0x1AFF00001AFF4,
+ 0x1AFF50001AFFC,
+ 0x1AFFD0001AFFF,
+ 0x1B0000001B001,
+ 0x1B1200001B123,
+ 0x1B1550001B156,
+ 0x1B1640001B168,
+ ),
+}
+joining_types = {
+ 0xAD: 84,
+ 0x300: 84,
+ 0x301: 84,
+ 0x302: 84,
+ 0x303: 84,
+ 0x304: 84,
+ 0x305: 84,
+ 0x306: 84,
+ 0x307: 84,
+ 0x308: 84,
+ 0x309: 84,
+ 0x30A: 84,
+ 0x30B: 84,
+ 0x30C: 84,
+ 0x30D: 84,
+ 0x30E: 84,
+ 0x30F: 84,
+ 0x310: 84,
+ 0x311: 84,
+ 0x312: 84,
+ 0x313: 84,
+ 0x314: 84,
+ 0x315: 84,
+ 0x316: 84,
+ 0x317: 84,
+ 0x318: 84,
+ 0x319: 84,
+ 0x31A: 84,
+ 0x31B: 84,
+ 0x31C: 84,
+ 0x31D: 84,
+ 0x31E: 84,
+ 0x31F: 84,
+ 0x320: 84,
+ 0x321: 84,
+ 0x322: 84,
+ 0x323: 84,
+ 0x324: 84,
+ 0x325: 84,
+ 0x326: 84,
+ 0x327: 84,
+ 0x328: 84,
+ 0x329: 84,
+ 0x32A: 84,
+ 0x32B: 84,
+ 0x32C: 84,
+ 0x32D: 84,
+ 0x32E: 84,
+ 0x32F: 84,
+ 0x330: 84,
+ 0x331: 84,
+ 0x332: 84,
+ 0x333: 84,
+ 0x334: 84,
+ 0x335: 84,
+ 0x336: 84,
+ 0x337: 84,
+ 0x338: 84,
+ 0x339: 84,
+ 0x33A: 84,
+ 0x33B: 84,
+ 0x33C: 84,
+ 0x33D: 84,
+ 0x33E: 84,
+ 0x33F: 84,
+ 0x340: 84,
+ 0x341: 84,
+ 0x342: 84,
+ 0x343: 84,
+ 0x344: 84,
+ 0x345: 84,
+ 0x346: 84,
+ 0x347: 84,
+ 0x348: 84,
+ 0x349: 84,
+ 0x34A: 84,
+ 0x34B: 84,
+ 0x34C: 84,
+ 0x34D: 84,
+ 0x34E: 84,
+ 0x34F: 84,
+ 0x350: 84,
+ 0x351: 84,
+ 0x352: 84,
+ 0x353: 84,
+ 0x354: 84,
+ 0x355: 84,
+ 0x356: 84,
+ 0x357: 84,
+ 0x358: 84,
+ 0x359: 84,
+ 0x35A: 84,
+ 0x35B: 84,
+ 0x35C: 84,
+ 0x35D: 84,
+ 0x35E: 84,
+ 0x35F: 84,
+ 0x360: 84,
+ 0x361: 84,
+ 0x362: 84,
+ 0x363: 84,
+ 0x364: 84,
+ 0x365: 84,
+ 0x366: 84,
+ 0x367: 84,
+ 0x368: 84,
+ 0x369: 84,
+ 0x36A: 84,
+ 0x36B: 84,
+ 0x36C: 84,
+ 0x36D: 84,
+ 0x36E: 84,
+ 0x36F: 84,
+ 0x483: 84,
+ 0x484: 84,
+ 0x485: 84,
+ 0x486: 84,
+ 0x487: 84,
+ 0x488: 84,
+ 0x489: 84,
+ 0x591: 84,
+ 0x592: 84,
+ 0x593: 84,
+ 0x594: 84,
+ 0x595: 84,
+ 0x596: 84,
+ 0x597: 84,
+ 0x598: 84,
+ 0x599: 84,
+ 0x59A: 84,
+ 0x59B: 84,
+ 0x59C: 84,
+ 0x59D: 84,
+ 0x59E: 84,
+ 0x59F: 84,
+ 0x5A0: 84,
+ 0x5A1: 84,
+ 0x5A2: 84,
+ 0x5A3: 84,
+ 0x5A4: 84,
+ 0x5A5: 84,
+ 0x5A6: 84,
+ 0x5A7: 84,
+ 0x5A8: 84,
+ 0x5A9: 84,
+ 0x5AA: 84,
+ 0x5AB: 84,
+ 0x5AC: 84,
+ 0x5AD: 84,
+ 0x5AE: 84,
+ 0x5AF: 84,
+ 0x5B0: 84,
+ 0x5B1: 84,
+ 0x5B2: 84,
+ 0x5B3: 84,
+ 0x5B4: 84,
+ 0x5B5: 84,
+ 0x5B6: 84,
+ 0x5B7: 84,
+ 0x5B8: 84,
+ 0x5B9: 84,
+ 0x5BA: 84,
+ 0x5BB: 84,
+ 0x5BC: 84,
+ 0x5BD: 84,
+ 0x5BF: 84,
+ 0x5C1: 84,
+ 0x5C2: 84,
+ 0x5C4: 84,
+ 0x5C5: 84,
+ 0x5C7: 84,
+ 0x610: 84,
+ 0x611: 84,
+ 0x612: 84,
+ 0x613: 84,
+ 0x614: 84,
+ 0x615: 84,
+ 0x616: 84,
+ 0x617: 84,
+ 0x618: 84,
+ 0x619: 84,
+ 0x61A: 84,
+ 0x61C: 84,
+ 0x620: 68,
+ 0x622: 82,
+ 0x623: 82,
+ 0x624: 82,
+ 0x625: 82,
+ 0x626: 68,
+ 0x627: 82,
+ 0x628: 68,
+ 0x629: 82,
+ 0x62A: 68,
+ 0x62B: 68,
+ 0x62C: 68,
+ 0x62D: 68,
+ 0x62E: 68,
+ 0x62F: 82,
+ 0x630: 82,
+ 0x631: 82,
+ 0x632: 82,
+ 0x633: 68,
+ 0x634: 68,
+ 0x635: 68,
+ 0x636: 68,
+ 0x637: 68,
+ 0x638: 68,
+ 0x639: 68,
+ 0x63A: 68,
+ 0x63B: 68,
+ 0x63C: 68,
+ 0x63D: 68,
+ 0x63E: 68,
+ 0x63F: 68,
+ 0x640: 67,
+ 0x641: 68,
+ 0x642: 68,
+ 0x643: 68,
+ 0x644: 68,
+ 0x645: 68,
+ 0x646: 68,
+ 0x647: 68,
+ 0x648: 82,
+ 0x649: 68,
+ 0x64A: 68,
+ 0x64B: 84,
+ 0x64C: 84,
+ 0x64D: 84,
+ 0x64E: 84,
+ 0x64F: 84,
+ 0x650: 84,
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+ 0x65F: 84,
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+ 0x671: 82,
+ 0x672: 82,
+ 0x673: 82,
+ 0x675: 82,
+ 0x676: 82,
+ 0x677: 82,
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+ 0x679: 68,
+ 0x67A: 68,
+ 0x67B: 68,
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+ 0x682: 68,
+ 0x683: 68,
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+ 0x685: 68,
+ 0x686: 68,
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+ 0x688: 82,
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+ 0x6FF: 68,
+ 0x70F: 84,
+ 0x710: 82,
+ 0x711: 84,
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+}
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/intranges.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/intranges.py
new file mode 100644
index 0000000000000000000000000000000000000000..7bfaa8d80d7dc471d572db0f949460901126e8bd
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/intranges.py
@@ -0,0 +1,57 @@
+"""
+Given a list of integers, made up of (hopefully) a small number of long runs
+of consecutive integers, compute a representation of the form
+((start1, end1), (start2, end2) ...). Then answer the question "was x present
+in the original list?" in time O(log(# runs)).
+"""
+
+import bisect
+from typing import List, Tuple
+
+
+def intranges_from_list(list_: List[int]) -> Tuple[int, ...]:
+ """Represent a list of integers as a sequence of ranges:
+ ((start_0, end_0), (start_1, end_1), ...), such that the original
+ integers are exactly those x such that start_i <= x < end_i for some i.
+
+ Ranges are encoded as single integers (start << 32 | end), not as tuples.
+ """
+
+ sorted_list = sorted(list_)
+ ranges = []
+ last_write = -1
+ for i in range(len(sorted_list)):
+ if i + 1 < len(sorted_list):
+ if sorted_list[i] == sorted_list[i + 1] - 1:
+ continue
+ current_range = sorted_list[last_write + 1 : i + 1]
+ ranges.append(_encode_range(current_range[0], current_range[-1] + 1))
+ last_write = i
+
+ return tuple(ranges)
+
+
+def _encode_range(start: int, end: int) -> int:
+ return (start << 32) | end
+
+
+def _decode_range(r: int) -> Tuple[int, int]:
+ return (r >> 32), (r & ((1 << 32) - 1))
+
+
+def intranges_contain(int_: int, ranges: Tuple[int, ...]) -> bool:
+ """Determine if `int_` falls into one of the ranges in `ranges`."""
+ tuple_ = _encode_range(int_, 0)
+ pos = bisect.bisect_left(ranges, tuple_)
+ # we could be immediately ahead of a tuple (start, end)
+ # with start < int_ <= end
+ if pos > 0:
+ left, right = _decode_range(ranges[pos - 1])
+ if left <= int_ < right:
+ return True
+ # or we could be immediately behind a tuple (int_, end)
+ if pos < len(ranges):
+ left, _ = _decode_range(ranges[pos])
+ if left == int_:
+ return True
+ return False
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/package_data.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/package_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..514ff7e2e68b65f309d30a0b06e6b290d2c353a8
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/package_data.py
@@ -0,0 +1 @@
+__version__ = "3.10"
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/uts46data.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/uts46data.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb894327410debecb64ddf40eddc3131cf8344de
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/idna/uts46data.py
@@ -0,0 +1,8681 @@
+# This file is automatically generated by tools/idna-data
+# vim: set fileencoding=utf-8 :
+
+from typing import List, Tuple, Union
+
+"""IDNA Mapping Table from UTS46."""
+
+
+__version__ = "15.1.0"
+
+
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+ + _seg_32()
+ + _seg_33()
+ + _seg_34()
+ + _seg_35()
+ + _seg_36()
+ + _seg_37()
+ + _seg_38()
+ + _seg_39()
+ + _seg_40()
+ + _seg_41()
+ + _seg_42()
+ + _seg_43()
+ + _seg_44()
+ + _seg_45()
+ + _seg_46()
+ + _seg_47()
+ + _seg_48()
+ + _seg_49()
+ + _seg_50()
+ + _seg_51()
+ + _seg_52()
+ + _seg_53()
+ + _seg_54()
+ + _seg_55()
+ + _seg_56()
+ + _seg_57()
+ + _seg_58()
+ + _seg_59()
+ + _seg_60()
+ + _seg_61()
+ + _seg_62()
+ + _seg_63()
+ + _seg_64()
+ + _seg_65()
+ + _seg_66()
+ + _seg_67()
+ + _seg_68()
+ + _seg_69()
+ + _seg_70()
+ + _seg_71()
+ + _seg_72()
+ + _seg_73()
+ + _seg_74()
+ + _seg_75()
+ + _seg_76()
+ + _seg_77()
+ + _seg_78()
+ + _seg_79()
+ + _seg_80()
+ + _seg_81()
+) # type: Tuple[Union[Tuple[int, str], Tuple[int, str, str]], ...]
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..0282933652fda5b154bd36f91b14ca75fe9e0901
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/METADATA
@@ -0,0 +1,74 @@
+Metadata-Version: 2.4
+Name: MarkupSafe
+Version: 3.0.3
+Summary: Safely add untrusted strings to HTML/XML markup.
+Maintainer-email: Pallets
+License-Expression: BSD-3-Clause
+Project-URL: Donate, https://palletsprojects.com/donate
+Project-URL: Documentation, https://markupsafe.palletsprojects.com/
+Project-URL: Changes, https://markupsafe.palletsprojects.com/page/changes/
+Project-URL: Source, https://github.com/pallets/markupsafe/
+Project-URL: Chat, https://discord.gg/pallets
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Web Environment
+Classifier: Intended Audience :: Developers
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
+Classifier: Topic :: Text Processing :: Markup :: HTML
+Classifier: Typing :: Typed
+Requires-Python: >=3.9
+Description-Content-Type: text/markdown
+License-File: LICENSE.txt
+Dynamic: license-file
+
+
+
+# MarkupSafe
+
+MarkupSafe implements a text object that escapes characters so it is
+safe to use in HTML and XML. Characters that have special meanings are
+replaced so that they display as the actual characters. This mitigates
+injection attacks, meaning untrusted user input can safely be displayed
+on a page.
+
+
+## Examples
+
+```pycon
+>>> from markupsafe import Markup, escape
+
+>>> # escape replaces special characters and wraps in Markup
+>>> escape("")
+Markup('<script>alert(document.cookie);</script>')
+
+>>> # wrap in Markup to mark text "safe" and prevent escaping
+>>> Markup("Hello")
+Markup('hello')
+
+>>> escape(Markup("Hello"))
+Markup('hello')
+
+>>> # Markup is a str subclass
+>>> # methods and operators escape their arguments
+>>> template = Markup("Hello {name}")
+>>> template.format(name='"World"')
+Markup('Hello "World"')
+```
+
+## Donate
+
+The Pallets organization develops and supports MarkupSafe and other
+popular packages. In order to grow the community of contributors and
+users, and allow the maintainers to devote more time to the projects,
+[please donate today][].
+
+[please donate today]: https://palletsprojects.com/donate
+
+## Contributing
+
+See our [detailed contributing documentation][contrib] for many ways to
+contribute, including reporting issues, requesting features, asking or answering
+questions, and making PRs.
+
+[contrib]: https://palletsprojects.com/contributing/
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..8df476b897fab0d70a53919754ad0d117ffbc29f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/RECORD
@@ -0,0 +1,14 @@
+markupsafe-3.0.3.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+markupsafe-3.0.3.dist-info/METADATA,sha256=ErTMYaf6KIz3Zn7j8hN4bZYZ21f7M_9vk0r7y1wS7IE,2690
+markupsafe-3.0.3.dist-info/RECORD,,
+markupsafe-3.0.3.dist-info/WHEEL,sha256=DxRnWQz-Kp9-4a4hdDHsSv0KUC3H7sN9Nbef3-8RjXU,190
+markupsafe-3.0.3.dist-info/licenses/LICENSE.txt,sha256=SJqOEQhQntmKN7uYPhHg9-HTHwvY-Zp5yESOf_N9B-o,1475
+markupsafe-3.0.3.dist-info/top_level.txt,sha256=qy0Plje5IJuvsCBjejJyhDCjEAdcDLK_2agVcex8Z6U,11
+markupsafe/__init__.py,sha256=u1fLcNCx0P8E7LT6z3OXf6ipnSmgm6aefne5y-d7o40,13248
+markupsafe/__pycache__/__init__.cpython-312.pyc,,
+markupsafe/__pycache__/_native.cpython-312.pyc,,
+markupsafe/_native.py,sha256=hSLs8Jmz5aqayuengJJ3kdT5PwNpBWpKrmQSdipndC8,210
+markupsafe/_speedups.c,sha256=t3tC6oVV7-bmKUqvCO5pVSky-G8ACIXpWMaJwkNtJjg,4327
+markupsafe/_speedups.cpython-312-x86_64-linux-gnu.so,sha256=9KMd4HHFZZWQAtspvzbG-NNa55KfZHAK3uukb6T5Da8,44072
+markupsafe/_speedups.pyi,sha256=ENd1bYe7gbBUf2ywyYWOGUpnXOHNJ-cgTNqetlW8h5k,41
+markupsafe/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..f3e8a970f16adf4526f1722547053522d94bf860
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/WHEEL
@@ -0,0 +1,7 @@
+Wheel-Version: 1.0
+Generator: setuptools (80.9.0)
+Root-Is-Purelib: false
+Tag: cp312-cp312-manylinux_2_17_x86_64
+Tag: cp312-cp312-manylinux2014_x86_64
+Tag: cp312-cp312-manylinux_2_28_x86_64
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..75bf729258f9daef77370b6df1a57940f90fc23f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/markupsafe-3.0.3.dist-info/top_level.txt
@@ -0,0 +1 @@
+markupsafe
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/LICENSE b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..1862de44521a83ca1462578766d0700b12ffe2b1
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2016 Tsuyoshi Hombashi
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..7ee53cbc327f5b648234bf9cb13e81d58bcf72ab
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/METADATA
@@ -0,0 +1,130 @@
+Metadata-Version: 2.2
+Name: mbstrdecoder
+Version: 1.1.4
+Summary: mbstrdecoder is a Python library for multi-byte character string decoder
+Home-page: https://github.com/thombashi/mbstrdecoder
+Author: Tsuyoshi Hombashi
+Author-email: tsuyoshi.hombashi@gmail.com
+License: MIT License
+Project-URL: Changelog, https://github.com/thombashi/mbstrdecoder/releases
+Project-URL: Source, https://github.com/thombashi/mbstrdecoder
+Project-URL: Tracker, https://github.com/thombashi/mbstrdecoder/issues
+Keywords: multi-byte character,unicode,decoder
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Information Technology
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Text Processing
+Requires-Python: >=3.9
+Description-Content-Type: text/x-rst
+License-File: LICENSE
+Requires-Dist: chardet<6,>=3.0.4
+Provides-Extra: test
+Requires-Dist: Faker>=1.0.2; extra == "test"
+Requires-Dist: pytest>=6.0.1; extra == "test"
+Requires-Dist: pytest-md-report>=0.6.2; extra == "test"
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: keywords
+Dynamic: license
+Dynamic: project-url
+Dynamic: provides-extra
+Dynamic: requires-dist
+Dynamic: requires-python
+Dynamic: summary
+
+.. contents:: **mbstrdecoder**
+ :backlinks: top
+ :local:
+
+
+Summary
+=======
+`mbstrdecoder `__ is a Python library for multi-byte character string decoder.
+
+
+.. image:: https://badge.fury.io/py/mbstrdecoder.svg
+ :target: https://badge.fury.io/py/mbstrdecoder
+ :alt: PyPI package version
+
+.. image:: https://img.shields.io/pypi/pyversions/mbstrdecoder.svg
+ :target: https://pypi.org/project/mbstrdecoder
+ :alt: Supported Python versions
+
+.. image:: https://img.shields.io/pypi/implementation/mbstrdecoder.svg
+ :target: https://pypi.org/project/mbstrdecoder
+ :alt: Supported Python implementations
+
+.. image:: https://github.com/thombashi/mbstrdecoder/actions/workflows/ci.yml/badge.svg
+ :target: https://github.com/thombashi/mbstrdecoder/actions/workflows/ci.yml
+ :alt: CI status of Linux/macOS/Windows
+
+.. image:: https://coveralls.io/repos/github/thombashi/mbstrdecoder/badge.svg?branch=master
+ :target: https://coveralls.io/github/thombashi/mbstrdecoder?branch=master
+ :alt: Test coverage
+
+.. image:: https://github.com/thombashi/mbstrdecoder/actions/workflows/github-code-scanning/codeql/badge.svg
+ :target: https://github.com/thombashi/mbstrdecoder/actions/workflows/github-code-scanning/codeql
+ :alt: CodeQL
+
+
+Installation
+============
+
+Install from PyPI
+------------------------------
+::
+
+ pip install mbstrdecoder
+
+Install from PPA (for Ubuntu)
+------------------------------
+::
+
+ sudo add-apt-repository ppa:thombashi/ppa
+ sudo apt update
+ sudo apt install python3-mbstrdecoder
+
+
+Usage
+=====
+
+:Sample Code:
+ .. code:: python
+
+ from mbstrdecoder import MultiByteStrDecoder
+
+ encoded_multibyte_text = "マルチバイト文字".encode("utf-8")
+ decoder = MultiByteStrDecoder(encoded_multibyte_text)
+
+ print("encoded bytes: {}".format(encoded_multibyte_text))
+ print("unicode: {}".format(decoder.unicode_str))
+ print("codec: {}".format(decoder.codec))
+
+:Output:
+ ::
+
+ encoded bytes: b'\xe3\x83\x9e\xe3\x83\xab\xe3\x83\x81\xe3\x83\x90\xe3\x82\xa4\xe3\x83\x88\xe6\x96\x87\xe5\xad\x97'
+ unicode: マルチバイト文字
+ codec: utf_8
+
+
+Dependencies
+============
+- Python 3.9+
+- `Python package dependencies (automatically installed) `__
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..eeac0fa3ed560dabe46db3891b713b35fa4a3b93
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/RECORD
@@ -0,0 +1,17 @@
+mbstrdecoder-1.1.4.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+mbstrdecoder-1.1.4.dist-info/LICENSE,sha256=dYgmUILu1en0r9UJDFfmELdA7FR7Fqqqtzm6B8Xu-xU,1074
+mbstrdecoder-1.1.4.dist-info/METADATA,sha256=w6809Ma7MwoF172f6rtiYfVBYC3dSHl7g8Z0ixZhMns,4324
+mbstrdecoder-1.1.4.dist-info/RECORD,,
+mbstrdecoder-1.1.4.dist-info/WHEEL,sha256=In9FTNxeP60KnTkGw7wk6mJPYd_dQSjEZmXdBdMCI-8,91
+mbstrdecoder-1.1.4.dist-info/top_level.txt,sha256=3y6PBjWqWXF9e7O35XqgW93XW_H9qgTn9hAdzSurYi8,13
+mbstrdecoder/__init__.py,sha256=PxnzGe3PGQin5go9OetP3JudLVAEYcCm9cgKE-u4HaI,413
+mbstrdecoder/__pycache__/__init__.cpython-312.pyc,,
+mbstrdecoder/__pycache__/__version__.cpython-312.pyc,,
+mbstrdecoder/__pycache__/_binary_ext_checker.cpython-312.pyc,,
+mbstrdecoder/__pycache__/_func.cpython-312.pyc,,
+mbstrdecoder/__pycache__/_mbstrdecoder.cpython-312.pyc,,
+mbstrdecoder/__version__.py,sha256=9uiRn0UjGmimLdMei8SZQr51ivxfcjH2E7poFlRv5Ls,263
+mbstrdecoder/_binary_ext_checker.py,sha256=9sw0C93xqgSLh4tZ1ZDvJ9YuU8OawGoLfSO_dDJ386U,3145
+mbstrdecoder/_func.py,sha256=hKIuRBCMFedtn4dJ5xlA2CNTxCDTZ5-0OK_kKWTL4Ug,1355
+mbstrdecoder/_mbstrdecoder.py,sha256=-Em6JE36aI-5zIeO8rm4_VPifMD1Z8hTGUoJTmvgRag,7465
+mbstrdecoder/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..505164bc02d63fe6b0b3299f849a77c5f1beeb41
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: setuptools (75.8.0)
+Root-Is-Purelib: true
+Tag: py3-none-any
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..31360f530d112f5bbb908674fcaa34adfd99bf4b
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder-1.1.4.dist-info/top_level.txt
@@ -0,0 +1 @@
+mbstrdecoder
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__init__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e38a6ea6e8f998e4b20351520bed3486af4788dc
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__init__.py
@@ -0,0 +1,18 @@
+"""
+.. codeauthor:: Tsuyoshi Hombashi
+"""
+
+from .__version__ import __author__, __copyright__, __email__, __license__, __version__
+from ._func import detect_file_encoding
+from ._mbstrdecoder import MultiByteStrDecoder
+
+
+__all__ = (
+ "__author__",
+ "__copyright__",
+ "__email__",
+ "__license__",
+ "__version__",
+ "detect_file_encoding",
+ "MultiByteStrDecoder",
+)
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__version__.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__version__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9efb6c14977a676921b35244a07cd84a3372f752
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/__version__.py
@@ -0,0 +1,9 @@
+from typing import Final
+
+
+__author__: Final = "Tsuyoshi Hombashi"
+__copyright__: Final = f"Copyright 2016, {__author__}"
+__license__: Final = "MIT License"
+__version__ = "1.1.4"
+__maintainer__: Final = __author__
+__email__: Final = "tsuyoshi.hombashi@gmail.com"
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_binary_ext_checker.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_binary_ext_checker.py
new file mode 100644
index 0000000000000000000000000000000000000000..41cbe1a4dbfd3af577fef078705a1bbc630b19d9
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_binary_ext_checker.py
@@ -0,0 +1,265 @@
+"""
+.. codeauthor:: Tsuyoshi Hombashi
+"""
+
+import os.path
+from typing import Final
+
+
+# list from https://github.com/sindresorhus/binary-extensions
+binary_exts: Final = (
+ "3dm",
+ "3ds",
+ "3g2",
+ "3gp",
+ "7z",
+ "a",
+ "aac",
+ "adp",
+ "ai",
+ "aif",
+ "aiff",
+ "alz",
+ "ape",
+ "apk",
+ "ar",
+ "arj",
+ "asf",
+ "au",
+ "avi",
+ "bak",
+ "baml",
+ "bh",
+ "bin",
+ "bk",
+ "bmp",
+ "btif",
+ "bz2",
+ "bzip2",
+ "cab",
+ "caf",
+ "cgm",
+ "class",
+ "cmx",
+ "cpio",
+ "cr2",
+ "cur",
+ "dat",
+ "dcm",
+ "deb",
+ "dex",
+ "djvu",
+ "dll",
+ "dmg",
+ "dng",
+ "doc",
+ "docm",
+ "docx",
+ "dot",
+ "dotm",
+ "dra",
+ "DS_Store",
+ "dsk",
+ "dts",
+ "dtshd",
+ "dvb",
+ "dwg",
+ "dxf",
+ "ecelp4800",
+ "ecelp7470",
+ "ecelp9600",
+ "egg",
+ "eol",
+ "eot",
+ "epub",
+ "exe",
+ "f4v",
+ "fbs",
+ "fh",
+ "fla",
+ "flac",
+ "fli",
+ "flv",
+ "fpx",
+ "fst",
+ "fvt",
+ "g3",
+ "gh",
+ "gif",
+ "graffle",
+ "gz",
+ "gzip",
+ "h261",
+ "h263",
+ "h264",
+ "icns",
+ "ico",
+ "ief",
+ "img",
+ "ipa",
+ "iso",
+ "jar",
+ "jpeg",
+ "jpg",
+ "jpgv",
+ "jpm",
+ "jxr",
+ "key",
+ "ktx",
+ "lha",
+ "lib",
+ "lvp",
+ "lz",
+ "lzh",
+ "lzma",
+ "lzo",
+ "m3u",
+ "m4a",
+ "m4v",
+ "mar",
+ "mdi",
+ "mht",
+ "mid",
+ "midi",
+ "mj2",
+ "mka",
+ "mkv",
+ "mmr",
+ "mng",
+ "mobi",
+ "mov",
+ "movie",
+ "mp3",
+ "mp4",
+ "mp4a",
+ "mpeg",
+ "mpg",
+ "mpga",
+ "mxu",
+ "nef",
+ "npx",
+ "numbers",
+ "nupkg",
+ "o",
+ "oga",
+ "ogg",
+ "ogv",
+ "otf",
+ "pages",
+ "pbm",
+ "pcx",
+ "pdb",
+ "pdf",
+ "pea",
+ "pgm",
+ "pic",
+ "png",
+ "pnm",
+ "pot",
+ "potm",
+ "potx",
+ "ppa",
+ "ppam",
+ "ppm",
+ "pps",
+ "ppsm",
+ "ppsx",
+ "ppt",
+ "pptm",
+ "pptx",
+ "psd",
+ "pya",
+ "pyc",
+ "pyo",
+ "pyv",
+ "qt",
+ "rar",
+ "ras",
+ "raw",
+ "resources",
+ "rgb",
+ "rip",
+ "rlc",
+ "rmf",
+ "rmvb",
+ "rtf",
+ "rz",
+ "s3m",
+ "s7z",
+ "scpt",
+ "sgi",
+ "shar",
+ "sil",
+ "sketch",
+ "slk",
+ "smv",
+ "snk",
+ "so",
+ "stl",
+ "suo",
+ "sub",
+ "swf",
+ "tar",
+ "tbz",
+ "tbz2",
+ "tga",
+ "tgz",
+ "thmx",
+ "tif",
+ "tiff",
+ "tlz",
+ "ttc",
+ "ttf",
+ "txz",
+ "udf",
+ "uvh",
+ "uvi",
+ "uvm",
+ "uvp",
+ "uvs",
+ "uvu",
+ "viv",
+ "vob",
+ "war",
+ "wav",
+ "wax",
+ "wbmp",
+ "wdp",
+ "weba",
+ "webm",
+ "webp",
+ "whl",
+ "wim",
+ "wm",
+ "wma",
+ "wmv",
+ "wmx",
+ "woff",
+ "woff2",
+ "wrm",
+ "wvx",
+ "xbm",
+ "xif",
+ "xla",
+ "xlam",
+ "xls",
+ "xlsb",
+ "xlsm",
+ "xlsx",
+ "xlt",
+ "xltm",
+ "xltx",
+ "xm",
+ "xmind",
+ "xpi",
+ "xpm",
+ "xwd",
+ "xz",
+ "z",
+ "zip",
+ "zipx",
+)
+
+
+def is_binary_ext_path(filepath) -> bool:
+ return os.path.splitext(filepath)[1].lstrip(".") in binary_exts
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_func.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_func.py
new file mode 100644
index 0000000000000000000000000000000000000000..c0e31dbecbd167e1426a7b73aaa91a0c63722878
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_func.py
@@ -0,0 +1,56 @@
+"""
+.. codeauthor:: Tsuyoshi Hombashi
+"""
+
+import os
+import stat
+from errno import EBADF, ENOENT, ENOTDIR
+from typing import Optional, Union
+
+from ._binary_ext_checker import is_binary_ext_path
+
+
+def is_fifo(file_path: Union[int, bytes, str]) -> bool:
+ try:
+ return stat.S_ISFIFO(os.stat(file_path).st_mode)
+ except OSError as e:
+ if e.errno not in (ENOENT, ENOTDIR, EBADF):
+ raise
+
+ return False
+ except ValueError:
+ return False
+
+
+def to_codec_name(name: Optional[str]) -> Optional[str]:
+ if not name:
+ return None
+
+ return name.lower().replace("-", "_")
+
+
+def detect_file_encoding(file_path) -> Optional[str]:
+ from chardet.universaldetector import UniversalDetector
+
+ if not os.path.isfile(file_path) or is_binary_ext_path(file_path) or is_fifo(file_path):
+ return None
+
+ detector = UniversalDetector()
+ READ_SIZE = 4 * 1024
+
+ try:
+ with open(file_path, mode="rb") as f:
+ while True:
+ binary = f.read(READ_SIZE)
+ if not binary:
+ break
+
+ detector.feed(binary)
+ if detector.done:
+ break
+ except OSError:
+ return None
+ finally:
+ detector.close()
+
+ return to_codec_name(detector.result.get("encoding"))
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_mbstrdecoder.py b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_mbstrdecoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..76b91aa97916096d0c34b87ad6c00ed7a116c186
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/_mbstrdecoder.py
@@ -0,0 +1,292 @@
+"""
+.. codeauthor:: Tsuyoshi Hombashi
+"""
+
+import copy
+import re
+from collections.abc import Sequence
+from typing import Final, Optional
+
+from ._func import to_codec_name
+
+
+def b(s: str) -> bytes:
+ return s.encode("latin-1")
+
+
+class MultiByteStrDecoder:
+ """
+ Reference:
+ https://docs.python.org/3/library/codecs.html
+ """
+
+ __CODECS: Final = [
+ "utf_7",
+ "utf_8",
+ "utf_8_sig",
+ "utf_16",
+ "utf_16_be",
+ "utf_16_le",
+ "utf_32",
+ "utf_32_be",
+ "utf_32_le",
+ "big5",
+ "big5hkscs",
+ "cp037",
+ "cp424",
+ "cp437",
+ "cp500",
+ "cp720",
+ "cp737",
+ "cp775",
+ "cp850",
+ "cp852",
+ "cp855",
+ "cp856",
+ "cp857",
+ "cp858",
+ "cp860",
+ "cp861",
+ "cp862",
+ "cp863",
+ "cp864",
+ "cp865",
+ "cp866",
+ "cp869",
+ "cp874",
+ "cp875",
+ "cp932",
+ "cp949",
+ "cp950",
+ "cp1006",
+ "cp1026",
+ "cp1140",
+ "cp1250",
+ "cp1251",
+ "cp1252",
+ "cp1253",
+ "cp1254",
+ "cp1255",
+ "cp1256",
+ "cp1257",
+ "cp1258",
+ "euc_jp",
+ "euc_jis_2004",
+ "euc_jisx0213",
+ "euc_kr",
+ "gb2312",
+ "gbk",
+ "gb18030",
+ "hz",
+ "iso2022_jp",
+ "iso2022_jp_1",
+ "iso2022_jp_2",
+ "iso2022_jp_2004",
+ "iso2022_jp_3",
+ "iso2022_jp_ext",
+ "iso2022_kr",
+ "latin_1",
+ "iso8859_2",
+ "iso8859_3",
+ "iso8859_4",
+ "iso8859_5",
+ "iso8859_6",
+ "iso8859_7",
+ "iso8859_8",
+ "iso8859_9",
+ "iso8859_10",
+ "iso8859_11",
+ "iso8859_13",
+ "iso8859_14",
+ "iso8859_15",
+ "iso8859_16",
+ "johab",
+ "koi8_r",
+ "koi8_u",
+ "mac_cyrillic",
+ "mac_greek",
+ "mac_iceland",
+ "mac_latin2",
+ "mac_roman",
+ "mac_turkish",
+ "ptcp154",
+ "shift_jis",
+ "shift_jis_2004",
+ "shift_jisx0213",
+ "base64_codec",
+ "bz2_codec",
+ "hex_codec",
+ "idna",
+ "mbcs",
+ "palmos",
+ "punycode",
+ "quopri_codec",
+ "raw_unicode_escape",
+ "rot_13",
+ "string_escape",
+ "unicode_escape",
+ "unicode_internal",
+ "uu_codec",
+ "zlib_codec",
+ ]
+ __RE_UTF7 = re.compile(b("[+].*?[-]"))
+
+ @property
+ def unicode_str(self) -> str:
+ return self.__unicode_str
+
+ @property
+ def codec(self) -> Optional[str]:
+ return self.__codec
+
+ def __init__(self, value, codec_candidates: Optional[Sequence[str]] = None) -> None:
+ self.__encoded_str = value
+ self.__codec: Optional[str] = None
+ if codec_candidates is None:
+ self.__codec_candidate_list: list[str] = []
+ else:
+ self.__codec_candidate_list = list(codec_candidates)
+
+ self.__validate_str()
+
+ self.__unicode_str = self.__to_unicode()
+
+ def __repr__(self) -> str:
+ return f"codec={self.codec:s}, unicode={self.unicode_str:s}"
+
+ def __validate_str(self) -> None:
+ if isinstance(self.__encoded_str, (str, bytes)):
+ return
+
+ raise ValueError(f"value must be a string: actual={type(self.__encoded_str)}")
+
+ def __is_buffer(self) -> bool:
+ return isinstance(self.__encoded_str, memoryview)
+
+ def __is_multibyte_utf7(self, encoded_str) -> bool:
+ if self.__codec != "utf_7":
+ return False
+
+ utf7_symbol_count = encoded_str.count(b("+"))
+ if utf7_symbol_count <= 0:
+ return False
+
+ if utf7_symbol_count != encoded_str.count(b("-")):
+ return False
+
+ return utf7_symbol_count == len(self.__RE_UTF7.findall(encoded_str))
+
+ def __get_encoded_str(self) -> str:
+ if self.__is_buffer():
+ return str(self.__encoded_str)
+
+ return self.__encoded_str
+
+ @staticmethod
+ def __detect_encoding_helper(encoded_str) -> Optional[str]:
+ import chardet
+
+ try:
+ detect = chardet.detect(encoded_str)
+ except TypeError:
+ detect = {} # type: ignore
+
+ detect_encoding = detect.get("encoding")
+ confidence = detect.get("confidence")
+
+ if detect_encoding not in ["ascii", "utf-8"] and confidence and confidence > 0.7:
+ # utf7 tend to be misrecognized as ascii
+ return detect_encoding
+
+ return None
+
+ def __get_codec_candidate_list(self, encoded_str) -> list[str]:
+ codec_candidate_list = copy.deepcopy(self.__CODECS)
+ detect_encoding = self.__detect_encoding_helper(encoded_str)
+
+ if detect_encoding:
+ try:
+ codec_candidate_list.remove(detect_encoding)
+ except ValueError:
+ pass
+
+ codec_candidate_list.insert(0, detect_encoding)
+
+ for codec_candidate in self.__codec_candidate_list:
+ try:
+ codec_candidate_list.remove(codec_candidate)
+ except ValueError:
+ pass
+
+ return self.__codec_candidate_list + codec_candidate_list
+
+ def __to_unicode(self):
+ encoded_str = self.__get_encoded_str()
+
+ if encoded_str == b"":
+ self.__codec = "unicode"
+ return ""
+
+ for codec in self.__get_codec_candidate_list(encoded_str):
+ if not codec:
+ continue
+
+ try:
+ self.__codec = to_codec_name(codec)
+ decoded_str = encoded_str.decode(codec) # type: ignore
+ break
+ except UnicodeDecodeError:
+ self.__codec = None
+ continue
+ except AttributeError:
+ if isinstance(encoded_str, str):
+ # already a unicode string (python 3)
+ self.__codec = "unicode"
+
+ if not encoded_str:
+ return encoded_str
+
+ return encoded_str
+
+ self.__codec = None
+
+ try:
+ return f"{encoded_str}"
+ except UnicodeDecodeError:
+ # some of the objects that cannot convertible to a string
+ # may reach this line
+ raise TypeError("argument must be a string")
+ else:
+ self.__codec = None
+
+ try:
+ message = f"unknown codec: encoded_str={encoded_str}"
+ except UnicodeDecodeError:
+ message = f"unknown codec: value-type={type(encoded_str)}"
+
+ raise UnicodeDecodeError("unknown", b"", 0, len(encoded_str), message)
+
+ if self.codec == "utf_7":
+ return self.__process_utf7(encoded_str, decoded_str)
+
+ return decoded_str
+
+ def __process_utf7(self, encoded_str, decoded_str) -> str:
+ if not encoded_str:
+ self.__codec = "unicode"
+
+ return encoded_str
+
+ if self.__is_multibyte_utf7(encoded_str):
+ try:
+ decoded_str.encode("ascii")
+
+ self.__codec = "ascii"
+
+ return encoded_str.decode("ascii")
+ except UnicodeEncodeError:
+ return decoded_str
+
+ self.__codec = "ascii"
+
+ return encoded_str.decode("ascii")
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/py.typed b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/mbstrdecoder/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/LICENSE.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d226599fd2ec2f3353ffb0c434cd8be1b570ac95
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/LICENSE.txt
@@ -0,0 +1,971 @@
+Copyright (c) 2005-2023, NumPy Developers.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+
+ * Neither the name of the NumPy Developers nor the names of any
+ contributors may be used to endorse or promote products derived
+ from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+----
+
+The NumPy repository and source distributions bundle several libraries that are
+compatibly licensed. We list these here.
+
+Name: lapack-lite
+Files: numpy/linalg/lapack_lite/*
+License: BSD-3-Clause
+ For details, see numpy/linalg/lapack_lite/LICENSE.txt
+
+Name: tempita
+Files: tools/npy_tempita/*
+License: MIT
+ For details, see tools/npy_tempita/license.txt
+
+Name: dragon4
+Files: numpy/core/src/multiarray/dragon4.c
+License: MIT
+ For license text, see numpy/core/src/multiarray/dragon4.c
+
+Name: libdivide
+Files: numpy/core/include/numpy/libdivide/*
+License: Zlib
+ For license text, see numpy/core/include/numpy/libdivide/LICENSE.txt
+
+
+Note that the following files are vendored in the repository and sdist but not
+installed in built numpy packages:
+
+Name: Meson
+Files: vendored-meson/meson/*
+License: Apache 2.0
+ For license text, see vendored-meson/meson/COPYING
+
+Name: spin
+Files: .spin/cmds.py
+License: BSD-3
+ For license text, see .spin/LICENSE
+
+----
+
+This binary distribution of NumPy also bundles the following software:
+
+
+Name: OpenBLAS
+Files: numpy.libs/libopenblas*.so
+Description: bundled as a dynamically linked library
+Availability: https://github.com/OpenMathLib/OpenBLAS/
+License: BSD-3-Clause
+ Copyright (c) 2011-2014, The OpenBLAS Project
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+
+ 1. Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+
+ 2. Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimer in
+ the documentation and/or other materials provided with the
+ distribution.
+ 3. Neither the name of the OpenBLAS project nor the names of
+ its contributors may be used to endorse or promote products
+ derived from this software without specific prior written
+ permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+ DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+ CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+ OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
+ USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+Name: LAPACK
+Files: numpy.libs/libopenblas*.so
+Description: bundled in OpenBLAS
+Availability: https://github.com/OpenMathLib/OpenBLAS/
+License: BSD-3-Clause-Attribution
+ Copyright (c) 1992-2013 The University of Tennessee and The University
+ of Tennessee Research Foundation. All rights
+ reserved.
+ Copyright (c) 2000-2013 The University of California Berkeley. All
+ rights reserved.
+ Copyright (c) 2006-2013 The University of Colorado Denver. All rights
+ reserved.
+
+ $COPYRIGHT$
+
+ Additional copyrights may follow
+
+ $HEADER$
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+
+ - Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+
+ - Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimer listed
+ in this license in the documentation and/or other materials
+ provided with the distribution.
+
+ - Neither the name of the copyright holders nor the names of its
+ contributors may be used to endorse or promote products derived from
+ this software without specific prior written permission.
+
+ The copyright holders provide no reassurances that the source code
+ provided does not infringe any patent, copyright, or any other
+ intellectual property rights of third parties. The copyright holders
+ disclaim any liability to any recipient for claims brought against
+ recipient by any third party for infringement of that parties
+ intellectual property rights.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+Name: GCC runtime library
+Files: numpy.libs/libgfortran*.so
+Description: dynamically linked to files compiled with gcc
+Availability: https://gcc.gnu.org/git/?p=gcc.git;a=tree;f=libgfortran
+License: GPL-3.0-with-GCC-exception
+ Copyright (C) 2002-2017 Free Software Foundation, Inc.
+
+ Libgfortran is free software; you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation; either version 3, or (at your option)
+ any later version.
+
+ Libgfortran is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ Under Section 7 of GPL version 3, you are granted additional
+ permissions described in the GCC Runtime Library Exception, version
+ 3.1, as published by the Free Software Foundation.
+
+ You should have received a copy of the GNU General Public License and
+ a copy of the GCC Runtime Library Exception along with this program;
+ see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
+ .
+
+----
+
+Full text of license texts referred to above follows (that they are
+listed below does not necessarily imply the conditions apply to the
+present binary release):
+
+----
+
+GCC RUNTIME LIBRARY EXCEPTION
+
+Version 3.1, 31 March 2009
+
+Copyright (C) 2009 Free Software Foundation, Inc.
+
+Everyone is permitted to copy and distribute verbatim copies of this
+license document, but changing it is not allowed.
+
+This GCC Runtime Library Exception ("Exception") is an additional
+permission under section 7 of the GNU General Public License, version
+3 ("GPLv3"). It applies to a given file (the "Runtime Library") that
+bears a notice placed by the copyright holder of the file stating that
+the file is governed by GPLv3 along with this Exception.
+
+When you use GCC to compile a program, GCC may combine portions of
+certain GCC header files and runtime libraries with the compiled
+program. The purpose of this Exception is to allow compilation of
+non-GPL (including proprietary) programs to use, in this way, the
+header files and runtime libraries covered by this Exception.
+
+0. Definitions.
+
+A file is an "Independent Module" if it either requires the Runtime
+Library for execution after a Compilation Process, or makes use of an
+interface provided by the Runtime Library, but is not otherwise based
+on the Runtime Library.
+
+"GCC" means a version of the GNU Compiler Collection, with or without
+modifications, governed by version 3 (or a specified later version) of
+the GNU General Public License (GPL) with the option of using any
+subsequent versions published by the FSF.
+
+"GPL-compatible Software" is software whose conditions of propagation,
+modification and use would permit combination with GCC in accord with
+the license of GCC.
+
+"Target Code" refers to output from any compiler for a real or virtual
+target processor architecture, in executable form or suitable for
+input to an assembler, loader, linker and/or execution
+phase. Notwithstanding that, Target Code does not include data in any
+format that is used as a compiler intermediate representation, or used
+for producing a compiler intermediate representation.
+
+The "Compilation Process" transforms code entirely represented in
+non-intermediate languages designed for human-written code, and/or in
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..8246dc4ed3bfc5e7ea1f402d2aff1b74ca62e16f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/METADATA
@@ -0,0 +1,1092 @@
+Metadata-Version: 2.1
+Name: numpy
+Version: 1.26.4
+Summary: Fundamental package for array computing in Python
+Home-page: https://numpy.org
+Author: Travis E. Oliphant et al.
+Maintainer-Email: NumPy Developers
+License: Copyright (c) 2005-2023, NumPy Developers.
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+
+
+
+
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+https://pypi.org/project/numpy/)
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+https://anaconda.org/conda-forge/numpy)
+[](
+https://stackoverflow.com/questions/tagged/numpy)
+[](
+https://doi.org/10.1038/s41586-020-2649-2)
+[](https://api.securityscorecards.dev/projects/github.com/numpy/numpy)
+
+
+NumPy is the fundamental package for scientific computing with Python.
+
+- **Website:** https://www.numpy.org
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+- **Bug reports:** https://github.com/numpy/numpy/issues
+- **Report a security vulnerability:** https://tidelift.com/docs/security
+
+It provides:
+
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+- sophisticated (broadcasting) functions
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+- useful linear algebra, Fourier transform, and random number capabilities
+
+Testing:
+
+NumPy requires `pytest` and `hypothesis`. Tests can then be run after installation with:
+
+ python -c "import numpy, sys; sys.exit(numpy.test() is False)"
+
+Code of Conduct
+----------------------
+
+NumPy is a community-driven open source project developed by a diverse group of
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+Call for Contributions
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+If you are new to contributing to open source, [this
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..5a242d1914efcf6460643da121f9e26a31413e0f
--- /dev/null
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..d98ef534f680b37433e9ab0f8470bdbe56c303d8
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/WHEEL
@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: meson
+Root-Is-Purelib: false
+Tag: cp312-cp312-manylinux_2_17_x86_64
+Tag: cp312-cp312-manylinux2014_x86_64
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/entry_points.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/entry_points.txt
new file mode 100644
index 0000000000000000000000000000000000000000..450d8ef27b9d42527fde6aced068dd7e13f2c9a3
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/numpy-1.26.4.dist-info/entry_points.txt
@@ -0,0 +1,9 @@
+[array_api]
+numpy = numpy.array_api
+
+[pyinstaller40]
+hook-dirs = numpy:_pyinstaller_hooks_dir
+
+[console_scripts]
+f2py = numpy.f2py.f2py2e:main
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/License.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/License.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b491c70e0aef319022ded661e111ddbd45b8a17f
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/License.txt
@@ -0,0 +1,1568 @@
+End User License Agreement
+--------------------------
+
+
+Preface
+-------
+
+The Software License Agreement in Chapter 1 and the Supplement
+in Chapter 2 contain license terms and conditions that govern
+the use of NVIDIA software. By accepting this agreement, you
+agree to comply with all the terms and conditions applicable
+to the product(s) included herein.
+
+
+NVIDIA Driver
+
+
+Description
+
+This package contains the operating system driver and
+fundamental system software components for NVIDIA GPUs.
+
+
+NVIDIA CUDA Toolkit
+
+
+Description
+
+The NVIDIA CUDA Toolkit provides command-line and graphical
+tools for building, debugging and optimizing the performance
+of applications accelerated by NVIDIA GPUs, runtime and math
+libraries, and documentation including programming guides,
+user manuals, and API references.
+
+
+Default Install Location of CUDA Toolkit
+
+Windows platform:
+
+%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v#.#
+
+Linux platform:
+
+/usr/local/cuda-#.#
+
+Mac platform:
+
+/Developer/NVIDIA/CUDA-#.#
+
+
+NVIDIA CUDA Samples
+
+
+Description
+
+This package includes over 100+ CUDA examples that demonstrate
+various CUDA programming principles, and efficient CUDA
+implementation of algorithms in specific application domains.
+
+
+Default Install Location of CUDA Samples
+
+Windows platform:
+
+%ProgramData%\NVIDIA Corporation\CUDA Samples\v#.#
+
+Linux platform:
+
+/usr/local/cuda-#.#/samples
+
+and
+
+$HOME/NVIDIA_CUDA-#.#_Samples
+
+Mac platform:
+
+/Developer/NVIDIA/CUDA-#.#/samples
+
+
+NVIDIA Nsight Visual Studio Edition (Windows only)
+
+
+Description
+
+NVIDIA Nsight Development Platform, Visual Studio Edition is a
+development environment integrated into Microsoft Visual
+Studio that provides tools for debugging, profiling, analyzing
+and optimizing your GPU computing and graphics applications.
+
+
+Default Install Location of Nsight Visual Studio Edition
+
+Windows platform:
+
+%ProgramFiles(x86)%\NVIDIA Corporation\Nsight Visual Studio Edition #.#
+
+
+1. License Agreement for NVIDIA Software Development Kits
+---------------------------------------------------------
+
+
+Release Date: July 26, 2018
+---------------------------
+
+
+Important NoticeRead before downloading, installing,
+copying or using the licensed software:
+-------------------------------------------------------
+
+This license agreement, including exhibits attached
+("Agreement”) is a legal agreement between you and NVIDIA
+Corporation ("NVIDIA") and governs your use of a NVIDIA
+software development kit (“SDK”).
+
+Each SDK has its own set of software and materials, but here
+is a description of the types of items that may be included in
+a SDK: source code, header files, APIs, data sets and assets
+(examples include images, textures, models, scenes, videos,
+native API input/output files), binary software, sample code,
+libraries, utility programs, programming code and
+documentation.
+
+This Agreement can be accepted only by an adult of legal age
+of majority in the country in which the SDK is used.
+
+If you are entering into this Agreement on behalf of a company
+or other legal entity, you represent that you have the legal
+authority to bind the entity to this Agreement, in which case
+“you” will mean the entity you represent.
+
+If you don’t have the required age or authority to accept
+this Agreement, or if you don’t accept all the terms and
+conditions of this Agreement, do not download, install or use
+the SDK.
+
+You agree to use the SDK only for purposes that are permitted
+by (a) this Agreement, and (b) any applicable law, regulation
+or generally accepted practices or guidelines in the relevant
+jurisdictions.
+
+
+1.1. License
+
+
+1.1.1. License Grant
+
+Subject to the terms of this Agreement, NVIDIA hereby grants
+you a non-exclusive, non-transferable license, without the
+right to sublicense (except as expressly provided in this
+Agreement) to:
+
+ 1. Install and use the SDK,
+
+ 2. Modify and create derivative works of sample source code
+ delivered in the SDK, and
+
+ 3. Distribute those portions of the SDK that are identified
+ in this Agreement as distributable, as incorporated in
+ object code format into a software application that meets
+ the distribution requirements indicated in this Agreement.
+
+
+1.1.2. Distribution Requirements
+
+These are the distribution requirements for you to exercise
+the distribution grant:
+
+ 1. Your application must have material additional
+ functionality, beyond the included portions of the SDK.
+
+ 2. The distributable portions of the SDK shall only be
+ accessed by your application.
+
+ 3. The following notice shall be included in modifications
+ and derivative works of sample source code distributed:
+ “This software contains source code provided by NVIDIA
+ Corporation.”
+
+ 4. Unless a developer tool is identified in this Agreement
+ as distributable, it is delivered for your internal use
+ only.
+
+ 5. The terms under which you distribute your application
+ must be consistent with the terms of this Agreement,
+ including (without limitation) terms relating to the
+ license grant and license restrictions and protection of
+ NVIDIA’s intellectual property rights. Additionally, you
+ agree that you will protect the privacy, security and
+ legal rights of your application users.
+
+ 6. You agree to notify NVIDIA in writing of any known or
+ suspected distribution or use of the SDK not in compliance
+ with the requirements of this Agreement, and to enforce
+ the terms of your agreements with respect to distributed
+ SDK.
+
+
+1.1.3. Authorized Users
+
+You may allow employees and contractors of your entity or of
+your subsidiary(ies) to access and use the SDK from your
+secure network to perform work on your behalf.
+
+If you are an academic institution you may allow users
+enrolled or employed by the academic institution to access and
+use the SDK from your secure network.
+
+You are responsible for the compliance with the terms of this
+Agreement by your authorized users. If you become aware that
+your authorized users didn’t follow the terms of this
+Agreement, you agree to take reasonable steps to resolve the
+non-compliance and prevent new occurrences.
+
+
+1.1.4. Pre-Release SDK
+
+The SDK versions identified as alpha, beta, preview or
+otherwise as pre-release, may not be fully functional, may
+contain errors or design flaws, and may have reduced or
+different security, privacy, accessibility, availability, and
+reliability standards relative to commercial versions of
+NVIDIA software and materials. Use of a pre-release SDK may
+result in unexpected results, loss of data, project delays or
+other unpredictable damage or loss.
+
+You may use a pre-release SDK at your own risk, understanding
+that pre-release SDKs are not intended for use in production
+or business-critical systems.
+
+NVIDIA may choose not to make available a commercial version
+of any pre-release SDK. NVIDIA may also choose to abandon
+development and terminate the availability of a pre-release
+SDK at any time without liability.
+
+
+1.1.5. Updates
+
+NVIDIA may, at its option, make available patches, workarounds
+or other updates to this SDK. Unless the updates are provided
+with their separate governing terms, they are deemed part of
+the SDK licensed to you as provided in this Agreement. You
+agree that the form and content of the SDK that NVIDIA
+provides may change without prior notice to you. While NVIDIA
+generally maintains compatibility between versions, NVIDIA may
+in some cases make changes that introduce incompatibilities in
+future versions of the SDK.
+
+
+1.1.6. Third Party Licenses
+
+The SDK may come bundled with, or otherwise include or be
+distributed with, third party software licensed by a NVIDIA
+supplier and/or open source software provided under an open
+source license. Use of third party software is subject to the
+third-party license terms, or in the absence of third party
+terms, the terms of this Agreement. Copyright to third party
+software is held by the copyright holders indicated in the
+third-party software or license.
+
+
+1.1.7. Reservation of Rights
+
+NVIDIA reserves all rights, title, and interest in and to the
+SDK, not expressly granted to you under this Agreement.
+
+
+1.2. Limitations
+
+The following license limitations apply to your use of the
+SDK:
+
+ 1. You may not reverse engineer, decompile or disassemble,
+ or remove copyright or other proprietary notices from any
+ portion of the SDK or copies of the SDK.
+
+ 2. Except as expressly provided in this Agreement, you may
+ not copy, sell, rent, sublicense, transfer, distribute,
+ modify, or create derivative works of any portion of the
+ SDK. For clarity, you may not distribute or sublicense the
+ SDK as a stand-alone product.
+
+ 3. Unless you have an agreement with NVIDIA for this
+ purpose, you may not indicate that an application created
+ with the SDK is sponsored or endorsed by NVIDIA.
+
+ 4. You may not bypass, disable, or circumvent any
+ encryption, security, digital rights management or
+ authentication mechanism in the SDK.
+
+ 5. You may not use the SDK in any manner that would cause it
+ to become subject to an open source software license. As
+ examples, licenses that require as a condition of use,
+ modification, and/or distribution that the SDK be:
+
+ a. Disclosed or distributed in source code form;
+
+ b. Licensed for the purpose of making derivative works;
+ or
+
+ c. Redistributable at no charge.
+
+ 6. Unless you have an agreement with NVIDIA for this
+ purpose, you may not use the SDK with any system or
+ application where the use or failure of the system or
+ application can reasonably be expected to threaten or
+ result in personal injury, death, or catastrophic loss.
+ Examples include use in avionics, navigation, military,
+ medical, life support or other life critical applications.
+ NVIDIA does not design, test or manufacture the SDK for
+ these critical uses and NVIDIA shall not be liable to you
+ or any third party, in whole or in part, for any claims or
+ damages arising from such uses.
+
+ 7. You agree to defend, indemnify and hold harmless NVIDIA
+ and its affiliates, and their respective employees,
+ contractors, agents, officers and directors, from and
+ against any and all claims, damages, obligations, losses,
+ liabilities, costs or debt, fines, restitutions and
+ expenses (including but not limited to attorney’s fees
+ and costs incident to establishing the right of
+ indemnification) arising out of or related to your use of
+ the SDK outside of the scope of this Agreement, or not in
+ compliance with its terms.
+
+
+1.3. Ownership
+
+ 1. NVIDIA or its licensors hold all rights, title and
+ interest in and to the SDK and its modifications and
+ derivative works, including their respective intellectual
+ property rights, subject to your rights described in this
+ section. This SDK may include software and materials from
+ NVIDIA’s licensors, and these licensors are intended
+ third party beneficiaries that may enforce this Agreement
+ with respect to their intellectual property rights.
+
+ 2. You hold all rights, title and interest in and to your
+ applications and your derivative works of the sample
+ source code delivered in the SDK, including their
+ respective intellectual property rights, subject to
+ NVIDIA’s rights described in this section.
+
+ 3. You may, but don’t have to, provide to NVIDIA
+ suggestions, feature requests or other feedback regarding
+ the SDK, including possible enhancements or modifications
+ to the SDK. For any feedback that you voluntarily provide,
+ you hereby grant NVIDIA and its affiliates a perpetual,
+ non-exclusive, worldwide, irrevocable license to use,
+ reproduce, modify, license, sublicense (through multiple
+ tiers of sublicensees), and distribute (through multiple
+ tiers of distributors) it without the payment of any
+ royalties or fees to you. NVIDIA will use feedback at its
+ choice. NVIDIA is constantly looking for ways to improve
+ its products, so you may send feedback to NVIDIA through
+ the developer portal at https://developer.nvidia.com.
+
+
+1.4. No Warranties
+
+THE SDK IS PROVIDED BY NVIDIA “AS IS” AND “WITH ALL
+FAULTS.” TO THE MAXIMUM EXTENT PERMITTED BY LAW, NVIDIA AND
+ITS AFFILIATES EXPRESSLY DISCLAIM ALL WARRANTIES OF ANY KIND
+OR NATURE, WHETHER EXPRESS, IMPLIED OR STATUTORY, INCLUDING,
+BUT NOT LIMITED TO, ANY WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE, TITLE, NON-INFRINGEMENT, OR THE
+ABSENCE OF ANY DEFECTS THEREIN, WHETHER LATENT OR PATENT. NO
+WARRANTY IS MADE ON THE BASIS OF TRADE USAGE, COURSE OF
+DEALING OR COURSE OF TRADE.
+
+
+1.5. Limitation of Liability
+
+TO THE MAXIMUM EXTENT PERMITTED BY LAW, NVIDIA AND ITS
+AFFILIATES SHALL NOT BE LIABLE FOR ANY SPECIAL, INCIDENTAL,
+PUNITIVE OR CONSEQUENTIAL DAMAGES, OR ANY LOST PROFITS, LOSS
+OF USE, LOSS OF DATA OR LOSS OF GOODWILL, OR THE COSTS OF
+PROCURING SUBSTITUTE PRODUCTS, ARISING OUT OF OR IN CONNECTION
+WITH THIS AGREEMENT OR THE USE OR PERFORMANCE OF THE SDK,
+WHETHER SUCH LIABILITY ARISES FROM ANY CLAIM BASED UPON BREACH
+OF CONTRACT, BREACH OF WARRANTY, TORT (INCLUDING NEGLIGENCE),
+PRODUCT LIABILITY OR ANY OTHER CAUSE OF ACTION OR THEORY OF
+LIABILITY. IN NO EVENT WILL NVIDIA’S AND ITS AFFILIATES
+TOTAL CUMULATIVE LIABILITY UNDER OR ARISING OUT OF THIS
+AGREEMENT EXCEED US$10.00. THE NATURE OF THE LIABILITY OR THE
+NUMBER OF CLAIMS OR SUITS SHALL NOT ENLARGE OR EXTEND THIS
+LIMIT.
+
+These exclusions and limitations of liability shall apply
+regardless if NVIDIA or its affiliates have been advised of
+the possibility of such damages, and regardless of whether a
+remedy fails its essential purpose. These exclusions and
+limitations of liability form an essential basis of the
+bargain between the parties, and, absent any of these
+exclusions or limitations of liability, the provisions of this
+Agreement, including, without limitation, the economic terms,
+would be substantially different.
+
+
+1.6. Termination
+
+ 1. This Agreement will continue to apply until terminated by
+ either you or NVIDIA as described below.
+
+ 2. If you want to terminate this Agreement, you may do so by
+ stopping to use the SDK.
+
+ 3. NVIDIA may, at any time, terminate this Agreement if:
+
+ a. (i) you fail to comply with any term of this
+ Agreement and the non-compliance is not fixed within
+ thirty (30) days following notice from NVIDIA (or
+ immediately if you violate NVIDIA’s intellectual
+ property rights);
+
+ b. (ii) you commence or participate in any legal
+ proceeding against NVIDIA with respect to the SDK; or
+
+ c. (iii) NVIDIA decides to no longer provide the SDK in
+ a country or, in NVIDIA’s sole discretion, the
+ continued use of it is no longer commercially viable.
+
+ 4. Upon any termination of this Agreement, you agree to
+ promptly discontinue use of the SDK and destroy all copies
+ in your possession or control. Your prior distributions in
+ accordance with this Agreement are not affected by the
+ termination of this Agreement. Upon written request, you
+ will certify in writing that you have complied with your
+ commitments under this section. Upon any termination of
+ this Agreement all provisions survive except for the
+ license grant provisions.
+
+
+1.7. General
+
+If you wish to assign this Agreement or your rights and
+obligations, including by merger, consolidation, dissolution
+or operation of law, contact NVIDIA to ask for permission. Any
+attempted assignment not approved by NVIDIA in writing shall
+be void and of no effect. NVIDIA may assign, delegate or
+transfer this Agreement and its rights and obligations, and if
+to a non-affiliate you will be notified.
+
+You agree to cooperate with NVIDIA and provide reasonably
+requested information to verify your compliance with this
+Agreement.
+
+This Agreement will be governed in all respects by the laws of
+the United States and of the State of Delaware as those laws
+are applied to contracts entered into and performed entirely
+within Delaware by Delaware residents, without regard to the
+conflicts of laws principles. The United Nations Convention on
+Contracts for the International Sale of Goods is specifically
+disclaimed. You agree to all terms of this Agreement in the
+English language.
+
+The state or federal courts residing in Santa Clara County,
+California shall have exclusive jurisdiction over any dispute
+or claim arising out of this Agreement. Notwithstanding this,
+you agree that NVIDIA shall still be allowed to apply for
+injunctive remedies or an equivalent type of urgent legal
+relief in any jurisdiction.
+
+If any court of competent jurisdiction determines that any
+provision of this Agreement is illegal, invalid or
+unenforceable, such provision will be construed as limited to
+the extent necessary to be consistent with and fully
+enforceable under the law and the remaining provisions will
+remain in full force and effect. Unless otherwise specified,
+remedies are cumulative.
+
+Each party acknowledges and agrees that the other is an
+independent contractor in the performance of this Agreement.
+
+The SDK has been developed entirely at private expense and is
+“commercial items” consisting of “commercial computer
+software” and “commercial computer software
+documentation” provided with RESTRICTED RIGHTS. Use,
+duplication or disclosure by the U.S. Government or a U.S.
+Government subcontractor is subject to the restrictions in
+this Agreement pursuant to DFARS 227.7202-3(a) or as set forth
+in subparagraphs (c)(1) and (2) of the Commercial Computer
+Software - Restricted Rights clause at FAR 52.227-19, as
+applicable. Contractor/manufacturer is NVIDIA, 2788 San Tomas
+Expressway, Santa Clara, CA 95051.
+
+The SDK is subject to United States export laws and
+regulations. You agree that you will not ship, transfer or
+export the SDK into any country, or use the SDK in any manner,
+prohibited by the United States Bureau of Industry and
+Security or economic sanctions regulations administered by the
+U.S. Department of Treasury’s Office of Foreign Assets
+Control (OFAC), or any applicable export laws, restrictions or
+regulations. These laws include restrictions on destinations,
+end users and end use. By accepting this Agreement, you
+confirm that you are not a resident or citizen of any country
+currently embargoed by the U.S. and that you are not otherwise
+prohibited from receiving the SDK.
+
+Any notice delivered by NVIDIA to you under this Agreement
+will be delivered via mail, email or fax. You agree that any
+notices that NVIDIA sends you electronically will satisfy any
+legal communication requirements. Please direct your legal
+notices or other correspondence to NVIDIA Corporation, 2788
+San Tomas Expressway, Santa Clara, California 95051, United
+States of America, Attention: Legal Department.
+
+This Agreement and any exhibits incorporated into this
+Agreement constitute the entire agreement of the parties with
+respect to the subject matter of this Agreement and supersede
+all prior negotiations or documentation exchanged between the
+parties relating to this SDK license. Any additional and/or
+conflicting terms on documents issued by you are null, void,
+and invalid. Any amendment or waiver under this Agreement
+shall be in writing and signed by representatives of both
+parties.
+
+
+2. CUDA Toolkit Supplement to Software License Agreement for
+NVIDIA Software Development Kits
+------------------------------------------------------------
+
+
+Release date: August 16, 2018
+-----------------------------
+
+The terms in this supplement govern your use of the NVIDIA
+CUDA Toolkit SDK under the terms of your license agreement
+(“Agreement”) as modified by this supplement. Capitalized
+terms used but not defined below have the meaning assigned to
+them in the Agreement.
+
+This supplement is an exhibit to the Agreement and is
+incorporated as an integral part of the Agreement. In the
+event of conflict between the terms in this supplement and the
+terms in the Agreement, the terms in this supplement govern.
+
+
+2.1. License Scope
+
+The SDK is licensed for you to develop applications only for
+use in systems with NVIDIA GPUs.
+
+
+2.2. Distribution
+
+The portions of the SDK that are distributable under the
+Agreement are listed in Attachment A.
+
+
+2.3. Operating Systems
+
+Those portions of the SDK designed exclusively for use on the
+Linux or FreeBSD operating systems, or other operating systems
+derived from the source code to these operating systems, may
+be copied and redistributed for use in accordance with this
+Agreement, provided that the object code files are not
+modified in any way (except for unzipping of compressed
+files).
+
+
+2.4. Audio and Video Encoders and Decoders
+
+You acknowledge and agree that it is your sole responsibility
+to obtain any additional third-party licenses required to
+make, have made, use, have used, sell, import, and offer for
+sale your products or services that include or incorporate any
+third-party software and content relating to audio and/or
+video encoders and decoders from, including but not limited
+to, Microsoft, Thomson, Fraunhofer IIS, Sisvel S.p.A.,
+MPEG-LA, and Coding Technologies. NVIDIA does not grant to you
+under this Agreement any necessary patent or other rights with
+respect to any audio and/or video encoders and decoders.
+
+
+2.5. Licensing
+
+If the distribution terms in this Agreement are not suitable
+for your organization, or for any questions regarding this
+Agreement, please contact NVIDIA at
+nvidia-compute-license-questions@nvidia.com.
+
+
+2.6. Attachment A
+
+The following portions of the SDK are distributable under the
+Agreement:
+
+Component
+
+CUDA Runtime
+
+Windows
+
+cudart.dll, cudart_static.lib, cudadevrt.lib
+
+Mac OSX
+
+libcudart.dylib, libcudart_static.a, libcudadevrt.a
+
+Linux
+
+libcudart.so, libcudart_static.a, libcudadevrt.a
+
+Android
+
+libcudart.so, libcudart_static.a, libcudadevrt.a
+
+Component
+
+CUDA FFT Library
+
+Windows
+
+cufft.dll, cufftw.dll, cufft.lib, cufftw.lib
+
+Mac OSX
+
+libcufft.dylib, libcufft_static.a, libcufftw.dylib,
+libcufftw_static.a
+
+Linux
+
+libcufft.so, libcufft_static.a, libcufftw.so,
+libcufftw_static.a
+
+Android
+
+libcufft.so, libcufft_static.a, libcufftw.so,
+libcufftw_static.a
+
+Component
+
+CUDA BLAS Library
+
+Windows
+
+cublas.dll, cublasLt.dll
+
+Mac OSX
+
+libcublas.dylib, libcublasLt.dylib, libcublas_static.a,
+libcublasLt_static.a
+
+Linux
+
+libcublas.so, libcublasLt.so, libcublas_static.a,
+libcublasLt_static.a
+
+Android
+
+libcublas.so, libcublasLt.so, libcublas_static.a,
+libcublasLt_static.a
+
+Component
+
+NVIDIA "Drop-in" BLAS Library
+
+Windows
+
+nvblas.dll
+
+Mac OSX
+
+libnvblas.dylib
+
+Linux
+
+libnvblas.so
+
+Component
+
+CUDA Sparse Matrix Library
+
+Windows
+
+cusparse.dll, cusparse.lib
+
+Mac OSX
+
+libcusparse.dylib, libcusparse_static.a
+
+Linux
+
+libcusparse.so, libcusparse_static.a
+
+Android
+
+libcusparse.so, libcusparse_static.a
+
+Component
+
+CUDA Linear Solver Library
+
+Windows
+
+cusolver.dll, cusolver.lib
+
+Mac OSX
+
+libcusolver.dylib, libcusolver_static.a
+
+Linux
+
+libcusolver.so, libcusolver_static.a
+
+Android
+
+libcusolver.so, libcusolver_static.a
+
+Component
+
+CUDA Random Number Generation Library
+
+Windows
+
+curand.dll, curand.lib
+
+Mac OSX
+
+libcurand.dylib, libcurand_static.a
+
+Linux
+
+libcurand.so, libcurand_static.a
+
+Android
+
+libcurand.so, libcurand_static.a
+
+Component
+
+CUDA Accelerated Graph Library
+
+Component
+
+NVIDIA Performance Primitives Library
+
+Windows
+
+nppc.dll, nppc.lib, nppial.dll, nppial.lib, nppicc.dll,
+nppicc.lib, nppicom.dll, nppicom.lib, nppidei.dll,
+nppidei.lib, nppif.dll, nppif.lib, nppig.dll, nppig.lib,
+nppim.dll, nppim.lib, nppist.dll, nppist.lib, nppisu.dll,
+nppisu.lib, nppitc.dll, nppitc.lib, npps.dll, npps.lib
+
+Mac OSX
+
+libnppc.dylib, libnppc_static.a, libnppial.dylib,
+libnppial_static.a, libnppicc.dylib, libnppicc_static.a,
+libnppicom.dylib, libnppicom_static.a, libnppidei.dylib,
+libnppidei_static.a, libnppif.dylib, libnppif_static.a,
+libnppig.dylib, libnppig_static.a, libnppim.dylib,
+libnppisu_static.a, libnppitc.dylib, libnppitc_static.a,
+libnpps.dylib, libnpps_static.a
+
+Linux
+
+libnppc.so, libnppc_static.a, libnppial.so,
+libnppial_static.a, libnppicc.so, libnppicc_static.a,
+libnppicom.so, libnppicom_static.a, libnppidei.so,
+libnppidei_static.a, libnppif.so, libnppif_static.a
+libnppig.so, libnppig_static.a, libnppim.so,
+libnppim_static.a, libnppist.so, libnppist_static.a,
+libnppisu.so, libnppisu_static.a, libnppitc.so
+libnppitc_static.a, libnpps.so, libnpps_static.a
+
+Android
+
+libnppc.so, libnppc_static.a, libnppial.so,
+libnppial_static.a, libnppicc.so, libnppicc_static.a,
+libnppicom.so, libnppicom_static.a, libnppidei.so,
+libnppidei_static.a, libnppif.so, libnppif_static.a
+libnppig.so, libnppig_static.a, libnppim.so,
+libnppim_static.a, libnppist.so, libnppist_static.a,
+libnppisu.so, libnppisu_static.a, libnppitc.so
+libnppitc_static.a, libnpps.so, libnpps_static.a
+
+Component
+
+NVIDIA JPEG Library
+
+Linux
+
+libnvjpeg.so, libnvjpeg_static.a
+
+Component
+
+Internal common library required for statically linking to
+cuBLAS, cuSPARSE, cuFFT, cuRAND, nvJPEG and NPP
+
+Mac OSX
+
+libculibos.a
+
+Linux
+
+libculibos.a
+
+Component
+
+NVIDIA Runtime Compilation Library and Header
+
+All
+
+nvrtc.h
+
+Windows
+
+nvrtc.dll, nvrtc-builtins.dll
+
+Mac OSX
+
+libnvrtc.dylib, libnvrtc-builtins.dylib
+
+Linux
+
+libnvrtc.so, libnvrtc-builtins.so
+
+Component
+
+NVIDIA Optimizing Compiler Library
+
+Windows
+
+nvvm.dll
+
+Mac OSX
+
+libnvvm.dylib
+
+Linux
+
+libnvvm.so
+
+Component
+
+NVIDIA Common Device Math Functions Library
+
+Windows
+
+libdevice.10.bc
+
+Mac OSX
+
+libdevice.10.bc
+
+Linux
+
+libdevice.10.bc
+
+Component
+
+CUDA Occupancy Calculation Header Library
+
+All
+
+cuda_occupancy.h
+
+Component
+
+CUDA Half Precision Headers
+
+All
+
+cuda_fp16.h, cuda_fp16.hpp
+
+Component
+
+CUDA Profiling Tools Interface (CUPTI) Library
+
+Windows
+
+cupti.dll
+
+Mac OSX
+
+libcupti.dylib
+
+Linux
+
+libcupti.so
+
+Component
+
+NVIDIA Tools Extension Library
+
+Windows
+
+nvToolsExt.dll, nvToolsExt.lib
+
+Mac OSX
+
+libnvToolsExt.dylib
+
+Linux
+
+libnvToolsExt.so
+
+Component
+
+NVIDIA CUDA Driver Libraries
+
+Linux
+
+libcuda.so, libnvidia-fatbinaryloader.so,
+libnvidia-ptxjitcompiler.so
+
+The NVIDIA CUDA Driver Libraries are only distributable in
+applications that meet this criteria:
+
+ 1. The application was developed starting from a NVIDIA CUDA
+ container obtained from Docker Hub or the NVIDIA GPU
+ Cloud, and
+
+ 2. The resulting application is packaged as a Docker
+ container and distributed to users on Docker Hub or the
+ NVIDIA GPU Cloud only.
+
+
+2.7. Attachment B
+
+
+Additional Licensing Obligations
+
+The following third party components included in the SOFTWARE
+are licensed to Licensee pursuant to the following terms and
+conditions:
+
+ 1. Licensee's use of the GDB third party component is
+ subject to the terms and conditions of GNU GPL v3:
+
+ This product includes copyrighted third-party software licensed
+ under the terms of the GNU General Public License v3 ("GPL v3").
+ All third-party software packages are copyright by their respective
+ authors. GPL v3 terms and conditions are hereby incorporated into
+ the Agreement by this reference: http://www.gnu.org/licenses/gpl.txt
+
+ Consistent with these licensing requirements, the software
+ listed below is provided under the terms of the specified
+ open source software licenses. To obtain source code for
+ software provided under licenses that require
+ redistribution of source code, including the GNU General
+ Public License (GPL) and GNU Lesser General Public License
+ (LGPL), contact oss-requests@nvidia.com. This offer is
+ valid for a period of three (3) years from the date of the
+ distribution of this product by NVIDIA CORPORATION.
+
+ Component License
+ CUDA-GDB GPL v3
+
+ 2. Licensee represents and warrants that any and all third
+ party licensing and/or royalty payment obligations in
+ connection with Licensee's use of the H.264 video codecs
+ are solely the responsibility of Licensee.
+
+ 3. Licensee's use of the Thrust library is subject to the
+ terms and conditions of the Apache License Version 2.0.
+ All third-party software packages are copyright by their
+ respective authors. Apache License Version 2.0 terms and
+ conditions are hereby incorporated into the Agreement by
+ this reference.
+ http://www.apache.org/licenses/LICENSE-2.0.html
+
+ In addition, Licensee acknowledges the following notice:
+ Thrust includes source code from the Boost Iterator,
+ Tuple, System, and Random Number libraries.
+
+ Boost Software License - Version 1.0 - August 17th, 2003
+ . . . .
+
+ Permission is hereby granted, free of charge, to any person or
+ organization obtaining a copy of the software and accompanying
+ documentation covered by this license (the "Software") to use,
+ reproduce, display, distribute, execute, and transmit the Software,
+ and to prepare derivative works of the Software, and to permit
+ third-parties to whom the Software is furnished to do so, all
+ subject to the following:
+
+ The copyright notices in the Software and this entire statement,
+ including the above license grant, this restriction and the following
+ disclaimer, must be included in all copies of the Software, in whole
+ or in part, and all derivative works of the Software, unless such
+ copies or derivative works are solely in the form of machine-executable
+ object code generated by a source language processor.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND
+ NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR
+ ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR
+ OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING
+ FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ OTHER DEALINGS IN THE SOFTWARE.
+
+ 4. Licensee's use of the LLVM third party component is
+ subject to the following terms and conditions:
+
+ ======================================================
+ LLVM Release License
+ ======================================================
+ University of Illinois/NCSA
+ Open Source License
+
+ Copyright (c) 2003-2010 University of Illinois at Urbana-Champaign.
+ All rights reserved.
+
+ Developed by:
+
+ LLVM Team
+
+ University of Illinois at Urbana-Champaign
+
+ http://llvm.org
+
+ Permission is hereby granted, free of charge, to any person obtaining a copy
+ of this software and associated documentation files (the "Software"), to
+ deal with the Software without restriction, including without limitation the
+ rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ sell copies of the Software, and to permit persons to whom the Software is
+ furnished to do so, subject to the following conditions:
+
+ * Redistributions of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimers.
+
+ * Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimers in the
+ documentation and/or other materials provided with the distribution.
+
+ * Neither the names of the LLVM Team, University of Illinois at Urbana-
+ Champaign, nor the names of its contributors may be used to endorse or
+ promote products derived from this Software without specific prior
+ written permission.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+ THE CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR
+ OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
+ ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+ DEALINGS WITH THE SOFTWARE.
+
+ 5. Licensee's use (e.g. nvprof) of the PCRE third party
+ component is subject to the following terms and
+ conditions:
+
+ ------------
+ PCRE LICENCE
+ ------------
+ PCRE is a library of functions to support regular expressions whose syntax
+ and semantics are as close as possible to those of the Perl 5 language.
+ Release 8 of PCRE is distributed under the terms of the "BSD" licence, as
+ specified below. The documentation for PCRE, supplied in the "doc"
+ directory, is distributed under the same terms as the software itself. The
+ basic library functions are written in C and are freestanding. Also
+ included in the distribution is a set of C++ wrapper functions, and a just-
+ in-time compiler that can be used to optimize pattern matching. These are
+ both optional features that can be omitted when the library is built.
+
+ THE BASIC LIBRARY FUNCTIONS
+ ---------------------------
+ Written by: Philip Hazel
+ Email local part: ph10
+ Email domain: cam.ac.uk
+ University of Cambridge Computing Service,
+ Cambridge, England.
+ Copyright (c) 1997-2012 University of Cambridge
+ All rights reserved.
+
+ PCRE JUST-IN-TIME COMPILATION SUPPORT
+ -------------------------------------
+ Written by: Zoltan Herczeg
+ Email local part: hzmester
+ Emain domain: freemail.hu
+ Copyright(c) 2010-2012 Zoltan Herczeg
+ All rights reserved.
+
+ STACK-LESS JUST-IN-TIME COMPILER
+ --------------------------------
+ Written by: Zoltan Herczeg
+ Email local part: hzmester
+ Emain domain: freemail.hu
+ Copyright(c) 2009-2012 Zoltan Herczeg
+ All rights reserved.
+
+ THE C++ WRAPPER FUNCTIONS
+ -------------------------
+ Contributed by: Google Inc.
+ Copyright (c) 2007-2012, Google Inc.
+ All rights reserved.
+
+ THE "BSD" LICENCE
+ -----------------
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimer in the
+ documentation and/or other materials provided with the distribution.
+
+ * Neither the name of the University of Cambridge nor the name of Google
+ Inc. nor the names of their contributors may be used to endorse or
+ promote products derived from this software without specific prior
+ written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ POSSIBILITY OF SUCH DAMAGE.
+
+ 6. Some of the cuBLAS library routines were written by or
+ derived from code written by Vasily Volkov and are subject
+ to the Modified Berkeley Software Distribution License as
+ follows:
+
+ Copyright (c) 2007-2009, Regents of the University of California
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+ * Neither the name of the University of California, Berkeley nor
+ the names of its contributors may be used to endorse or promote
+ products derived from this software without specific prior
+ written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR
+ IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,
+ INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
+ HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
+ STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
+ IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ POSSIBILITY OF SUCH DAMAGE.
+
+ 7. Some of the cuBLAS library routines were written by or
+ derived from code written by Davide Barbieri and are
+ subject to the Modified Berkeley Software Distribution
+ License as follows:
+
+ Copyright (c) 2008-2009 Davide Barbieri @ University of Rome Tor Vergata.
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+ * The name of the author may not be used to endorse or promote
+ products derived from this software without specific prior
+ written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR
+ IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,
+ INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
+ HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
+ STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
+ IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ POSSIBILITY OF SUCH DAMAGE.
+
+ 8. Some of the cuBLAS library routines were derived from
+ code developed by the University of Tennessee and are
+ subject to the Modified Berkeley Software Distribution
+ License as follows:
+
+ Copyright (c) 2010 The University of Tennessee.
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer listed in this license in the documentation and/or
+ other materials provided with the distribution.
+ * Neither the name of the copyright holders nor the names of its
+ contributors may be used to endorse or promote products derived
+ from this software without specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 9. Some of the cuBLAS library routines were written by or
+ derived from code written by Jonathan Hogg and are subject
+ to the Modified Berkeley Software Distribution License as
+ follows:
+
+ Copyright (c) 2012, The Science and Technology Facilities Council (STFC).
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+ * Neither the name of the STFC nor the names of its contributors
+ may be used to endorse or promote products derived from this
+ software without specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE STFC BE
+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+ BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+ WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
+ OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN
+ IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 10. Some of the cuBLAS library routines were written by or
+ derived from code written by Ahmad M. Abdelfattah, David
+ Keyes, and Hatem Ltaief, and are subject to the Apache
+ License, Version 2.0, as follows:
+
+ -- (C) Copyright 2013 King Abdullah University of Science and Technology
+ Authors:
+ Ahmad Abdelfattah (ahmad.ahmad@kaust.edu.sa)
+ David Keyes (david.keyes@kaust.edu.sa)
+ Hatem Ltaief (hatem.ltaief@kaust.edu.sa)
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions
+ are met:
+
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimer in the
+ documentation and/or other materials provided with the distribution.
+ * Neither the name of the King Abdullah University of Science and
+ Technology nor the names of its contributors may be used to endorse
+ or promote products derived from this software without specific prior
+ written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE
+
+ 11. Some of the cuSPARSE library routines were written by or
+ derived from code written by Li-Wen Chang and are subject
+ to the NCSA Open Source License as follows:
+
+ Copyright (c) 2012, University of Illinois.
+
+ All rights reserved.
+
+ Developed by: IMPACT Group, University of Illinois, http://impact.crhc.illinois.edu
+
+ Permission is hereby granted, free of charge, to any person obtaining
+ a copy of this software and associated documentation files (the
+ "Software"), to deal with the Software without restriction, including
+ without limitation the rights to use, copy, modify, merge, publish,
+ distribute, sublicense, and/or sell copies of the Software, and to
+ permit persons to whom the Software is furnished to do so, subject to
+ the following conditions:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimers in the documentation and/or other materials provided
+ with the distribution.
+ * Neither the names of IMPACT Group, University of Illinois, nor
+ the names of its contributors may be used to endorse or promote
+ products derived from this Software without specific prior
+ written permission.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ NONINFRINGEMENT. IN NO EVENT SHALL THE CONTRIBUTORS OR COPYRIGHT
+ HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+ IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
+ IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH THE
+ SOFTWARE.
+
+ 12. Some of the cuRAND library routines were written by or
+ derived from code written by Mutsuo Saito and Makoto
+ Matsumoto and are subject to the following license:
+
+ Copyright (c) 2009, 2010 Mutsuo Saito, Makoto Matsumoto and Hiroshima
+ University. All rights reserved.
+
+ Copyright (c) 2011 Mutsuo Saito, Makoto Matsumoto, Hiroshima
+ University and University of Tokyo. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+ * Neither the name of the Hiroshima University nor the names of
+ its contributors may be used to endorse or promote products
+ derived from this software without specific prior written
+ permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 13. Some of the cuRAND library routines were derived from
+ code developed by D. E. Shaw Research and are subject to
+ the following license:
+
+ Copyright 2010-2011, D. E. Shaw Research.
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions, and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions, and the following
+ disclaimer in the documentation and/or other materials provided
+ with the distribution.
+ * Neither the name of D. E. Shaw Research nor the names of its
+ contributors may be used to endorse or promote products derived
+ from this software without specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 14. Some of the Math library routines were written by or
+ derived from code developed by Norbert Juffa and are
+ subject to the following license:
+
+ Copyright (c) 2015-2017, Norbert Juffa
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions
+ are met:
+
+ 1. Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+
+ 2. Redistributions in binary form must reproduce the above copyright
+ notice, this list of conditions and the following disclaimer in the
+ documentation and/or other materials provided with the distribution.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 15. Licensee's use of the lz4 third party component is
+ subject to the following terms and conditions:
+
+ Copyright (C) 2011-2013, Yann Collet.
+ BSD 2-Clause License (http://www.opensource.org/licenses/bsd-license.php)
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are
+ met:
+
+ * Redistributions of source code must retain the above copyright
+ notice, this list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above
+ copyright notice, this list of conditions and the following disclaimer
+ in the documentation and/or other materials provided with the
+ distribution.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ 16. The NPP library uses code from the Boost Math Toolkit,
+ and is subject to the following license:
+
+ Boost Software License - Version 1.0 - August 17th, 2003
+ . . . .
+
+ Permission is hereby granted, free of charge, to any person or
+ organization obtaining a copy of the software and accompanying
+ documentation covered by this license (the "Software") to use,
+ reproduce, display, distribute, execute, and transmit the Software,
+ and to prepare derivative works of the Software, and to permit
+ third-parties to whom the Software is furnished to do so, all
+ subject to the following:
+
+ The copyright notices in the Software and this entire statement,
+ including the above license grant, this restriction and the following
+ disclaimer, must be included in all copies of the Software, in whole
+ or in part, and all derivative works of the Software, unless such
+ copies or derivative works are solely in the form of machine-executable
+ object code generated by a source language processor.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND
+ NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR
+ ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR
+ OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING
+ FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ OTHER DEALINGS IN THE SOFTWARE.
+
+ 17. Portions of the Nsight Eclipse Edition is subject to the
+ following license:
+
+ The Eclipse Foundation makes available all content in this plug-in
+ ("Content"). Unless otherwise indicated below, the Content is provided
+ to you under the terms and conditions of the Eclipse Public License
+ Version 1.0 ("EPL"). A copy of the EPL is available at http://
+ www.eclipse.org/legal/epl-v10.html. For purposes of the EPL, "Program"
+ will mean the Content.
+
+ If you did not receive this Content directly from the Eclipse
+ Foundation, the Content is being redistributed by another party
+ ("Redistributor") and different terms and conditions may apply to your
+ use of any object code in the Content. Check the Redistributor's
+ license that was provided with the Content. If no such license exists,
+ contact the Redistributor. Unless otherwise indicated below, the terms
+ and conditions of the EPL still apply to any source code in the
+ Content and such source code may be obtained at http://www.eclipse.org.
+
+ 18. Some of the cuBLAS library routines uses code from
+ OpenAI, which is subject to the following license:
+
+ License URL
+ https://github.com/openai/openai-gemm/blob/master/LICENSE
+
+ License Text
+ The MIT License
+
+ Copyright (c) 2016 OpenAI (http://openai.com), 2016 Google Inc.
+
+ Permission is hereby granted, free of charge, to any person obtaining a copy
+ of this software and associated documentation files (the "Software"), to deal
+ in the Software without restriction, including without limitation the rights
+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ copies of the Software, and to permit persons to whom the Software is
+ furnished to do so, subject to the following conditions:
+
+ The above copyright notice and this permission notice shall be included in
+ all copies or substantial portions of the Software.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ THE SOFTWARE.
+
+ 19. Licensee's use of the Visual Studio Setup Configuration
+ Samples is subject to the following license:
+
+ The MIT License (MIT)
+ Copyright (C) Microsoft Corporation. All rights reserved.
+
+ Permission is hereby granted, free of charge, to any person
+ obtaining a copy of this software and associated documentation
+ files (the "Software"), to deal in the Software without restriction,
+ including without limitation the rights to use, copy, modify, merge,
+ publish, distribute, sublicense, and/or sell copies of the Software,
+ and to permit persons to whom the Software is furnished to do so,
+ subject to the following conditions:
+
+ The above copyright notice and this permission notice shall be included
+ in all copies or substantial portions of the Software.
+
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+ OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+ 20. Licensee's use of linmath.h header for CPU functions for
+ GL vector/matrix operations from lunarG is subject to the
+ Apache License Version 2.0.
+
+ 21. The DX12-CUDA sample uses the d3dx12.h header, which is
+ subject to the MIT license .
+
+-----------------
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..f8e857fa2ae30c6714fae1abaa2f8196efda7ab9
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/METADATA
@@ -0,0 +1,44 @@
+Metadata-Version: 2.2
+Name: nvidia-cuda-nvrtc-cu12
+Version: 12.8.93
+Summary: NVRTC native runtime libraries
+Home-page: https://developer.nvidia.com/cuda-zone
+Author: Nvidia CUDA Installer Team
+Author-email: compute_installer@nvidia.com
+License: NVIDIA Proprietary Software
+Keywords: cuda,nvidia,runtime,machine learning,deep learning
+Classifier: Development Status :: 4 - Beta
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: Other/Proprietary License
+Classifier: Natural Language :: English
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.5
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Topic :: Scientific/Engineering
+Classifier: Topic :: Scientific/Engineering :: Mathematics
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Classifier: Topic :: Software Development
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX :: Linux
+Requires-Python: >=3
+License-File: License.txt
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: home-page
+Dynamic: keywords
+Dynamic: license
+Dynamic: requires-python
+Dynamic: summary
+
+NVRTC native runtime libraries
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..381575134ae029948b721b7d03d08e7270151f94
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/RECORD
@@ -0,0 +1,19 @@
+nvidia/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+nvidia/__pycache__/__init__.cpython-312.pyc,,
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+nvidia/cuda_nvrtc/include/nvrtc.h,sha256=BzidLPMU_nSQUHZ2Qaho-VFO5Bx1kEgojFMeJPd4UE4,44261
+nvidia/cuda_nvrtc/lib/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
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+nvidia/cuda_nvrtc/lib/libnvrtc-builtins.so.12.8,sha256=7MqoJCMO54WKlKMFXLAfHLY03wXTE4gNC9zxlRYfy04,6338504
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+nvidia/cuda_nvrtc/lib/libnvrtc.so.12,sha256=Q3MeJM2J43SYJjBPME6KoR--zxGIcVJxsfUBjWISteY,104487248
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+nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/License.txt,sha256=rW9YU_ugyg0VnQ9Y1JrkmDDC-Mk_epJki5zpCttMbM0,59262
+nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/METADATA,sha256=N2RYoiBUtKNuEQ36tXDfS8ZYwDei-0cYS9xN_3q5DSM,1684
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..1ce22213ca080d1066f9438436aabd77121bada0
--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/WHEEL
@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: setuptools (75.8.0)
+Root-Is-Purelib: true
+Tag: py3-none-manylinux2010_x86_64
+Tag: py3-none-manylinux_2_12_x86_64
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..862f7abf232cdfbb928609856247292e81c9decb
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cuda_nvrtc_cu12-12.8.93.dist-info/top_level.txt
@@ -0,0 +1 @@
+nvidia
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/INSTALLER
new file mode 100644
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--- /dev/null
+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/METADATA
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/METADATA
@@ -0,0 +1,138 @@
+Metadata-Version: 2.2
+Name: nvidia-cusparselt-cu12
+Version: 0.7.1
+Summary: NVIDIA cuSPARSELt
+Home-page: https://developer.nvidia.com/cusparselt
+Author: NVIDIA Corporation
+Author-email: cuda_installer@nvidia.com
+License: NVIDIA Proprietary Software
+Keywords: cuda,nvidia,machine learning,high-performance computing
+Classifier: Topic :: Scientific/Engineering
+Classifier: Environment :: GPU :: NVIDIA CUDA
+Classifier: Environment :: GPU :: NVIDIA CUDA :: 12
+Description-Content-Type: text/x-rst
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: keywords
+Dynamic: license
+Dynamic: summary
+
+###################################################################################
+cuSPARSELt: A High-Performance CUDA Library for Sparse Matrix-Matrix Multiplication
+###################################################################################
+
+**NVIDIA cuSPARSELt** is a high-performance CUDA library dedicated to general matrix-matrix operations in which at least one operand is a sparse matrix:
+
+.. math::
+
+ D = Activation(\alpha op(A) \cdot op(B) + \beta op(C) + bias) \cdot scale
+
+where :math:`op(A)/op(B)` refers to in-place operations such as transpose/non-transpose, and :math:`alpha, beta, scale` are scalars.
+
+The *cuSPARSELt APIs* allow flexibility in the algorithm/operation selection, epilogue, and matrix characteristics, including memory layout, alignment, and data types.
+
+**Download:** `developer.nvidia.com/cusparselt/downloads `_
+
+**Provide Feedback:** `Math-Libs-Feedback@nvidia.com `_
+
+**Examples**:
+`cuSPARSELt Example 1 `_,
+`cuSPARSELt Example 2 `_
+
+**Blog post**:
+
+- `Exploiting NVIDIA Ampere Structured Sparsity with cuSPARSELt `_
+- `Structured Sparsity in the NVIDIA Ampere Architecture and Applications in Search Engines `__
+- `Making the Most of Structured Sparsity in the NVIDIA Ampere Architecture `__
+
+================================================================================
+Key Features
+================================================================================
+
+* *NVIDIA Sparse MMA tensor core* support
+* Mixed-precision computation support:
+
+ +--------------+----------------+-----------------+-------------+
+ | Input A/B | Input C | Output D | Compute |
+ +==============+================+=================+=============+
+ | `FP32` | `FP32` | `FP32` | `FP32` |
+ +--------------+----------------+-----------------+-------------+
+ | `FP16` | `FP16` | `FP16` | `FP32` |
+ + + + +-------------+
+ | | | | `FP16` |
+ +--------------+----------------+-----------------+-------------+
+ | `BF16` | `BF16` | `BF16` | `FP32` |
+ +--------------+----------------+-----------------+-------------+
+ | `INT8` | `INT8` | `INT8` | `INT32` |
+ + +----------------+-----------------+ +
+ | | `INT32` | `INT32` | |
+ + +----------------+-----------------+ +
+ | | `FP16` | `FP16` | |
+ + +----------------+-----------------+ +
+ | | `BF16` | `BF16` | |
+ +--------------+----------------+-----------------+-------------+
+ | `E4M3` | `FP16` | `E4M3` | `FP32` |
+ + +----------------+-----------------+ +
+ | | `BF16` | `E4M3` | |
+ + +----------------+-----------------+ +
+ | | `FP16` | `FP16` | |
+ + +----------------+-----------------+ +
+ | | `BF16` | `BF16` | |
+ + +----------------+-----------------+ +
+ | | `FP32` | `FP32` | |
+ +--------------+----------------+-----------------+-------------+
+ | `E5M2` | `FP16` | `E5M2` | `FP32` |
+ + +----------------+-----------------+ +
+ | | `BF16` | `E5M2` | |
+ + +----------------+-----------------+ +
+ | | `FP16` | `FP16` | |
+ + +----------------+-----------------+ +
+ | | `BF16` | `BF16` | |
+ + +----------------+-----------------+ +
+ | | `FP32` | `FP32` | |
+ +--------------+----------------+-----------------+-------------+
+
+* Matrix pruning and compression functionalities
+* Activation functions, bias vector, and output scaling
+* Batched computation (multiple matrices in a single run)
+* GEMM Split-K mode
+* Auto-tuning functionality (see `cusparseLtMatmulSearch()`)
+* NVTX ranging and Logging functionalities
+
+================================================================================
+Support
+================================================================================
+
+* *Supported SM Architectures*: `SM 8.0`, `SM 8.6`, `SM 8.9`, `SM 9.0`, `SM 10.0`, `SM 12.0`
+* *Supported CPU architectures and operating systems*:
+
++------------+--------------------+
+| OS | CPU archs |
++============+====================+
+| `Windows` | `x86_64` |
++------------+--------------------+
+| `Linux` | `x86_64`, `Arm64` |
++------------+--------------------+
+
+
+================================================================================
+Documentation
+================================================================================
+
+Please refer to https://docs.nvidia.com/cuda/cusparselt/index.html for the cuSPARSELt documentation.
+
+================================================================================
+Installation
+================================================================================
+
+The cuSPARSELt wheel can be installed as follows:
+
+.. code-block:: bash
+
+ pip install nvidia-cusparselt-cuXX
+
+where XX is the CUDA major version (currently CUDA 12 only is supported).
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/RECORD
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@@ -0,0 +1,8 @@
+nvidia/cusparselt/LICENSE.txt,sha256=6NFYiFpoG5Xsem_AbdjUpSmJ83TLE4DIpMj7J_09XV4,17948
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/WHEEL b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/WHEEL
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: setuptools (75.8.0)
+Root-Is-Purelib: true
+Tag: py3-none-manylinux2014_x86_64
+
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/top_level.txt b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_cusparselt_cu12-0.7.1.dist-info/top_level.txt
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@@ -0,0 +1 @@
+nvidia/cusparselt
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/INSTALLER b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/INSTALLER
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+++ b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/INSTALLER
@@ -0,0 +1 @@
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diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/METADATA b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/METADATA
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@@ -0,0 +1,45 @@
+Metadata-Version: 2.4
+Name: nvidia-nvshmem-cu12
+Version: 3.4.5
+Summary: NVSHMEM creates a global address space that provides efficient and scalable communication for NVIDIA GPU clusters.
+Home-page: https://developer.nvidia.com/cuda-zone
+Author: Nvidia CUDA Installer Team
+Author-email: compute_installer@nvidia.com
+License-Expression: LicenseRef-NVIDIA-Proprietary
+Keywords: cuda,nvidia,runtime,machine learning,deep learning
+Classifier: Development Status :: 4 - Beta
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
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+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Topic :: Scientific/Engineering
+Classifier: Topic :: Scientific/Engineering :: Mathematics
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Classifier: Topic :: Software Development
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX :: Linux
+Requires-Python: >=3
+License-File: License.txt
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
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+Dynamic: license
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+Dynamic: license-expression
+Dynamic: requires-python
+Dynamic: summary
+
+NVSHMEM is a parallel programming interface based on OpenSHMEM that provides efficient and scalable communication for NVIDIA GPU clusters. NVSHMEM creates a global address space for data that spans the memory of multiple GPUs and can be accessed with fine-grained GPU-initiated operations, CPU-initiated operations, and operations on CUDA streams.
diff --git a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/RECORD b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/nvidia_nvshmem_cu12-3.4.5.dist-info/RECORD
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