id stringlengths 14 16 | text stringlengths 44 2.73k | source stringlengths 49 114 |
|---|---|---|
c3bc2f3fbb9c-0 | Source code for langchain.document_loaders.gcs_directory
"""Loading logic for loading documents from an GCS directory."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.gcs_file import GCSFileLoader
[docs]cl... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_directory.html |
e5589608af86-0 | Source code for langchain.document_loaders.csv_loader
from csv import DictReader
from typing import Dict, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class CSVLoader(BaseLoader):
"""Loads a CSV file into a list of documents.
Each d... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/csv_loader.html |
e5589608af86-1 | with open(self.file_path, newline="", encoding=self.encoding) as csvfile:
csv = DictReader(csvfile, **self.csv_args) # type: ignore
for i, row in enumerate(csv):
content = "\n".join(f"{k.strip()}: {v.strip()}" for k, v in row.items())
if self.source_column is not... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/csv_loader.html |
3a5b2d04548d-0 | Source code for langchain.document_loaders.slack_directory
"""Loader for documents from a Slack export."""
import json
import zipfile
from pathlib import Path
from typing import Dict, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class Slack... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/slack_directory.html |
3a5b2d04548d-1 | channel_name = Path(channel_path).parent.name
if not channel_name:
continue
if channel_path.endswith(".json"):
messages = self._read_json(zip_file, channel_path)
for message in messages:
document = self._... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/slack_directory.html |
3a5b2d04548d-2 | "timestamp": timestamp,
"user": user,
}
def _get_message_source(self, channel_name: str, user: str, timestamp: str) -> str:
"""
Get the message source as a string.
Args:
channel_name (str): The name of the channel the message belongs to.
user (str)... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/slack_directory.html |
0a901d8d090a-0 | Source code for langchain.document_loaders.notiondb
"""Notion DB loader for langchain"""
from typing import Any, Dict, List
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
NOTION_BASE_URL = "https://api.notion.com/v1"
DATABASE_URL = NOTION_BASE_URL... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/notiondb.html |
0a901d8d090a-1 | def _retrieve_page_ids(
self, query_dict: Dict[str, Any] = {"page_size": 100}
) -> List[str]:
"""Get all the pages from a Notion database."""
pages: List[Dict[str, Any]] = []
while True:
data = self._request(
DATABASE_URL.format(database_id=self.database_i... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/notiondb.html |
0a901d8d090a-2 | metadata[prop_name.lower()] = value
metadata["id"] = page_id
return Document(page_content=self._load_blocks(page_id), metadata=metadata)
def _load_blocks(self, block_id: str, num_tabs: int = 0) -> str:
"""Read a block and its children."""
result_lines_arr: List[str] = []
cur_... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/notiondb.html |
0a901d8d090a-3 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/notiondb.html |
b0b61d1c6543-0 | Source code for langchain.document_loaders.readthedocs
"""Loader that loads ReadTheDocs documentation directory dump."""
from pathlib import Path
from typing import Any, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class ReadTheDocsLoader(B... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
b0b61d1c6543-1 | text = text[0].get_text()
else:
text = ""
return "\n".join([t for t in text.split("\n") if t])
docs = []
for p in Path(self.file_path).rglob("*"):
if p.is_dir():
continue
with open(p, encoding=self.encoding, errors=self.erro... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
3edc009100e7-0 | Source code for langchain.document_loaders.gutenberg
"""Loader that loads .txt web files."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class GutenbergLoader(BaseLoader):
"""Loader that uses urllib to load .txt web files."""
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/gutenberg.html |
ef57e4e64ca9-0 | Source code for langchain.document_loaders.googledrive
"""Loader that loads data from Google Drive."""
# Prerequisites:
# 1. Create a Google Cloud project
# 2. Enable the Google Drive API:
# https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com
# 3. Authorize credentials for desktop app:
# htt... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-1 | if values.get("folder_id") and (
values.get("document_ids") or values.get("file_ids")
):
raise ValueError(
"Cannot specify both folder_id and document_ids nor "
"folder_id and file_ids"
)
if (
not values.get("folder_id")
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-2 | if not creds or not creds.valid:
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file(
str(self.credentials_path), SCOPES
)
creds = f... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-3 | title = header[j].strip() if len(header) > j else ""
content.append(f"{title}: {v.strip()}")
page_content = "\n".join(content)
documents.append(Document(page_content=page_content, metadata=metadata))
return documents
def _load_document_from_id(self, id: st... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-4 | from googleapiclient.discovery import build
creds = self._load_credentials()
service = build("drive", "v3", credentials=creds)
files = self._fetch_files_recursive(service, folder_id)
returns = []
for file in files:
if file["mimeType"] == "application/vnd.google-apps.d... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-5 | return returns
def _load_documents_from_ids(self) -> List[Document]:
"""Load documents from a list of IDs."""
if not self.document_ids:
raise ValueError("document_ids must be set")
return [self._load_document_from_id(doc_id) for doc_id in self.document_ids]
def _load_file_fro... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
ef57e4e64ca9-6 | docs = []
for file_id in self.file_ids:
docs.extend(self._load_file_from_id(file_id))
return docs
[docs] def load(self) -> List[Document]:
"""Load documents."""
if self.folder_id:
return self._load_documents_from_folder(self.folder_id)
elif self.documen... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/googledrive.html |
614bc78f9dcb-0 | Source code for langchain.document_loaders.gitbook
"""Loader that loads GitBook."""
from typing import Any, List, Optional
from urllib.parse import urljoin, urlparse
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class GitbookLoader(WebBaseLoader):
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/gitbook.html |
614bc78f9dcb-1 | [docs] def load(self) -> List[Document]:
"""Fetch text from one single GitBook page."""
if self.load_all_paths:
soup_info = self.scrape()
relative_paths = self._get_paths(soup_info)
documents = []
for path in relative_paths:
url = urljoi... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/gitbook.html |
b44ec3fdcb33-0 | Source code for langchain.document_loaders.dataframe
"""Load from Dataframe object"""
from typing import Any, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class DataFrameLoader(BaseLoader):
"""Load Pandas DataFrames."""
def __init__(self, dat... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/dataframe.html |
bc8d05ced339-0 | Source code for langchain.document_loaders.text
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class TextLoader(BaseLoader):
"""Load text files."""
def __init__(self, file_path: str, encoding: Optional[str] = None):... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
a2d5f7a5f039-0 | Source code for langchain.document_loaders.ifixit
"""Loader that loads iFixit data."""
from typing import List, Optional
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.web_base import WebBaseLoader
IFIXIT_BASE_URL =... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
a2d5f7a5f039-1 | """Teardowns are just guides by a different name"""
self.page_type = pieces[0] if pieces[0] != "Teardown" else "Guide"
if self.page_type == "Guide" or self.page_type == "Answers":
self.id = pieces[2]
else:
self.id = pieces[1]
self.web_path = web_path
[docs] def... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
a2d5f7a5f039-2 | self, url_override: Optional[str] = None
) -> List[Document]:
loader = WebBaseLoader(self.web_path if url_override is None else url_override)
soup = loader.scrape()
output = []
title = soup.find("h1", "post-title").text
output.append("# " + title)
output.append(soup.s... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
a2d5f7a5f039-3 | text = "\n".join(
[
data[key]
for key in ["title", "description", "contents_raw"]
if key in data
]
).strip()
metadata = {"source": self.web_path, "title": data["title"]}
documents.append(Document(page_content=text, metadata=... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
a2d5f7a5f039-4 | doc_parts.append("\n - " + part["text"])
for row in data["steps"]:
doc_parts.append(
"\n\n## "
+ (
row["title"]
if row["title"] != ""
else "Step {}".format(row["orderby"])
)
)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/ifixit.html |
073e1f990ca5-0 | Source code for langchain.document_loaders.confluence
"""Load Data from a Confluence Space"""
import logging
from typing import Any, Callable, List, Optional, Union
from tenacity import (
before_sleep_log,
retry,
stop_after_attempt,
wait_exponential,
)
from langchain.docstore.document import Document
fr... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-1 | :param url: _description_
:type url: str
:param api_key: _description_, defaults to None
:type api_key: str, optional
:param username: _description_, defaults to None
:type username: str, optional
:param oauth2: _description_, defaults to {}
:type oauth2: dict, optional
:param cloud: _de... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-2 | if errors:
raise ValueError(f"Error(s) while validating input: {errors}")
self.base_url = url
self.number_of_retries = number_of_retries
self.min_retry_seconds = min_retry_seconds
self.max_retry_seconds = max_retry_seconds
try:
from atlassian import Conflu... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-3 | "`username` and provide a value for `oauth2`"
)
if oauth2 and oauth2.keys() != [
"access_token",
"access_token_secret",
"consumer_key",
"key_cert",
]:
errors.append(
"You have either ommited require keys or added ext... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-4 | :param include_comments: defaults to False
:type include_comments: bool, optional
:param limit: Maximum number of pages to retrieve per request, defaults to 50
:type limit: int, optional
:param max_pages: Maximum number of pages to retrieve in total, defaults 1000
:type max_pages... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-5 | max_pages=max_pages,
expand="body.storage.value",
)
for page in pages:
doc = self.process_page(
page, include_attachments, include_comments, text_maker
)
docs.append(doc)
if cql:
pages = self.... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-6 | doesn't match the limit value. If `limit` is >100 confluence
seems to cap the response to 100. Also, due to the Atlassian Python
package, we don't get the "next" values from the "_links" key because
they only return the value from the results key. So here, the pagination
starts from 0 a... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-7 | return docs[:max_pages]
[docs] def process_page(
self,
page: dict,
include_attachments: bool,
include_comments: bool,
text_maker: Any,
) -> Document:
if include_attachments:
attachment_texts = self.process_attachment(page["id"])
else:
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-8 | texts = []
for attachment in attachments:
media_type = attachment["metadata"]["mediaType"]
absolute_url = self.base_url + attachment["_links"]["download"]
title = attachment["title"]
if media_type == "application/pdf":
text = title + self.process_p... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-9 | or response.content == b""
or response.content is None
):
return text
try:
images = convert_from_bytes(response.content)
except ValueError:
return text
for i, image in enumerate(images):
image_text = pytesseract.image_to_string(... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-10 | text = ""
if (
response.status_code != 200
or response.content == b""
or response.content is None
):
return text
file_data = BytesIO(response.content)
return docx2txt.process(file_data)
[docs] def process_xls(self, link: str) -> str:
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
073e1f990ca5-11 | "`pytesseract`, `Pillow`, or `svglib` package not found,"
"please run `pip install pytesseract Pillow svglib`"
)
response = self.confluence.request(path=link, absolute=True)
text = ""
if (
response.status_code != 200
or response.content == b""
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
2291f40ef84b-0 | Source code for langchain.document_loaders.word_document
"""Loader that loads word documents."""
import os
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredWordDocumentLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load w... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
2291f40ef84b-1 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
3b4c55411188-0 | Source code for langchain.document_loaders.chatgpt
"""Load conversations from ChatGPT data export"""
import datetime
import json
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(message: dict, title: str) -> str:
if ... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/chatgpt.html |
3b4c55411188-1 | documents.append(Document(page_content=text, metadata=metadata))
return documents
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/chatgpt.html |
3f466f1f3b76-0 | Source code for langchain.document_loaders.html
"""Loader that uses unstructured to load HTML files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredHTMLLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load HTML files."... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/html.html |
f45709be2157-0 | Source code for langchain.document_loaders.roam
"""Loader that loads Roam directory dump."""
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class RoamLoader(BaseLoader):
"""Loader that loads Roam files fr... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/roam.html |
81f0d772a7aa-0 | Source code for langchain.document_loaders.evernote
"""Load documents from Evernote.
https://gist.github.com/foxmask/7b29c43a161e001ff04afdb2f181e31c
"""
import hashlib
from base64 import b64decode
from time import strptime
from typing import Any, Dict, List
from langchain.docstore.document import Document
from langcha... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
81f0d772a7aa-1 | else:
note_dict[elem.tag] = elem.text
note_dict["resource"] = resources
return note_dict
def _parse_note_xml(xml_file: str) -> str:
"""Parse Evernote xml."""
# Without huge_tree set to True, parser may complain about huge text node
# Try to recover, because there may be " ", which w... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
c64b22e034dc-0 | Source code for langchain.document_loaders.web_base
"""Web base loader class."""
import asyncio
import logging
import warnings
from typing import Any, List, Optional, Union
import aiohttp
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = log... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html |
c64b22e034dc-1 | ):
"""Initialize with webpage path."""
# TODO: Deprecate web_path in favor of web_paths, and remove this
# left like this because there are a number of loaders that expect single
# urls
if isinstance(web_path, str):
self.web_paths = [web_path]
elif isinstance(... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html |
c64b22e034dc-2 | if i == retries - 1:
raise
else:
logger.warning(
f"Error fetching {url} with attempt "
f"{i + 1}/{retries}: {e}. Retrying..."
)
await asyncio.sleep(... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html |
c64b22e034dc-3 | """Fetch all urls, then return soups for all results."""
from bs4 import BeautifulSoup
results = asyncio.run(self.fetch_all(urls))
final_results = []
for i, result in enumerate(results):
url = urls[i]
if parser is None:
if url.endswith(".xml"):
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html |
c64b22e034dc-4 | results = self.scrape_all(self.web_paths)
docs = []
for i in range(len(results)):
soup = results[i]
text = soup.get_text()
metadata = _build_metadata(soup, self.web_paths[i])
docs.append(Document(page_content=text, metadata=metadata))
return docs
B... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html |
a2bebfc28a5e-0 | Source code for langchain.document_loaders.s3_file
"""Loading logic for loading documents from an s3 file."""
import os
import tempfile
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.unstructured import Unst... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_file.html |
dddccd30eb77-0 | Source code for langchain.document_loaders.html_bs
"""Loader that uses bs4 to load HTML files, enriching metadata with page title."""
import logging
from typing import Dict, List, Union
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.getLogger(__n... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/html_bs.html |
dddccd30eb77-1 | "source": self.file_path,
"title": title,
}
return [Document(page_content=text, metadata=metadata)]
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/html_bs.html |
8935ea941e75-0 | Source code for langchain.document_loaders.imsdb
"""Loader that loads IMSDb."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class IMSDbLoader(WebBaseLoader):
"""Loader that loads IMSDb webpages."""
[docs] def load(se... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/imsdb.html |
6491fe68634a-0 | Source code for langchain.document_loaders.azure_blob_storage_container
"""Loading logic for loading documents from an Azure Blob Storage container."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.azure_blob_storage_file import (
AzureBlobStorageFileLoader... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_container.html |
cba7a2cf41a5-0 | Source code for langchain.document_loaders.sitemap
"""Loader that fetches a sitemap and loads those URLs."""
import re
from typing import Any, Callable, List, Optional
from langchain.document_loaders.web_base import WebBaseLoader
from langchain.schema import Document
def _default_parsing_function(content: Any) -> str:
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
cba7a2cf41a5-1 | re.match(r, loc.text) for r in self.filter_urls
):
continue
els.append(
{
tag: prop.text
for tag in ["loc", "lastmod", "changefreq", "priority"]
if (prop := url.find(tag))
}
)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
744d4a904198-0 | Source code for langchain.llms.llamacpp
"""Wrapper around llama.cpp."""
import logging
from typing import Any, Dict, Generator, List, Optional
from pydantic import Field, root_validator
from langchain.llms.base import LLM
logger = logging.getLogger(__name__)
[docs]class LlamaCpp(LLM):
"""Wrapper around the llama.cp... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-1 | """Use half-precision for key/value cache."""
logits_all: bool = Field(False, alias="logits_all")
"""Return logits for all tokens, not just the last token."""
vocab_only: bool = Field(False, alias="vocab_only")
"""Only load the vocabulary, no weights."""
use_mlock: bool = Field(False, alias="use_mlo... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-2 | top_k: Optional[int] = 40
"""The top-k value to use for sampling."""
last_n_tokens_size: Optional[int] = 64
"""The number of tokens to look back when applying the repeat_penalty."""
use_mmap: Optional[bool] = True
"""Whether to keep the model loaded in RAM"""
streaming: bool = True
"""Whethe... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-3 | n_threads=n_threads,
n_batch=n_batch,
use_mmap=use_mmap,
last_n_tokens_size=last_n_tokens_size,
)
except ImportError:
raise ModuleNotFoundError(
"Could not import llama-cpp-python library. "
"Please install t... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-4 | Args:
stop (Optional[List[str]]): List of stop sequences for llama_cpp.
Returns:
Dictionary containing the combined parameters.
"""
# Raise error if stop sequences are in both input and default params
if self.stop and stop is not None:
raise ValueError... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-5 | return result["choices"][0]["text"]
[docs] def stream(
self, prompt: str, stop: Optional[List[str]] = None
) -> Generator[Dict, None, None]:
"""Yields results objects as they are generated in real time.
BETA: this is a beta feature while we figure out the right abstraction:
Once t... | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
744d4a904198-6 | token=token, verbose=self.verbose, log_probs=log_probs
)
yield chunk
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/llamacpp.html |
c01f71c0543f-0 | Source code for langchain.llms.aleph_alpha
"""Wrapper around Aleph Alpha APIs."""
from typing import Any, Dict, List, Optional, Sequence
from pydantic import Extra, root_validator
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
from langchain.utils import get_from_dict_or_env
[d... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
c01f71c0543f-1 | presence_penalty: float = 0.0
"""Penalizes repeated tokens."""
frequency_penalty: float = 0.0
"""Penalizes repeated tokens according to frequency."""
repetition_penalties_include_prompt: Optional[bool] = False
"""Flag deciding whether presence penalty or frequency penalty are
updated from the pr... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
c01f71c0543f-2 | sequence_penalty: float = 0.0
sequence_penalty_min_length: int = 2
use_multiplicative_sequence_penalty: bool = False
completion_bias_inclusion: Optional[Sequence[str]] = None
completion_bias_inclusion_first_token_only: bool = False
completion_bias_exclusion: Optional[Sequence[str]] = None
comple... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
c01f71c0543f-3 | values, "aleph_alpha_api_key", "ALEPH_ALPHA_API_KEY"
)
try:
import aleph_alpha_client
values["client"] = aleph_alpha_client.Client(token=aleph_alpha_api_key)
except ImportError:
raise ValueError(
"Could not import aleph_alpha_client python pack... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
c01f71c0543f-4 | "sequence_penalty": self.sequence_penalty,
"sequence_penalty_min_length": self.sequence_penalty_min_length,
"use_multiplicative_sequence_penalty": self.use_multiplicative_sequence_penalty, # noqa: E501
"completion_bias_inclusion": self.completion_bias_inclusion,
"complet... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
c01f71c0543f-5 | from aleph_alpha_client import CompletionRequest, Prompt
params = self._default_params
if self.stop_sequences is not None and stop is not None:
raise ValueError(
"stop sequences found in both the input and default params."
)
elif self.stop_sequences is not... | https://python.langchain.com/en/latest/_modules/langchain/llms/aleph_alpha.html |
9022a96104ae-0 | Source code for langchain.llms.predictionguard
"""Wrapper around Prediction Guard APIs."""
import logging
from typing import Any, Dict, List, Optional
from pydantic import Extra, root_validator
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
from langchain.utils import get_from_... | https://python.langchain.com/en/latest/_modules/langchain/llms/predictionguard.html |
9022a96104ae-1 | values["client"] = pg.Client(token=token)
except ImportError:
raise ValueError(
"Could not import predictionguard python package. "
"Please install it with `pip install predictionguard`."
)
return values
@property
def _default_params(self) ... | https://python.langchain.com/en/latest/_modules/langchain/llms/predictionguard.html |
9022a96104ae-2 | "temperature": params["temperature"],
},
)
text = response["text"]
# If stop tokens are provided, Prediction Guard's endpoint returns them.
# In order to make this consistent with other endpoints, we strip them.
if stop is not None or self.stop is not None:
... | https://python.langchain.com/en/latest/_modules/langchain/llms/predictionguard.html |
a25311748176-0 | Source code for langchain.llms.sagemaker_endpoint
"""Wrapper around Sagemaker InvokeEndpoint API."""
from abc import abstractmethod
from typing import Any, Dict, Generic, List, Mapping, Optional, TypeVar, Union
from pydantic import Extra, root_validator
from langchain.llms.base import LLM
from langchain.llms.utils impo... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
a25311748176-1 | def transform_input(self, prompt: INPUT_TYPE, model_kwargs: Dict) -> bytes:
"""Transforms the input to a format that model can accept
as the request Body. Should return bytes or seekable file
like object in the format specified in the content_type
request header.
"""
@abstrac... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
a25311748176-2 | )
se = SagemakerEndpoint(
endpoint_name=endpoint_name,
region_name=region_name,
credentials_profile_name=credentials_profile_name
)
"""
client: Any #: :meta private:
endpoint_name: str = ""
"""The name of the endpoint from the depl... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
a25311748176-3 | response_json = json.loads(output.read().decode("utf-8"))
return response_json[0]["generated_text"]
"""
model_kwargs: Optional[Dict] = None
"""Key word arguments to pass to the model."""
endpoint_kwargs: Optional[Dict] = None
"""Optional attributes passed to the invoke_endpoint
... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
a25311748176-4 | """Get the identifying parameters."""
_model_kwargs = self.model_kwargs or {}
return {
**{"endpoint_name": self.endpoint_name},
**{"model_kwargs": _model_kwargs},
}
@property
def _llm_type(self) -> str:
"""Return type of llm."""
return "sagemaker_e... | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
a25311748176-5 | text = enforce_stop_tokens(text, stop)
return text
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 25, 2023. | https://python.langchain.com/en/latest/_modules/langchain/llms/sagemaker_endpoint.html |
81ade6317d2b-0 | Source code for langchain.llms.huggingface_hub
"""Wrapper around HuggingFace APIs."""
from typing import Any, Dict, List, Mapping, Optional
from pydantic import Extra, root_validator
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
from langchain.utils import get_from_dict_or_env... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
81ade6317d2b-1 | @root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
huggingfacehub_api_token = get_from_dict_or_env(
values, "huggingfacehub_api_token", "HUGGINGFACEHUB_API_TOKEN"
)
try:
... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
81ade6317d2b-2 | Args:
prompt: The prompt to pass into the model.
stop: Optional list of stop words to use when generating.
Returns:
The string generated by the model.
Example:
.. code-block:: python
response = hf("Tell me a joke.")
"""
_mod... | https://python.langchain.com/en/latest/_modules/langchain/llms/huggingface_hub.html |
01c44ee1d92e-0 | Source code for langchain.llms.writer
"""Wrapper around Writer APIs."""
from typing import Any, Dict, List, Mapping, Optional
import requests
from pydantic import Extra, root_validator
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
from langchain.utils import get_from_dict_or_e... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
01c44ee1d92e-1 | by fixing the random seed (assuming all other hyperparameters
are also fixed)"""
beam_search_diversity_rate: float = 1.0
"""Only applies to beam search, i.e. when the beam width is >1.
A higher value encourages beam search to return a more diverse
set of candidates"""
beam_width: Optional[int] =... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
01c44ee1d92e-2 | "temperature": self.temperature,
"top_p": self.top_p,
"top_k": self.top_k,
"repetition_penalty": self.repetition_penalty,
"random_seed": self.random_seed,
"beam_search_diversity_rate": self.beam_search_diversity_rate,
"beam_width": self.beam_width,... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
01c44ee1d92e-3 | },
json={"prompt": prompt, **self._default_params},
)
text = response.text
if stop is not None:
# I believe this is required since the stop tokens
# are not enforced by the model parameters
text = enforce_stop_tokens(text, stop)
return text... | https://python.langchain.com/en/latest/_modules/langchain/llms/writer.html |
5d4b6aa210f4-0 | Source code for langchain.llms.self_hosted
"""Run model inference on self-hosted remote hardware."""
import importlib.util
import logging
import pickle
from typing import Any, Callable, List, Mapping, Optional
from pydantic import Extra
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_t... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
5d4b6aa210f4-1 | if device < 0 and cuda_device_count > 0:
logger.warning(
"Device has %d GPUs available. "
"Provide device={deviceId} to `from_model_id` to use available"
"GPUs for execution. deviceId is -1 for CPU and "
"can be a positive integer associated wi... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
5d4b6aa210f4-2 | model_load_fn=load_pipeline,
hardware=gpu,
model_reqs=model_reqs, inference_fn=inference_fn
)
Example for <2GB model (can be serialized and sent directly to the server):
.. code-block:: python
from langchain.llms import SelfHostedPipeline
i... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
5d4b6aa210f4-3 | """Key word arguments to pass to the model load function."""
model_reqs: List[str] = ["./", "torch"]
"""Requirements to install on hardware to inference the model."""
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
def __init__(self, **kwargs: Any):
... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
5d4b6aa210f4-4 | logger.warning(
"Serializing pipeline to send to remote hardware. "
"Note, it can be quite slow"
"to serialize and send large models with each execution. "
"Consider sending the pipeline"
"to the cluster and passing the path to the pipeline... | https://python.langchain.com/en/latest/_modules/langchain/llms/self_hosted.html |
68fe0d53f106-0 | Source code for langchain.llms.ai21
"""Wrapper around AI21 APIs."""
from typing import Any, Dict, List, Optional
import requests
from pydantic import BaseModel, Extra, root_validator
from langchain.llms.base import LLM
from langchain.utils import get_from_dict_or_env
class AI21PenaltyData(BaseModel):
"""Parameters ... | https://python.langchain.com/en/latest/_modules/langchain/llms/ai21.html |
68fe0d53f106-1 | """Penalizes repeated tokens according to count."""
frequencyPenalty: AI21PenaltyData = AI21PenaltyData()
"""Penalizes repeated tokens according to frequency."""
numResults: int = 1
"""How many completions to generate for each prompt."""
logitBias: Optional[Dict[str, float]] = None
"""Adjust the... | https://python.langchain.com/en/latest/_modules/langchain/llms/ai21.html |
68fe0d53f106-2 | @property
def _identifying_params(self) -> Dict[str, Any]:
"""Get the identifying parameters."""
return {**{"model": self.model}, **self._default_params}
@property
def _llm_type(self) -> str:
"""Return type of llm."""
return "ai21"
def _call(self, prompt: str, stop: Optio... | https://python.langchain.com/en/latest/_modules/langchain/llms/ai21.html |
68fe0d53f106-3 | optional_detail = response.json().get("error")
raise ValueError(
f"AI21 /complete call failed with status code {response.status_code}."
f" Details: {optional_detail}"
)
response_json = response.json()
return response_json["completions"][0]["data"][... | https://python.langchain.com/en/latest/_modules/langchain/llms/ai21.html |
93469452885e-0 | Source code for langchain.llms.replicate
"""Wrapper around Replicate API."""
import logging
from typing import Any, Dict, List, Mapping, Optional
from pydantic import Extra, Field, root_validator
from langchain.llms.base import LLM
from langchain.utils import get_from_dict_or_env
logger = logging.getLogger(__name__)
[d... | https://python.langchain.com/en/latest/_modules/langchain/llms/replicate.html |
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