Update pycares requirement from <5.0.0 to <6.0.0

[//]: # (dependabot-start)
⚠  **Dependabot is rebasing this PR** ⚠

Rebasing might not happen immediately, so don't worry if this takes some time.

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---

[//]: # (dependabot-end)

Updates the requirements on [pycares](https://github.com/saghul/pycares) to permit the latest version.

Changelog

Sourced from pycares's changelog.

No longer updated. Please check the commits.

Version 4.0.0

doc: uppdate README

core: add support for CAA queries

core: add support for getaddrinfo()

doc: update README

core: add ability to use the system installed c-ares

misc: set version to 4.0.0

test: remove TTL tests

core: update c-ares and use a submodule

core: drop bundled c-ares version

misc: drop tasks.py

Version 3.2.0

misc: add Python 3.9 classifier

core: drop py3.5 from CI and documentation

ci: run tests in Python 3.9

ci: fix SDK path in appveyor

ci: fix VS linker in appveyor

ci: update python installer script in appveyor

misc: add compiled windows dll to gitignore

test: skip SOA non-ascii test due to changes in remote host

test: fix broken chunked TXT test due to changes in remote host

test: skip ANY test due to problems with mac

ci: add action to release wheels to PyPi

ci: drop AppVeyor

ci: don't fail fast

ci: stop testing on Travis

test: add generic way to check for a CI

test: relax check

test: try to avoid spurious CI failures

ci: test all platforms on GH actions

ci: build wheels on GH Actions

build: fix build error on macOS

ci: explicitly set Python versions to build wheels for

ci: update cibuildwheel

ci: re-add IDNA test

Version 3.1.1

ffi: new style callbacks

Version 3.1.0

misc: add Python 3.8 classifier

(origin/master, origin/HEAD) build: use Travis to build Python Wheels

... (truncated)

Commits

8ef6485 Update README

db895c8 Update documentation

36950d8 Extend timeout for test

188ee73 Fix crash if socket state callback is called during destruction

9b38166 Explicitly close channel in test tearDown

0cb3c42 Workaround test failure on Windows 11 ARM

27aeb52 Make test more resilient

1a79e76 Fixup tests

d7db89d Make arguments to Channel keyword only

64aaa54 Remove event_thread opt


Update torchao requirement from <0.15,>=0.12 to >=0.12,<0.16

Updates the requirements on [torchao](https://github.com/pytorch/ao) to permit the latest version.

Release notes

Sourced from torchao's releases.

v0.15.0

Highlights

We are excited to announce the 0.15.0 release of torchao! This release adds:

MXFP8 MoE training demonstrates 1.2x e2e training speedup with identical convergence versus bf16, training Llama4 Scout on a 64 node GB200 Crusoe cluster!

MXFP8 MoE kernels shipped with torchao builds for CUDA 12.8+ (just pip install instead of building from source to use!)

Safetensors enablement

Quantization with parameter level targeting

MXFP8 MoE training demonstrates 1.2x e2e training speedup with identical convergence versus bf16, training Llama4 Scout on a 64 node GB200 Crusoe cluster

Training runs on 64 node GB200 cluster with TorchTitan Llama4 Scout demonstrated a 1.2x e2e training speedup with equivalent convergence to bfloat16 training baseline. In fact, after 3,000 steps it finishes with slightly lower loss than bfloat16! This is consistent with our scaling experiments with MXFP8 training for dense models.

Number of GPUs
BF16 tokens/sec
MXFP8 tokens/sec
MXFP8 speedup vs BF16

512
6169
7401
1.20x

See the TorchAO MXFP8 MoE training documentation for more details. You can also check out the TorchTitan MXFP8 documentation to run pretraining jobs with TorchAO MXFP8 by adding a single config.

Safetensors Enablement

You can now save and load TorchAO model checkpoints using safetensors! This feature is integrated with Hugging Face transformers starting from v5.0.0 and vLLM 0.13.0 for model inference/serving.

We currently support the following stable configs:
Float8DynamicActivationFloat8WeightConfig
Int4WeightOnlyConfig
IntxWeightOnlyConfig
Int8DynamicActivationIntxWeightConfig
Int8WeightOnlyConfig
Int8DynamicActivationInt8WeightConfig

and will continue to add support for configs as they become stable in the future.

Example:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TorchAoConfig
from torchao.quantization import Float8WeightOnlyConfig

model_id = "facebook/opt-125m"
quant_config = Float8WeightOnlyConfig()
quantization_config = TorchAoConfig(quant_type=quant_config)
quantized_model = AutoModelForCausalLM.from_pretrained(
model_id,
</tr></table>

... (truncated)

Commits

9338966 use python version agnostic binding for mxfp8 cuda kernels (#3471)

acc9103 Fix NVFP4 QAT backward typo (#3478)

286c2d8 Fix NVFP4 QAT convert path (#3450


Update pillow requirement from <11.4,>=11.3 to >=11.3,<12.1

Updates the requirements on [pillow](https://github.com/python-pillow/Pillow) to permit the latest version.

Release notes

Sourced from pillow's releases.

12.0.0

https://pillow.readthedocs.io/en/stable/releasenotes/12.0.0.html

Removals

Remove support for FreeType <= 2.9.0 #9159 [@radarhere]

Drop support for Python 3.9 #9119 [@hugovk]

Remove deprecations for Pillow 12.0.0 #9053 [@radarhere]

Deprecations

Deprecate Image._show #9186 [@radarhere]

Deprecate ImageCmsProfile product_name and product_info #8995 [@lukegb]

Documentation

ImagingHistogramInstance can use two bands #9251 [@radarhere]

Update 12.0.0 release notes #9247 [@hugovk]

Added ImageDraw alpha channel examples #9201 [@radarhere]

Update Python version #9230 [@radarhere]

Updated macOS tested Pillow versions #9209 [@radarhere]

Add GitHub profile link to release notes #9197 [@radarhere]

Split versionadded info #9190 [@radarhere]

Document ImageFile.MAXBLOCK #9163 [@radarhere]

Updated macOS version in CI targets #9157 [@radarhere]

Fix typos #9135 [@radarhere]

Added "Colors" to concepts #9067 [@radarhere]

Update macOS tested Pillow versions #9068 [@radarhere]

Thanks, folks! #9056 [@aclark4life]

Setup nit: "f


Update typer requirement from <0.20.1 to <0.21.1

Updates the requirements on [typer](https://github.com/fastapi/typer) to permit the latest version.

Release notes

Sourced from typer's releases.

0.21.0

Breaking Changes

➖ Drop support for Python 3.8. PR #1464 by @tiangolo.

➖ Drop support for Python 3.8 in CI. PR #1463 by @YuriiMotov and @tiangolo.

Docs

📝 Update code examples to Python 3.9. PR #1459 by @YuriiMotov.

Internal

💚 Move ruff dependency to shared requirements-docs-tests.txt to fix "Build docs" workflow in CI. PR #1458 by @YuriiMotov.

⬆ Bump markdown-include-variants from 0.0.5 to 0.0.8. PR #1442 by @dependabot[bot].

👷 Add pre-commit workflow. PR #1453 by @tiangolo.

👷 Configure coverage, error on main tests, don't wait for Smokeshow. PR #1448 by @YuriiMotov.

👷 Run Smokeshow always, even on test failures. PR #1447 by @YuriiMotov.

🔨 Add Typer script to generate example variants for Python files. PR #1452 by @tiangolo.

Changelog

Sourced from typer's changelog.

0.21.0

Breaking Changes

➖ Drop support for Python 3.8. PR #1464 by @tiangolo.

➖ Drop support for Python 3.8 in CI. PR #1463 by @YuriiMotov and @tiangolo.

Docs

📝 Update code examples to Python 3.9. PR #1459 by @YuriiMotov.

Internal

💚 Move ruff dependency to shared requirements-docs-tests.txt to fix "Build docs" workflow in CI. PR #1458 by @YuriiMotov.

⬆ Bump markdown-include-variants from 0.0.5 to 0.0.8. PR #1442 by @dependabot[bot].

👷 Add pre-commit workflow. PR #1453 by @tiangolo.<


[docs] add docs build step

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[docs] Add custom theme

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[cli] minor cli updates

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[docs] misc updates & cleanup

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- [docs] update CLI command tables with complete command list

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[tiny] minor judge command UX improvements

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[tiny] fix typo

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deprecate protobuf conversation definitions

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[docs] add analyze, tune, and quantize CLI reference sections

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[docs] fix inference recipe paths to match directory structure


add skypilot k8s dependency

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Towards LOU-208

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[tiny] update deprecated torch_dtype

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- torch_dtype is marked as deprecated by `transformers`. This PR updates to `dtype`

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Update cli: list aliases, auto-complete, help, common args

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- Add a `--list` option to all commands, showing available aliases
- Add missing verb aliases (e.g. synth)
- Add auto-complete with fuzzy matching for recipes
- Add common changed parameters to CLI (merged into the config)
- Add misc help and tooltips

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Add ty config

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- Add config to use ty for type checking, matching pyright as much as possible
- Not enabled by default yet, users can run with `make ty`

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[bug] Pin typer version causing build docs failures

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- Pin typer version causing build docs failures
- More details here: https://github.com/sphinx-contrib/typer/issues/54

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Towards OPE-1806

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Update click requirement from <8.3.0 to <8.4.0

Updates the requirements on [click](https://github.com/pallets/click) to permit the latest version.

Release notes

Sourced from click's releases.

8.3.1

This is the Click 8.3.1 fix release, which fixes bugs but does not otherwise change behavior and should not result in breaking changes compared to the latest feature release.

PyPI: https://pypi.org/project/click/8.3.1/
Changes: https://click.palletsprojects.com/page/changes/#version-8-3-1
Milestone: https://github.com/pallets/click/milestone/28

Don't discard pager arguments by correctly using subprocess.Popen. #3039 #3055

Replace Sentinel.UNSET default values by None as they're passed through the Context.invoke() method. #3066 #3065 #3068

Fix conversion of Sentinel.UNSET happening too early, which caused incorrect behavior for multiple parameters using the same name. #3071 #3079

Fix rendering when prompt and confirm parameter prompt_suffix is empty. #3019 #3021

When Sentinel.UNSET is found during parsing, it will skip calls to type_cast_value. #3069 #3090

Hide Sentinel.UNSET values as None when looking up for other parameters through the context inside parameter callbacks. #3136 #3137

Changelog

Sourced from click's changelog.

Version 8.3.1

Released 2025-11-15

Don't discard pager arguments by correctly using subprocess.Popen. :issue:3039
:pr:3055

Replace Sentinel.UNSET default values by None as they're passed through
the Context.invoke() method. :issue:3066 :issue:3065 :pr:3068

Fix conversion of Sentinel.UNSET happening too early, which caused incorrect
behavior for multiple parameters using the same name. :issue:3071 :pr:3079

Hide Sentinel.UNSET values as None when looking up for other parameters
through the context inside parameter callbacks. :issue:3136 :pr:3137

Fix rendering when prompt and confirm parameter prompt_suffix is
empty. :issue:3019 :pr:3021

When Sentinel.UNSET is found during parsing, it will skip calls to
type_cast_value. :issue:3069 :pr:3090

Version 8.3.0

Released 2025-09-17

I


Update bitsandbytes requirement from <0.49,>=0.47 to >=0.47,<0.50

Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.

Release notes

Sourced from bitsandbytes's releases.

0.49.0

Highlights

x86-64 CPU Improvements

CPU performance for 4bit is significantly improved on x86-64, with optimized kernel paths for CPUs that have AVX512 or AVX512BF16 support.

AMD ROCm Experimental Wheels

Experimental support for AMD devices is now included in our PyPI wheels on Linux x86-64.

We've added additional GPU target devices as outlined in our docs.

Support for using the default blocksize of 64 for 4bit was added for RDNA GPUs in #1748.

macOS 14+ Wheels

We're now publishing wheels for macOS 14+!

The 4bit and 8bit quantization features are supported on MPS by slow implementations. We plan to enable Metal kernels with improved performance in the future.

🚨 Breaking Changes

Dropped support for Python 3.9.

Dropped compilation support for Maxwell GPUs in the CUDA backend.

What's Changed

[ROCm] Update build targets by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1788

Drop Python 3.9 support by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1795

Fix indexing overflow issue for blockwise quantization on AMD by @sstamenk in bitsandbytes-foundation/bitsandbytes#1796

Tests: Run CPU tests against PyTorch 2.9 by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1797

Remove deprecated code by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1798

Cpu C++ kernel  by @jiqing-feng in bitsandbytes-foundation/bitsandbytes#1789

fix build error: "no case matching constant switch condition" by @yuguo68 in bitsandbytes-foundation/bitsandbytes#1802

CI: skip rebuilding CPU lib when building/installing wheels by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1803

add support for 64 block size on 32 warp size supported amd gpus by @electron271 in bitsandbytes-foundation/bitsandbytes#1748

Enable more tests on AMD for warp size 32 by @sstamenk in <a href="https://redirect.github.com/bits


Update uvicorn requirement from <0.36.0 to <0.41.0

Updates the requirements on [uvicorn](https://github.com/Kludex/uvicorn) to permit the latest version.

Release notes

Sourced from uvicorn's releases.

Version 0.40.0

What's Changed

Drop Python 3.9 by @Kludex in Kludex/uvicorn#2772

Full Changelog: https://github.com/Kludex/uvicorn/compare/0.39.0...0.40.0

Changelog

Sourced from uvicorn's changelog.

0.40.0 (December 21, 2025)

Remove

Drop support for Python 3.9 (#2772)

0.39.0 (December 21, 2025)

Fixed

Send close frame on ASGI return for WebSockets (#2769)

Explicitly start ASGI run with empty context (#2742)

0.38.0 (October 18, 2025)

Added

Support Python 3.14 (#2723)

0.37.0 (September 23, 2025)

Added

Add --timeout-worker-healthcheck option (#2711)

Add os.PathLike[str] type to ssl_ca_certs (#2676)

0.36.1 (September 23, 2025)

Fixed

Raise an exception when calling removed Config.setup_event_loop() (#2709)

0.36.0 (September 20, 2025)

Added

Support custom IOLOOPs (#2435)

Allow to provide importable string in --http, --ws and --loop (#2658)

0.35.0 (June 28, 2025)

Added

Add WebSocketsSansIOProtocol (#2540)

Changed

Refine help message for option --proxy-headers (#2653)

0.34.3 (June 1, 2025)

... (truncated)

Commits

9ff6004 Version 0.40.0 (#2773)

19df042 Drop Python 3.9 (#2772)

865ce7c Run strict mypy on test suite (#2771)

4f40b84 Version 0.39.0 (#2770)

5692dfc</


Update peft requirement from <0.18,>=0.17 to >=0.17,<0.19

Updates the requirements on [peft](https://github.com/huggingface/peft) to permit the latest version.

Release notes

Sourced from peft's releases.

0.18.0: RoAd, ALoRA, Arrow, WaveFT, DeLoRA, OSF, and more

Highlights

FIXME update list of all changes, so some more commits were added

New Methods

RoAd

@ppetrushkov added RoAd: 2D Rotary Adaptation to PEFT in #2678. RoAd learns 2D rotation matrices that are applied using only element-wise multiplication, thus promising very fast inference with adapters in unmerged state.

Remarkably, besides LoRA, RoAd is the only PEFT method that supports mixed adapter batches. This means that when you have loaded a model with multiple RoAd adapters, you can use all of them for different samples in the same batch, which is much more efficient than switching adapters between batches:

model = PeftModel.from_pretrained(base_model, <path-to-road-adapter-A>, adapter_name="adapter-A")
model.add_adapter("adapter-B", <path-to-road-adapter-B>)

inputs = ...  # input with 3 samples

apply adapter A to sample 0, adapter B to sample 1, and use the base model for sample 2:

adapter_names = ["adapter-A", "adapter-B", "base"]
output_mixed = model(**inputs, adapter_names=adapter_names)
gen_mixed = model.generate(**inputs, adapter_names=adapter_names)

ALoRA

Activated LoRA is a technique added by @kgreenewald in #2609 for causal language models, allowing to selectively enable LoRA adapters depending on a specific token invocation sequence in the input. This has the major benefit of being able to re-use most of the KV cache during inference when the adapter is only used to generate part of the response, after which the base model takes over again.

Arrow & GenKnowSub

@TheTahaaa contributed not only support for Arrow, a dynamic routing algorithm between multiple loaded LoRAs in #2644, but also GenKnowSub, a technique built upon Arrow where the 'library' of LoRAs available to Arrow is first modified by subtracting general knowledge adapters (e.g., trained on subsets of Wikipedia) to enhance task-specific performance.

WaveFT

Thanks to @Bilican, Wavelet Fine-Tuning (WaveFT) was added to PEFT in #2560. This method trains sparse updates in the wavelet domain of residual matrices, which is especially parameter efficient. It is very interesting for image generation, as it promises to generate diverse outputs while preserving subject fidelity.

DeLoRA

Decoupled Low-rank Adaptation (DeLoRA) was added by @mwbini in #2780. This new PEFT method is similar to DoRA in so far as it decouples the angle and magnitude of the learned adapter weights. However, DeLoRA implements this in a way that promises to better prevent divergence. Moreover, it constrains the dev


Bump actions/cache from 4 to 5 in the all-actions group

Bumps the all-actions group with 1 update: [actions/cache](https://github.com/actions/cache).

Updates `actions/cache` from 4 to 5

Release notes

Sourced from actions/cache's releases.

v5.0.0

[!IMPORTANT]
actions/cache@v5 runs on the Node.js 24 runtime and requires a minimum Actions Runner version of 2.327.1.

If you are using self-hosted runners, ensure they are updated before upgrading.

What's Changed

Upgrade to use node24 by @salmanmkc in actions/cache#1630

Prepare v5.0.0 release by @salmanmkc in actions/cache#1684

Full Changelog: https://github.com/actions/cache/compare/v4.3.0...v5.0.0

v4.3.0

What's Changed

Add note on runner versions by @GhadimiR in actions/cache#1642

Prepare v4.3.0 release by @Link- in actions/cache#1655

New Contributors

@GhadimiR made their first contribution in actions/cache#1642

Full Changelog: https://github.com/actions/cache/compare/v4...v4.3.0

v4.2.4

What's Changed

Update README.md by @nebuk89 in actions/cache#1620

Upgrade @actions/cache to 4.0.5 and move @protobuf-ts/plugin to dev depdencies by @Link- in actions/cache#1634

Prepare release 4.2.4 by @Link- in actions/cache#1636

New Contributors

@nebuk89 made their first contribution in actions/cache#1620

Full Changelog: https://github.com/actions/cache/compare/v4...v4.2.4

v4.2.3

What's Changed

Update to use @actions/cache 4.0.3 package & prepare for new release by @salmanmkc in actions/cache#1577 (SAS tokens for cache entries are now masked in debug logs)

New Contributors

@salmanmkc made their first contribution in actions/cache#1577

Full Changelog: https://github.com/actions/cache/compare/v4.2.2...v4.2.3

... (truncated)

Changelog

Sourc


Dec news updates

December updates:

* Oumi v0.6.0 release
* Hackathon webinar
* Hackathon per se


[perf] Add lazy imports in the cli

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- Add lazy imports in the cli code paths
- Benchmarks:

| Module | Before | After | Improvement |
|--------|--------|-------|-------------|
| CLI startup | 320-340ms | 56-58ms | **83%** |

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[deps] upgrade pytorch 2.9 & python 3.14

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- Enable python 3.14 and pytorch 2.9

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edits to docs guide

Reorganized the to-do list for submitting changes to the docs. Moved, "to update the documentation" to the beginning of the sentence to emphasize the action that will be completed. Now "make a PR" is a checklist item.

+ small type editing.


Fix issue with synthesis rounding errors

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Due to rounding errors, many configs fail to parse because they don't sum up to exactly 1, so this adds some tolerance.
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[configs] create folders for infer


[configs] Add train/infer/eval configs

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- Add example train/eval/infer configs for recent models
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Make top_p optional for API models

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Sonnet 4.5 requires that either temperature or top_p be set, but NOT BOTH.

Updating our generation params to allow us to support this type of definition more broadly across API models (which often have their own default top_p which we wouldn't want to overwrite anyway).
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[deps] upgrade trl to 0.26

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- Upgrade trl version

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Enable python 3.13 support & add github actions cache

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- Enable support for python 3.13
- Add github actions cache for hf resources

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Update nvidia-ml-py requirement from <13.581,>=13.580 to >=13.580,<13.591

Updates the requirements on [nvidia-ml-py](https://forums.developer.nvidia.com) to permit the latest version.

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Update skypilot requirement from <0.11,>=0.10.2 to >=0.10.2,<0.12

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Updates the requirements on [skypilot](https://github.com/skypilot-org/skypilot) to permit the latest version.

Release notes

Sourced from skypilot's releases.

SkyPilot v0.11.0: Multi-Cloud Pools, Fast Managed Jobs, Enterprise-Readiness at Large Scale, Programmability

SkyPilot v0.11.0 delivers major new features: Pools and Managed Jobs Consolidation Mode; significant improvement enterprise-readiness at large scale: supports hundreds of AI engineers with a single API server instance, avoid OOM, >10x performance improvement on many requests, additional observability, and more; and UX improvements: Templates, Python SDK, CI/CD, Git Support, and more.

Get it now with:

uv pip install "skypilot>=0.11.0"

Or, upgrade your team SkyPilot API server:

NAMESPACE=skypilot
RELEASE_NAME=skypilot
VERSION=0.11.0

helm repo update skypilot
helm upgrade -n $NAMESPACE $RELEASE_NAME skypilot/skypilot

--set apiService.image=berkeleyskypilot/skypilot:$VERSION

--version $VERSION --devel --reuse-values

Highlights

[Beta] SkyPilot Pools: Batch inference across clouds & k8s

SkyPilot supports spawning a pool that launches a set of workers across many clouds and Kubernetes clusters (docs, #6260, #6426, #6459, #6552, #6591, #6665, #6675, #7332, #7963, #8008, #7876, #8047, #7930,#8039, #7846, #7855, #7919, #7920). Jobs can be scheduled on this pool and distributed to workers as they become available.

Key benefits include:

Fully utilize your GPU capacity across clouds & k8s

Unified queue for jobs on all infra

Keep workers warm, scale elastically

Step aside for other higher priority jobs; reschedule when GPUs become available

Learn more in our blog post.

<!


feat(judges): add code evaluation judges for software quality assessment

Add 5 new judge configurations for evaluating code quality:
- code_quality.yaml: Readability, structure, documentation, DRY principle
- security.yaml: Injection prevention, auth, data protection, crypto
- correctness.yaml: Functional correctness, edge cases, logic accuracy
- performance.yaml: Time/space complexity, I/O efficiency, caching
- maintainability.yaml: Modularity, testability, extensibility

These judges enable automated evaluation of LLM-generated code outputs, useful for code generation, refactoring, and code review tasks.

Contributed as part of AssembleHack25 hackathon submission.


pin pycares

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https://pypi.org/project/pycares/#history recent bump has caused errors on our dataset

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Towards LOU-331

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Remove references to sphinx_rtd_theme

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Remove a module as its import was removed in #2075
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Update pydantic requirement from <2.12,>=2.11 to >=2.11,<2.13

Updates the requirements on [pydantic](https://github.com/pydantic/pydantic) to permit the latest version.

Release notes

Sourced from pydantic's releases.

v2.12.5 2025-11-26

v2.12.5 (2025-11-26)

This is the fifth 2.12 patch release, addressing an issue with the MISSING sentinel and providing several documentation improvements.

The next 2.13 minor release will be published in a couple weeks, and will include a new polymorphic serialization feature addressing
the remaining unexpected changes to the serialize as any behavior.

Fix pickle error when using model_construct() on a model with MISSING as a default value by @ornariece in #12522.

Several updates to the documentation by @Viicos.

Full Changelog: https://github.com/pydantic/pydantic/compare/v2.12.4...v2.12.5

Changelog

Sourced from pydantic's changelog.

v2.12.5 (2025-11-26)

GitHub release

This is the fifth 2.12 patch release, addressing an issue with the MISSING sentinel and providing several documentation improvements.

The next 2.13 minor release will be published in a couple weeks, and will include a new polymorphic serialization feature addressing
the remaining unexpected changes to the serialize as any behavior.

Fix pickle error when using model_construct() on a model with MISSING as a default value by @ornariece in #12522.

Several updates to the documentation by @Viicos.

v2.12.4 (2025-11-05)

GitHub release

This is the fourth 2.12 patch release, fixing more regressions, and reverting a change in the build() method
of the AnyUrl and Dsn types.

This patch release also fixes an issue with the serialization of IP address types, when serialize_as_any is used. The next patch release
will try to address the remaining issues with serialize as any behavior by introducing a new polymorphic serialization feature, that
should be used in most cases in place of serialize as any.

Fix issue with forward references in parent TypedDict classes by @Viicos in #12427.

This issue is only relevant on Python 3.14 and greater.

Exclude fields with exclude_if from JSON Schema required fields by @Viicos in #12430

Revert URL percent-encoding of credentials in the build() method
of the AnyUrl and Dsn types by @davidhewitt in
<a href="https://redirect.github.com/pydantic/pydantic-core/


Update deepspeed requirement from <0.18.0,>=0.17.0 to >=0.17.0,<0.19.0

Updates the requirements on [deepspeed](https://github.com/deepspeedai/DeepSpeed) to permit the latest version.

Release notes

Sourced from deepspeed's releases.

v0.18.2 Patch Release

What's Changed

Update version after 0.18.1 release by @loadams in deepspeedai/DeepSpeed#7647

Deduplicate fp32 weights under torch autocast and ZeRO3 by @eternalNight in deepspeedai/DeepSpeed#7651

ulysses mpu: additional api by @stas00 in deepspeedai/DeepSpeed#7649

ALST/UlyssesSP: more intuitive API wrt variable seqlen by @stas00 in deepspeedai/DeepSpeed#7656

Fix misplaced overflow handling return in fused_optimizer.py by @rraminen in deepspeedai/DeepSpeed#7645

[bug]: fixed comm_dtype in extra_large_param_to_reduce by @therealnaveenkamal in deepspeedai/DeepSpeed#7660

UlyssesSP: TiledMLP doc - recomputes forward twice by @stas00 in deepspeedai/DeepSpeed#7664

resolved a 0-dim tensor slicing bug from _get_state_without_padding by @therealnaveenkamal in deepspeedai/DeepSpeed#7659

Fix typo in pytorch-profiler.md documentation by @kunheek in deepspeedai/DeepSpeed#7652

README refresh by @sfc-gh-truwase in deepspeedai/DeepSpeed#7668

New Contributors

@kunheek made their first contribution in deepspeedai/DeepSpeed#7652

Full Changelog: https://github.com/deepspeedai/DeepSpeed/compare/v0.18.1...v0.18.2

Commits

e993fea README refresh (#7668)

4691beb Fix typo in pytorch-profiler.md documentation (#7652)

6fe3c7a resolved a 0-dim tensor slicing bug from _get_state_without_padding (#7659)

<a href="https://github.com/deeps


Update torchao requirement from <0.13,>=0.12 to >=0.12,<0.15

Updates the requirements on [torchao](https://github.com/pytorch/ao) to permit the latest version.

Release notes

Sourced from torchao's releases.

v0.14.1

Highlights

We are excited to announce the 0.14.1 release of torchao! This release adds support for MoE training on Backwell GPUs and NVFP4 QAT!

(Prototype) MoE training on Blackwell GPUs

We’ve added a quantized building block for speeding up MoE training on Blackwell GPUs: torchao’s `_scaled_grouped_mm`! It is a differentiable drop-in replacement for `torch._grouped_mm` that dynamically quantizes inputs using the given recipe, performs a scaled grouped GEMM, then returns the results in original precision. This results in significant speedups (see benchmarks below)!

import torch
from torch.nn import functional as F
from torchao.prototype.moe_training import (
    _scaled_grouped_mm as torchao_scaled_grouped_mm
)
from torchao.prototype.moe_training.conversion_utils import MoEScalingType
from torchao.prototype.moe_training.utils import generate_jagged_offs

num_groups, total_M, N, K = 8, 131072, 8192, 5120

A = input actvations, B = expert weights

A = torch.randn(total_M, K, dtype=torch.bfloat16, device="cuda", requires_grad=True)
B = torch.randn(num_groups, N, K, dtype=torch.bfloat16, device="cuda", requires_grad=True)

Token group offsets computed by router in actual MoE layer

offs = generate_jagged_offs(num_groups, total_M, device="cuda")

Forward and backward example

out = torchao_scaled_grouped_mm(
A,
B.transpose(-2, -1),
offs=offs,
scaling_type=MoEScalingType.MXFP8,
)
labels = torch.ones_like(out)
loss = F.mse_loss(out, labels)
loss.backward()

Microbenchmarks (see README for commands to reproduce benchmarks):

Forward + backward pass vs torch._grouped_mm:

~1.4-1.8x faster for Llama4 17bx16e shapes

~1.2-1.4x faster for DeepSeekV3 671b shapes

Full MoE layer forward + backward pass:

~1.4x faster (Llama4 17bx16e shapes, batch_size=8, seq_len=16384)

~1.2x faster (DeepSeekV3 671b shapes, batch_size=8, seq_len=16384).

It’s also already integrated into TorchTitan for E2E training with DeepSeekV3 and Llama4! Just use the command line flag: `--model.converters=”quantize.grouped_mm.mx”, which will convert all `torch._grouped_mm` ops to torchao _scaled_grouped_mm ops under the hood:

... (truncated)

Commits

d94bb19 Update version to 0.14.1 (#3213)

1a578d1 Fix TORCHAO_SKIP_LOADING_SO_FILES behavior (#3189)

937e3a4 Fix SyntaxWarning during installation / import (#3184)

2dedd73 Update compatibility matrix (#3178)

0294124 Fix setuptools version for docs build (<a href="https://redirect.github.com/pytorch/ao/iss


[ops] Update dependabot config

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[cli] Add cli groups & update descriptions

# Description

**Changes**
- Add cli typer groups to organize all the commands since we have quite a few now
- Update / cleanup descriptions to make them more consistent

**After**

**Before**

## Related issues

Fixes # (issue)

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[docs] add analyze documentation and example configs

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Add analyze CLI command

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- Add analyze command to CLI for dataset analysis

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adding k8s as cloud provider for skypilot

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Adding support for k8s for oumi launcher

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Fixes #2067

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update github actions triggers

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- Run GPU tests when integration tests are updated
- Deprecate gcp release action
- Avoid running install tests on all workflows

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Fix too many files open error

# Description
Cap TCPConnector connection limit at 200 to prevent file descriptor
exhaustion when requests_per_minute is set to 500 or 1000. HTTP
connections are reused, so we don't need one connection per concurrent
request. The semaphore still controls concurrency properly.

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Towards LOU-283

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[docs] Add local docker guide

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- [docs] Add local docker guide

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Fix length analyzer column naming and add comprehensive message summary tests

# Description

After the latest upgrade to analyze to use a schema, the summery generation is broken. The summary generation expected column names like text_content_length_analyzer_char_count (5+ parts), but analyzers create columns like text_content_char_count (4 parts), so the parsing never matched and returned empty summaries. We need to change the column names to include the analyzer's name. The change should happen in length_analzyer to generate the expected column names

- Updated length analyzer to use analyzer_id in column names (text_content_length_char_count format)
- Updated all length analyzer tests to use new column naming format
- Added comprehensive test for message level summary structure and statistics
- Verified summary generation works correctly with new column naming format

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Fixes LOU-277

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Remove deprecated `target_col` field mentions

# Description

- This field doesn't do anything, so removed all references to it. We can delete it in a future Oumi version.
- We can also remove lines specifying `dataset_text_field: "text"` as this is the default value in HF TrainingArguments.
- Added a deprecation warning for the field

## Related issues

Towards OPE-1781

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add instructions to deploy Oumi on a k8s cluster

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add documentation for deploying Oumi on a k8s cluster

including a quickstart of launching an Oumi pod and examples for AWS and GKE.

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Fixes #1337

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Update aiofiles requirement from <25,>=24.1.0 to >=24.1.0,<26

Updates the requirements on [aiofiles](https://github.com/Tinche/aiofiles) to permit the latest version.

Release notes

Sourced from aiofiles's releases.

v25.1.0

Switch to uv + add Python v3.14 support.  (#219)

Add ruff formatter and linter. #216

Drop Python 3.8 support. If you require it, use version 24.1.0. #204

New Contributors

@danielsmyers made their first contribution in Tinche/aiofiles#185

@stankudrow made their first contribution in Tinche/aiofiles#192

@waketzheng made their first contribution in Tinche/aiofiles#221

Full Changelog: https://github.com/Tinche/aiofiles/compare/v24.1.0...v25.1.0

Changelog

Sourced from aiofiles's changelog.

25.1.0 (2025-10-09)

Switch to uv + add Python v3.14 support.
(#219)

Add ruff formatter and linter.
#216

Drop Python 3.8 support. If you require it, use version 24.1.0.
#204

24.1.0 (2024-06-24)

Import os.link conditionally to fix importing on android.
#175

Remove spurious items from aiofiles.os.__all__ when running on Windows.

Switch to more modern async idioms: Remove types.coroutine and make AiofilesContextManager an awaitable instead a coroutine.

Add aiofiles.os.path.abspath and aiofiles.os.getcwd.
#174

aiofiles is now tested on Python 3.13 too.
#184

Drop Python 3.7 support. If you require it, use version 23.2.1.

23.2.1 (2023-08-09)

Import os.statvfs conditionally to fix importing on non-UNIX systems.
#171 #172

aiofiles is now also tested on Windows.

23.2.0 (2023-08-09)

aiofiles is now tested on Python 3.12 too.
#166 #168

On Python 3.12, aiofiles.tempfile.NamedTemporaryFile now accepts a delete_on_close argument, just like the stdlib version.

On Python 3.12, aiofiles.tempfile.NamedTemporaryFile no longer exposes a delete attribute, just like the stdlib version.

Added aiofiles.os.statvfs and aiofiles.os.path.ismount.
<a href="https://redirect.git


Bump actions/checkout from 5 to 6 in the all-actions group

Bumps the all-actions group with 1 update: [actions/checkout](https://github.com/actions/checkout).

Updates `actions/checkout` from 5 to 6

Release notes

Sourced from actions/checkout's releases.

v6.0.0

What's Changed

Update README to include Node.js 24 support details and requirements by @salmanmkc in actions/checkout#2248

Persist creds to a separate file by @ericsciple in actions/checkout#2286

v6-beta by @ericsciple in actions/checkout#2298

update readme/changelog for v6 by @ericsciple in actions/checkout#2311

Full Changelog: https://github.com/actions/checkout/compare/v5.0.0...v6.0.0

v6-beta

What's Changed

Updated persist-credentials to store the credentials under $RUNNER_TEMP instead of directly in the local git config.

This requires a minimum Actions Runner version of v2.329.0 to access the persisted credentials for Docker container action scenarios.

v5.0.1

What's Changed

Port v6 cleanup to v5 by @ericsciple in actions/checkout#2301

Full Changelog: https://github.com/actions/checkout/compare/v5...v5.0.1

Changelog

Sourced from actions/checkout's changelog.

Changelog

V6.0.0

Persist creds to a separate file by @ericsciple in actions/checkout#2286

Update README to include Node.js 24 support details and requirements by @salmanmkc in actions/checkout#2248

V5.0.1

Port v6 cleanup to v5 by @ericsciple in actions/checkout#2301

V5.0.0

Update actions checkout to use node 24 by @salmanmkc in actions/checkout#2226

V4.3.1

Port v6 cleanup to v4 by @ericsciple in actions/checkout#2305

V4.3.0

docs: update README.md by @motss in actions/checkout#1971

Add internal repos for checking out multiple repositories by <a href="https://github.


[docker] build arm docker image for mac

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- [docker] build arm docker image for mac

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# Description

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- [nit] avoid using mutable dict as default argument in conversation

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# Description

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- [docs] Add docs for missing inference params and how to serve lora adapters

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Fixes # OPE-1330 & OPE-1583

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