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build(deps): bump the python-runtime group with 5 updates - #233

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Aug 13, 2026
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build(deps): bump the python-runtime group with 5 updates#233
jagoff merged 3 commits into
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Bumps the python-runtime group with 5 updates:

Package From To
fastmcp 3.4.5 3.4.6
sentence-transformers 5.6.1 5.7.0
hypothesis 6.165.0 6.165.2
diff-cover 10.4.1 10.5.0
ruff 0.16.1 0.16.2

Updates fastmcp from 3.4.5 to 3.4.6

Release notes

Sourced from fastmcp's releases.

v3.4.6: Trust, but Proxy

FastMCP 3.4.6 backports trusted-proxy support for SSRF-protected OAuth metadata and JWKS fetches. Deployments can now route these requests through a mandated corporate proxy while preserving custom CA certificates; FastMCP refuses the fetch when no proxy is configured instead of risking an unprotected direct request.

What's Changed

Fixes 🐞

Docs 📚

Full Changelog: PrefectHQ/fastmcp@v3.4.5...v3.4.6

Changelog

Sourced from fastmcp's changelog.

title: "Changelog" icon: "list-check" rss: true tag: NEW

v3.4.7: Know Your Audience

FastMCP 3.4.7 fixes CIMD private_key_jwt authentication on bare-origin OAuth proxy deployments by validating client assertions against the exact token endpoint advertised in OAuth metadata.

Security 🔒

Docs 📚

Full Changelog: v3.4.6...v3.4.7

v3.4.6: Trust, but Proxy

FastMCP 3.4.6 backports trusted-proxy support for SSRF-protected OAuth metadata and JWKS fetches. Deployments can now route these requests through a mandated corporate proxy while preserving custom CA certificates; FastMCP refuses the fetch when no proxy is configured instead of risking an unprotected direct request.

Fixes 🐞

Docs 📚

Full Changelog: v3.4.5...v3.4.6

v4.0.0b1: Fourgone Conclusion

FastMCP 4 makes stateful MCP applications work on the sessionless 2026-07-28 protocol while one deployment continues serving handshake-era clients. Tools can ask follow-up questions across requests, preserve authenticated user state, and move long-running work into background tasks without sticky sessions. Protocol extensions and enterprise identity become first-class surfaces, and most FastMCP 3 servers upgrade unchanged even though MCP Python SDK v2 rewrote the engine underneath them. Server-initiated sampling and roots are removed from the server API; the upgrade guide covers their replacements.

New Features 🎉

  • Migrate to MCP Python SDK v2 by @​jlowin in #4437
  • Teach fastmcp.Client the modern protocol: mode negotiation, MRTR driver, response cache by @​jlowin in #4450
  • Forward-port Hugging Face auth provider by @​jlowin in #4475
  • Add server-side identity assertion (SEP-990 ID-JAG) by @​jlowin in #4483

... (truncated)

Commits

Updates sentence-transformers from 5.6.1 to 5.7.0

Release notes

Sourced from sentence-transformers's releases.

v5.7.0 - GradCache Overhaul, torch.compile Inference, and a Large Batch of Correctness Fixes

This minor version is a correctness and performance-focused release. It rebuilds all gradient-cached losses on one shared engine, fixing several silently wrong gradients and adding token-based mini-batching for up to 3.9x faster cached-loss training. It also makes model.compile() actually speed up inference, and brings a long list of fixes across embedding quantization, evaluators, hard-negative mining, community detection, and multimodal inputs.

Two changes are marked breaking (🚨): int8/uint8 embedding quantization now clips out-of-range values and floors bucket values, so int8 outputs are no longer bit-identical with earlier versions, and AdaptiveLayerLoss/Matryoshka2dLoss now weight prior-layer losses uniformly by default. There's also a forward-looking deprecation: loading models whose modules import classes from outside sentence_transformers will require trust_remote_code=True from v6.0.

Install this version with

# Training + Inference
pip install sentence-transformers[train]==5.7.0
Inference only, use one of:
pip install sentence-transformers==5.7.0
pip install sentence-transformers[onnx-gpu]==5.7.0
pip install sentence-transformers[onnx]==5.7.0
pip install sentence-transformers[openvino]==5.7.0
Multimodal dependencies (optional):
pip install sentence-transformers[image]==5.7.0
pip install sentence-transformers[audio]==5.7.0
pip install sentence-transformers[video]==5.7.0
Or combine as needed:
pip install sentence-transformers[train,onnx,image]==5.7.0

GradCache overhaul: correct gradients and token-based mini-batching (#3862)

The gradient-cached losses (CachedMultipleNegativesRankingLoss, CachedGISTEmbedLoss, CachedSpladeLoss, the Cross Encoder CachedMultipleNegativesRankingLoss, and MegaBatchMarginLoss) train with large batch sizes at constant memory by embedding in mini-batches and replaying them with cached gradients. Each loss carried its own diverged copy of that machinery. They are now all rebuilt on one shared engine, which fixed several bugs that silently corrupted gradients:

  • Cross Encoder CachedMultipleNegativesRankingLoss on GPU: the backward pass used different dropout masks than the forward pass, silently biasing gradients for every reranker trained with dropout active on CUDA or MPS. CPU training was unaffected.
  • Running two forward passes before a backward pass (e.g. in custom training loops) made CachedGISTEmbedLoss and the Cross Encoder loss backpropagate the wrong batch's gradients, because the cache was stored on the loss module. The cache now travels with each forward pass's backward hook (the .cache and .random_states loss attributes are gone as a result).
  • Pooling(include_prompt=False) (e.g. Instructor models) mutated the attention mask in place, so the backward re-embedding of every cached loss ran with a different mask than the forward pass.
  • MatryoshkaLoss(GISTEmbedLoss(...)): the guide model overwrote the cached embeddings, so only the largest Matryoshka dimension was actually trained.

Along the way, this also fixed an autocast dtype crash in the backward pass and the trainer retaining autograd graphs between logging steps when tracking loss components.

MegaBatchMarginLoss's default mini-batched version is rebuilt on the engine as well. It crashed outright on recent releases, and underneath that, its historical implementation only applied the last mini-batch's gradients. It now trains on the full batch (results will differ, for the better), works with MatryoshkaLoss, evaluates under torch.no_grad, and raises for a third input column instead of silently ignoring it.

The headline feature is mini_batch_num_tokens, available on CachedMultipleNegativesRankingLoss, CachedMultipleNegativesSymmetricRankingLoss, CachedGISTEmbedLoss, CachedSpladeLoss, and MegaBatchMarginLoss. Instead of a fixed number of sequences per mini-batch, mini-batches are greedily packed by total non-padding token count, giving near-constant work per mini-batch on variable-length data:

from sentence_transformers import SentenceTransformer
from sentence_transformers.sentence_transformer.losses import CachedMultipleNegativesRankingLoss
model = SentenceTransformer("microsoft/mpnet-base")
loss = CachedMultipleNegativesRankingLoss(model, mini_batch_num_tokens=16384)

On the PR's Natural Questions benchmark, cached-loss training with flash attention and a tuned token budget dropped from 715 to 182 seconds (3.9x) versus the previous release, with unchanged quality. The engine also trims trailing padding from each mini-batch, which alone is worth about 26% throughput on the default padded path. The updated training efficiency documentation recommends the smallest token budget that saturates your GPU. mini_batch_size keeps working everywhere as before.

... (truncated)

Commits
  • b2a9529 [fix] Name the lone suggested parameter in the mine_hard_negatives missing-ne...
  • 00e696c Release v5.7.0
  • b69081a [fix] Treat a 1-dimensional query embedding as a single query in semantic_sea...
  • c9c4250 Keep queries aligned in semantic_search_seismic when a query matches nothing ...
  • 6d331a5 [fix] Support mixed sparse/dense inputs in euclidean and manhattan similari...
  • 68c8cda [fix] Reject num_negatives larger than the range_min/range_max window in mine...
  • cfb6d43 [trainer] Fix eval DataLoader worker leak with dataloader_persistent_worker...
  • f6d3a40 Expand the community window on ties with the threshold (#3900)
  • 0b3fcbd Correct the corpus_precision values documented for semantic_search_faiss ...
  • 62724e7 Drop FAISS padding placeholders from semantic_search_faiss results (#3887)
  • Additional commits viewable in compare view

Updates hypothesis from 6.165.0 to 6.165.2

Commits
  • deb4d49 Bump hypothesis version to 6.165.2 and update changelog
  • a9eff28 Merge pull request #4842 from HypothesisWorks/claude/invert-everything
  • c555e58 Cover the remaining _invert error paths in tests
  • f9882a3 Apply review feedback: type ValueHole.value as object, polish docs and tests
  • 8dca9e1 Restructure timezones() so its draws can be re-encoded
  • 7e309df Invert dictionaries, unique lists with tuple_suffixes, and fixed_dictionaries
  • 77ca292 Implement _invert for most remaining strategy combinators
  • 5b20755 Bump hypothesis version to 6.165.1 and update changelog
  • b4f2e92 Merge pull request #4806 from HypothesisWorks/claude/widening-shrinks
  • 9431e20 Apply suggestions from code review
  • Additional commits viewable in compare view

Updates diff-cover from 10.4.1 to 10.5.0

Release notes

Sourced from diff-cover's releases.

Version 10.5.0

What's Changed

New Contributors

Full Changelog: Bachmann1234/diff_cover@v10.4.2...v10.5.0

Version 10.4.2

What's Changed

New Contributors

Dependencies

Full Changelog: Bachmann1234/diff_cover@v10.4.1...v10.4.2

Changelog

Sourced from diff-cover's changelog.

8/08/2026 v10.5.0

8/06/2026 v10.4.2

7/23/2026 v10.4.1

7/21/2026 v10.4.0

  • Add --branch-coverage flag to diff-cover to treat partially covered branches in Cobertura XML reports as uncovered PR 608 Thanks @​mofr

05/30/2026 v10.3.0

  • Add --show-covered flag to highlight covered diff lines in HTML report PR 600 Thanks @​duxiaocheng

  • Update readme with cli flags PR 601 Thanks me

05/23/2026 v10.2.1

01/08/2026 v10.2.0

12/30/2025 v10.1.0

  • Add support for floating-point total percentage in reports PR 565 thanks @​tilaven

12/09/2025 v10.0.0

  • Remove python 3.9 support
  • Add python 3.14 support
  • Normalize exlude/include in pyproject.toml to support string or list

11/10/2025 v9.7.2

09/25/2025 v9.7.1

... (truncated)

Commits
  • e34eec3 Version 10.5.0
  • 5fc9e82 Support PHPUnit clover reports (silently reported as zero coverage) (#617)
  • f6a43b7 Version 10.4.2
  • 3fdbf40 fix(plugins): accept reports/options in diff_cover_report_quality hookspec (#...
  • 4c44508 fix(config): honor format option from config file (#612)
  • b490adc Bump actions/setup-python from 6 to 7 (#614)
  • 19da277 Bump ruff from 0.15.20 to 0.16.0 (#615)
  • 8f80569 Bump github/codeql-action from 4 to 4.37.3 (#616)
  • See full diff in compare view

Updates ruff from 0.16.1 to 0.16.2

Release notes

Sourced from ruff's releases.

0.16.2

Release Notes

Released on 2026-08-06.

Bug fixes

  • [flake8-pyi] Avoid false positives on singledispatch functions (PYI041) (#27335)

Server

  • Register formatting capabilities dynamically to exclude TOML files (#27332)

Contributors

Install ruff 0.16.2

Install prebuilt binaries via shell script

curl --proto '=https' --tlsv1.2 -LsSf https://releases.astral.sh/github/ruff/releases/download/0.16.2/ruff-installer.sh | sh

Install prebuilt binaries via powershell script

powershell -ExecutionPolicy Bypass -c "irm https://releases.astral.sh/github/ruff/releases/download/0.16.2/ruff-installer.ps1 | iex"

Download ruff 0.16.2

File Platform Checksum
ruff-aarch64-apple-darwin.tar.gz Apple Silicon macOS checksum
ruff-x86_64-apple-darwin.tar.gz Intel macOS checksum
ruff-aarch64-pc-windows-msvc.zip ARM64 Windows checksum
ruff-i686-pc-windows-msvc.zip x86 Windows checksum
ruff-x86_64-pc-windows-msvc.zip x64 Windows checksum
ruff-aarch64-unknown-linux-gnu.tar.gz ARM64 Linux checksum
ruff-i686-unknown-linux-gnu.tar.gz x86 Linux checksum
ruff-powerpc64-unknown-linux-gnu.tar.gz PPC64 Linux checksum
ruff-powerpc64le-unknown-linux-gnu.tar.gz PPC64LE Linux checksum
ruff-riscv64gc-unknown-linux-gnu.tar.gz RISCV Linux checksum
ruff-s390x-unknown-linux-gnu.tar.gz S390x Linux checksum

... (truncated)

Changelog

Sourced from ruff's changelog.

0.16.2

Released on 2026-08-06.

Bug fixes

  • [flake8-pyi] Avoid false positives on singledispatch functions (PYI041) (#27335)

Server

  • Register formatting capabilities dynamically to exclude TOML files (#27332)

Contributors

Commits
  • 5b48a04 Bump 0.16.2 (#27555)
  • 1b9e5fc Update Swatinem/rust-cache action to v2.9.2 (#27568)
  • c4e86fc [ty] Add helper extension methods for half-range and equality constraints (#2...
  • 17a00de [ty] Reuse primer commands in memory reports (#27553)
  • 6ea296b [ty] Normalize type labels in structured docstrings (#26923)
  • 2fc445f [ty] Diagnose invalid getattr calls (#27502)
  • 22c7823 [ty] Enable (but downrank) auto-import completion suggestions from stub-only ...
  • 05160d5 [ty] Diagnose invalid descriptor __get__ calls (#27400)
  • baea3d0 [ty] Expose strict analysis options in the playground (#27543)
  • c88946e [ty] Bump ecosystem-analyzer for strict project settings (#27542)
  • Additional commits viewable in compare view

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@dependabot
build(deps): bump the python-runtime group with 5 updates
e5436ee 
Bumps the python-runtime group with 5 updates:

| Package | From | To |
| --- | --- | --- |
| [fastmcp](https://github.com/PrefectHQ/fastmcp) | `3.4.5` | `3.4.6` |
| [sentence-transformers](https://github.com/huggingface/sentence-transformers) | `5.6.1` | `5.7.0` |
| [hypothesis](https://github.com/HypothesisWorks/hypothesis) | `6.165.0` | `6.165.2` |
| [diff-cover](https://github.com/Bachmann1234/diff-cover) | `10.4.1` | `10.5.0` |
| [ruff](https://github.com/astral-sh/ruff) | `0.16.1` | `0.16.2` |


Updates `fastmcp` from 3.4.5 to 3.4.6
- [Release notes](https://github.com/PrefectHQ/fastmcp/releases)
- [Changelog](https://github.com/PrefectHQ/fastmcp/blob/main/docs/changelog.mdx)
- [Commits](PrefectHQ/fastmcp@v3.4.5...v3.4.6)

Updates `sentence-transformers` from 5.6.1 to 5.7.0
- [Release notes](https://github.com/huggingface/sentence-transformers/releases)
- [Commits](huggingface/sentence-transformers@v5.6.1...v5.7.0)

Updates `hypothesis` from 6.165.0 to 6.165.2
- [Release notes](https://github.com/HypothesisWorks/hypothesis/releases)
- [Commits](HypothesisWorks/hypothesis@v6.165.0...v6.165.2)

Updates `diff-cover` from 10.4.1 to 10.5.0
- [Release notes](https://github.com/Bachmann1234/diff-cover/releases)
- [Changelog](https://github.com/Bachmann1234/diff_cover/blob/main/CHANGELOG)
- [Commits](Bachmann1234/diff_cover@v10.4.1...v10.5.0)

Updates `ruff` from 0.16.1 to 0.16.2
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](astral-sh/ruff@0.16.1...0.16.2)

---
updated-dependencies:
- dependency-name: fastmcp
  dependency-version: 3.4.6
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: python-runtime
- dependency-name: sentence-transformers
  dependency-version: 5.7.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: python-runtime
- dependency-name: hypothesis
  dependency-version: 6.165.2
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: python-runtime
- dependency-name: diff-cover
  dependency-version: 10.5.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: python-runtime
- dependency-name: ruff
  dependency-version: 0.16.2
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: python-runtime
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python:uv Pull requests that update python:uv code labels Aug 12, 2026
@jagoff
jagoff merged commit 21cacde into master Aug 13, 2026
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@jagoff
jagoff deleted the dependabot/uv/python-runtime-f13fd4a0a2 branch August 13, 2026 23:20
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