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chore(deps): bump the runtime-dependencies group with 6 updates - #437

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Bumps the runtime-dependencies group with 6 updates:

Package From To
anthropic 0.120.2 0.121.0
pydantic-settings 2.14.2 2.15.0
asyncpraw 8.0.2 8.0.3
sentence-transformers 5.6.1 5.7.0
fastmcp 3.4.6 3.4.7
hypothesis 6.165.2 6.165.3

Updates anthropic from 0.120.2 to 0.121.0

Release notes

Sourced from anthropic's releases.

v0.121.0

0.121.0 (2026-08-07)

Full Changelog: v0.120.2...v0.121.0

Features

  • api: add mid-conversation-tool-changes-2026-07-01 beta (c7d1531)
  • api: add support for session budgets, advisor tool, pinned inference location and skills auto-loading from GitHub (193bae0)

Chores

  • api: remove retired Claude Opus 4.1 models (5352a33)
  • docs: small updates to descriptions (b8d4176)
  • docs: updates to a few documentation strings (3a5dd69)
  • ensure all dependencies have major version constraints (#274) (d52999b)
Changelog

Sourced from anthropic's changelog.

0.121.0 (2026-08-07)

Full Changelog: v0.120.2...v0.121.0

Features

  • api: add mid-conversation-tool-changes-2026-07-01 beta (c7d1531)
  • api: add support for session budgets, advisor tool, pinned inference location and skills auto-loading from GitHub (193bae0)

Chores

  • api: remove retired Claude Opus 4.1 models (5352a33)
  • docs: small updates to descriptions (b8d4176)
  • docs: updates to a few documentation strings (3a5dd69)
  • ensure all dependencies have major version constraints (#274) (d52999b)
Commits
  • 204fa8e release: 0.121.0
  • 284a537 feat(api): add support for session budgets, advisor tool, pinned inference lo...
  • de568f2 chore(docs): updates to a few documentation strings
  • e271587 chore(api): remove retired Claude Opus 4.1 models
  • 3d4115e chore: ensure all dependencies have major version constraints (#274)
  • 5840eaa chore(docs): small updates to descriptions
  • b4cfb5e feat(api): add mid-conversation-tool-changes-2026-07-01 beta
  • See full diff in compare view

Updates pydantic-settings from 2.14.2 to 2.15.0

Release notes

Sourced from pydantic-settings's releases.

v2.15.0

Highlights

Behavior changes

  • case_sensitive now applies to init kwargs and config-file sources (#900). InitSettingsSource and the JSON/TOML/YAML config sources previously ignored case_sensitive. Since it defaults to False, case-insensitive matching is now the default for these sources — e.g. Settings(TeSt=...) now populates a test field where it previously did not. Nested keys are still matched case-sensitively.
  • Fields with unresolved forward references now emit a warning (#901). Settings sources can silently fail to resolve such fields; they now raise IncompleteFieldDefinitionWarning telling you to call model_rebuild(). If you have filterwarnings = error configured, this may surface as a new failure.
  • Non-JSON env values for strict fields now raise ValidationError (#926) instead of a less specific error.

New features

  • Show environment variable names in CLI help via cli_show_env_vars=True (#860), so generated --help output doubles as configuration documentation.
  • PYDANTIC_SETTINGS_DEBUG for debugging settings resolution (#906, #913). Set it to a truthy value with DEBUG logging enabled to see each source's contribution in priority order, which source won for each value, and which env_file/secret files were probed, loaded, or skipped — the long-standing "why isn't my .env being picked up?" question.
  • toml_table_header for regular TOML files (#882, #886, #887), letting you root settings at a nested table in any TOML file, not just pyproject.toml.
  • Traversable support for JSON/TOML/YAML file sources (#902), so you can load config packaged inside a distribution — including files inside a zip or wheel — via importlib.resources.files(...) without casting to Path.
  • GCP: project_id can come from an earlier settings source (#878), rather than only from the constructor or GOOGLE_CLOUD_PROJECT.

Bug fixes

  • Fix env vars not loading on Windows with case_sensitive=True (#894). Windows upper-cases os.environ keys, so fields raised Field required instead of picking up their values.
  • Read secret files as UTF-8 instead of the platform locale encoding (#917). On Windows code pages such as cp1252 this silently corrupted non-ASCII secrets.
  • Fix AliasPath on nested model fields not JSON-decoding env values (#898).
  • Fix case-insensitive matching for optional nested models (#905).
  • Fix dotenv extras being wrongly claimed by a complex field sharing a name prefix (#912) — e.g. dbx_token being swallowed by a db: dict field.
  • Fix nested_model_default_partial_update=True corrupting discriminated unions (#876).
  • Fix Secret subclasses crashing when loaded from the environment (#920).
  • Fix enum names not parsing through nested annotations such as Optional[Annotated[MyEnum, ...]] with env_parse_enums=True (#910).
  • An empty yaml_config_section now falls back to defaults instead of raising AttributeError: 'NoneType' object has no attribute 'keys' (#914).
  • NestedSecretsSettingsSource no longer follows symlinks pointing outside secrets_dir (#889).
  • GCP: skip the list_secrets call when case_sensitive=True (#862), lowering the required IAM permissions to just roles/secretmanager.secretAccessor.
  • AWS: types-boto3[secretsmanager] is no longer required at runtime (#880).

Documentation

  • Document JSON parsing of complex env values, plus a comma-separated-values recipe (#919).
  • Recommend an async settings loading pattern (#908).
  • Clarify behavior when an unprefixed value is present in a dotenv file (#895).
  • Clarify environment variable helper descriptions (#867) and fix assorted typos (#904).

What's Changed

... (truncated)

Commits
  • f725ca1 Prepare release 2.15.0 (#930)
  • 28f35c2 Bump the python-packages group with 4 updates (#929)
  • 9056db0 test: move function-local imports to the top of test modules (#927)
  • f077e3a fix: raise ValidationError for non-JSON env values on strict fields (#926)
  • ae25d70 fix: treat Secret subclasses as non-complex fields (#716) (#920)
  • 798dcea Bump the python-packages group with 4 updates (#924)
  • a190041 Bump the github-actions group with 4 updates (#925)
  • 5d93332 Bump the python-packages group with 4 updates (#921)
  • d2fdeda fix: read secret files as UTF-8 instead of the locale encoding (#917)
  • 2256a4e Bump the python-packages group with 3 updates (#915)
  • Additional commits viewable in compare view

Updates asyncpraw from 8.0.2 to 8.0.3

Release notes

Sourced from asyncpraw's releases.

v8.0.3

Fixed

  • :meth:.Reddit.post rewinds seekable file objects before retrying a request after a rate limit response. Previously the retry read from the exhausted stream, which could upload empty or truncated file contents.
Changelog

Sourced from asyncpraw's changelog.

############ Change Log ############

asyncpraw follows semantic versioning <https://semver.org/>_.

Unreleased

8.0.3 (2026/08/12)

Fixed

  • :meth:.Reddit.post rewinds seekable file objects before retrying a request after a rate limit response. Previously the retry read from the exhausted stream, which could upload empty or truncated file contents.

8.0.2 (2026/06/24)

Changed

  • Reword property docstrings and clarify in the 8.0.0 change log that arguments deprecated for positional use in v7 are now keyword-only. Maintenance and documentation only; no functional changes.

8.0.1 (2026/06/15)

Fixed

  • Declare __all__ in asyncpraw and asyncpraw.models so that, now that Async PRAW ships a py.typed marker, type checkers recognize documented imports such as from asyncpraw import Reddit and from asyncpraw.models import Redditor as public re-exports instead of reporting them as private.

8.0.0 (2026/06/14)

Added

  • :class:.Announcement and :class:.AnnouncementHelper, exposed as :attr:.Reddit.announcements, for listing, hiding, and marking the currently authenticated user's announcements as read. Provides :meth:.Announcement.hide,

... (truncated)

Commits
  • c1c7ecd Bump to v8.0.3
  • 618023c Merge pull request #412 from praw-dev/bump-shared-workflows-v1.11.0
  • 1d2d8b7 Bump praw-dev/.github reusable workflows to v1.11.0
  • 6e4eb0c Merge pull request #411 from praw-dev/dependabot/github_actions/github-action...
  • c59e59a Bump github/codeql-action/upload-sarif in the github-actions group
  • 2f66b67 Merge pull request #410 from praw-dev/collapse-github-actions-group
  • 68fe38e Collapse the github-actions Dependabot group
  • 8a19b02 Merge pull request #404 from praw-dev/dependabot/github_actions/github-action...
  • 19485f3 Merge pull request #409 from praw-dev/dependabot/uv/python-8bd81e8b75
  • f38c0c4 Bump pre-commit from 4.6.1 to 4.6.2 in the python group
  • Additional commits viewable in compare view

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 fastmcp from 3.4.6 to 3.4.7

Release notes

Sourced from fastmcp's releases.

v3.4.7: Know Your Audience

FastMCP 3.4.7 restores CIMD private_key_jwt authentication for OAuthProxy deployments at a bare origin. Client assertions are now validated against the exact token endpoint advertised in authorization server metadata, eliminating the doubled-slash audience mismatch.

What's Changed

Security 🔒

Docs 📚

Full Changelog: PrefectHQ/fastmcp@v3.4.6...v3.4.7

Changelog

Sourced from fastmcp's changelog.

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

v4.0.0b3: Fast Fourward

FastMCP 4 beta 3 moves the v4 line toward general availability with Prefect Horizon authentication, CallArgument and Depends bindings for tools and background tasks, and a round of OAuth, proxy, OpenAPI, and Python 3.14 compatibility hardening.

Enhancements ✨

Security 🔒

Fixes 🐞

Docs 📚

New Contributors

Full Changelog: v4.0.0b2...v4.0.0b3

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.

... (truncated)

Commits

Updates hypothesis from 6.165.2 to 6.165.3

Commits
  • 0b818d6 Bump hypothesis version to 6.165.3 and update changelog
  • 8388d0d Merge pull request #4846 from reachsridhard/fix/bytestring-provider-negative-...
  • 219b2c1 Fix RELEASE.rst: use plain RST backticks instead of markdown links
  • 1b028df Add RELEASE.rst for bytestring provider float fix
  • 5520d9e fix: draw 65 bits in BytestringProvider.draw_float to support negative floats
  • d139e32 Merge pull request #4844 from msimacek/msimacek/graalpy
  • 850d0da Update PyO3 to 0.29.2
  • See full diff in compare view

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@dependabot
chore(deps): bump the runtime-dependencies group with 6 updates
e986fe2 
Bumps the runtime-dependencies group with 6 updates:

| Package | From | To |
| --- | --- | --- |
| [anthropic](https://github.com/anthropics/anthropic-sdk-python) | `0.120.2` | `0.121.0` |
| [pydantic-settings](https://github.com/pydantic/pydantic-settings) | `2.14.2` | `2.15.0` |
| [asyncpraw](https://github.com/praw-dev/asyncpraw) | `8.0.2` | `8.0.3` |
| [sentence-transformers](https://github.com/huggingface/sentence-transformers) | `5.6.1` | `5.7.0` |
| [fastmcp](https://github.com/PrefectHQ/fastmcp) | `3.4.6` | `3.4.7` |
| [hypothesis](https://github.com/HypothesisWorks/hypothesis) | `6.165.2` | `6.165.3` |


Updates `anthropic` from 0.120.2 to 0.121.0
- [Release notes](https://github.com/anthropics/anthropic-sdk-python/releases)
- [Changelog](https://github.com/anthropics/anthropic-sdk-python/blob/main/CHANGELOG.md)
- [Commits](anthropics/anthropic-sdk-python@v0.120.2...v0.121.0)

Updates `pydantic-settings` from 2.14.2 to 2.15.0
- [Release notes](https://github.com/pydantic/pydantic-settings/releases)
- [Commits](pydantic/pydantic-settings@v2.14.2...v2.15.0)

Updates `asyncpraw` from 8.0.2 to 8.0.3
- [Release notes](https://github.com/praw-dev/asyncpraw/releases)
- [Changelog](https://github.com/praw-dev/asyncpraw/blob/main/CHANGES.rst)
- [Commits](praw-dev/asyncpraw@v8.0.2...v8.0.3)

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 `fastmcp` from 3.4.6 to 3.4.7
- [Release notes](https://github.com/PrefectHQ/fastmcp/releases)
- [Changelog](https://github.com/PrefectHQ/fastmcp/blob/main/docs/changelog.mdx)
- [Commits](PrefectHQ/fastmcp@v3.4.6...v3.4.7)

Updates `hypothesis` from 6.165.2 to 6.165.3
- [Release notes](https://github.com/HypothesisWorks/hypothesis/releases)
- [Commits](HypothesisWorks/hypothesis@v6.165.2...v6.165.3)

---
updated-dependencies:
- dependency-name: anthropic
  dependency-version: 0.121.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: runtime-dependencies
- dependency-name: pydantic-settings
  dependency-version: 2.15.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: runtime-dependencies
- dependency-name: asyncpraw
  dependency-version: 8.0.3
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: runtime-dependencies
- dependency-name: sentence-transformers
  dependency-version: 5.7.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: runtime-dependencies
- dependency-name: fastmcp
  dependency-version: 3.4.7
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: runtime-dependencies
- dependency-name: hypothesis
  dependency-version: 6.165.3
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: runtime-dependencies
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python:uv Pull requests that update python:uv code labels Aug 15, 2026
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Looks like these dependencies are updatable in another way, so this is no longer needed.

@dependabot dependabot Bot closed this Aug 22, 2026
@dependabot
dependabot Bot deleted the dependabot/uv/runtime-dependencies-022f507838 branch August 22, 2026 18:46
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