meta: update pydantic requirement from >=2.13.0 to >=2.13.1

[dependabot]

Updates the requirements on pydantic to permit the latest version.

Release notes

Sourced from pydantic's releases.

v2.13.1 2026-04-15

v2.13.1 (2026-04-15)

What's Changed

Fixes

• Fix ValidationInfo.data missing with model_validate_json() by @​davidhewitt in #13079

Full Changelog: pydantic/pydantic@v2.13.0...v2.13.1

Changelog

Sourced from pydantic's changelog.

v2.13.1 (2026-04-15)

GitHub release

What's Changed

Fixes

• Fix ValidationInfo.data missing with model_validate_json() by @​davidhewitt in #13079

v2.13.0 (2026-04-13)

GitHub release

The highlights of the v2.13 release are available in the blog post. Several minor changes (considered non-breaking changes according to our versioning policy) are also included in this release. Make sure to look into them before upgrading.

This release contains the updated pydantic.v1 namespace, matching version 1.10.26 which includes support for Python 3.14.

What's Changed

See the beta releases for all changes sinces 2.12.

New Features

• Allow default factories of private attributes to take validated model data by @​Viicos in #13013

Changes

• Warn when serializing fixed length tuples with too few items by @​arvindsaripalli in #13016

Fixes

• Change type of Any when synthesizing _build_sources for BaseSettings.__init__() signature in the mypy plugin by @​Viicos in #13049
• Fix model equality when using runtime extra configuration by @​Viicos in #13062

Packaging

• Add zizmor for GitHub Actions workflow linting by @​Viicos in #13039
• Update jiter to v0.14.0 to fix a segmentation fault on musl Linux by @​Viicos in #13064

New Contributors

• @​arvindsaripalli made their first contribution in #13016

v2.13.0b3 (2026-03-31)

GitHub release

... (truncated)

Commits

• d45d8be Prepare release 2.13.1
• 54aca60 Fix ValidationInfo.data missing with model_validate_json()
• See full diff in compare view

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Smart Link Intelligence

Target	Kind	State	Confidence	Semantics
#2	PR	closed	85.0%	related

Integrity Fingerprint: d117807feb1abbef2b8a

[github-actions]

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[github-actions]

✅ Automated approval for security update.

[github-actions]

⚠️ Title is too vague for Autobot

Your PR title "meta: update pydantic requirement from >=2.13.0 to >=2.13.1" does not contain any keywords that trigger automation.

Please include at least one keyword from these categories in your title:

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[github-actions]

Relationship Graph

graph TD
    PR13["PR #13<br/>meta: update pydantic requirement from >=2.13.0 to >=2.13.1"]
    style PR13 fill:#9f7,stroke:#333,stroke-width:2px
    PR2["PR #2<br/>meta: update vulture requirement from >=2.10 to >=2.16"]
    style PR2 fill:#c9f,stroke:#333,stroke-width:2px
    PR13 -.->|Related| PR2

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[github-actions]

Autobot — Changes Analysis

PR #13 · dependabot/pip/pydantic-gte-2.13.1 → main · 2026-04-16

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Autobot Summary

What Changed

This pull request updates the pydantic dependency in pyproject.toml from version 2.13.0 to 2.13.1, a patch-level upgrade. The change is isolated to development tooling and adheres to semantic versioning, suggesting backward compatibility and no functional runtime or schema implications.

Release Relevance

• Ensures development tooling is aligned with the latest bug fixes and improvements.
• Promotes best practices in dependency and version management for sustained maintainability.

Risks And Testing

• Regression Risks: Unexpected issues from the updated pydantic version, though unlikely due to the nature of patch-level changes.
• Dependency Compatibility: Minor possibility of version conflicts with other libraries or configurations.
• Reproducibility: Risks related to version mismatch impacting builds or tests.
• Full Test Suite Validation: Critical to ensure no adverse effects are introduced.
• Workflow Assurance: Requires confirmation that development workflows (e.g., testing, linting) remain unaffected.

Classification Signals

• Dependency Update (Development-only): Demonstrated by the isolated change restricted to pyproject.toml.
• Patch-Level Upgrade: Strong indicator of backward compatibility with low risk of breaking changes.
• No Runtime Impact: Explicitly non-impactful to runtime environments or APIs.
• Scoped Change: Single-file change with concise and predictable effects.

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🏷️ AI Label Classification

Applied labels: dependencies

Labels were determined by AI analysis of the code diff — not the PR title or description.