feat: Reflect Pydantic Field metadata (description and required) in function declarations

[t-miyak]

Summary

Implements support for propagating Pydantic Field metadata (descriptions and required fields) to function declaration schemas, enabling LLMs to receive accurate parameter information when using Pydantic models as function tool arguments.

[gemini-code-assist]

Summary of Changes

Hello @t-miyak, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the function declaration generation process by integrating Pydantic Field metadata. Specifically, it ensures that field descriptions and their required status are accurately reflected in the generated schemas. This improvement is crucial for Large Language Models (LLMs) to receive precise and complete parameter information when utilizing Pydantic models as function tool arguments, leading to more robust and intelligent tool interactions.

Highlights

• Pydantic Field Description Propagation: The system now correctly extracts and applies descriptions from Pydantic Field metadata to the generated function declaration schemas, providing richer context for parameters.
• Pydantic Field Required Status Reflection: The required status of Pydantic fields, determined by Field metadata, is now accurately reflected in the function declaration schemas, ensuring LLMs understand which parameters are mandatory.
• Enhanced Testing for Pydantic Metadata: A new, comprehensive test case has been added to validate the correct propagation of description and required attributes for nested Pydantic models, including those using Optional types and Field annotations.

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[adk-bot]

Response from ADK Triaging Agent

Hello @t-miyak, thank you for creating this PR!

To help reviewers evaluate your contribution, could you please address the following points from our contribution guidelines:

• Associated Issue: For new features, please create an issue that describes the feature and associate it with this PR.
• Testing Plan: Please add a testing plan section to your PR description to detail how you've tested these changes.

This information will help us to review your PR more efficiently. Thanks!

[gemini-code-assist]

Code Review

This pull request adds a valuable feature to reflect Pydantic Field metadata, such as descriptions and required status, in the generated function declaration schemas. The implementation correctly extracts this information, and the new unit test is comprehensive, covering various scenarios with nested models and different field types. I have one suggestion to slightly refactor the code for improved efficiency and clarity. Overall, the changes are well-implemented and tested.

[gemini-code-assist]

For better performance and code clarity, you can determine the required fields within the main loop that processes each field (lines 291-305), rather than iterating over model_fields a second time here. You could initialize schema.required = [] before the loop, and then append field_name to it inside the loop when field_info.is_required() is true.

[t-miyak]

addressed by 7709595...ad8a0e4

[ryanaiagent]

Hi @t-miyak , Thank you for your contribution!
To complete the review, could you also add a brief manual E2E test plan to confirm the LLM correctly interprets and uses this new metadata in a live scenario?