feat: Implement a vertex based task store for the 1.0 branch

[gaborfeher]

For #751

[gemini-code-assist]

Summary of Changes

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This pull request integrates the system with Google Cloud's Vertex AI Agent Engine by introducing a new task storage implementation. It provides the necessary components to save, retrieve, and update tasks directly within Vertex AI, enhancing the platform's capabilities for managing AI-driven workflows. The changes include core logic for data conversion and a robust testing suite to ensure reliability.

Highlights

• New Vertex AI Task Store: Implemented a VertexTaskStore to enable persistence and management of tasks using the Google Cloud Vertex AI Agent Engine.
• Type Conversion Utilities: Introduced vertex_task_converter.py to facilitate seamless conversion between internal SDK task types and Vertex AI's specific data structures.
• Dependency Management: Added google-cloud-aiplatform as a new optional dependency under the vertex extra, and updated the all extra to include it.
• Comprehensive Testing: Included new test files and a dedicated shell script to ensure the correct functionality and integration of the Vertex AI task store and its conversion logic.

Changelog

• pyproject.toml
  • Added google-cloud-aiplatform as a vertex optional dependency.
  • Updated the all optional dependency to include vertex.
  • Adjusted Python version resolution markers.
• src/a2a/contrib/tasks/vertex_task_converter.py
  • Added a new module for converting between SDK Task and Artifact types and Vertex AI A2aTask and TaskArtifact types.
• src/a2a/contrib/tasks/vertex_task_store.py
  • Added a new VertexTaskStore class that implements the TaskStore interface using the Vertex AI Agent Engine.
  • Provided methods for saving, retrieving, and updating tasks, including handling state, metadata, and artifact changes.
• tck/sut_agent_with_vertex_task_store.py
  • Added a new test agent script to demonstrate serving with the VertexTaskStore, requiring Vertex AI environment variables.
• tests/contrib/tasks/fake_vertex_client.py
  • Added a mock implementation of the Vertex AI client for unit testing the VertexTaskStore without actual cloud calls.
• tests/contrib/tasks/run_vertex_tests.sh
  • Added a shell script to execute Vertex AI related tests, checking for necessary environment variables.
• tests/contrib/tasks/test_vertex_task_converter.py
  • Added comprehensive unit tests for the vertex_task_converter module, covering state, part, artifact, and task conversions.
• tests/contrib/tasks/test_vertex_task_store.py
  • Added unit and integration tests for the VertexTaskStore, including saving, retrieving, updating tasks, and handling metadata and artifacts.
• uv.lock
  • Updated the lock file to reflect new dependencies and adjusted Python version constraints.

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[gemini-code-assist]

Code Review

This pull request introduces a new TaskStore implementation using Google Cloud Vertex AI, along with the necessary data converters and tests. The implementation is well-structured and includes comprehensive tests for both fake and real backends. My feedback includes suggestions for improving code readability and maintainability, such as refactoring a complex method to use list comprehensions, using f-strings for path construction, and improving test setup practices. I've also noted a few minor points regarding docstrings and exception handling, and added a style guide reference for import placement.

_{Note: Security Review did not run due to the size of the PR.}