fix: resolve Memory Bank Service agent ID extraction issue #2940

[ishanrajsingh]

Bug Fix: Memory Bank Service Agent ID Extraction (#2940)

Problem

Users were unable to find the agent ID when setting up Memory Bank Service. The api_resource.name attribute returns the full Google Cloud resource path, but Memory Bank Service expects only the agent engine ID.

Root Cause

• Add extract_agent_engine_id utility function with validation
• Create comprehensive test suite (14 tests, all passing)
• Update VertexAiMemoryBankService with enhanced documentation
• Add warning for common full-path vs ID mistake

The core fix: Use agent_engine.api_resource.name.split('/')[-1] to extract agent ID from full resource path for Memory Bank Service initialization.

Resolves #2940: Users unable to find agent ID for Memory Bank Service

[gemini-code-assist]

Summary of Changes

Hello @ishanrajsingh, 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 resolves a critical issue where users encountered difficulties setting up the Memory Bank Service due to an incorrect understanding of the required agent ID format. The changes provide a robust solution by introducing dedicated utility functions for agent ID extraction, significantly improving the clarity of documentation, and implementing proactive warnings and more informative error messages to guide users toward successful service configuration.

Highlights

• Agent ID Extraction Utility: Introduced a new utility function, extract_agent_engine_id, to correctly parse and extract the agent engine ID from the full Google Cloud resource path, addressing a common user issue with Memory Bank Service setup.
• Enhanced Documentation and Warnings: Updated the VertexAiMemoryBankService class with detailed documentation and examples demonstrating the correct agent ID extraction. A warning is now logged if an agent_engine_id containing '/' is passed, guiding users to the correct format.
• Improved Error Handling: Enhanced error messages within VertexAiMemoryBankService to provide clearer guidance when agent_engine_id is incorrectly formatted or missing, suggesting the use of agent_engine.api_resource.name.split('/')[-1].
• New Example and Test Suite: Added a new example (memory_bank_complete_setup.py) to illustrate the complete and correct setup of Memory Bank Service, along with a comprehensive test suite (14 tests) for the new resource utility functions to ensure robustness.

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[gemini-code-assist]

Code Review

This pull request addresses an issue with agent ID extraction for the Memory Bank Service by introducing utility functions and improving documentation and error handling. The core logic fix is sound and well-documented. However, I've identified a few issues, including a critical bug that breaks the package's public API by redefining __all__, and another critical bug in an example script's path manipulation that will cause it to fail. I've also noted some areas for improvement regarding import conventions, exception handling, and test coverage. Please review the detailed comments.

[ishanrajsingh]

@DeanChensj I have worked on the issue, kindly review my pr#2941