feat(python-tutor): Enhance short/long-term memory example with Vertex AI Memory Bank #400
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This commit refactors the auto_save_to_memory_callback and search_memory functions. - In agent.py, the logic for saving sessions to the memory bank is updated to directly use the memory_service from the invocation context, removing the need for manual VertexAiMemoryBankService initialization. - In memory_tools.py, the search_memory tool is simplified to use the tool_context.search_memory helper method, which abstracts away the details of the memory service. These changes align the implementation with the latest ADK documentation, improving code clarity and maintainability.
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Description:
This pull request introduces a series of enhancements to the python-tutor agent, focusing on the use of Vertex AI Memory Bank for both short and long-term memory. The changes also include refactoring the agent's memory management tools to align with Agent Development Kit (ADK) best practices and improving the overall clarity of the documentation.
Key changes include:
auto_save_to_memory_callbackandsearch_memoryfunctions have been updated to use the recommendedmemory_serviceandtool_contexthelpers from the ADK. This simplifies the implementation and improves maintainability.search_memoryfunction.README.mdfile has been refined to provide clearer and more precise instructions for setup and usage.