VertexAiMemoryBankService

So sánh triển khai Python trong src/google/adk/memory/vertex_ai_memory_bank_service.py với BaseMemoryService của Java và hàm khởi tạo Runner chấp nhận một dịch vụ bộ nhớ. Theo dõi cách LlmAgent xử lý bộ nhớ, sau đó kiểm tra các điểm vào được đề cập của công cụ search_memory và auto_save_to_memory_callback. Hoàn thành nghĩa là lập tài liệu về việc các thành phần này đã tích hợp với nhau hay chưa, hoặc Java còn thiếu chức năng nào.

I’m interested in using VertexAiMemoryBankService for long-term memory when working with an agent through ADK. I see that the VertexAiMemoryBankService https://github.com/google/adk-python/blob/632bf8b0bcf18ff4e4505e4e5f4c626510f366a2/src/google/adk/memory/vertex_ai_memory_bank_service.py#L38 is implemented in the Python version of ADK, but it’s not yet available in the Java version.

By analogy with the Python version, I can implement my own Java version of VertexAiMemoryBankService (implements BaseMemoryService). I can also create a custom version of VertexAiRunner based on com.google.adk.runner.Runner#Runner(com.google.adk.agents.BaseAgent, java.lang.String, com.google.adk.artifacts.BaseArtifactService, com.google.adk.sessions.BaseSessionService, com.google.adk.memory.BaseMemoryService).

My question is the following: is it enough to simply implement my own version of VertexAiMemoryBankService and pass it into the Runner constructor, since the Java ADK already has the functionality for working with long-term memory implemented at this point? In other words, does the Java ADK already know how to add and retrieve the necessary information from memory by itself for LlmAgent? Or, apart from implementing my own VertexAiMemoryBankService and passing it to the Runner constructor, would I need to do anything else to make it work? What is the current state of this memory-related functionality as of now?

It seems to me that, in addition to providing the VertexAiMemoryBankService to the agent, I also need to provide the search_memory tool (so that the agent can search the memory by itself) and add a callback for writing to the Memory Bank after each user prompt and LLM response using after_agent_callback=[auto_save_to_memory_callback]? Both, and both the search_memory tool and the auto_save_to_memory_callback should internally use the corresponding methods from VertexAiMemoryBankService, right?