Conversation
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@rickyloynd-microsoft, minor comments that could be addressed in a different PR.
What do you think? |
I like it. Probably in a new PR. |
Replace agent with agent teachable_agent as recommended.
Created a PR #329 @rickyloynd-microsoft @gagb |
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@qingyun-wu We need to run OpenAI test before merging this PR. Please confirm that you understand when this is required or let me know if you have questions. |
You mean issue. |
Yes created an issue #329 @rickyloynd-microsoft @gagb |
I've got the latest changes ready that @sonichi and @qingyun-wu requested. Can I push those now? Those changes are to test on just one version of python, and to change agent to teachable_agent in places. |
You are right. We should run OpenAI test when there are new tests added. Is this understanding correct? |
Incorrect. Not all tests require openai, and sometimes openai test needs to be run even when no new test is added. |
Why are these changes needed?
TeachableAgentallows users to teach their assistant facts, preferences, and tasks unrelated to code generation.Conversational assistants based on LLMs can remember the current chat with the user, and can even demonstrate in-context learning of things that the user teaches the assistant during the chat. But these memories and learnings are lost once the chat is over, or when a single chat grows too long. In subsequent chats, the user is forced to repeat any necessary instructions over and over.
TeachableAgentaddresses these limitations by persisting user teachings across chat boundaries in long-term memory (a vector database). Memory is saved to disk at the end of each chat, then loaded from disk at the start of the next. Instead of copying all of memory into the context window, which would eat up valuable space, individual memories (called memos) are retrieved into context as needed. This allows the user to teach frequently used facts, preferences and skills to the agent just once, and have the agent remember them in later chats.Related issue number
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