question, it truthfully says it does not know.    Relevant pieces of previous conversation:    input: My favorite food is pizza    output: that's good to know    (You do not need to use these pieces of information if not relevant)    Current conversation:    Human: Whats my favorite food    AI:    > Finished chain.    ' You said your favorite food is pizza.'# The memories from the conversation are automatically stored,# since this query best matches the introduction chat above,# the agent is able to 'remember' the user's name.conversation_with_summary.predict(input="What's my name?")    > Entering new ConversationChain chain...    Prompt after formatting:    The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.    Relevant pieces of previous conversation:    input: Hi, my name is Perry, what's up?    response:  Hi Perry, I'm doing well. How about you?    (You do not need to use these pieces of information if not relevant)    Current conversation:    Human: What's my name?    AI:    > Finished chain.    ' Your name is Perry.'PreviousConversation Token BufferNextMemory in LLMChainInitialize your vector storeCreate your VectorStoreRetrieverMemoryUsing in a chainCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
VectorStoreRetrieverMemory stores memories in a vector store and queries the top-K most "salient" docs every time it is called.
VectorStoreRetrieverMemory stores memories in a vector store and queries the top-K most "salient" docs every time it is called. ->: question, it truthfully says it does not know.    Relevant pieces of previous conversation:    input: My favorite food is pizza    output: that's good to know    (You do not need to use these pieces of information if not relevant)    Current conversation:    Human: Whats my favorite food    AI:    > Finished chain.    ' You said your favorite food is pizza.'# The memories from the conversation are automatically stored,# since this query best matches the introduction chat above,# the agent is able to 'remember' the user's name.conversation_with_summary.predict(input="What's my name?")    > Entering new ConversationChain chain...    Prompt after formatting:    The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.    Relevant pieces of previous conversation:    input: Hi, my name is Perry, what's up?    response:  Hi Perry, I'm doing well. How about you?    (You do not need to use these pieces of information if not relevant)    Current conversation:    Human: What's my name?    AI:    > Finished chain.    ' Your name is Perry.'PreviousConversation Token BufferNextMemory in LLMChainInitialize your vector storeCreate your VectorStoreRetrieverMemoryUsing in a chainCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.