conversation:        Human: Hi, what's up?    AI:        > Finished chain.    " Hi there! I'm doing great. I'm learning about the latest advances in artificial intelligence. What about you?"conversation_with_summary.predict(input="Just working on writing some documentation!")            > 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.        Current conversation:    Human: Hi, what's up?    AI:  Hi there! I'm doing great. I'm spending some time learning about the latest developments in AI technology. How about you?    Human: Just working on writing some documentation!    AI:        > Finished chain.    ' That sounds like a great use of your time. Do you have experience with writing documentation?'# We can see here that there is a summary of the conversation and then some previous interactionsconversation_with_summary.predict(input="For LangChain! Have you heard of it?")            > 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.        Current conversation:    System:     The human asked the AI what it was up to and the AI responded that it was learning about the latest developments in AI technology.    Human: Just working on writing some documentation!    AI:  That sounds like a great use of your time. Do you have experience with writing documentation?    Human: For LangChain! Have you heard of it?    AI:        > Finished chain.    " No, I haven't heard of LangChain. Can you tell me more about it?"# We can see here that the summary and the buffer are
ConversationSummaryBufferMemory combines the two ideas. It keeps a buffer of recent interactions in memory, but rather than just completely flushing old interactions it compiles them into a summary and uses both.
ConversationSummaryBufferMemory combines the two ideas. It keeps a buffer of recent interactions in memory, but rather than just completely flushing old interactions it compiles them into a summary and uses both. ->: conversation:        Human: Hi, what's up?    AI:        > Finished chain.    " Hi there! I'm doing great. I'm learning about the latest advances in artificial intelligence. What about you?"conversation_with_summary.predict(input="Just working on writing some documentation!")            > 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.        Current conversation:    Human: Hi, what's up?    AI:  Hi there! I'm doing great. I'm spending some time learning about the latest developments in AI technology. How about you?    Human: Just working on writing some documentation!    AI:        > Finished chain.    ' That sounds like a great use of your time. Do you have experience with writing documentation?'# We can see here that there is a summary of the conversation and then some previous interactionsconversation_with_summary.predict(input="For LangChain! Have you heard of it?")            > 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.        Current conversation:    System:     The human asked the AI what it was up to and the AI responded that it was learning about the latest developments in AI technology.    Human: Just working on writing some documentation!    AI:  That sounds like a great use of your time. Do you have experience with writing documentation?    Human: For LangChain! Have you heard of it?    AI:        > Finished chain.    " No, I haven't heard of LangChain. Can you tell me more about it?"# We can see here that the summary and the buffer are