= ConversationChain(    llm=llm,    # We set a very low max_token_limit for the purposes of testing.    memory=ConversationTokenBufferMemory(llm=OpenAI(), max_token_limit=60),    verbose=True,)conversation_with_summary.predict(input="Hi, what's up?")            > 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:        > Finished chain.    " Hi there! I'm doing great, just enjoying the day. How 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, just enjoying the day. How about you?    Human: Just working on writing some documentation!    AI:        > Finished chain.    ' Sounds like a productive day! What kind of documentation are you writing?'conversation_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:    Human: Hi, what's up?    AI:  Hi there! I'm doing great, just enjoying the day. How about you?    Human: Just working on writing some documentation!
ConversationTokenBufferMemory keeps a buffer of recent interactions in memory, and uses token length rather than number of interactions to determine when to flush interactions.
ConversationTokenBufferMemory keeps a buffer of recent interactions in memory, and uses token length rather than number of interactions to determine when to flush interactions. ->: = ConversationChain(    llm=llm,    # We set a very low max_token_limit for the purposes of testing.    memory=ConversationTokenBufferMemory(llm=OpenAI(), max_token_limit=60),    verbose=True,)conversation_with_summary.predict(input="Hi, what's up?")            > 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:        > Finished chain.    " Hi there! I'm doing great, just enjoying the day. How 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, just enjoying the day. How about you?    Human: Just working on writing some documentation!    AI:        > Finished chain.    ' Sounds like a productive day! What kind of documentation are you writing?'conversation_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:    Human: Hi, what's up?    AI:  Hi there! I'm doing great, just enjoying the day. How about you?    Human: Just working on writing some documentation!