How to persist LangChain conversation memory (save and load)?

garage_greg

I'm creating a conversation like so: llm = ChatOpenAI(temperature=0, openai_api_key=OPENAI_API_KEY, model_name=OPENAI_DEFAULT_MODEL) conversation = ConversationChain(llm=llm, memory=ConversationBufferMemory()) But what I really want is to be able to save and load that ConversationBufferMemory() so that it's persistent between sessions. There doesn't seem to be any obvious tutorials for this but I noticed "Pydantic" so I tried to do this:...

Originally asked by Neil C. Obremski on Stack Exchange (stackoverflow) (CC BY-SA 4.0).

uphilltech

Great question — answering as the UphillTech team:

I just did something similar, hopefully this will be helpful. On a high level: use ConversationBufferMemory as the memory to pass to the Chain initialization llm = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo-0301') original_chain = ConversationChain( llm=llm, verbose=True, memory=ConversationBufferMemory() ) original_chain.run('what do you know about Python in less than 10 words') extract messages from memory in the form of List[langchain.schema.HumanMessage|AIMessage] (not serializable) extracted_messages = original_chain.memory.chat_memory.messages transform the extracted message to serializable native Python objects ingest_to_db = messages_to_dict(extracted_messages) perform db...

Full answer by Shum: https://stackoverflow.stackexchange.com/a/76240942 (CC BY-SA 4.0).

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