给聊天机器人装“短期记忆“：Flask版实现指南

📌 实现思路图解

核心实现代码

def debug(self, app_id: UUID):
    # 1.提取从接口中获取的输入
    req = CompletionReq()
    if not req.validate():
        return validate_error_json(req.errors)

    # 2.创建prompt与memory
    prompt = ChatPromptTemplate.from_messages([
        ("system", "你是一个强大的聊天机器人，能根据用户的提问回复对应的问题"),
        MessagesPlaceholder("history"),
        ("human", "{query}"),
    ])
    memory = ConversationBufferWindowMemory(
        k=3,
        input_key="query",
        output_key="output",
        return_messages=True,
        chat_memory=FileChatMessageHistory("./storage/memory/chat_history.txt"),
    )

    # 3.构建llm应用
    llm = ChatOpenAI(model="gpt-3.5-turbo-16k")

    # 4.创建链应用
    chain = RunnablePassthrough.assign(
        history=RunnableLambda(memory.load_memory_variables) | itemgetter("history")
    ) | prompt | llm | StrOutputParser()

    # 5.调用链生成内容
    chain_input = {"query": req.query.data}
    content = chain.invoke(chain_input)

    # 6.存储链状态
    memory.save_context(chain_input, {"output": content})

    return success_json({"content": content})