使用缓冲内存与聊天模型翻译的中文结果

本示例介绍如何将聊天特定的内存类与聊天模型配合使用。翻译的中文结果 需要注意的关键点是，设置 returnMessages: true 会使内存返回聊天消息列表而不是字符串。翻译的中文结果

import { ConversationChain } from "langchain/chains";
import { ChatOpenAI } from "langchain/chat_models/openai";
import {
  ChatPromptTemplate,
  HumanMessagePromptTemplate,
  SystemMessagePromptTemplate,
  MessagesPlaceholder,
} from "langchain/prompts";
import { BufferMemory } from "langchain/memory";

export const run = async () => {
  const chat = new ChatOpenAI({ temperature: 0 });

  const chatPrompt = ChatPromptTemplate.fromPromptMessages([
    SystemMessagePromptTemplate.fromTemplate(
      "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."
    ),
    new MessagesPlaceholder("history"),
    HumanMessagePromptTemplate.fromTemplate("{input}"),
  ]);

  const chain = new ConversationChain({
    memory: new BufferMemory({ returnMessages: true, memoryKey: "history" }),
    prompt: chatPrompt,
    llm: chat,
  });

  const response = await chain.call({
    input: "hi! whats up?",
  });

  console.log(response);
};