基于Redis的聊天存储

如果需要在聊天会话之间进行长期持久化，可以将默认的内存chatHistory替换为一个Redis实例来支持聊天存储类，如BufferMemory。

设置

您需要在项目中安装node-redis。

npm

npm install redis

Yarn

yarn add redis

pnpm

pnpm add redis

您还需要一个Redis实例来连接。请参阅Redis官方网站上运行本地服务器的说明。

用法

Redis中存储的每个聊天历史记录会话都必须具有唯一的ID。你可以提供一个可选的sessionTTL参数来使会话在一定时间后过期。 传递给createClient方法的config参数直接传递给node-redis，并使用所有相同的参数。

import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "langchain/stores/message/redis";
import { ChatOpenAI } from "langchain/chat_models/openai";
import { ConversationChain } from "langchain/chains";

const memory = new BufferMemory({
  chatHistory: new RedisChatMessageHistory({
    sessionId: new Date().toISOString(), // Or some other unique identifier for the conversation
    sessionTTL: 300, // 5 minutes, omit this parameter to make sessions never expire
    config: {
      url: "redis://localhost:6379", // Default value, override with your own instance's URL
    },
  }),
});

const model = new ChatOpenAI({
  modelName: "gpt-3.5-turbo",
  temperature: 0,
});

const chain = new ConversationChain({ llm: model, memory });

const res1 = await chain.call({ input: "Hi! I'm Jim." });
console.log({ res1 });
/*
{
  res1: {
    text: "Hello Jim! It's nice to meet you. My name is AI. How may I assist you today?"
  }
}
*/

const res2 = await chain.call({ input: "What did I just say my name was?" });
console.log({ res2 });

/*
{
  res1: {
    text: "You said your name was Jim."
  }
}
*/

高级用法

您也可以直接传递先前创建的node-redis客户端实例:

import { createClient } from "redis";
import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "langchain/stores/message/redis";
import { ChatOpenAI } from "langchain/chat_models/openai";
import { ConversationChain } from "langchain/chains";

const client = createClient({
  url: "redis://localhost:6379",
});

const memory = new BufferMemory({
  chatHistory: new RedisChatMessageHistory({
    sessionId: new Date().toISOString(),
    sessionTTL: 300,
    client,
  }),
});

const model = new ChatOpenAI({
  modelName: "gpt-3.5-turbo",
  temperature: 0,
});

const chain = new ConversationChain({ llm: model, memory });

const res1 = await chain.call({ input: "Hi! I'm Jim." });
console.log({ res1 });
/*
{
  res1: {
    text: "Hello Jim! It's nice to meet you. My name is AI. How may I assist you today?"
  }
}
*/

const res2 = await chain.call({ input: "What did I just say my name was?" });
console.log({ res2 });

/*
{
  res1: {
    text: "You said your name was Jim."
  }
}
*/