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基于 Redis 的聊天记忆

为了在多个聊天会话中实现更长期的持久化存储，您可以将 BufferMemory 等聊天记忆类默认使用的内存中 chatHistory 替换为 Redis 实例。

环境准备​

您需要在项目中安装 node-redis：

:::提示 请参阅安装集成包的一般说明部分。 :::

npm install @langchain/openai @langchain/community @langchain/core redis

同时，您还需要一个可以连接的 Redis 实例。关于如何在本地运行 Redis 服务器，请参阅 Redis 官方网站 上的说明。

使用方法​

存储在 Redis 中的每个聊天历史会话都必须具有唯一的 ID。您还可以提供可选的 sessionTTL 参数，用于设置会话在指定秒数后自动过期。 config 参数将直接传递给 node-redis 的 createClient 方法，支持其所有相同的参数。

import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "@langchain/redis";
import { ChatOpenAI } from "@langchain/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
  }),
});

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

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

const res1 = await chain.invoke({ 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.invoke({ input: "What did I just say my name was?" });
console.log({ res2 });

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

API Reference:

高级用法​

您也可以直接传入一个先前创建的 node-redis 客户端实例：

import { Redis } from "ioredis";
import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "@langchain/community/stores/message/ioredis";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";

const client = new Redis("redis://localhost:6379");

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

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

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

const res1 = await chain.invoke({ 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.invoke({ input: "What did I just say my name was?" });
console.log({ res2 });

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

API Reference:

Redis Sentinel 支持​

您可以使用 ioredis 启用基于 Redis Sentinel 的缓存。

这需要在项目中安装 ioredis。

npm install ioredis
import { Redis } from "ioredis";
import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "@langchain/community/stores/message/ioredis";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";

// Uses ioredis to facilitate Sentinel Connections see their docs for details on setting up more complex Sentinels: https://github.com/redis/ioredis#sentinel
const client = new Redis({
  sentinels: [
    { host: "localhost", port: 26379 },
    { host: "localhost", port: 26380 },
  ],
  name: "mymaster",
});

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

const model = new ChatOpenAI({ model: "gpt-4o-mini", temperature: 0.5 });

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

const res1 = await chain.invoke({ 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.invoke({ input: "What did I just say my name was?" });
console.log({ res2 });

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

API Reference:

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