PlanetScale 聊天记忆

由于 PlanetScale 通过 REST API 工作，您可以将其与Vercel Edge、Cloudflare Workers 和其他无服务器环境一起使用。

为了在聊天会话之间实现长期持久性，您可以用 PlanetScale 数据库 实例替换默认的内存中 chatHistory，它支持 BufferMemory 等聊天记忆类。

设置

您需要在项目中安装@planetscale/database

提示

请参见本节以获取有关安装集成包的一般说明.

npm

npm install @langchain/openai @planetscale/database @langchain/community

Yarn

yarn add @langchain/openai @planetscale/database @langchain/community

pnpm

pnpm add @langchain/openai @planetscale/database @langchain/community

您还需要一个 PlanetScale 帐户和一个要连接的数据库。有关如何创建 HTTP 客户端的说明，请参见PlanetScale 文档.

用法

存储在 PlanetScale 数据库中的每个聊天历史会话必须具有一个唯一的 ID。config 参数直接传递给 @planetscale/database 的 new Client() 构造函数，并接受所有相同的参数。

import { BufferMemory } from "langchain/memory";
import { PlanetScaleChatMessageHistory } from "@langchain/community/stores/message/planetscale";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";

const memory = new BufferMemory({
  chatHistory: new PlanetScaleChatMessageHistory({
    tableName: "stored_message",
    sessionId: "lc-example",
    config: {
      url: "ADD_YOURS_HERE", // Override with your own database instance's URL
    },
  }),
});

const model = new ChatOpenAI();
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 参考

• BufferMemory 来自 langchain/memory
• PlanetScaleChatMessageHistory 来自 @langchain/community/stores/message/planetscale
• ChatOpenAI 来自 @langchain/openai
• ConversationChain 来自 langchain/chains

高级用法

您还可以直接传递之前创建的 @planetscale/database 客户端实例

import { BufferMemory } from "langchain/memory";
import { PlanetScaleChatMessageHistory } from "@langchain/community/stores/message/planetscale";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";
import { Client } from "@planetscale/database";

// Create your own Planetscale database client
const client = new Client({
  url: "ADD_YOURS_HERE", // Override with your own database instance's URL
});

const memory = new BufferMemory({
  chatHistory: new PlanetScaleChatMessageHistory({
    tableName: "stored_message",
    sessionId: "lc-example",
    client, // You can reuse your existing database client
  }),
});

const model = new ChatOpenAI();
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 参考

• BufferMemory 来自 langchain/memory
• PlanetScaleChatMessageHistory 来自 @langchain/community/stores/message/planetscale
• ChatOpenAI 来自 @langchain/openai
• ConversationChain 来自 langchain/chains