Postgres 聊天记忆

如果你需要在聊天会话之间实现更长期的数据持久化，可以将默认的内存型 chatHistory 替换为 Postgres 数据库。

安装配置

首先安装 node-postgres 包：

:::提示 请参阅安装集成包的一般说明部分。 :::

npm

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

Yarn

yarn add @langchain/openai @langchain/community @langchain/core pg

pnpm

pnpm add @langchain/openai @langchain/community @langchain/core pg

使用方法

每次聊天历史记录会话都存储在 Postgres 数据库中，并且需要一个会话 ID。

Postgres 的连接是通过连接池（pool）进行管理的。你可以通过 pool 参数传入一个已有的连接池实例，或者通过 poolConfig 参数传入连接池的配置。更多信息请参考 pg-node 的连接池文档。如果同时提供了连接池实例和配置，将以连接池实例为准。

import pg from "pg";

import { PostgresChatMessageHistory } from "@langchain/community/stores/message/postgres";
import { ChatOpenAI } from "@langchain/openai";
import { RunnableWithMessageHistory } from "@langchain/core/runnables";
import {
  ChatPromptTemplate,
  MessagesPlaceholder,
} from "@langchain/core/prompts";
import { StringOutputParser } from "@langchain/core/output_parsers";

const poolConfig = {
  host: "127.0.0.1",
  port: 5432,
  user: "myuser",
  password: "ChangeMe",
  database: "api",
};

const pool = new pg.Pool(poolConfig);

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

const prompt = ChatPromptTemplate.fromMessages([
  [
    "system",
    "You are a helpful assistant. Answer all questions to the best of your ability.",
  ],
  new MessagesPlaceholder("chat_history"),
  ["human", "{input}"],
]);

const chain = prompt.pipe(model).pipe(new StringOutputParser());

const chainWithHistory = new RunnableWithMessageHistory({
  runnable: chain,
  inputMessagesKey: "input",
  historyMessagesKey: "chat_history",
  getMessageHistory: async (sessionId) => {
    const chatHistory = new PostgresChatMessageHistory({
      sessionId,
      pool,
      // Can also pass `poolConfig` to initialize the pool internally,
      // but easier to call `.end()` at the end later.
    });
    return chatHistory;
  },
});

const res1 = await chainWithHistory.invoke(
  {
    input: "Hi! I'm MJDeligan.",
  },
  { configurable: { sessionId: "langchain-test-session" } }
);
console.log(res1);
/*
  "Hello MJDeligan! It's nice to meet you. My name is AI. How may I assist you today?"
*/

const res2 = await chainWithHistory.invoke(
  { input: "What did I just say my name was?" },
  { configurable: { sessionId: "langchain-test-session" } }
);
console.log(res2);

/*
  "You said your name was MJDeligan."
*/

// If you provided a pool config you should close the created pool when you are done
await pool.end();

API Reference:

• PostgresChatMessageHistory from @langchain/community/stores/message/postgres
• ChatOpenAI from @langchain/openai
• RunnableWithMessageHistory from @langchain/core/runnables
• ChatPromptTemplate from @langchain/core/prompts
• MessagesPlaceholder from @langchain/core/prompts
• StringOutputParser from @langchain/core/output_parsers