凸透镜聊天记忆

对于跨聊天会话的长期持久性，您可以将支持聊天记忆类的默认内存中 chatHistory（如 BufferMemory）替换为 凸透镜.

设置

创建项目

获取一个可运行的 凸透镜 项目设置，例如使用

npm create convex@latest

添加数据库访问器

在 convex/langchain/db.ts 中添加查询和变异帮助器

convex/langchain/db.ts

export * from "@langchain/community/utils/convex";

配置您的架构

设置您的架构（用于索引）

convex/schema.ts

import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  messages: defineTable({
    sessionId: v.string(),
    message: v.object({
      type: v.string(),
      data: v.object({
        content: v.string(),
        role: v.optional(v.string()),
        name: v.optional(v.string()),
        additional_kwargs: v.optional(v.any()),
      }),
    }),
  }).index("bySessionId", ["sessionId"]),
});

用法

存储在 Convex 中的每个聊天历史会话都必须具有唯一的会话 ID。

提示

查看 此部分以获取有关安装集成包的一般说明.

npm

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

Yarn

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

pnpm

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

convex/myActions.ts

"use node";

import { v } from "convex/values";
import { BufferMemory } from "langchain/memory";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";
import { ConvexChatMessageHistory } from "@langchain/community/stores/message/convex";
import { action } from "./_generated/server.js";

export const ask = action({
  args: { sessionId: v.string() },
  handler: async (ctx, args) => {
    // pass in a sessionId string
    const { sessionId } = args;

    const memory = new BufferMemory({
      chatHistory: new ConvexChatMessageHistory({ sessionId, ctx }),
    });

    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 });

    /*
      {
        res2: {
          text: "You said your name was Jim."
        }
      }
    */

    // See the chat history in the Convex database
    console.log(await memory.chatHistory.getMessages());

    // clear chat history
    await memory.chatHistory.clear();
  },
});

API 参考

• BufferMemory 来自 langchain/memory
• ChatOpenAI 来自 @langchain/openai
• ConversationChain 来自 langchain/chains
• ConvexChatMessageHistory 来自 @langchain/community/stores/message/convex