@langgraph-js/memory/src/server/index.ts

A memory management system based on PostgreSQL + pgvector for LangGraph workflows

import { MemoryDataBase } from '../MemoryDatabase.js';
import { MemoryDatabaseServer } from './server.js';
import { Pool } from 'pg';
import { PostgresVectorStore } from '../vector-store/pg.js';
import { LangChainEmbedder } from '../embedder/langchain.js';
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
// import { serveStatic } from 'hono/serve-static';
// import { Context, Env } from 'hono';
// import { Data } from 'hono/dist/types/context';
// import { readFile } from 'fs/promises';
// import { join } from 'path';

// 从环境变量读取配置
const PORT = parseInt(process.env.PORT || '3553');
const DATABASE_URL = process.env.MEMORY_DATABASE_URL;
const ORG_ID = process.env.MEMORY_ORG_ID || 'default-org';
const MODEL_NAME = process.env.MEMORY_MODEL_NAME || 'gpt-4o-mini';
const EMBEDDER_MODEL_NAME = process.env.MEMORY_EMBEDDER_MODEL_NAME || 'text-embedding-3-small';

// 初始化依赖
async function initializeDependencies() {
    if (!DATABASE_URL) {
        throw new Error('MEMORY_DATABASE_URL environment variable is required');
    }

    const pool = new Pool({
        connectionString: DATABASE_URL,
    });

    // 这里需要根据实际的 LLM 和 Embedder 实现进行初始化
    // 由于这些依赖较为复杂，这里提供一个示例结构
    const llm = new ChatOpenAI({ modelName: MODEL_NAME }); // 需要根据实际实现初始化
    const embedder = new LangChainEmbedder(new OpenAIEmbeddings({ modelName: EMBEDDER_MODEL_NAME })); // 需要根据实际实现初始化

    // 初始化向量存储
    const vectorStore = new PostgresVectorStore({ pool, tableName: 'memory_vectors', dimension: 1536 });

    // 初始化记忆数据库
    const memoryDb = new MemoryDataBase(ORG_ID, llm, embedder, vectorStore);

    // 初始化数据库
    await memoryDb.setup();

    return memoryDb;
}

// 启动服务器
export async function startServer() {
    try {
        console.log('Initializing Memory Database Server...');

        const memoryDb = await initializeDependencies();

        const server = new MemoryDatabaseServer(memoryDb);
        const app = server.getApp();

        // 添加静态文件服务
        // app.use(
        //     '/public/*',
        //     serveStatic({
        //         root: './',
        //         getContent: function (path: string, c: Context<Env, any, {}>): Promise<Data | Response | null> {
        //             return readFile(join(process.cwd(), path), 'utf-8');
        //         },
        //     }),
        // );

        console.log(`Starting server on port ${PORT}...`);

        console.log(`✅ Memory Database Server is running on http://localhost:${PORT}`);
        console.log(`📚 API Documentation available at /health`);
        console.log(`🌐 Static files served from /public http://localhost:${PORT}/dashboard`);
        return app;
        // serve({
        //     fetch: app.fetch,
        //     port: PORT,
        // });
    } catch (error) {
        console.error('❌ Failed to start server:', error);
        process.exit(1);
    }
}