146 lines
4.0 KiB
JavaScript
146 lines
4.0 KiB
JavaScript
// server.js
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const express = require("express");
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const multer = require("multer");
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const cors = require("cors");
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const fs = require("fs");
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const path = require("path");
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const OpenAI = require("openai");
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const bodyParser = require("body-parser");
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const app = express();
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const port = 30003;
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const mysql = require("mysql2/promise");
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// 初始化数据库连接池
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const pool = mysql.createPool({
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host: "localhost",
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user: "root",
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password: "maibu520",
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database: "fastbee",
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waitForConnections: true,
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connectionLimit: 10,
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});
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// 允许大文件请求体
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app.use(bodyParser.json({ limit: "500mb" }));
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app.use(bodyParser.urlencoded({ limit: "500mb", extended: true }));
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// Multer 上传目录
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const upload = multer({
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dest: "uploads/",
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limits: { fileSize: 500 * 1024 * 1024 }, // 500MB
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});
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// Node <20 兼容 File
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if (typeof File === "undefined") {
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globalThis.File = require("node:buffer").File;
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}
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// 启用 CORS
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app.use(cors());
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app.use(express.json({ limit: "200mb" })); // 支持大 JSON
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app.use(express.urlencoded({ extended: true })); // 支持 form-data 字段
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// 初始化混元客户端
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const client = new OpenAI({
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apiKey: "sk-LVfG90qgdhf9kKQUucqBSLioxamDu7gBeW9boXqKOxIDJt7H",
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baseURL: "https://api.hunyuan.cloud.tencent.com/v1",
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timeout: 120000,
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});
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app.get("/test-db", async (req, res) => {
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try {
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await pool.query(
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"INSERT INTO ai_chat_messages (session_id, role, content) VALUES (?, 'user', ?)",
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["sess1", "hello"]
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);
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res.send("OK");
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} catch (err) {
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console.error(err);
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res.send("FAIL");
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}
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});
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// ====================== API ======================
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app.post("/analyze", upload.single("file"), async (req, res) => {
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try {
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res.setHeader("Content-Type", "text/plain; charset=utf-8");
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res.setHeader("Transfer-Encoding", "chunked");
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res.setHeader("Cache-Control", "no-cache");
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res.setHeader("Connection", "keep-alive");
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const { userPrompt, imageBase64, userId, sessionId } = req.body;
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// 如果前端没有传 sessionId，生成一个
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const sessId = sessionId || Date.now().toString();
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// 1️⃣ 保存用户提问到数据库
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await pool.query(
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"INSERT INTO ai_chat_messages (session_id, role, content) VALUES (?, 'user', ?)",
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[sessId, userPrompt || ""]
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);
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// 2️⃣ 调用 HunYuan Vision
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const completion = await client.chat.completions.create({
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model: "hunyuan-vision",
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stream: true,
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do_scene: true,
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do_behavior: true,
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llm_model: "hunyuan-turbos-latest",
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messages: [
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{
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role: "system",
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content: "你是一个图像分析专家，擅长描述和解释图片内容。",
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},
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{
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role: "user",
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content: [
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{ type: "text", text: userPrompt || "请描述图片内容。" },
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imageBase64
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? {
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type: "image_url",
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image_url: {
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url: imageBase64.startsWith("data:")
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? imageBase64
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: `data:image/png;base64,${imageBase64}`,
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},
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}
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: null,
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].filter(Boolean),
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},
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],
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});
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// 3️⃣ 处理流式返回，并同时拼接内容
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let assistantContent = "";
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for await (const chunk of completion) {
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const delta = chunk.choices[0]?.delta?.content || "";
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if (delta) {
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assistantContent += delta;
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res.write(`data: ${JSON.stringify({ content: delta })}\n\n`);
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}
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}
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res.write("data: [DONE]\n\n");
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res.end();
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// 4️⃣ 保存模型回复到数据库
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await pool.query(
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"INSERT INTO chat_messages (session_id, role, content) VALUES (?, 'assistant', ?)",
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[sessId, assistantContent]
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);
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} catch (err) {
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console.error("❌ 调用失败:", err.response?.data || err.message);
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res.status(500).json({ code: 1, error: err.response?.data || err.message });
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}
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});
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// 静态文件服务
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app.use("/uploads", express.static("uploads"));
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// 启动服务
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app.listen(port, () => {
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console.log(`✅ 服务器运行：http://localhost:${port}`);
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});
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