如何快速开发一款AI小程序？基于微信云开发的实战指南

// app.js
App({
  onLaunch() {
    if (!wx.cloud) {
      console.error('请使用 2.2.3 或以上的基础库以使用云能力')
    } else {
      wx.cloud.init({
        env: 'your-env-id' // 这里填写你在微信云开发创建的环境ID
      })
    }
  }
})

// cloudfunctions/imageRecognition/index.js
const cloud = require('wx-server-sdk')
const tencentcloud = require("tencentcloud-sdk-nodejs");

cloud.init()

// 实例化腾讯云的图像识别API
const CVM = tencentcloud.cvm.v20170312.Client;
const clientConfig = {
  credential: {
    secretId: "YOUR_SECRET_ID",
    secretKey: "YOUR_SECRET_KEY",
  },
  region: "ap-shanghai",
  profile: {
    httpProfile: {
      endpoint: "cvm.tencentcloudapi.com",
    },
  },
};
const client = new CVM(clientConfig);

exports.main = async (event, context) => {
  const { fileID } = event;
  const res = await cloud.downloadFile({ fileID });
  const buffer = res.fileContent;
  
  // 调用图像识别接口
  const params = {
    "Image": buffer.toString('base64')
  };
  return client.ImageRecognition(params).then(
    (data) => {
      return { success: true, data };
    },
    (err) => {
      console.error("error", err);
      return { success: false, error: err };
    }
  );
}

<!-- pages/index/index.wxml -->
<view class="container">
  <button bindtap="chooseImage">选择图片</button>
  <image src="{{imagePath}}" wx:if="{{imagePath}}" style="width: 100%;"/>
  <button bindtap="recognizeImage" wx:if="{{imagePath}}">识别图片</button>
  <text wx:if="{{result}}">识别结果：{{result}}</text>
</view>

<button type="primary" bindtap="doUpload" style="margin-top: 150rpx;">上传图片</button>

// pages/index/index.js
Page({
  data: {
    imagePath: '',
    result: ''
  },
  
  chooseImage() {
    wx.chooseImage({
      count: 1,
      sourceType: ['album', 'camera'],
      success: res => {
        this.setData({
          imagePath: res.tempFilePaths[0]
        })
      }
    })
  },

  recognizeImage() {
    const filePath = this.data.imagePath;
    
    // 上传图片到云存储
    wx.cloud.uploadFile({
      cloudPath: `images/${Date.now()}-${Math.floor(Math.random(0, 1) * 1000)}.png`,
      filePath: filePath,
      success: res => {
        const fileID = res.fileID;
        
        // 调用云函数进行图像识别
        wx.cloud.callFunction({
          name: 'imageRecognition',
          data: { fileID },
          success: res => {
            if (res.result.success) {
              this.setData({ result: res.result.data });
            } else {
              wx.showToast({ title: '识别失败', icon: 'none' });
            }
          },
          fail: err => {
            console.error("调用云函数失败", err);
            wx.showToast({ title: '识别失败', icon: 'none' });
          }
        })
      },
      fail: err => {
        console.error("上传图片失败", err);
        wx.showToast({ title: '上传失败', icon: 'none' });
      }
    });
  }
})

// pages/history/history.js
Page({
  data: {
    history: []
  },
  onLoad() {
    wx.cloud.database().collection('user_info').where({
      _openid: this.data.openid
    }).get().then(res => {
      this.setData({ history: res.data });
    });
  },
  viewImage(e) {
    const { imageUrl, result } = e.currentTarget.dataset;
    wx.previewImage({
      urls: [imageUrl],
      current: imageUrl
    });
    wx.showToast({ title: '识别结果：' + result, icon: 'none' });
  }
})

// pages/index/index.js
connectWebSocket() {
  const socket = wx.connectSocket({
    url: 'wss://your-websocket-url',
  });
  socket.onMessage((message) => {
    const data = JSON.parse(message.data);
    if (data.status === 'completed') {
      this.setData({ result: data.result });
    }
  });
  socket.onOpen(() => {
    console.log('WebSocket连接已建立');
  });
},