npm install @tensorflow/tfjs

npm install openai

<template>
  <div>
    <h1>Object Detection</h1>
    <video ref="video" autoplay></video>
    <canvas ref="canvas"></canvas>
  </div>
</template>

<script>
import * as cocoSsd from '@tensorflow-models/coco-ssd';
import '@tensorflow/tfjs';

export default {
  data() {
    return {
      model: null
    };
  },
  methods: {
    async loadModel() {
      this.model = await cocoSsd.load();
      this.detectObjects();
    },
    async detectObjects() {
      const video = this.$refs.video;
      const canvas = this.$refs.canvas;
      const ctx = canvas.getContext('2d');

      navigator.mediaDevices.getUserMedia({ video: true }).then((stream) => {
        video.srcObject = stream;
        video.onloadeddata = async () => {
          canvas.width = video.videoWidth;
          canvas.height = video.videoHeight;

          while (true) {
            const predictions = await this.model.detect(video);
            ctx.clearRect(0, 0, canvas.width, canvas.height);
            ctx.drawImage(video, 0, 0, canvas.width, canvas.height);

            predictions.forEach((prediction) => {
              ctx.beginPath();
              ctx.rect(...prediction.bbox);
              ctx.lineWidth = 2;
              ctx.strokeStyle = 'red';
              ctx.fillStyle = 'red';
              ctx.stroke();
              ctx.fillText(
                `${prediction.class} (${Math.round(prediction.score * 100)}%)`,
                prediction.bbox[0],
                prediction.bbox[1] > 10 ? prediction.bbox[1] - 5 : 10
              );
            });
          }
        };
      });
    }
  },
  mounted() {
    this.loadModel();
  }
};
</script>

<template>
  <div>
    <h1>AI Chatbot</h1>
    <textarea v-model="userInput" placeholder="Ask me anything..."></textarea>
    <button @click="getResponse">Send</button>
    <div v-if="response">
      <h2>Response:</h2>
      <p>{{ response }}</p>
    </div>
  </div>
</template>

<script>
import { Configuration, OpenAIApi } from 'openai';

export default {
  data() {
    return {
      userInput: '',
      response: null
    };
  },
  methods: {
    async getResponse() {
      const configuration = new Configuration({
        apiKey: 'your-openai-api-key'
      });
      const openai = new OpenAIApi(configuration);
      const completion = await openai.createCompletion({
        model: 'text-davinci-003',
        prompt: this.userInput,
        max_tokens: 150
      });
      this.response = completion.data.choices[0].text.trim();
    }
  }
};
</script>

const express = require('express');
const app = express();
const bodyParser = require('body-parser');

app.use(bodyParser.json());

app.post('/api/predict', async (req, res) => {
  const data = req.body.input;
  // ประมวลผลด้วย AI Model
  const prediction = await runModel(data);
  res.json({ prediction });
});

app.listen(3000, () => console.log('Server running on port 3000'));