Update index.js

index.js

@@ -1,79 +1,57 @@
-import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.9.0';
-
-// Since we will download the model from the Hugging Face Hub, we can skip the local model check
-env.allowLocalModels = false;
-
-// Reference the elements that we will need
-const status = document.getElementById('status');
-const fileUpload = document.getElementById('upload');
-const imageContainer = document.getElementById('container');
-const example = document.getElementById('example');
-
-const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
-
-// Create a new object detection pipeline
-status.textContent = 'Loading model...';
-const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
-status.textContent = 'Ready';
-
-example.addEventListener('click', (e) => {
-    e.preventDefault();
-    detect(EXAMPLE_URL);
-});
-
-fileUpload.addEventListener('change', function (e) {
-    const file = e.target.files[0];
-    if (!file) {
-        return;
+const http = require('http');
+const querystring = require('querystring');
+const url = require('url');
+
+class MyClassificationPipeline {
+    static task = 'text-classification';
+    static model = 'Xenova/distilbert-base-uncased-finetuned-sst-2-english';
+    static instance = null;
+  
+    static async getInstance(progress_callback = null) {
+      if (this.instance === null) {
+        // Dynamically import the Transformers.js library
+        let { pipeline, env } = await import('@xenova/transformers');
+  
+        // NOTE: Uncomment this to change the cache directory
+        // env.cacheDir = './.cache';
+  
+        this.instance = pipeline(this.task, this.model, { progress_callback });
+      }
+  
+      return this.instance;
     }
-
-    const reader = new FileReader();
-
-    // Set up a callback when the file is loaded
-    reader.onload = e2 => detect(e2.target.result);
-
-    reader.readAsDataURL(file);
+  }
+
+  // Define the HTTP server
+const server = http.createServer();
+const hostname = '127.0.0.1';
+const port = 3000;
+
+// Listen for requests made to the server
+server.on('request', async (req, res) => {
+  // Parse the request URL
+  const parsedUrl = url.parse(req.url);
+
+  // Extract the query parameters
+  const { text } = querystring.parse(parsedUrl.query);
+
+  // Set the response headers
+  res.setHeader('Content-Type', 'application/json');
+
+  let response;
+  if (parsedUrl.pathname === '/classify' && text) {
+    const classifier = await MyClassificationPipeline.getInstance();
+    response = await classifier(text);
+    res.statusCode = 200;
+  } else {
+    response = { 'error': 'Bad request' }
+    res.statusCode = 400;
+  }
+
+  // Send the JSON response
+  res.end(JSON.stringify(response));
 });
 
-
-// Detect objects in the image
-async function detect(img) {
-    imageContainer.innerHTML = '';
-    imageContainer.style.backgroundImage = `url(${img})`;
-
-    status.textContent = 'Analysing...';
-    const output = await detector(img, {
-        threshold: 0.5,
-        percentage: true,
-    });
-    status.textContent = '';
-    output.forEach(renderBox);
-}
-
-// Render a bounding box and label on the image
-function renderBox({ box, label }) {
-    const { xmax, xmin, ymax, ymin } = box;
-
-    // Generate a random color for the box
-    const color = '#' + Math.floor(Math.random() * 0xFFFFFF).toString(16).padStart(6, 0);
-
-    // Draw the box
-    const boxElement = document.createElement('div');
-    boxElement.className = 'bounding-box';
-    Object.assign(boxElement.style, {
-        borderColor: color,
-        left: 100 * xmin + '%',
-        top: 100 * ymin + '%',
-        width: 100 * (xmax - xmin) + '%',
-        height: 100 * (ymax - ymin) + '%',
-    })
-
-    // Draw label
-    const labelElement = document.createElement('span');
-    labelElement.textContent = label;
-    labelElement.className = 'bounding-box-label';
-    labelElement.style.backgroundColor = color;
-
-    boxElement.appendChild(labelElement);
-    imageContainer.appendChild(boxElement);
-}
+server.listen(port, hostname, () => {
+  console.log(`Server running at http://${hostname}:${port}/`);
+});