Update index.js

index.js

@@ -1,79 +1,50 @@
-import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.10.1';
-
-// 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);
-});
+$(document).ready(function() {
+    const messagesDiv = $('#messages');
+    const userInput = $('#userInput');
+    const sendBtn = $('#sendBtn');
+    const chartCanvas = $('#chart');
+
+    sendBtn.on('click', function() {
+        const userMessage = userInput.val();
+        if (userMessage) {
+            messagesDiv.append(`<div><strong>You:</strong> ${userMessage}</div>`);
+            userInput.val('');
+            generateChart(userMessage);
+        }
+    });
 
-fileUpload.addEventListener('change', function (e) {
-    const file = e.target.files[0];
-    if (!file) {
-        return;
+    function generateChart(query) {
+        // Simulate AI response and chart generation
+        messagesDiv.append(`<div><strong>AI:</strong> Generating chart for "${query}"...</div>`);
+
+        // Simulated data for the chart
+        const labels = ['January', 'February', 'March', 'April', 'May', 'June', 'July'];
+        const data = [65, 59, 80, 81, 56, 55, 40];
+
+        // Create the chart
+        const ctx = chartCanvas[0].getContext('2d');
+        const chart = new Chart(ctx, {
+            type: 'line',
+            data: {
+                labels: labels,
+                datasets: [{
+                    label: 'Stock Trend',
+                    data: data,
+                    borderColor: 'rgba(75, 192, 192, 1)',
+                    borderWidth: 2,
+                    fill: false
+                }]
+            },
+            options: {
+                responsive: true,
+                scales: {
+                    y: {
+                        beginAtZero: true
+                    }
+                }
+            }
+        });
+
+        chartCanvas.show();
     }
-
-    const reader = new FileReader();
-
-    // Set up a callback when the file is loaded
-    reader.onload = e2 => detect(e2.target.result);
-
-    reader.readAsDataURL(file);
 });
-
-
-// Detect objects in the image
-async function detect(img) {
-    imageContainer.innerHTML = '';
-    imageContainer.style.backgroundImage = `url(${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);
-}