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Create templates/index.html
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templates/index.html
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| 1 |
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>MenuVision AI</title>
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<script type="module" src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.4.0/model-viewer.min.js"></script>
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<script src="https://cdn.tailwindcss.com"></script>
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<style>
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body { background-color: #1a1a2e; color: white; font-family: sans-serif; }
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.ar-window { height: 500px; width: 100%; background: #fff; border-radius: 15px; overflow: hidden; }
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/* AR Button Style */
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#ar-button {
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background: linear-gradient(90deg, #ff4b1f, #ff9068);
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color: white; border: none; padding: 10px 20px; border-radius: 30px;
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position: absolute; bottom: 20px; left: 50%; transform: translateX(-50%);
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font-weight: bold; cursor: pointer; z-index: 100;
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}
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</style>
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</head>
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<body class="p-4">
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<header class="text-center mb-8">
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<h1 class="text-4xl font-bold text-transparent bg-clip-text bg-gradient-to-r from-blue-400 to-pink-600">
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MenuVision AI
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</h1>
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<p class="text-gray-400">Real-world 3D Food & Code Visualization</p>
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</header>
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<div class="max-w-md mx-auto bg-gray-800 p-4 rounded-xl mb-8 shadow-2xl border border-gray-700">
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<h2 class="text-xl font-bold mb-4">🍕 3D Food on Table</h2>
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<div class="mb-4">
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<label class="block text-sm text-gray-400 mb-2">Upload Food Image to Analyze:</label>
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<input type="file" id="foodInput" class="block w-full text-sm text-gray-400 file:mr-4 file:py-2 file:px-4 file:rounded-full file:border-0 file:bg-blue-600 file:text-white">
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</div>
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<div class="ar-window relative">
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<model-viewer
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id="food-viewer"
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src="/static/models/default.glb"
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alt="3D Food"
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ar
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ar-modes="webxr scene-viewer quick-look"
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camera-controls
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auto-rotate
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shadow-intensity="1"
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scale="0.5 0.5 0.5"> <button slot="ar-button" id="ar-button">
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👋 Place on Real Table
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</button>
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</model-viewer>
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</div>
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<div id="food-stats" class="mt-2 text-center text-green-400 font-mono hidden">
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Analyzing...
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</div>
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</div>
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<div class="max-w-md mx-auto bg-gray-800 p-4 rounded-xl mb-8 border border-gray-700">
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<h2 class="text-xl font-bold mb-4">🧠 AI Code Visualizer</h2>
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<textarea id="codeInput" class="w-full p-2 bg-gray-900 rounded h-24 text-xs font-mono" placeholder="Paste python code logic here..."></textarea>
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<button onclick="generateDiagram()" class="w-full bg-blue-600 mt-2 py-2 rounded hover:bg-blue-500">Generate Visual Diagram</button>
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<div id="diagramResult" class="mt-4 text-center">
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</div>
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</div>
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<div class="max-w-md mx-auto bg-gray-800 p-4 rounded-xl border border-gray-700">
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<h2 class="text-xl font-bold mb-2">💬 AI Guide</h2>
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<div id="chatHistory" class="h-20 overflow-y-auto mb-2 text-sm text-gray-300"></div>
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<div class="flex">
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<input type="text" id="chatInput" class="flex-1 p-2 bg-gray-900 rounded-l" placeholder="Ask about the food...">
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<button onclick="sendChat()" class="bg-green-600 px-4 rounded-r">Send</button>
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</div>
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</div>
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<script>
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// --- 1. HANDLE FOOD UPLOAD & AR SWITCHING ---
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const foodInput = document.getElementById('foodInput');
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const viewer = document.getElementById('food-viewer');
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const stats = document.getElementById('food-stats');
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foodInput.addEventListener('change', async (e) => {
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const file = e.target.files[0];
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if (!file) return;
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stats.classList.remove('hidden');
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stats.innerText = "🔍 AI Analyzing Food Structure...";
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const formData = new FormData();
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formData.append('image', file);
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// Send to Backend
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const response = await fetch('/analyze_food', { method: 'POST', body: formData });
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const data = await response.json();
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// Update UI with AI results
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stats.innerText = `✅ Detected: ${data.food_detected.toUpperCase()} (Confidence: ${data.confidence})`;
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// SWAP THE 3D MODEL
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// This is the key: The AR model changes based on the "AI" analysis
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viewer.src = data.model_url;
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});
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// --- 2. HANDLE CODE DIAGRAM GENERATION ---
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async function generateDiagram() {
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const code = document.getElementById('codeInput').value;
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const res = await fetch('/generate_code_diagram', {
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method: 'POST',
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headers: {'Content-Type': 'application/json'},
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body: JSON.stringify({ code: code })
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});
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const data = await res.json();
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const imgHtml = `<img src="${data.diagram_url}" class="w-full rounded border border-blue-500" alt="Code Flow">`;
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document.getElementById('diagramResult').innerHTML = imgHtml;
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}
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// --- 3. HANDLE CHAT ---
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async function sendChat() {
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const input = document.getElementById('chatInput');
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const history = document.getElementById('chatHistory');
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const msg = input.value;
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history.innerHTML += `<div>You: ${msg}</div>`;
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input.value = "";
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const res = await fetch('/chat_guide', {
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method: 'POST',
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headers: {'Content-Type': 'application/json'},
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body: JSON.stringify({ message: msg })
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});
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const data = await res.json();
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history.innerHTML += `<div class="text-green-400">AI: ${data.reply}</div>`;
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}
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</script>
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</body>
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</html>
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