Update app.py

app.py

@@ -1,115 +1,95 @@
-import gradio as gr
-from modules import api_manager, health_ai, database, image_gen
+# app.py
 import os
+from flask import Flask, render_template, request, jsonify, send_from_directory
+from graphviz import Digraph
+import random
 
-# Initialize Database on startup
-database.init_db()
+app = Flask(__name__)
 
-# --- LOGIC FUNCTIONS ---
+# CONFIGURATION
+UPLOAD_FOLDER = 'static/uploads'
+DIAGRAM_FOLDER = 'static/diagrams'
+MODEL_FOLDER = 'static/models'
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+os.makedirs(DIAGRAM_FOLDER, exist_ok=True)
 
-# 1. Menu Analysis Logic
-def process_menu_upload(image, language):
-    if image is None:
-        return "No image provided", "", {}, "Error"
-    extracted_text, ocr_source = api_manager.perform_ocr(image)
-    translated_text, trans_source = api_manager.translate_text(extracted_text, language)
-    health_data = health_ai.analyze_health(translated_text)
-    api_log = f"OCR Source: {ocr_source}\nTranslation Source: {trans_source}"
-    return extracted_text, translated_text, health_data, api_log
+# --- FEATURE 1: AI CODE VISUALIZATION ENGINE ---
+@app.route('/generate_code_diagram', methods=['POST'])
+def generate_code_diagram():
+    """
+    Takes code/logic text and creates a visual flowchart image.
+    In a real app, you would use an LLM to parse complex code.
+    Here, we simulate the visualization of logic flow.
+    """
+    data = request.json
+    code_text = data.get('code', '')
+    
+    # Create a visual graph (The "Code Image")
+    dot = Digraph(comment='Code Flow', format='png')
+    dot.attr(rankdir='TB', size='8,5')
+    
+    # Logic to turn text into nodes (Simulated AI parsing)
+    dot.node('A', 'Start: User Input')
+    dot.node('B', 'AI Analysis')
+    dot.node('C', 'Generate 3D Asset')
+    dot.node('D', 'AR Deployment')
+    
+    dot.edge('A', 'B', label='Upload Image')
+    dot.edge('B', 'C', label='Identify Food')
+    dot.edge('C', 'D', label='Render GLB')
+    
+    # Save the diagram
+    filename = f"flow_{random.randint(1000,9999)}"
+    filepath = os.path.join(DIAGRAM_FOLDER, filename)
+    dot.render(filepath)
+    
+    return jsonify({'diagram_url': f"/{filepath}.png"})
 
-# 2. 3D Image Generation Logic
-def generate_dish_visualization(dish_name):
-    if not dish_name:
-        return None, "Please enter a dish name."
-    image, status = image_gen.generate_food_image(dish_name)
-    return image, status
+# --- FEATURE 2: AI FOOD ANALYSIS & 3D SELECTOR ---
+@app.route('/analyze_food', methods=['POST'])
+def analyze_food():
+    """
+    1. Receives food image.
+    2. 'AI' identifies it (Simulated for this demo).
+    3. Returns the correct 3D model file for the table.
+    """
+    if 'image' not in request.files:
+        return jsonify({'error': 'No image uploaded'}), 400
+    
+    file = request.files['image']
+    # Save file logic here...
+    
+    # MOCK AI RECOGNITION LOGIC
+    # In a real app, use TensorFlow/YOLO here to detect "Pizza" or "Burger"
+    # For demo, we randomly detect one to show the switching capability.
+    detected_food = random.choice(['burger', 'pizza']) 
+    
+    response_data = {
+        'food_detected': detected_food,
+        'confidence': '98%',
+        'model_url': f"/static/models/{detected_food}.glb", # Returns the 3D file path
+        'calories': '450 kcal'
+    }
+    return jsonify(response_data)
 
-# 3. Auth & Database Logic
-def register_rest_ui(name, loc, owner):
-    return database.add_restaurant(name, loc, owner)
-def search_rest_ui(query):
-    return database.search_restaurants(query)
-def signup_ui(email, password, role):
-    return database.create_user(email, password, role)
-def login_ui(email, password):
-    return database.verify_login(email, password)
-
-# --- UI LAYOUT ---
-
-with gr.Blocks(theme=gr.themes.Soft(), title="MenuVision AI") as demo:
-    gr.Markdown("# 🍽️ MenuVision AI")
-    gr.Markdown("### Intelligent Restaurant Menu & 3D Visualization Platform")
-
-    with gr.Tabs():
+# --- FEATURE 3: AI GUIDE CHAT ---
+@app.route('/chat_guide', methods=['POST'])
+def chat_guide():
+    user_msg = request.json.get('message', '').lower()
+    
+    if "price" in user_msg:
+        reply = "This dish costs $12.99 based on the portion size shown."
+    elif "spicy" in user_msg:
+        reply = "This dish is rated 2/5 on the spice scale."
+    else:
+        reply = "I am your MenuVision Assistant. Upload a photo to see it in 3D on your table!"
         
-        # --- TAB 1: LOGIN & SIGNUP ---
-        with gr.Tab("🔐 Login & Signup"):
-            with gr.Row():
-                with gr.Column():
-                    gr.Markdown("### 📝 Create Account")
-                    su_email = gr.Textbox(label="Email")
-                    su_pass = gr.Textbox(label="Password", type="password")
-                    su_role = gr.Radio(["User", "Restaurant Owner"], label="Account Type", value="User")
-                    su_btn = gr.Button("Sign Up", variant="primary")
-                    su_msg = gr.Textbox(label="Status")
-                    su_btn.click(signup_ui, inputs=[su_email, su_pass, su_role], outputs=su_msg)
-                
-                with gr.Column():
-                    gr.Markdown("### 🔑 Login")
-                    li_email = gr.Textbox(label="Email")
-                    li_pass = gr.Textbox(label="Password", type="password")
-                    li_btn = gr.Button("Login")
-                    li_msg = gr.Textbox(label="Login Status")
-                    li_btn.click(login_ui, inputs=[li_email, li_pass], outputs=li_msg)
-
-        # --- TAB 2: MENU SCANNER ---
-        with gr.Tab("📸 Menu Scanner"):
-            gr.Markdown("Upload a menu to extract text, translate it, and check health stats.")
-            with gr.Row():
-                with gr.Column():
-                    img_input = gr.Image(type="pil", label="Upload Menu Image")
-                    lang_input = gr.Dropdown(
-                        ["es", "fr", "de", "ur", "zh", "ar", "hi", "ru", "pt"], 
-                        label="Translate to", value="es"
-                    )
-                    analyze_btn = gr.Button("Analyze Menu", variant="primary")
-                with gr.Column():
-                    ocr_output = gr.Textbox(label="Extracted Text", interactive=False, lines=4)
-                    trans_output = gr.Textbox(label="Translated Text", interactive=False, lines=4)
-                    health_output = gr.JSON(label="Health Insights")
-                    api_status = gr.Textbox(label="Logs", interactive=False)
-            analyze_btn.click(process_menu_upload, inputs=[img_input, lang_input], outputs=[ocr_output, trans_output, health_output, api_status])
-
-        # --- TAB 3: 3D FOOD VISUALIZER ---
-        with gr.Tab("🍔 3D Food Visualizer"):
-            gr.Markdown("### See it before you order!")
-            gr.Markdown("Type a dish name to generate a realistic **3D image on a restaurant table**.")
-            
-            with gr.Row():
-                with gr.Column():
-                    dish_input = gr.Textbox(label="Enter Dish Name (e.g., 'Spicy Pepperoni Pizza')")
-                    gen_btn = gr.Button("Generate 3D Image", variant="primary")
-                with gr.Column():
-                    gen_output = gr.Image(label="AI Generated Preview")
-                    gen_status = gr.Textbox(label="Status", interactive=False)
-            
-            gen_btn.click(generate_dish_visualization, inputs=dish_input, outputs=[gen_output, gen_status])
-
-        # --- TAB 4: SEARCH ---
-        with gr.Tab("🔍 Search Restaurants"):
-            search_input = gr.Textbox(label="Search by Name or Location")
-            search_btn = gr.Button("Search")
-            search_output = gr.Dataframe(label="Results")
-            search_btn.click(search_rest_ui, inputs=search_input, outputs=search_output)
+    return jsonify({'reply': reply})
 
-        # --- TAB 5: OWNER DASHBOARD ---
-        with gr.Tab("👨‍🍳 Owner Dashboard"):
-            r_name = gr.Textbox(label="Restaurant Name")
-            r_loc = gr.Textbox(label="Location")
-            r_owner = gr.Textbox(label="Owner Name")
-            reg_btn = gr.Button("Register Restaurant")
-            reg_msg = gr.Textbox(label="Status")
-            reg_btn.click(register_rest_ui, inputs=[r_name, r_loc, r_owner], outputs=reg_msg)
+@app.route('/')
+def index():
+    return render_template('index.html')
 
-if __name__ == "__main__":
-    demo.launch()
+if __name__ == '__main__':
+    # Run on 0.0.0.0 so you can access it from your phone
+    app.run(host='0.0.0.0', port=5000, debug=True)