Create app.py

app.py

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+import gradio as gr
+from modules import api_manager, health_ai, database
+import os
+
+# Initialize DB on startup
+database.init_db()
+
+# --- LOGIC FUNCTIONS ---
+
+def process_menu_upload(image, language):
+    if image is None:
+        return "No image provided", "", {}, "Error"
+
+    # 1. OCR Step
+    extracted_text, ocr_source = api_manager.perform_ocr(image)
+    
+    # 2. Translation Step
+    translated_text, trans_source = api_manager.translate_text(extracted_text, language)
+    
+    # 3. Health Analysis Step
+    health_data = health_ai.analyze_health(translated_text)
+    
+    # Logs
+    api_log = f"OCR Source: {ocr_source}\nTranslation Source: {trans_source}"
+    
+    return extracted_text, translated_text, health_data, api_log
+
+def register_rest_ui(name, loc, owner):
+    return database.add_restaurant(name, loc, owner)
+
+def search_rest_ui(query):
+    return database.search_restaurants(query)
+
+# --- UI LAYOUT ---
+
+with gr.Blocks(theme=gr.themes.Soft(), title="MenuVision AI") as demo:
+    gr.Markdown("# 🍽️ MenuVision AI")
+    gr.Markdown("### Intelligent Restaurant Menu Platform (Dual-API Architecture)")
+
+    with gr.Tabs():
+        
+        # TAB 1: MENU ANALYSIS
+        with gr.Tab("📸 Guest: Analyze Menu"):
+            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"], 
+                        label="Translate to", 
+                        value="es"
+                    )
+                    analyze_btn = gr.Button("Analyze Menu", variant="primary")
+                
+                with gr.Column():
+                    ocr_output = gr.Textbox(label="Extracted Text (OCR)", 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="System Logs", interactive=False)
+
+            analyze_btn.click(
+                process_menu_upload, 
+                inputs=[img_input, lang_input], 
+                outputs=[ocr_output, trans_output, health_output, api_status]
+            )
+
+        # TAB 2: SEARCH RESTAURANTS
+        with gr.Tab("🔍 Guest: Search Restaurants"):
+            search_input = gr.Textbox(label="Search by Name or Location (e.g., 'Pizza')")
+            search_btn = gr.Button("Search")
+            search_output = gr.Dataframe(label="Results")
+            search_btn.click(search_rest_ui, inputs=search_input, outputs=search_output)
+
+        # TAB 3: OWNER DASHBOARD
+        with gr.Tab("👨‍🍳 Owner: Register"):
+            gr.Markdown("Add your restaurant to the public database.")
+            with gr.Row():
+                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)
+
+if __name__ == "__main__":
+    demo.launch()