app.py

import gradio as gr
import easyocr
import numpy as np
from PIL import Image
import os
import folium
from huggingface_hub import InferenceClient

# --- CONFIGURATION ---
# Replace with your actual token if you don't want to paste it in the UI every time
HF_TOKEN = "hf_..." 

# Initialize Tools
reader = easyocr.Reader(['en'])

# --- LOGIC 1: AI HEALTH ANALYZER & IMAGE GENERATOR ---
def analyze_food(food_name, language, api_key):
    """
    Generates a real-world image AND detailed health analysis in the selected language.
    """
    if not food_name:
        return None, "Please select a food item.", ""

    token = api_key if api_key else HF_TOKEN
    
    # Check if token is present
    if not token or token.startswith("hf_..."):
        return None, "Error: Please enter a valid Hugging Face Token in the box above."

    client = InferenceClient(token=token)
    
    # 1. Generate Image (Visual)
    img_prompt = (
        f"Professional food photography of {food_name}, "
        "8k resolution, hyperrealistic, cinematic lighting, "
        "macro details, steam rising, delicious, gourmet plating, "
        "unreal engine 5 render style, depth of field."
    )
    
    generated_image = None
    try:
        print(f"Generating image for {food_name}...")
        generated_image = client.text_to_image(
            prompt=img_prompt,
            model="stabilityai/stable-diffusion-xl-base-1.0",
            negative_prompt="cartoon, drawing, anime, text, blurry, low quality",
            width=1024, height=1024
        )
    except Exception as e:
        print(f"Image Error: {e}")

    # 2. Generate Health Info (Text) in Selected Language
    text_prompt = (
        f"Act as a nutritionist. Analyze the food item '{food_name}'. "
        f"Provide the response in {language} language. "
        "Format the response strictly with two sections:\n"
        "1. Health Benefits\n"
        "2. Potential Consequences or Cons (e.g., high calories, allergies).\n"
        "Keep it concise and bulleted."
    )
    
    health_info = ""
    try:
        response = client.text_generation(
            prompt=text_prompt,
            model="tiiuae/falcon-7b-instruct", # Using a fast text model
            max_new_tokens=400,
            temperature=0.7
        )
        health_info = response
    except Exception as e:
        health_info = f"Could not retrieve health data: {e}"

    return generated_image, health_info

# --- LOGIC 2: INTERACTIVE MAP (SCROLLABLE) ---
def get_map_html(location_name="Bahawalpur"):
    """
    Creates an interactive HTML map centered on a location.
    """
    # Default coordinates (Bahawalpur)
    start_coords = [29.3544, 71.6911]
    
    # Simple coordinate lookup for demo (You can add more cities)
    loc_lower = location_name.lower()
    if "islamabad" in loc_lower:
        start_coords = [33.6844, 73.0479]
    elif "lahore" in loc_lower:
        start_coords = [31.5497, 74.3436]
    elif "karachi" in loc_lower:
        start_coords = [24.8607, 67.0011]
    elif "multan" in loc_lower:
        start_coords = [30.1575, 71.5249]

    # Create Map
    m = folium.Map(location=start_coords, zoom_start=13)
    
    # Add Marker
    folium.Marker(
        start_coords, 
        popup=f"<i>{location_name}</i>", 
        tooltip="Click me!"
    ).add_to(m)

    return m._repr_html_()

# --- LOGIC 3: MENU SCANNING ---
def scan_menu(image):
    if image is None:
        return "Please upload an image.", []
    
    try:
        results = reader.readtext(image)
        # Filter for food-like text (longer than 3 chars, not numbers)
        detected_items = [res[1] for res in results if len(res[1]) > 3 and not res[1].isdigit()]
        
        status = f"✅ Found {len(detected_items)} items!"
        return status, gr.update(choices=detected_items, value=detected_items[0] if detected_items else None)
    except Exception as e:
        return f"Error scanning: {str(e)}", []

# --- UI LAYOUT ---
with gr.Blocks(theme=gr.themes.Soft(primary_hue="orange", secondary_hue="gray")) as demo:
    
    gr.Markdown("# 🥗 MenuVision AI: Health & Visual Analyzer")
    
    with gr.Row():
        api_input = gr.Textbox(label="Hugging Face Token (Required)", type="password", placeholder="Paste your Access Token here")
        language_drop = gr.Dropdown(label="🌐 Select Language", choices=["English", "Urdu", "French", "Spanish", "Arabic"], value="English")

    with gr.Tabs():
        
        # --- TAB 1: SCAN & HEALTH ANALYSIS ---
        with gr.TabItem("📸 Scan & Analyze"):
            with gr.Row():
                # LEFT COLUMN: INPUT
                with gr.Column(scale=1):
                    menu_input = gr.Image(type="numpy", label="1. Upload Menu Photo")
                    scan_btn = gr.Button("🔍 Scan Text", variant="secondary")
                    
                    gr.Markdown("---")
                    status_output = gr.Textbox(label="Status", interactive=False)
                    food_dropdown = gr.Dropdown(label="2. Select Detected Food", choices=[])
                    analyze_btn = gr.Button("✨ Analyze Health & Generate Image", variant="primary")
                
                # RIGHT COLUMN: OUTPUT
                with gr.Column(scale=2):
                    # 1. Real World Image
                    result_image = gr.Image(label="Real-World Representation", type="pil", height=400)
                    
                    # 2. Health Columns
                    gr.Markdown("### 🩺 Nutritional Analysis")
                    health_output = gr.Textbox(label="Benefits & Consequences", lines=10)

        # --- TAB 2: INTERACTIVE MAPS ---
        with gr.TabItem("🗺️ Interactive Map"):
            with gr.Row():
                place_search = gr.Textbox(label="Search Location (e.g., Islamabad)", placeholder="Type a city...")
                map_btn = gr.Button("Update Map")
            
            # This HTML component holds the interactive scrollable map
            map_html = gr.HTML(value=get_map_html(), label="Scrollable Map")

        # --- TAB 3: ABOUT ME ---
        with gr.TabItem("👨‍💻 About Developer"):
            with gr.Row():
                with gr.Column(scale=1):
                    # FIXED LINE: Removed 'show_download_button' to fix your error
                    gr.Image(
                        value="https://cdn-icons-png.flaticon.com/512/4140/4140048.png", 
                        width=200, 
                        show_label=False, 
                        interactive=False
                    )
                
                with gr.Column(scale=3):
                    gr.Markdown("""
                    ### 👋 Hi, I'm Abdullah!
                    
                    **Computer Engineering Student | AI Enthusiast | Web Developer**
                    
                    I am currently an undergraduate student at **COMSATS University Islamabad**, specializing in Computer Engineering. 
                    I have a passion for merging **Embedded Systems** with **Generative AI** to create real-world solutions.
                    
                    * **Role:** Intern Web Developer at MyK Global Forwarding.
                    * **Focus:** TinyML, IoT, and GenAI Applications.
                    * **Location:** Bahawalpur / Islamabad.
                    
                    **About MenuVision AI:**
                    This project was designed to help people make better dietary choices by visualizing food from plain text menus and understanding the health implications immediately.
                    """)

    # --- EVENT HANDLERS ---
    
    # 1. Scan Button
    scan_btn.click(
        fn=scan_menu,
        inputs=menu_input,
        outputs=[status_output, food_dropdown]
    )

    # 2. Analyze Button (Image + Health Info)
    analyze_btn.click(
        fn=analyze_food,
        inputs=[food_dropdown, language_drop, api_input],
        outputs=[result_image, health_output]
    )
    
    # 3. Map Update
    map_btn.click(
        fn=get_map_html,
        inputs=place_search,
        outputs=map_html
    )

# Launch App
demo.launch()