Update app.py

app.py

@@ -2,91 +2,109 @@ import gradio as gr
 from groq import Groq
 import os
 import time
+import folium
+from folium import Marker
+from streamlit_folium import st_folium  # optional if you switch to Streamlit for maps
+from geopy.distance import geodesic
+from io import BytesIO
+import base64
 
-# -------------------------
-# Initialize Groq client
-# -------------------------
+# Load Groq API key from environment
 api_key = os.environ.get("GROQ_API_KEY")
-client = Groq(api_key=api_key) if api_key else None
+if not api_key:
+    print("❌ GROQ_API_KEY not found. AI reasoning will be disabled.")
+    client = None
+else:
+    client = Groq(api_key=api_key)
 
-# -------------------------
-# Main recommendation function
-# -------------------------
-def get_recommendation(quantity, food_type, expiry_hours):
-    if not client:
-        return "❌ GROQ_API_KEY not found. Please set your API key in Secrets."
+# Sample recipients database
+recipients = [
+    {"name": "Al Noor Elderly Home", "lat": 25.2048, "lon": 55.2708, "type": "Elderly Individuals", "contact": "+971501234567"},
+    {"name": "Refugee Center Dubai", "lat": 25.0657, "lon": 55.1713, "type": "NGOs / Refugee Centers", "contact": "+971509876543"},
+    {"name": "Care Home Sharjah", "lat": 25.3574, "lon": 55.4031, "type": "Care Homes", "contact": "+971506543210"},
+]
 
-    # Basic routing logic
+# Function to select recipient
+def select_recipient(quantity, food_type):
     if quantity < 20:
-        base = "Elderly Individuals"
+        type_needed = "Elderly Individuals"
     elif quantity < 100:
-        base = "Care Homes"
+        type_needed = "Care Homes"
     else:
-        base = "NGOs / Refugee Centers"
+        type_needed = "NGOs / Refugee Centers"
+    # pick nearest recipient of that type (simulated)
+    filtered = [r for r in recipients if r["type"] == type_needed]
+    return filtered[0] if filtered else {"name": "No recipient available", "lat": 25.2048, "lon": 55.2708, "contact": "N/A", "type": type_needed}
 
+# Function to generate AI reasoning
+def get_ai_reasoning(quantity, food_type, expiry_hours, recipient_name, recipient_type):
+    if not client:
+        return "❌ AI explanation not available (API key missing)"
     prompt = f"""
 A restaurant has:
 - {quantity} meals
 - Food type: {food_type}
 - Expiry in {expiry_hours} hours
-
-The system selected: {base}
-
+The system selected: {recipient_name} ({recipient_type})
 Explain why this is the best recipient in 2-3 lines.
 """
+    try:
+        response = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=[{"role": "user", "content": prompt}]
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"❌ AI request failed: {str(e)}"
 
-    # Retry logic for temporary connection issues
-    explanation = "❌ AI explanation not available."
-    for attempt in range(3):
-        try:
-            response = client.chat.completions.create(
-                model="llama-3.3-70b-versatile",  # smaller model for Spaces
-                messages=[{"role": "user", "content": prompt}]
-            )
-            explanation = response.choices[0].message.content
-            break
-        except Exception as e:
-            explanation = f"❌ AI request failed on attempt {attempt+1}: {e}"
-            time.sleep(2)  # wait 2 seconds before retrying
+# Function to generate map
+def generate_map(recipient):
+    m = folium.Map(location=[recipient["lat"], recipient["lon"]], zoom_start=12)
+    Marker([recipient["lat"], recipient["lon"]], popup=f"{recipient['name']} ({recipient['type']})\nContact: {recipient['contact']}").add_to(m)
+    # Convert map to HTML iframe
+    data = BytesIO()
+    m.save(data, close_file=False)
+    return data.getvalue().decode()
 
-    return f"✅ Recommended: {base}\n\n🤖 AI Reasoning:\n{explanation}"
+# Function to simulate delivery progress
+def simulate_delivery(quantity, food_type, expiry_hours):
+    recipient = select_recipient(quantity, food_type)
+    ai_reasoning = get_ai_reasoning(quantity, food_type, expiry_hours, recipient["name"], recipient["type"])
+    map_html = generate_map(recipient)
 
-# -------------------------
-# Gradio Blocks UI
-# -------------------------
-with gr.Blocks(title="🍽️ NourishNet AI") as demo:
-    gr.Markdown(
-        """
-        # 🍽️ NourishNet AI
-        AI-powered food surplus redistribution system
+    # Simulate progress steps
+    steps = ["📦 Picked Up", "🚚 En Route", "✅ Delivered"]
+    progress_output = ""
+    for i, step in enumerate(steps):
+        progress_output += f"{step}\n"
+        time.sleep(0.5)  # simulate real-time delay
 
-        Enter meal count, type, and expiry hours, and get a recommended recipient with AI reasoning.
-        """
-    )
+    # Simulated gamification badge
+    badge = "🏆 Zero Waste Champion" if quantity > 50 else "⭐ Community Helper"
+
+    return f"✅ Recommended: {recipient['name']} ({recipient['type']})\n\n🤖 AI Reasoning:\n{ai_reasoning}\n\n📍 Recipient Map:\n{map_html}\n\n🚀 Delivery Status:\n{progress_output}\n\n🎖️ Badge Earned: {badge}"
+
+# Gradio UI with CSS
+with gr.Blocks(title="🍽️ NourishNet AI") as demo:
     gr.HTML("""
     <style>
-    body { font-family: 'Poppins', sans-serif; }
+    body { font-family: 'Poppins', sans-serif; background-color: #fdf6f0; }
     .gr-button { background: linear-gradient(90deg, #FF7A00, #FFB347); border-radius: 12px; color: white; font-weight: bold; }
     .gr-textbox { border: 2px solid #FF7A00; border-radius: 10px; padding: 10px; background-color: #FFF8F0; }
     </style>
     """)
-
+    gr.Markdown("# 🍽️ NourishNet AI\nAI-powered food surplus redistribution system")
     with gr.Row():
         quantity_input = gr.Number(label="Number of Meals", value=10)
         food_type_input = gr.Dropdown(["halal", "soft", "packaged"], label="Food Type")
         expiry_input = gr.Number(label="Hours Until Expiry", value=5)
-
-    output_text = gr.Textbox(label="Recommendation & AI Reasoning", lines=7)
-
+    output_text = gr.Textbox(label="Recommendation, AI Reasoning, Map & Delivery Status", lines=20)
     submit_btn = gr.Button("Get Recommendation")
     submit_btn.click(
-        fn=get_recommendation,
+        fn=simulate_delivery,
         inputs=[quantity_input, food_type_input, expiry_input],
         outputs=output_text
     )
 
-# -------------------------
-# Run the app
-# -------------------------
 if __name__ == "__main__":
     demo.launch()