Update app.py

app.py

@@ -2,19 +2,13 @@ import gradio as gr
 from groq import Groq
 import os
 
-# Get Groq API key from environment
+# Groq client
 api_key = os.environ.get("GROQ_API_KEY")
-
-
-# Initialize Groq client
+if not api_key:
+    raise ValueError("❌ GROQ_API_KEY not found in environment variables")
 client = Groq(api_key=api_key)
 
 def get_recommendation(quantity, food_type, expiry_hours):
-    """
-    Returns a recommended recipient for surplus food along with AI explanation.
-    """
-
-    # Basic routing logic
     if quantity < 20:
         base = "Elderly Individuals"
     elif quantity < 100:
@@ -22,7 +16,6 @@ def get_recommendation(quantity, food_type, expiry_hours):
     else:
         base = "NGOs / Refugee Centers"
 
-    # Prompt for AI explanation
     prompt = f"""
 A restaurant has:
 - {quantity} meals
@@ -32,40 +25,42 @@ A restaurant has:
 The system selected: {base}
 
 Explain why this is the best recipient in 2-3 lines.
-Output format:
-Recommended recipient: <recipient>
-Reason: <AI explanation>
 """
-
-    # Call Groq AI with retry logic
     try:
         response = client.chat.completions.create(
-            model="llama-3.3-70b-versatile",
+            model="llama-2-7b-chat",
             messages=[{"role": "user", "content": prompt}]
         )
-    except Exception as e:
-        return f"❌ AI request failed:\n{str(e)}"
-
-    # Safely extract AI explanation
-    try:
         explanation = response.choices[0].message.content
-    except (AttributeError, IndexError):
-        explanation = "❌ No AI explanation returned."
+    except:
+        explanation = "❌ AI explanation not available."
 
     return f"✅ Recommended: {base}\n\n🤖 AI Reasoning:\n{explanation}"
 
-# Gradio UI
-demo = gr.Interface(
-    fn=get_recommendation,
-    inputs=[
-        gr.Number(label="Number of Meals", value=10),
-        gr.Dropdown(["halal", "soft", "packaged"], label="Food Type"),
-        gr.Number(label="Hours Until Expiry", value=5)
-    ],
-    outputs="text",
-    title="🍽️ NourishNet AI",
-    description="AI-powered food surplus redistribution system"
-)
+# Gradio Blocks UI
+with gr.Blocks(title="🍽️ NourishNet AI") as demo:
+    gr.Markdown(
+        """
+        # 🍽️ NourishNet AI
+        AI-powered food surplus redistribution system
+
+        Enter meal count, type, and expiry hours, and get a recommended recipient with AI reasoning.
+        """
+    )
+
+    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")
+
+    submit_btn = gr.Button("Get Recommendation")
+    submit_btn.click(
+        fn=get_recommendation,
+        inputs=[quantity_input, food_type_input, expiry_input],
+        outputs=output_text
+    )
 
 if __name__ == "__main__":
     demo.launch()