Create app.py

app.py

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+import gradio as gr
+from groq import Groq
+import os
+
+# Load API key from Hugging Face Secrets
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+def get_recommendation(quantity, food_type, expiry_hours):
+    # Basic logic (fast + reliable)
+    if quantity < 20:
+        base = "Elderly Individuals"
+    elif quantity < 100:
+        base = "Care Homes"
+    else:
+        base = "NGOs / Refugee Centers"
+
+    # AI explanation
+    prompt = f"""
+    A restaurant has:
+    - {quantity} meals
+    - Food type: {food_type}
+    - Expiry in {expiry_hours} hours
+
+    The system selected: {base}
+
+    Explain why this is the best recipient in 2-3 lines.
+    """
+
+    response = client.chat.completions.create(
+        model="llama3-70b-8192",
+        messages=[{"role": "user", "content": prompt}]
+    )
+
+    explanation = response.choices[0].message.content
+
+    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"),
+        gr.Dropdown(["halal", "soft", "packaged"], label="Food Type"),
+        gr.Number(label="Hours Until Expiry")
+    ],
+    outputs="text",
+    title="🍽️ NourishNet AI",
+    description="AI-powered food surplus redistribution system"
+)
+
+if __name__ == "__main__":
+    demo.launch()