Update app.py

app.py

@@ -1,70 +1,58 @@
 import gradio as gr
-import requests
 import os
+import requests
 
-# Initialize Groq API
-GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-if not GROQ_API_KEY:
-    raise ValueError("❌ Groq API Key not found! Please set it in Hugging Face Secrets")
+# Groq API configuration
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+MODEL = "mixtral-8x7b-32768"  # Use a supported model if this one is deprecated
 
-def get_flood_warning(location, water_level, rainfall):
-    """Get flood prediction from Groq AI"""
+def get_flood_risk(location, water_level, rainfall):
     prompt = f"""
     Analyze flood risk based on:
     - Location: {location}
     - Current water level: {water_level} meters
     - 24-hour rainfall: {rainfall} mm
     - Historical flood data for area
-    
+
     Provide output in this exact format:
     "RISK: <HIGH/MEDIUM/LOW> | ALERT: <Warning message> | ACTION: <Recommended action>"
     """
-    
-    try:
-        headers = {
-            "Authorization": f"Bearer {GROQ_API_KEY}",
-            "Content-Type": "application/json"
-        }
-        payload = {
-            "messages": [{"role": "user", "content": prompt}],
-            "model": "mixtral-8x7b-32768"
-        }
-        response = requests.post(
-            "https://api.groq.com/openai/v1/chat/completions",
-            headers=headers,
-            json=payload
-        )
-        return response.json()["choices"][0]["message"]["content"]
-    except Exception as e:
-        return f"Error: {str(e)}"
 
-# Create Gradio Interface
-with gr.Blocks(theme=gr.themes.Soft(), title="Flood Prediction System") as app:
-    gr.Markdown("# 🌊 AI Flood Warning System")
-    gr.Markdown("Predict flood risks using Groq AI and real-time data")
-    
-    with gr.Row():
-        with gr.Column():
-            location = gr.Textbox(label="📍 Location Name", placeholder="Enter city/village name")
-            water_level = gr.Slider(label="💧 Water Level (meters)", minimum=0, maximum=15, step=0.1)
-            rainfall = gr.Slider(label="🌧️ 24h Rainfall (mm)", minimum=0, maximum=300)
-            submit_btn = gr.Button("Analyze Flood Risk", variant="primary")
-        
-        with gr.Column():
-            output = gr.Textbox(label="⚠️ Flood Alert", interactive=False)
-            gr.Examples(
-                examples=[
-                    ["Delhi", 4.5, 120],
-                    ["Mumbai", 2.1, 250],
-                    ["Chennai", 1.8, 80]
-                ],
-                inputs=[location, water_level, rainfall]
-            )
-    
-    submit_btn.click(
-        fn=get_flood_warning,
-        inputs=[location, water_level, rainfall],
-        outputs=output
-    )
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    data = {
+        "model": MODEL,
+        "messages": [
+            {"role": "system", "content": "You are a flood risk analysis expert."},
+            {"role": "user", "content": prompt}
+        ]
+    }
+
+    response = requests.post(GROQ_API_URL, headers=headers, json=data)
+
+    if response.status_code == 200:
+        result = response.json()
+        message = result["choices"][0]["message"]["content"].strip()
+        return message
+    else:
+        return f"❌ Error: {response.status_code} - {response.text}"
+
+# Gradio UI
+iface = gr.Interface(
+    fn=get_flood_risk,
+    inputs=[
+        gr.Textbox(label="Location"),
+        gr.Number(label="Current Water Level (m)"),
+        gr.Number(label="24-hour Rainfall (mm)")
+    ],
+    outputs="text",
+    title="🌊 Flood Risk Predictor",
+    description="Enter location, water level and rainfall to get flood risk prediction using Groq AI"
+)
 
-app.launch()
+if __name__ == "__main__":
+    iface.launch()