Update app.py

app.py

@@ -4,26 +4,35 @@ import requests
 import json
 from datetime import datetime
 
-# Configuration - Use Hugging Face Secrets
+# Configuration
 GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 MODEL = "llama3-70b-8192"
 API_URL = "https://api.groq.com/openai/v1/chat/completions"
 
+def get_risk_color(risk_level):
+    """Return color based on risk level"""
+    colors = {
+        "HIGH": "#ff4d4d",  # Red
+        "MEDIUM": "#ffa64d", # Orange
+        "LOW": "#4dff4d",   # Green
+    }
+    return colors.get(risk_level.upper(), "#666666")
+
 def analyze_flood(location, water_level, rainfall, historical_data):
-    """Enhanced flood analysis with error handling"""
+    """Enhanced flood analysis with structured output"""
     prompt = f"""
-    As FloodAI Expert, analyze:
-    - Location: {location}
-    - Water Level: {water_level}m
-    - Rainfall: {rainfall}mm
-    - Historical Data: {'Available' if historical_data else 'Unavailable'}
+    As a hydrology expert, analyze flood risk for:
+    Location: {location}
+    Water Level: {water_level}m
+    Rainfall: {rainfall}mm
+    Historical Data: {'Available' if historical_data else 'Not available'}
     
-    Respond in JSON with:
+    Respond in JSON format with:
     - risk_level (HIGH/MEDIUM/LOW)
-    - confidence (0-100)
-    - alert_message
-    - actions (3 bullet points)
-    - emergency (boolean)
+    - summary (1 sentence)
+    - detailed_analysis (3-5 bullet points)
+    - recommended_actions (3 bullet points)
+    - confidence (percentage)
     """
     
     try:
@@ -38,7 +47,7 @@ def analyze_flood(location, water_level, rainfall, historical_data):
                 "messages": [
                     {
                         "role": "system",
-                        "content": "You are FloodAI. Respond in valid JSON only."
+                        "content": "You are a flood risk analysis AI. Respond in valid JSON format."
                     },
                     {
                         "role": "user",
@@ -52,57 +61,74 @@ def analyze_flood(location, water_level, rainfall, historical_data):
         response.raise_for_status()
         result = json.loads(response.json()["choices"][0]["message"]["content"])
         
-        # Format for Gradio output
-        return {
-            "Risk Level": result.get("risk_level", "UNKNOWN"),
-            "Confidence": f"{result.get('confidence', 0)}%",
-            "Alert": result.get("alert_message", "No alert generated"),
-            "Recommended Actions": "\n".join([f"• {action}" for action in result.get("actions", [])]),
-            "Emergency": "🚨 EVACUATE" if result.get("emergency") else "⚠️ Monitor"
-        }
+        return format_output(result)
         
     except Exception as e:
-        return {"Error": f"API Failure: {str(e)}"}
+        return format_output({"error": str(e)})
+
+def format_output(data):
+    """Format the API response for Gradio display"""
+    if "error" in data:
+        return {
+            "Risk Level": "ERROR",
+            "Summary": data["error"],
+            "Details": "Failed to get analysis",
+            "Actions": "Please try again later"
+        }
+    
+    risk_level = data.get("risk_level", "UNKNOWN")
+    color = get_risk_color(risk_level)
+    
+    return {
+        "Risk Level": f"<span style='color: {color}; font-weight: bold'>{risk_level}</span>",
+        "Summary": data.get("summary", "No summary available"),
+        "Detailed Analysis": "\n".join([f"• {point}" for point in data.get("detailed_analysis", [])]),
+        "Recommended Actions": "\n".join([f"• {action}" for action in data.get("recommended_actions", [])]),
+        "Confidence": f"{data.get('confidence', 'N/A')}%"
+    }
 
-# Hugging Face Optimized Interface
-with gr.Blocks(theme=gr.themes.Soft(), title="FloodAI Pro") as app:
-    # Header Section
+# Gradio Interface
+with gr.Blocks(theme=gr.themes.Soft(), title="Flood Risk Analyzer") as app:
+    # Header
     gr.Markdown("""
     <div style='text-align: center'>
-        <h1>🌊 FloodAI Pro</h1>
-        <p>Real-time Flood Risk Assessment powered by Groq AI</p>
+        <h1>🌊 Flood Risk Assessment</h1>
+        <p>Instant flood risk analysis powered by Groq AI</p>
     </div>
     """)
     
     # Input Section
     with gr.Row():
         with gr.Column():
-            gr.Markdown("### 📍 Location Data")
-            location = gr.Textbox(label="City/Region", placeholder="e.g. Karachi, Pakistan")
+            gr.Markdown("### 📍 Enter Location Details")
+            location = gr.Textbox(label="City/Region")
             water_level = gr.Slider(0, 15, step=0.1, label="Water Level (meters)")
             rainfall = gr.Slider(0, 500, step=5, label="24h Rainfall (mm)")
             historical = gr.Checkbox(label="Include historical flood data")
             submit_btn = gr.Button("Analyze Risk", variant="primary")
             
-        # Output Section
+    # Output Section
+    with gr.Row():
         with gr.Column():
-            gr.Markdown("### 📊 Risk Assessment")
-            risk_output = gr.JSON(label="Analysis Results")
+            gr.Markdown("### 🚨 Risk Overview")
+            risk_level = gr.HTML(label="Risk Level")
+            summary = gr.Textbox(label="Summary", interactive=False)
             
-            with gr.Accordion("🛡️ Safety Recommendations", open=False):
-                gr.Markdown("""
-                - Move to higher ground if risk is HIGH
-                - Prepare emergency supplies
-                - Monitor local authorities' instructions
-                """)
+            with gr.Accordion("📊 Detailed Analysis", open=False):
+                details = gr.Markdown()
+                
+            with gr.Accordion("🛡️ Recommended Actions", open=False):
+                actions = gr.Markdown()
+                
+            confidence = gr.Textbox(label="Confidence Level", interactive=False)
     
-    # Examples Section
-    gr.Markdown("### 🧪 Try Example Scenarios")
+    # Examples
+    gr.Markdown("### 🧪 Example Scenarios")
     gr.Examples(
         examples=[
-            ["Dhaka, Bangladesh", 4.5, 200, True],
-            ["Lahore, Pakistan", 2.1, 80, False],
-            ["Mumbai, India", 3.8, 300, True]
+            ["Karachi, Pakistan", 4.2, 180, True],
+            ["Delhi, India", 2.5, 90, False],
+            ["Dhaka, Bangladesh", 5.1, 250, True]
         ],
         inputs=[location, water_level, rainfall, historical],
         label="Click any example to load"
@@ -110,9 +136,8 @@ with gr.Blocks(theme=gr.themes.Soft(), title="FloodAI Pro") as app:
     
     # Footer
     gr.Markdown(f"""
-    <div style='text-align: center; color: #666'>
-        <p>Last Updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
-        <p>Powered by Groq LPU • Model: {MODEL}</p>
+    <div style='text-align: center; color: #666; margin-top: 20px'>
+        <p>Last update: {datetime.now().strftime('%Y-%m-%d %H:%M')} | Model: {MODEL}</p>
     </div>
     """)
     
@@ -120,8 +145,13 @@ with gr.Blocks(theme=gr.themes.Soft(), title="FloodAI Pro") as app:
     submit_btn.click(
         fn=analyze_flood,
         inputs=[location, water_level, rainfall, historical],
-        outputs=risk_output
+        outputs={
+            "Risk Level": risk_level,
+            "Summary": summary,
+            "Detailed Analysis": details,
+            "Recommended Actions": actions,
+            "Confidence": confidence
+        }
     )
 
-# Required for Hugging Face Spaces
-app.launch(debug=True)
+app.launch()