app.py

import gradio as gr
import os
import requests
import json
from datetime import datetime

# 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 structured output"""
    prompt = f"""
    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 format with:
    - risk_level (HIGH/MEDIUM/LOW)
    - summary (1 sentence)
    - detailed_analysis (3-5 bullet points)
    - recommended_actions (3 bullet points)
    - confidence (percentage)
    """
    
    try:
        response = requests.post(
            API_URL,
            headers={
                "Authorization": f"Bearer {GROQ_API_KEY}",
                "Content-Type": "application/json"
            },
            json={
                "model": MODEL,
                "messages": [
                    {
                        "role": "system",
                        "content": "You are a flood risk analysis AI. Respond in valid JSON format."
                    },
                    {
                        "role": "user",
                        "content": prompt
                    }
                ],
                "response_format": {"type": "json_object"}
            },
            timeout=10
        )
        response.raise_for_status()
        result = json.loads(response.json()["choices"][0]["message"]["content"])
        
        return format_output(result)
        
    except Exception as 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')}%"
    }

# Gradio Interface
with gr.Blocks(theme=gr.themes.Soft(), title="Flood Risk Analyzer") as app:
    # Header
    gr.Markdown("""
    <div style='text-align: center'>
        <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("### 📍 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
    with gr.Row():
        with gr.Column():
            gr.Markdown("### 🚨 Risk Overview")
            risk_level = gr.HTML(label="Risk Level")
            summary = gr.Textbox(label="Summary", interactive=False)
            
            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
    gr.Markdown("### 🧪 Example Scenarios")
    gr.Examples(
        examples=[
            ["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"
    )
    
    # Footer
    gr.Markdown(f"""
    <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>
    """)
    
    # Event Handling
    submit_btn.click(
        fn=analyze_flood,
        inputs=[location, water_level, rainfall, historical],
        outputs={
            "Risk Level": risk_level,
            "Summary": summary,
            "Detailed Analysis": details,
            "Recommended Actions": actions,
            "Confidence": confidence
        }
    )

app.launch()