#gradio app

import gradio as gr
import json
from Agent import create_environmental_analyzer

def analyze_environmental_impact(product_description):
    """Main analysis function that processes input and returns formatted results"""
    
    if not product_description.strip():
        return "Please enter a product description to analyze.", "", "", ""
    
    # Initialize the analyzer
    analyzer = create_environmental_analyzer()
    
    # Run the analysis
    initial_state = {
        "messages": [],
        "product_description": product_description,
        "extracted_data": {},
        "carbon_footprint": 0.0,
        "environmental_score": 0.0,
        "recommendations": [],
        "analysis_complete": False
    }
    
    # Process through the workflow
    final_state = analyzer.invoke(initial_state)
    
    # Format results for display
    score_display, status_message, details_json, recommendations_text = format_results(final_state)
    
    return score_display, status_message, details_json, recommendations_text

def format_results(state):
    """Format the analysis results for Gradio display"""
    
    # Environmental Score Display
    score = state['environmental_score']
    carbon = state['carbon_footprint']
    
    score_display = f"""
    ## Environmental Impact Score
    
    **Score: {score}/100**
    
    **Carbon Footprint: {carbon:.2f} kg CO2e**
    """
    
    # Status Message based on score
    if score >= 80:
        status_message = "🌟 **Excellent environmental performance!**\n\nThis product demonstrates outstanding sustainability practices."
    elif score >= 60:
        status_message = "⚡ **Good, but room for improvement**\n\nThis product has decent environmental performance with potential for enhancement."
    else:
        status_message = "🚨 **High environmental impact**\n\nThis product has significant environmental concerns that should be addressed."
    
    # Analysis Details as JSON
    details_json = state['extracted_data']
    
    # Recommendations as formatted text
    recommendations_text = "## Sustainability Recommendations\n\n"
    if state['recommendations']:
        for i, rec in enumerate(state['recommendations'], 1):
            recommendations_text += f"{i}. {rec}\n\n"
    else:
        recommendations_text += "No specific recommendations available."
    
    return score_display, status_message, details_json, recommendations_text

def create_gradio_interface():
    """Create the Gradio interface"""
    
    with gr.Blocks(
        title="🌱 AI Environmental Impact Analyzer",
        theme=gr.themes.Soft()
    ) as interface:
        
        # Header
        gr.Markdown("# 🌱 AI Environmental Impact Analyzer")
        gr.Markdown("Analyze the environmental footprint of consumer products using AI")
        
        with gr.Row():
            with gr.Column(scale=2):
                # Input section
                product_input = gr.Textbox(
                    label="Product Description/URL",
                    placeholder="e.g., Organic cotton t-shirt manufactured in India, packaged in recyclable materials...",
                    lines=4,
                    max_lines=8
                )
                
                analyze_btn = gr.Button(
                    "🔍 Analyze Environmental Impact",
                    variant="primary",
                    size="lg"
                )
            
            with gr.Column(scale=3):
                # Results section
                with gr.Group():
                    score_output = gr.Markdown(
                        label="Environmental Score",
                        value="Enter a product description/URL and click analyze to see results."
                    )
                    
                    status_output = gr.Markdown(
                        label="Performance Status"
                    )
        
        # Detailed results in tabs
        with gr.Tabs():
            with gr.Tab("📊 Analysis Details"):
                details_output = gr.JSON(
                    label="Extracted Environmental Data",
                    value={}
                )
            
            with gr.Tab("💡 Recommendations"):
                recommendations_output = gr.Markdown(
                    label="Sustainability Recommendations",
                    value="Analysis results will appear here..."
                )
        
        # Event handlers
        analyze_btn.click(
            fn=analyze_environmental_impact,
            inputs=[product_input],
            outputs=[score_output, status_output, details_output, recommendations_output],
            show_progress=True
        )
        
        # Optional: Add examples
        gr.Examples(
            examples=[
                ["Organic cotton t-shirt manufactured in India, packaged in recyclable cardboard"],
                ["Plastic water bottle made from recycled materials, shipped internationally"],
                ["Local handmade wooden furniture using sustainable forest wood"],
                ["Electronic smartphone with aluminum body, manufactured in China"]
            ],
            inputs=[product_input],
            label="Example Products to Analyze"
        )
        gr.Markdown("""
        **Note**: add the Following Secret Key to your environment variables:
                    - `HF_API_KEY` (Hugging Face API token) to access private models or higher rate limits.
                    - `CLIMATIQ_API_KEY` (Climatiq API token) for carbon footprint calculations.
                    """)
    
    return interface

def main():
    """Launch the Gradio application"""
    interface = create_gradio_interface()
    
    # Launch with custom settings
    interface.launch()

if __name__ == "__main__":
    main()