# app.py
import gradio as gr
from smart_web_analyzer import WebAnalyzer
from typing import Dict, List, Any

analyzer = WebAnalyzer()

def format_results(results: Dict[str, Any]) -> Dict[str, str]:
    """Format analysis results for Gradio components"""
    if 'error' in results:
        return {
            "clean_text": f"❌ Error: {results['error']}",
            "summary": "",
            "sentiment": "",
            "topics": ""
        }
    
    formatted = {}
    
    # Format clean text
    text = results.get('clean_text', 'No text extracted')
    formatted["clean_text"] = text[:2000] + "..." if len(text) > 2000 else text
    
    # Format summary
    formatted["summary"] = (
        f"**AI Summary:**\n{results['summary']}"
        if 'summary' in results else ""
    )
    
    # Format sentiment
    formatted["sentiment"] = (
        f"**Sentiment Analysis:**\n{results['sentiment']}"
        if 'sentiment' in results else ""
    )
    
    # Format topics
    if 'topics' in results:
        topics_list = sorted(
            results['topics'].items(),
            key=lambda x: x[1],
            reverse=True
        )
        topics_text = "\n".join(
            f"- **{topic}**: {score:.1%}" 
            for topic, score in topics_list
        )
        formatted["topics"] = f"**Detected Topics:**\n{topics_text}"
    else:
        formatted["topics"] = ""
    
    return formatted

def validate_url(url: str) -> bool:
    """Basic URL validation"""
    return bool(url and url.strip().startswith(('http://', 'https://')))

def update_button_state(url: str) -> Dict:
    """Update button state based on URL validity"""
    return gr.update(interactive=validate_url(url))

with gr.Blocks(title="Smart Web Analyzer Plus", theme=gr.themes.Soft()) as demo:
    # Header
    gr.Markdown("# 🌐 Smart Web Analyzer Plus")
    gr.Markdown("Analyze web content using AI to extract summaries, determine sentiment, and identify topics.")
    
    # Input Section
    with gr.Row():
        with gr.Column(scale=3):
            url_input = gr.Textbox(
                label="Enter URL",
                placeholder="https://example.com",
                show_label=True
            )
        with gr.Column(scale=2):
            analysis_types = gr.CheckboxGroup(
                choices=["summarize", "sentiment", "topics"],
                label="Analysis Types",
                value=["summarize"],
                show_label=True
            )
        with gr.Column(scale=1):
            analyze_btn = gr.Button(
                "Analyze",
                variant="primary",
                interactive=False
            )
    
    # Content display with single row of tabs
    output_tabs = gr.Tabs([
        gr.Tab("📄 Clean Text", gr.Markdown(label="Clean Text")),
        gr.Tab("📝 Summary", gr.Markdown(label="Summary")),
        gr.Tab("🎭 Sentiment", gr.Markdown(label="Sentiment")),
        gr.Tab("📊 Topics", gr.Markdown(label="Topics"))
    ])
    
    # Loading indicator
    status = gr.Markdown(visible=False)
    
    # Example Section
    gr.Examples(
        label="Try these examples",
        examples=[
            ["https://www.bbc.com/news/technology-67881954", ["summarize", "sentiment"]],
            ["https://arxiv.org/html/2312.17296v1", ["topics", "summarize"]]
        ],
        inputs=[url_input, analysis_types]
    )
    
    # Event Handlers
    url_input.change(
        fn=update_button_state,
        inputs=[url_input],
        outputs=[analyze_btn],
        queue=False
    )
    
    def on_analyze_start():
        return gr.update(value="⏳ Analysis in progress...", visible=True)
    
    def on_analyze_end():
        return gr.update(value="", visible=False)
    
    analyze_btn.click(
        fn=on_analyze_start,
        outputs=[status],
        queue=False
    ).then(
        fn=lambda url, m: format_results(analyzer.analyze(url, m)),
        inputs=[url_input, analysis_types],
        outputs=[
            output_tabs.select(0),  # Clean Text
            output_tabs.select(1),  # Summary
            output_tabs.select(2),  # Sentiment
            output_tabs.select(3)   # Topics
        ]
    ).then(
        fn=on_analyze_end,
        outputs=[status]
    )

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860
    )