import gradio as gr
from smolagents import load_tool

# Load the tool
web_analyzer = load_tool("MHamdan/web-analyzer", trust_remote_code=True)

def analyze_content(url, mode):
    return web_analyzer(url, mode)

def create_interface():
    with gr.Blocks(title="AI Web Analyzer") as iface:
        gr.Markdown("# 🤖 AI-Powered Web Content Analyzer")
        gr.Markdown("""
        ## Features:
        - 📊 **Analyze**: Complete content analysis with AI summary
        - 📝 **Summarize**: AI-generated multi-section summary
        - 😊 **Sentiment**: Section-by-section sentiment analysis
        - 🎯 **Topics**: AI topic classification
        """)
        
        with gr.Row():
            with gr.Column():
                url_input = gr.Textbox(
                    label="Webpage URL",
                    placeholder="Enter URL to analyze..."
                )
                mode = gr.Dropdown(
                    choices=["analyze", "summarize", "sentiment", "topics"],
                    label="Analysis Mode",
                    value="analyze"
                )
                submit_btn = gr.Button("Analyze Content", variant="primary")
                
            with gr.Column():
                output = gr.Textbox(
                    label="AI Analysis Results",
                    lines=15
                )

        # Example data       
        examples = [
            ["https://www.artificialintelligence-news.com/2024/02/14/openai-anthropic-google-white-house-red-teaming/", "analyze"],
            ["https://www.artificialintelligence-news.com/2024/02/13/ai-21-labs-wordtune-chatgpt-plugin/", "summarize"],
            ["https://www.artificialintelligence-news.com/2024/02/12/google-responds-gemini-ai-historical-images/", "sentiment"],
            ["https://www.artificialintelligence-news.com/2024/02/09/anthropic-claude-3-models-preview/", "topics"]
        ]
        
        gr.Examples(
            examples=examples,
            inputs=[url_input, mode],
            outputs=output,
            fn=analyze_content,
            cache_examples=True
        )
        
        submit_btn.click(
            fn=analyze_content,
            inputs=[url_input, mode],
            outputs=output
        )
    
    return iface

# Create and launch the interface
demo = create_interface()
demo.launch()