app.py

import gradio as gr
from smolagents import CodeAgent, HfApiModel

# Initialize the AI agent
agent = CodeAgent(
    tools=[],
    model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
)

def analyze_content(file_paths, progress=gr.Progress()):
    """Process files and generate report with progress tracking"""
    full_content = []
    
    progress(0, desc="Starting analysis...")
    for i, path in enumerate(file_paths):
        progress(i/len(file_paths), desc=f"Reading {path.split('/')[-1]}...")
        try:
            with open(path, 'r', encoding='utf-8') as f:
                content = f.read()
                full_content.append(f"## {path.split('/')[-1]}\n{content}\n")
        except Exception as e:
            return f"Error processing {path}: {str(e)}", ""

    progress(0.8, desc="Analyzing content...")
    report = agent.run(f"""
    Analyze these documents:
    {"".join(full_content)[:10000]}
    
    Create report with:
    1. Key insights
    2. Important patterns
    3. Actionable recommendations
    4. Supporting evidence
    
    Use markdown formatting with headers.
    """)
    
    progress(1.0, desc="Analysis complete!")
    return report, "Process completed successfully"

with gr.Blocks() as demo:
    gr.Markdown("# Document Analysis System")
    
    with gr.Row():
        file_input = gr.File(
            file_count="multiple",
            file_types=[".txt"],
            label="Upload Documents"
        )
        process_btn = gr.Button("Generate Report", variant="primary")
    
    report_output = gr.Markdown(label="Analysis Report")
    status = gr.Textbox(label="Status", visible=False)

    process_btn.click(
        fn=analyze_content,
        inputs=file_input,
        outputs=[report_output, status],
        show_progress="full"
    )

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True  # Public link enabled
    )