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):
    """Process files and generate comprehensive report"""
    full_content = []
    
    for path in file_paths:
        try:
            with open(path, 'r', encoding='utf-8') as f:
                content = f.read()
                full_content.append(f"--- {path.split('/')[-1]} ---\n{content}")
        except Exception as e:
            return f"Error processing {path}: {str(e)}"
    
    report = agent.run(f"""
    Analyze these documents and create a detailed report:
    
    {''.join(full_content)[:10000]}  # First 10k characters
    
    Report should include:
    1. Key themes and patterns
    2. Important relationships
    3. Contextual insights
    4. Actionable recommendations
    
    Use professional markdown formatting with headings.
    """)
    
    return report

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")

    process_btn.click(
        fn=analyze_content,
        inputs=file_input,
        outputs=report_output
    )

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