app.py

import gradio as gr
from markitdown import MarkItDown
import google.generativeai as genai
import tempfile
import os
from pathlib import Path

# Initialize MarkItDown
md = MarkItDown()

# Configure Gemini AI
genai.configure(api_key=os.getenv('GEMINI_KEY'))
model = genai.GenerativeModel('gemini-1.5-flash')

def process_with_markitdown(input_path):
    """Process file or URL with MarkItDown and return text content"""
    try:
        result = md.convert(input_path)
        return result.text_content
    except Exception as e:
        return f"Error processing input: {str(e)}"

def save_uploaded_file(file):
    """Save uploaded file to temporary location and return path"""
    if file is None:
        return None
    
    try:
        temp_dir = tempfile.gettempdir()
        temp_path = os.path.join(temp_dir, file.name)
        
        with open(temp_path, 'wb') as f:
            f.write(file.read())
        
        return temp_path
    except Exception as e:
        return f"Error saving file: {str(e)}"

async def summarize_text(text):
    """Summarize the input text using Gemini AI"""
    try:
        prompt = f"""Please provide a concise summary of the following text. Focus on the main points and key takeaways:

{text}

Summary:"""
        
        response = await model.generate_content_async(prompt)
        return response.text
    except Exception as e:
        return f"Error generating summary: {str(e)}"

async def process_input(input_text, uploaded_file=None):
    """Main function to process either URL or uploaded file"""
    try:
        if uploaded_file is not None:
            # Handle file upload
            temp_path = save_uploaded_file(uploaded_file)
            if temp_path.startswith('Error'):
                return temp_path
                
            text = process_with_markitdown(temp_path)
            
            # Clean up temporary file
            try:
                os.remove(temp_path)
            except:
                pass
        
        elif input_text.startswith(('http://', 'https://')):
            # Handle URL
            text = process_with_markitdown(input_text)
        
        else:
            # Handle direct text input
            text = input_text
        
        if text.startswith('Error'):
            return text
            
        # Generate summary using Gemini AI
        summary = await summarize_text(text)
        return summary
    
    except Exception as e:
        return f"Error processing input: {str(e)}"

# Create Gradio interface with drag-and-drop
with gr.Blocks(css="""
    .upload-box { 
        border: 2px dashed #ccc;
        border-radius: 8px;
        padding: 20px;
        text-align: center;
        transition: border-color 0.3s ease;
    }
    .upload-box:hover, .upload-box.dragover {
        border-color: #666;
    }
""") as iface:
    gr.Markdown("# Text Summarization Tool")
    gr.Markdown("Enter a URL, paste text, or drag & drop a file to get a summary.")
    
    with gr.Row():
        input_text = gr.Textbox(
            label="Enter URL or text",
            placeholder="Enter a URL or paste text here...",
            scale=2
        )
    
    with gr.Row():
        file_upload = gr.File(
            label="Drop files here or click to upload",
            file_types=[
                ".pdf", ".docx", ".xlsx", ".csv", ".txt", ".md", 
                ".html", ".htm", ".xml", ".json"
            ],
            file_count="single",
            scale=2,
            elem_classes=["upload-box"]
        )
    
    with gr.Row():
        submit_btn = gr.Button("Summarize", variant="primary")
        clear_btn = gr.Button("Clear")
    
    output_text = gr.Textbox(label="Summary", lines=10)
    
    # Add JavaScript for drag-and-drop highlighting
    gr.JS("""
        function setupDragDrop() {
            const uploadBox = document.querySelector('.upload-box');
            
            ['dragenter', 'dragover'].forEach(eventName => {
                uploadBox.addEventListener(eventName, (e) => {
                    e.preventDefault();
                    uploadBox.classList.add('dragover');
                });
            });
            
            ['dragleave', 'drop'].forEach(eventName => {
                uploadBox.addEventListener(eventName, (e) => {
                    e.preventDefault();
                    uploadBox.classList.remove('dragover');
                });
            });
        }
        
        // Call setup when the page loads
        if (document.readyState === 'complete') {
            setupDragDrop();
        } else {
            window.addEventListener('load', setupDragDrop);
        }
    """)
    
    # Set up event handlers
    submit_btn.click(
        fn=process_input,
        inputs=[input_text, file_upload],
        outputs=output_text
    )
    
    clear_btn.click(
        fn=lambda: (None, None, ""),
        inputs=None,
        outputs=[input_text, file_upload, output_text]
    )
    
    # Add examples
    gr.Examples(
        examples=[
            ["https://example.com/article"],
            ["This is a sample text that needs to be summarized..."],
        ],
        inputs=input_text  genai.configure(api_key=os.getenv('GEMINI_KEY'))
    model = genai.GenerativeModel('gemini-1.5-flash')
    )

if __name__ == "__main__":
    iface.launch()