app.py

import json
import os
import re
import time
import logging
import mimetypes
import zipfile
import tempfile
from datetime import datetime
from typing import List, Dict, Optional
from pathlib import Path
import requests
import validators
import gradio as gr
from bs4 import BeautifulSoup
from fake_useragent import UserAgent
from cleantext import clean

# Setup logging with detailed configuration
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - [%(filename)s:%(lineno)d] - %(message)s',
    handlers=[
        logging.StreamHandler(),
        logging.FileHandler('app.log', encoding='utf-8')
    ]
)
logger = logging.getLogger(__name__)

class URLProcessor:
    def __init__(self):
        self.session = requests.Session()
        self.timeout = 10  # seconds
        self.session.headers.update({
            'User-Agent': UserAgent().random,
            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
            'Accept-Language': 'en-US,en;q=0.5',
            'Accept-Encoding': 'gzip, deflate, br',
            'Connection': 'keep-alive',
            'Upgrade-Insecure-Requests': '1'
        })

    def advanced_text_cleaning(self, text: str) -> str:
        """Robust text cleaning with version compatibility"""
        try:
            cleaned_text = clean(
                text,
                fix_unicode=True,
                to_ascii=True,
                lower=True,
                no_line_breaks=True,
                no_urls=True,
                no_emails=True,
                no_phone_numbers=True,
                no_numbers=False,
                no_digits=False,
                no_currency_symbols=True,
                no_punct=False
            ).strip()
            return cleaned_text
        except Exception as e:
            logger.warning(f"Text cleaning error: {e}. Using fallback method.")
            text = re.sub(r'[\x00-\x1F\x7F-\x9F]', '', text)  # Remove control characters
            text = text.encode('ascii', 'ignore').decode('ascii')  # Remove non-ASCII characters
            text = re.sub(r'\s+', ' ', text)  # Normalize whitespace
            return text.strip()

    def validate_url(self, url: str) -> Dict:
        """Validate URL format and accessibility"""
        try:
            if not validators.url(url):
                return {'is_valid': False, 'message': 'Invalid URL format'}
            
            response = self.session.head(url, timeout=self.timeout)
            response.raise_for_status()
            return {'is_valid': True, 'message': 'URL is valid and accessible'}
        except Exception as e:
            return {'is_valid': False, 'message': f'URL validation failed: {str(e)}'}

    def fetch_content(self, url: str) -> Optional[Dict]:
        """Universal content fetcher with special case handling"""
        try:
            if 'drive.google.com' in url:
                return self._handle_google_drive(url)
            if 'calendar.google.com' in url and 'ical' in url:
                return self._handle_google_calendar(url)
            return self._fetch_html_content(url)
        except Exception as e:
            logger.error(f"Content fetch failed: {e}")
            return None

    def _handle_google_drive(self, url: str) -> Optional[Dict]:
        """Process Google Drive file links"""
        try:
            file_id = re.search(r'/file/d/([a-zA-Z0-9_-]+)', url)
            if not file_id:
                logger.error(f"Invalid Google Drive URL: {url}")
                return None
                
            direct_url = f"https://drive.google.com/uc?export=download&id={file_id.group(1)}"
            response = self.session.get(direct_url, timeout=self.timeout)
            response.raise_for_status()
            
            return {
                'content': response.text,
                'content_type': response.headers.get('Content-Type', ''),
                'timestamp': datetime.now().isoformat()
            }
        except Exception as e:
            logger.error(f"Google Drive processing failed: {e}")
            return None

    def _handle_google_calendar(self, url: str) -> Optional[Dict]:
        """Process Google Calendar ICS feeds"""
        try:
            response = self.session.get(url, timeout=self.timeout)
            response.raise_for_status()
            return {
                'content': response.text,
                'content_type': 'text/calendar',
                'timestamp': datetime.now().isoformat()
            }
        except Exception as e:
            logger.error(f"Calendar fetch failed: {e}")
            return None

    def _fetch_html_content(self, url: str) -> Optional[Dict]:
        """Standard HTML content processing"""
        try:
            response = self.session.get(url, timeout=self.timeout)
            response.raise_for_status()
            
            soup = BeautifulSoup(response.text, 'html.parser')
            
            for element in soup(['script', 'style', 'nav', 'footer', 'header', 'meta', 'link']):
                element.decompose()
                
            main_content = soup.find('main') or soup.find('article') or soup.body
            
            text_content = main_content.get_text(separator='\n', strip=True)
            cleaned_content = self.advanced_text_cleaning(text_content)
            
            return {
                'content': cleaned_content,
                'content_type': response.headers.get('Content-Type', ''),
                'timestamp': datetime.now().isoformat()
            }
        except Exception as e:
            logger.error(f"HTML processing failed: {e}")
            return None
            
class FileProcessor:
    """Class to handle file processing"""
    
    def __init__(self, max_file_size: int = 2 * 1024 * 1024 * 1024):  # 2GB default
        self.max_file_size = max_file_size
        self.supported_text_extensions = {'.txt', '.md', '.csv', '.json', '.xml'}

    def process_file(self, file) -> List[Dict]:
        """Process uploaded file with enhanced error handling"""
        if not file:
            return []

        dataset = []
        try:
            file_size = os.path.getsize(file.name)
            if file_size > self.max_file_size:
                logger.warning(f"File size ({file_size} bytes) exceeds maximum allowed size")
                return [{"error": f"File size ({file_size} bytes) exceeds maximum allowed size of {self.max_file_size} bytes."}]

            with tempfile.TemporaryDirectory() as temp_dir:
                if zipfile.is_zipfile(file.name):
                    dataset.extend(self._process_zip_file(file.name, temp_dir))
                else:
                    dataset.extend(self._process_single_file(file))

        except Exception as e:
            logger.error(f"Error processing file: {str(e)}")
            return []

        return dataset

    def _process_zip_file(self, zip_path: str, temp_dir: str) -> List[Dict]:
        """Process ZIP file contents"""
        results = []
        with zipfile.ZipFile(zip_path, 'r') as zip_ref:
            zip_ref.extractall(temp_dir)
            for root, _, files in os.walk(temp_dir):
                for filename in files:
                    filepath = os.path.join(root, filename)
                    if self.is_text_file(filepath):
                        try:
                            with open(filepath, 'r', encoding='utf-8', errors='ignore') as f:
                                content = f.read()
                            if content.strip():
                                results.append({
                                    "source": "file",
                                    "filename": filename,
                                    "content": content,
                                    "timestamp": datetime.now().isoformat()
                                })
                        except Exception as e:
                            logger.error(f"Error reading file {filename}: {str(e)}")
        return results

    def _process_single_file(self, file) -> List[Dict]:
        try:
            file_stat = os.stat(file.name)
            with open(file.name, 'r', encoding='utf-8', errors='ignore') as f:
                content = f.read()
            
            return [{
                'source': 'file',
                'filename': os.path.basename(file.name),
                'file_size': file_stat.st_size,
                'mime_type': mimetypes.guess_type(file.name)[0],
                'created': datetime.fromtimestamp(file_stat.st_ctime).isoformat(),
                'modified': datetime.fromtimestamp(file_stat.st_mtime).isoformat(),
                'content': content,
                'timestamp': datetime.now().isoformat()
            }]
        except Exception as e:
            logger.error(f"File processing error: {e}")
            return []

class Chatbot:
    """Simple chatbot that uses provided JSON data for responses."""
    
    def __init__(self):
        self.data = None

    def load_data(self, json_data: str):
        """Load JSON data into the chatbot."""
        try:
            self.data = json.loads(json_data)
            return "Data loaded successfully!"
        except json.JSONDecodeError:
            return "Invalid JSON data. Please check your input."

    def chat(self, user_input: str) -> str:
        """Generate a response based on user input and loaded data."""
        if not self.data:
            return "No data loaded. Please load your JSON data first."

        # Simple keyword-based response logic
        for key, value in self.data.items():
            if key.lower() in user_input.lower():
                return f"{key}: {value}"
        
        return "I don't have information on that. Please ask about something else."

def create_interface():
    """Create a comprehensive Gradio interface with advanced features"""
    
    css = """
    .container { max-width: 1200px; margin: auto; }
    .warning { background-color: #fff3cd; color: #856404; }
    .error { background-color: #f8d7da; color: #721c24; }
    """
    
    with gr.Blocks(css=css, title="Advanced Text & URL Processor") as interface:
        gr.Markdown("# 🌐 Advanced URL & Text Processing Toolkit")
        
        with gr.Tab("URL Processing"):
            url_input = gr.Textbox(
                label="Enter URLs (comma or newline separated)", 
                lines=5,
                placeholder="https://example1.com\nhttps://example2.com"
            )
        
        with gr.Tab("File Input"):
            file_input = gr.File(
                label="Upload text file or ZIP archive",
                file_types=[".txt", ".zip", ".md", ".csv", ".json", ".xml"]
            )

        with gr.Tab("Text Input"):
            text_input = gr.Textbox(
                label="Raw Text Input", 
                lines=5,
                placeholder="Paste your text here..."
            )
        
        with gr.Tab("Chat"):
            json_input = gr.Textbox(
                label="Load JSON Data",
                placeholder="Paste your JSON data here...",
                lines=5
            )
            load_btn = gr.Button("Load Data", variant="primary")
            chat_input = gr.Textbox(
                label="Chat with your data",
                placeholder="Type your question here..."
            )
            chat_output = gr.Textbox(label="Chatbot Response", interactive=False)
        
        process_btn = gr.Button("Process Input", variant="primary")
        
        output_text = gr.Textbox(label="Processing Results", interactive=False)
        output_file = gr.File(label="Processed Output")
        
        # Initialize chatbot
        chatbot = Chatbot()

        def process_all_inputs(urls, file, text):
            """Process all input types with progress tracking"""
            try:
                processor = URLProcessor()
                file_processor = FileProcessor()
                results = []
                
                # Process URLs
                if urls:
                    url_list = re.split(r'[,\n]', urls)
                    url_list = [url.strip() for url in url_list if url.strip()]
                    
                    for url in url_list:
                        validation = processor.validate_url(url)
                        if validation.get('is_valid'):
                            content = processor.fetch_content(url)
                            if content:
                                results.append({
                                    'source': 'url',
                                    'url': url,
                                    'content': content,
                                    'timestamp': datetime.now().isoformat()
                                })
                
                # Process files
                if file:
                    results.extend(file_processor.process_file(file))
        
                # Process text input
                if text:
                    cleaned_text = processor.advanced_text_cleaning(text)
                    results.append({
                        'source': 'direct_input',
                        'content': cleaned_text,
                        'timestamp': datetime.now().isoformat()
                    })
                
                # Generate output
                if results:
                    output_dir = Path('output') / datetime.now().strftime('%Y-%m-%d')
                    output_dir.mkdir(parents=True, exist_ok=True)
                    output_path = output_dir / f'processed_{int(time.time())}.json'
                    
                    with open(output_path, 'w', encoding='utf-8') as f:
                        json.dump(results, f, ensure_ascii=False, indent=2)
                    
                    summary = f"Processed {len(results)} items successfully!"
                    return str(output_path), summary
                else:
                    return None, "No valid content to process."
            
            except Exception as e:
                logger.error(f"Processing error: {e}")
                return None, f"Error: {str(e)}"

        def load_chat_data(json_data):
            """Load JSON data into the chatbot."""
            return chatbot.load_data(json_data)

        def chat_with_data(user_input):
            """Chat with the loaded data."""
            return chatbot.chat(user_input)

        process_btn.click(
            process_all_inputs, 
            inputs=[url_input, file_input, text_input], 
            outputs=[output_file, output_text]
        )

        load_btn.click(
            load_chat_data,
            inputs=json_input,
            outputs=chat_output
        )

        chat_input.submit(
            chat_with_data,
            inputs=chat_input,
            outputs=chat_output
        )
        
        gr.Markdown("""
        ### Usage Guidelines
        - **URL Processing**: Enter valid HTTP/HTTPS URLs
        - **File Input**: Upload text files or ZIP archives
        - **Text Input**: Direct text processing
        - **Chat**: Load JSON data and ask questions about it
        - Advanced cleaning and validation included
        """)
    
    return interface

def main():
    # Configure system settings
    mimetypes.init()
    
    # Create and launch interface
    interface = create_interface()
    
    # Launch with proper configuration
    interface.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        inbrowser=False,  # Disable browser opening in container
        debug=False       # Disable debug mode for production
    )

if __name__ == "__main__":
    main()