import json
import os
import shutil
import threading
import uuid
from pathlib import Path
from typing import Dict, List, Optional
from flask import Flask, render_template, request, jsonify, send_file, send_from_directory
from flask_cors import CORS
from werkzeug.utils import secure_filename
import torch

import main as extractor
from loguru import logger

app = Flask(__name__)
# Enable CORS for all routes
CORS(app, resources={r"/api/*": {"origins": "*"}})
app.config['MAX_CONTENT_LENGTH'] = 500 * 1024 * 1024  # 500MB max file size
app.config['UPLOAD_FOLDER'] = './uploads'
app.config['OUTPUT_FOLDER'] = './output'

# Ensure directories exist
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
os.makedirs(app.config['OUTPUT_FOLDER'], exist_ok=True)

# Global model instance
_model = None

# Progress tracking: {task_id: {'status': 'processing'|'completed'|'error', 'progress': 0-100, 'message': str, 'results': [], 'file_progress': {filename: progress}}}
_progress_tracker: Dict[str, Dict] = {}
_progress_lock = threading.RLock()  # Use RLock for reentrant locking


def get_device_info() -> Dict[str, any]:
    """Get information about GPU/CPU availability."""
    cuda_available = torch.cuda.is_available()
    device = "cuda" if cuda_available else "cpu"
    
    info = {
        "device": device,
        "cuda_available": cuda_available,
        "device_name": None,
        "device_count": 0,
    }
    
    if cuda_available:
        info["device_name"] = torch.cuda.get_device_name(0)
        info["device_count"] = torch.cuda.device_count()
    
    return info


def load_model_once():
    """Load the model once and cache it."""
    global _model
    if _model is None:
        logger.info("Loading DocLayout-YOLO model...")
        _model = extractor.get_model()
        logger.info("Model loaded successfully")
    return _model


@app.route('/')
def index():
    """Main page."""
    device_info = get_device_info()
    return render_template('index.html', device_info=device_info)


@app.route('/api/docs')
def api_docs():
    """API documentation page showing all available endpoints."""
    routes = []
    for rule in app.url_map.iter_rules():
        if rule.rule.startswith('/api') or rule.rule.startswith('/output'):
            methods = ','.join(sorted(rule.methods - {'OPTIONS', 'HEAD'}))
            func = app.view_functions.get(rule.endpoint)
            doc = func.__doc__ if func and hasattr(func, '__doc__') else 'No description'
            
            routes.append({
                'endpoint': rule.rule,
                'methods': methods,
                'description': doc.strip() if doc else 'No description'
            })
    
    # Force HTTPS for Hugging Face Spaces (always use HTTPS)
    base_url = request.host_url.rstrip('/')
    if base_url.startswith('http://'):
        base_url = base_url.replace('http://', 'https://')
    return render_template('api_docs.html', routes=routes, base_url=base_url)


@app.route('/api/predict', methods=['POST', 'GET'])
def predict():
    # Handle GET requests with info message
    if request.method == 'GET':
        return jsonify({
            'status': 'info',
            'message': 'This endpoint accepts POST requests only. Please use POST method with a PDF file in the "file" field.',
            'usage': {
                'method': 'POST',
                'content_type': 'multipart/form-data',
                'body': {
                    'file': 'PDF file to process'
                },
                'example_curl': 'curl -X POST https://saifisvibin-volaris-pdf-tool.hf.space/api/predict -F "file=@document.pdf"'
            }
        }), 405
    """
    Clean REST API endpoint for PDF extraction.
    Accepts a PDF file and returns extracted text, tables, and figures.
    
    Request:
        - Method: POST
        - Content-Type: multipart/form-data
        - Body: file (PDF file)
    
    Response:
        {
            "status": "success",
            "filename": "document.pdf",
            "text": "extracted markdown text...",
            "tables": [...],
            "figures": [...],
            "summary": {...}
        }
    """
    try:
        # Check if file is present
        if 'file' not in request.files:
            return jsonify({
                'status': 'error',
                'error': 'No file provided. Please upload a PDF file using the "file" field.'
            }), 400
        
        file = request.files['file']
        
        if file.filename == '':
            return jsonify({
                'status': 'error',
                'error': 'No file selected'
            }), 400
        
        if not file.filename.lower().endswith('.pdf'):
            return jsonify({
                'status': 'error',
                'error': 'Invalid file type. Please upload a PDF file.'
            }), 400
        
        filename = secure_filename(file.filename)
        stem = Path(filename).stem
        
        # Create a permanent output directory for this request (using stem + timestamp for uniqueness)
        import time
        unique_id = f"{stem}_{int(time.time())}"
        output_dir = Path(app.config['OUTPUT_FOLDER']) / unique_id
        output_dir.mkdir(parents=True, exist_ok=True)
        
        # Create temporary upload directory
        temp_upload = Path(app.config['UPLOAD_FOLDER']) / f"temp_{uuid.uuid4().hex}"
        temp_upload.mkdir(parents=True, exist_ok=True)
        
        try:
            # Save uploaded file
            pdf_path = temp_upload / filename
            file_data = file.read()
            pdf_path.write_bytes(file_data)
            
            # Load model if needed
            load_model_once()
            
            # Process PDF (extract both images and markdown)
            extractor.USE_MULTIPROCESSING = False
            extractor.process_pdf_with_pool(
                pdf_path,
                output_dir,
                pool=None,
                extract_images=True,
                extract_markdown=True,
            )
            
            # Collect extracted data
            result = {
                'status': 'success',
                'filename': filename,
                'text': '',
                'tables': [],
                'figures': [],
                'summary': {
                    'total_pages': 0,
                    'figures_count': 0,
                    'tables_count': 0,
                    'elements_count': 0
                }
            }
            
            # Extract markdown text
            markdown_path = output_dir / f"{stem}.md"
            if markdown_path.exists():
                result['text'] = markdown_path.read_text(encoding='utf-8')
            
            # Get base URL for constructing full image URLs
            base_url = request.host_url.rstrip('/')
            if 'hf.space' in base_url:
                # Force HTTPS for Hugging Face Spaces
                base_url = base_url.replace('http://', 'https://')
            
            # Extract figures and tables from JSON
            json_path = output_dir / f"{stem}_content_list.json"
            if json_path.exists():
                elements = json.loads(json_path.read_text(encoding='utf-8'))
                
                figures = [e for e in elements if e.get('type') == 'figure']
                tables = [e for e in elements if e.get('type') == 'table']
                
                # Get page count
                try:
                    import pypdfium2 as pdfium
                    pdf_bytes = pdf_path.read_bytes()
                    doc = pdfium.PdfDocument(pdf_bytes)
                    result['summary']['total_pages'] = len(doc)
                    doc.close()
                except:
                    pass
                
                # Format figures
                for fig in figures:
                    figure_data = {
                        'page': fig.get('page', 0),
                        'bbox': fig.get('bbox_pixels', []),
                        'confidence': fig.get('conf', 0.0),
                        'width': fig.get('width', 0),
                        'height': fig.get('height', 0),
                    }
                    
                    # Include image URL if available
                    if fig.get('image_path'):
                        img_path = output_dir / fig['image_path']
                        if img_path.exists():
                            # Get relative path from OUTPUT_FOLDER
                            relative_path = str(img_path.relative_to(app.config['OUTPUT_FOLDER']))
                            # Construct full URL
                            image_url = f"{base_url}/output/{relative_path}"
                            figure_data['image_url'] = image_url
                            figure_data['image_path'] = relative_path
                    
                    result['figures'].append(figure_data)
                
                # Format tables
                for tab in tables:
                    table_data = {
                        'page': tab.get('page', 0),
                        'bbox': tab.get('bbox_pixels', []),
                        'confidence': tab.get('conf', 0.0),
                        'width': tab.get('width', 0),
                        'height': tab.get('height', 0),
                    }
                    
                    # Include image URL if available
                    if tab.get('image_path'):
                        img_path = output_dir / tab['image_path']
                        if img_path.exists():
                            # Get relative path from OUTPUT_FOLDER
                            relative_path = str(img_path.relative_to(app.config['OUTPUT_FOLDER']))
                            # Construct full URL
                            image_url = f"{base_url}/output/{relative_path}"
                            table_data['image_url'] = image_url
                            table_data['image_path'] = relative_path
                    
                    result['tables'].append(table_data)
                
                result['summary']['figures_count'] = len(figures)
                result['summary']['tables_count'] = len(tables)
                result['summary']['elements_count'] = len(elements)
            
            return jsonify(result)
            
        finally:
            # Clean up temporary upload directory only (keep output_dir for file access)
            try:
                if temp_upload.exists():
                    if temp_upload.is_file():
                        temp_upload.unlink()
                    else:
                        shutil.rmtree(temp_upload, ignore_errors=True)
            except Exception as e:
                logger.warning(f"Error cleaning up temp upload files: {e}")
    
    except Exception as e:
        logger.error(f"Error in /api/predict: {e}")
        import traceback
        logger.error(traceback.format_exc())
        return jsonify({
            'status': 'error',
            'error': str(e)
        }), 500


@app.route('/api/device-info')
def device_info():
    """API endpoint to get device information."""
    return jsonify(get_device_info())


def _update_task_progress(task_id: str, filename: str, file_progress: int, message: str):
    """Update progress for a specific file and calculate overall progress."""
    with _progress_lock:
        if task_id not in _progress_tracker:
            return
        
        # Update file-specific progress
        if 'file_progress' not in _progress_tracker[task_id]:
            _progress_tracker[task_id]['file_progress'] = {}
        _progress_tracker[task_id]['file_progress'][filename] = file_progress
        
        # Calculate overall progress (average of all files)
        file_progresses = _progress_tracker[task_id]['file_progress']
        if file_progresses:
            total_progress = sum(file_progresses.values()) / len(file_progresses)
            _progress_tracker[task_id]['progress'] = int(total_progress)
        
        _progress_tracker[task_id]['message'] = message


def process_file_background(task_id: str, file_data: bytes, filename: str, extraction_mode: str):
    """Process a single file in the background and update progress."""
    filename = secure_filename(filename)
    
    try:
        _update_task_progress(task_id, filename, 5, f'Processing {filename}...')
        
        stem = Path(filename).stem
        include_images = extraction_mode != 'markdown'
        include_markdown = extraction_mode != 'images'
        
        # Ensure upload directory exists
        upload_dir = Path(app.config['UPLOAD_FOLDER'])
        upload_dir.mkdir(parents=True, exist_ok=True)
        
        # Save uploaded file from bytes data
        upload_path = upload_dir / filename
        upload_path.write_bytes(file_data)
        
        _update_task_progress(task_id, filename, 15, f'Saved {filename}, preparing output...')
        
        # Prepare output directory
        output_dir = Path(app.config['OUTPUT_FOLDER']) / stem
        output_dir.mkdir(parents=True, exist_ok=True)
        
        # Copy PDF to output directory
        pdf_path = output_dir / filename
        upload_path.rename(pdf_path)
        
        _update_task_progress(task_id, filename, 25, f'Loading model and processing {filename}...')
        
        # Process PDF
        extractor.USE_MULTIPROCESSING = False
        logger.info(f"Processing {filename} (images={include_images}, markdown={include_markdown})")
        
        if include_images:
            try:
                load_model_once()
                logger.info(f"Model loaded successfully for {filename}")
            except Exception as model_error:
                logger.error(f"Failed to load model for {filename}: {model_error}")
                import traceback
                logger.error(traceback.format_exc())
                raise Exception(f"Model loading failed: {str(model_error)}. The processing service may be unavailable.")
        
        _update_task_progress(task_id, filename, 30, f'Extracting content from {filename}...')
        
        extractor.process_pdf_with_pool(
            pdf_path,
            output_dir,
            pool=None,
            extract_images=include_images,
            extract_markdown=include_markdown,
        )
        
        _update_task_progress(task_id, filename, 85, f'Collecting results for {filename}...')
        
        # Collect results
        json_path = output_dir / f"{stem}_content_list.json"
        elements = []
        if include_images and json_path.exists():
            elements = json.loads(json_path.read_text(encoding='utf-8'))
        
        annotated_pdf = None
        if include_images:
            candidate_pdf = output_dir / f"{stem}_layout.pdf"
            if candidate_pdf.exists():
                annotated_pdf = str(candidate_pdf.relative_to(app.config['OUTPUT_FOLDER']))
        
        markdown_path = None
        if include_markdown:
            candidate_md = output_dir / f"{stem}.md"
            if candidate_md.exists():
                markdown_path = str(candidate_md.relative_to(app.config['OUTPUT_FOLDER']))
        
        # Get figure and table counts
        figures = [e for e in elements if e.get('type') == 'figure']
        tables = [e for e in elements if e.get('type') == 'table']
        
        # Get base URL for constructing full URLs
        # Note: We can't use request.host_url here since we're in a background thread
        # So we'll construct URLs that will be completed in the API endpoint
        result = {
            'filename': filename,
            'stem': stem,
            'output_dir': str(output_dir.relative_to(app.config['OUTPUT_FOLDER'])),
            'figures_count': len(figures),
            'tables_count': len(tables),
            'elements_count': len(elements),
            'annotated_pdf': annotated_pdf,
            'markdown_path': markdown_path,
            'include_images': include_images,
            'include_markdown': include_markdown,
        }
        
        with _progress_lock:
            # Update file progress to 100%
            if 'file_progress' not in _progress_tracker[task_id]:
                _progress_tracker[task_id]['file_progress'] = {}
            _progress_tracker[task_id]['file_progress'][filename] = 100
            
            # Calculate overall progress
            file_progresses = _progress_tracker[task_id]['file_progress']
            if file_progresses:
                total_progress = sum(file_progresses.values()) / len(file_progresses)
                _progress_tracker[task_id]['progress'] = int(total_progress)
            
            # Add result
            _progress_tracker[task_id]['results'].append(result)
            _progress_tracker[task_id]['message'] = f'Completed processing {filename}'
            
            # Check if all files are done
            total_files = _progress_tracker[task_id].get('total_files', 1)
            completed_count = len([r for r in _progress_tracker[task_id]['results'] if 'error' not in r])
            error_count = len([r for r in _progress_tracker[task_id]['results'] if 'error' in r])
            
            if completed_count + error_count >= total_files:
                if error_count == 0:
                    _progress_tracker[task_id]['status'] = 'completed'
                    _progress_tracker[task_id]['progress'] = 100
                    _progress_tracker[task_id]['message'] = f'All {total_files} file(s) processed successfully'
                else:
                    _progress_tracker[task_id]['status'] = 'completed'  # Still mark as completed even with some errors
                    _progress_tracker[task_id]['message'] = f'Processing complete: {completed_count} succeeded, {error_count} failed'
        
    except Exception as e:
        logger.error(f"Error processing {filename}: {e}")
        import traceback
        logger.error(traceback.format_exc())
        with _progress_lock:
            _progress_tracker[task_id]['results'].append({
                'filename': filename,
                'error': str(e)
            })
            # Check if this was the last file
            total_files = _progress_tracker[task_id].get('total_files', 1)
            if len(_progress_tracker[task_id]['results']) >= total_files:
                _progress_tracker[task_id]['status'] = 'error'
                _progress_tracker[task_id]['message'] = f'Error processing {filename}: {str(e)}'


@app.route('/api/upload', methods=['POST'])
def upload_files():
    """Handle multiple PDF file uploads with background processing."""
    if 'files[]' not in request.files:
        return jsonify({'error': 'No files provided'}), 400
    
    files = request.files.getlist('files[]')
    extraction_mode = request.form.get('extraction_mode', 'images')
    
    if not files or all(f.filename == '' for f in files):
        return jsonify({'error': 'No files selected'}), 400
    
    # Create a task ID for this upload
    task_id = str(uuid.uuid4())
    
    # Initialize progress tracking
    with _progress_lock:
        _progress_tracker[task_id] = {
            'status': 'processing',
            'progress': 0,
            'message': 'Starting upload...',
            'results': [],
            'total_files': len([f for f in files if f.filename.endswith('.pdf')])
        }
    
    # Process files in background threads
    # Read file data before starting threads to avoid "read of closed file" error
    threads = []
    started_count = 0
    for file in files:
        if file and file.filename.endswith('.pdf'):
            try:
                # Read file data into memory before starting background thread
                # This prevents "read of closed file" errors when request context ends
                file_data = file.read()
                file.seek(0)  # Reset file pointer for potential reuse
                filename = file.filename
                
                if not file_data:
                    logger.warning(f"Empty file data for {filename}")
                    with _progress_lock:
                        _progress_tracker[task_id]['results'].append({
                            'filename': filename,
                            'error': 'File is empty or could not be read'
                        })
                    continue
                
                thread = threading.Thread(
                    target=process_file_background,
                    args=(task_id, file_data, filename, extraction_mode)
                )
                thread.daemon = True
                thread.start()
                threads.append(thread)
                started_count += 1
                logger.info(f"Started background thread for {filename}")
            except Exception as e:
                logger.error(f"Failed to start processing thread for {file.filename}: {e}")
                import traceback
                logger.error(traceback.format_exc())
                with _progress_lock:
                    _progress_tracker[task_id]['results'].append({
                        'filename': file.filename,
                        'error': f'Failed to start processing: {str(e)}'
                    })
    
    # Check if any threads were started
    if started_count == 0:
        with _progress_lock:
            _progress_tracker[task_id]['status'] = 'error'
            _progress_tracker[task_id]['message'] = 'No files could be processed. Check file format and size.'
        return jsonify({
            'error': 'No files could be processed',
            'task_id': task_id,
            'message': 'Processing could not be started. Please check your files and try again.'
        }), 400
    
    # Return task ID immediately
    return jsonify({
        'task_id': task_id,
        'message': 'Processing started',
        'total_files': started_count
    })


@app.route('/api/progress/<task_id>')
def get_progress(task_id):
    """Get progress for a processing task."""
    with _progress_lock:
        progress = _progress_tracker.get(task_id)
        if not progress:
            return jsonify({'error': 'Task not found'}), 404
        
        # Get base URL for constructing full URLs
        base_url = request.host_url.rstrip('/')
        if 'hf.space' in base_url:
            # Force HTTPS for Hugging Face Spaces
            base_url = base_url.replace('http://', 'https://')
        
        # Add full URLs to results if they exist
        if 'results' in progress:
            for result in progress['results']:
                # Add full URL for annotated PDF
                if result.get('annotated_pdf'):
                    result['annotated_pdf_url'] = f"{base_url}/output/{result['annotated_pdf']}"
                
                # Add full URL for markdown
                if result.get('markdown_path'):
                    result['markdown_url'] = f"{base_url}/output/{result['markdown_path']}"
                
                # Add image URLs for figures and tables if available
                output_dir = Path(app.config['OUTPUT_FOLDER']) / result.get('stem', '')
                if output_dir.exists():
                    # Load content list to get figure and table image paths
                    json_files = list(output_dir.glob('*_content_list.json'))
                    if json_files:
                        try:
                            elements = json.loads(json_files[0].read_text(encoding='utf-8'))
                            figures = [e for e in elements if e.get('type') == 'figure']
                            tables = [e for e in elements if e.get('type') == 'table']
                            
                            # Add figure URLs
                            figure_urls = []
                            for fig in figures:
                                if fig.get('image_path'):
                                    img_path = output_dir / fig['image_path']
                                    if img_path.exists():
                                        relative_path = str(img_path.relative_to(app.config['OUTPUT_FOLDER']))
                                        figure_urls.append({
                                            'page': fig.get('page', 0),
                                            'url': f"{base_url}/output/{relative_path}",
                                            'path': relative_path
                                        })
                            
                            # Add table URLs
                            table_urls = []
                            for tab in tables:
                                if tab.get('image_path'):
                                    img_path = output_dir / tab['image_path']
                                    if img_path.exists():
                                        relative_path = str(img_path.relative_to(app.config['OUTPUT_FOLDER']))
                                        table_urls.append({
                                            'page': tab.get('page', 0),
                                            'url': f"{base_url}/output/{relative_path}",
                                            'path': relative_path
                                        })
                            
                            if figure_urls:
                                result['figure_urls'] = figure_urls
                            if table_urls:
                                result['table_urls'] = table_urls
                        except Exception as e:
                            logger.warning(f"Error loading image URLs for {result.get('stem')}: {e}")
        
        return jsonify(progress)


@app.route('/api/pdf-list')
def pdf_list():
    """Get list of processed PDFs."""
    output_dir = Path(app.config['OUTPUT_FOLDER'])
    pdfs = []
    
    for item in output_dir.iterdir():
        if item.is_dir():
            # Check if this directory has processed content
            json_files = list(item.glob('*_content_list.json'))
            md_files = list(item.glob('*.md'))
            pdf_files = list(item.glob('*.pdf'))
            
            if json_files or md_files or pdf_files:
                stem = item.name
                pdfs.append({
                    'stem': stem,
                    'output_dir': str(item.relative_to(app.config['OUTPUT_FOLDER'])),
                })
    
    return jsonify({'pdfs': pdfs})


@app.route('/api/pdf-details/<path:pdf_stem>')
def pdf_details(pdf_stem):
    """Get detailed information about a processed PDF."""
    output_dir = Path(app.config['OUTPUT_FOLDER']) / pdf_stem
    
    if not output_dir.exists():
        return jsonify({'error': 'PDF not found'}), 404
    
    # Get base URL for constructing full URLs
    base_url = request.host_url.rstrip('/')
    if 'hf.space' in base_url:
        # Force HTTPS for Hugging Face Spaces
        base_url = base_url.replace('http://', 'https://')
    
    # Load content list
    json_files = list(output_dir.glob('*_content_list.json'))
    elements = []
    if json_files:
        elements = json.loads(json_files[0].read_text(encoding='utf-8'))
    
    # Get figures and tables
    figures = [e for e in elements if e.get('type') == 'figure']
    tables = [e for e in elements if e.get('type') == 'table']
    
    # Get file paths
    annotated_pdf = None
    pdf_files = list(output_dir.glob('*_layout.pdf'))
    if pdf_files:
        annotated_pdf = str(pdf_files[0].relative_to(app.config['OUTPUT_FOLDER']))
    
    markdown_path = None
    md_files = list(output_dir.glob('*.md'))
    if md_files:
        markdown_path = str(md_files[0].relative_to(app.config['OUTPUT_FOLDER']))
    
    # Get figure and table images
    figure_dir = output_dir / 'figures'
    table_dir = output_dir / 'tables'
    
    figure_images = []
    if figure_dir.exists():
        figure_images = [str(f.relative_to(app.config['OUTPUT_FOLDER'])) 
                        for f in sorted(figure_dir.glob('*.png'))]
    
    table_images = []
    if table_dir.exists():
        table_images = [str(t.relative_to(app.config['OUTPUT_FOLDER'])) 
                       for t in sorted(table_dir.glob('*.png'))]
    
    return jsonify({
        'stem': pdf_stem,
        'figures': figures,
        'tables': tables,
        'figures_count': len(figures),
        'tables_count': len(tables),
        'elements_count': len(elements),
        'annotated_pdf': annotated_pdf,
        'markdown_path': markdown_path,
        'figure_images': figure_images,
        'table_images': table_images,
        # Add full URLs for direct access
        'urls': {
            'annotated_pdf': f"{base_url}/output/{annotated_pdf}" if annotated_pdf else None,
            'markdown': f"{base_url}/output/{markdown_path}" if markdown_path else None,
            'figures': [f"{base_url}/output/{img}" for img in figure_images] if figure_images else [],
            'tables': [f"{base_url}/output/{img}" for img in table_images] if table_images else [],
        },
        # Keep relative paths for backward compatibility
        'download_urls': {
            'annotated_pdf': f"/output/{annotated_pdf}" if annotated_pdf else None,
            'markdown': f"/output/{markdown_path}" if markdown_path else None,
            'figures': [f"/output/{img}" for img in figure_images] if figure_images else [],
            'tables': [f"/output/{img}" for img in table_images] if table_images else [],
        }
    })


@app.route('/output/<path:filename>')
def output_file(filename):
    """Serve output files (PDFs, images, markdown)."""
    try:
        output_folder = Path(app.config['OUTPUT_FOLDER']).resolve()
        file_path = (output_folder / filename).resolve()
        
        # Security: Prevent path traversal attacks
        if not str(file_path).startswith(str(output_folder)):
            return jsonify({'error': 'Invalid file path'}), 400
        
        # Check if file exists
        if not file_path.exists():
            return jsonify({
                'error': 'File not found',
                'requested_path': filename,
                'hint': 'Use /api/pdf-details/<stem> to get correct file paths'
            }), 404
        
        if not file_path.is_file():
            return jsonify({'error': 'Path is not a file'}), 400
        
        # Determine MIME type based on extension
        mime_types = {
            '.pdf': 'application/pdf',
            '.png': 'image/png',
            '.jpg': 'image/jpeg',
            '.jpeg': 'image/jpeg',
            '.md': 'text/markdown',
            '.json': 'application/json',
            '.txt': 'text/plain'
        }
        
        ext = file_path.suffix.lower()
        mimetype = mime_types.get(ext, 'application/octet-stream')
        
        return send_file(str(file_path), mimetype=mimetype, as_attachment=False)
    
    except Exception as e:
        logger.error(f"Error serving file {filename}: {e}")
        return jsonify({
            'error': 'Failed to serve file',
            'message': str(e)
        }), 500


def _delete_by_stem(stem_raw: str):
    stem = (stem_raw or "").strip()
    if not stem:
        return jsonify({'error': 'Missing stem'}), 400

    # Resolve output directory safely
    output_root = Path(app.config['OUTPUT_FOLDER']).resolve()
    target_dir = (output_root / stem).resolve()

    # Prevent path traversal - ensure target is within output_root
    if output_root not in target_dir.parents and target_dir != output_root:
        return jsonify({'error': 'Invalid stem path'}), 400

    if not target_dir.exists() or not target_dir.is_dir():
        return jsonify({'error': 'Not found'}), 404

    # Delete the directory
    shutil.rmtree(target_dir, ignore_errors=False)
    logger.info(f"Deleted processed output: {target_dir}")

    return jsonify({'ok': True, 'deleted': stem})


@app.route('/api/delete', methods=['POST'])
def delete_pdf():
    """Delete a processed PDF directory by stem (JSON or form body)."""
    try:
        data = request.get_json(silent=True) or {}
        stem = (data.get('stem') or request.form.get('stem') or '').strip()
        return _delete_by_stem(stem)
    except Exception as e:
        logger.error(f"Delete failed: {e}")
        return jsonify({'error': str(e)}), 500


@app.route('/api/delete/<path:stem>', methods=['POST', 'GET'])
def delete_pdf_by_path(stem: str):
    """Alternate endpoint to delete using URL path, for clients avoiding bodies."""
    try:
        return _delete_by_stem(stem)
    except Exception as e:
        logger.error(f"Delete failed: {e}")
        return jsonify({'error': str(e)}), 500


if __name__ == '__main__':
    # Run on port 7860 for Hugging Face Spaces, or 5000 for local development
    port = int(os.environ.get('PORT', 7860))
    app.run(debug=False, host='0.0.0.0', port=port)