# routes/docx_routes.py - DOCX/DOC Upload and Processing Routes

import json
from flask import Blueprint, request, jsonify

from db import get_db
from docx_processor import process_docx_to_markdown
from ai_processor import process_document_smartly
from auth import login_required

docx_bp = Blueprint('docx', __name__)


@docx_bp.route('/api/upload-docx', methods=['POST'])
@login_required
def upload_docx():
    """Upload and process a DOCX or DOC file."""
    if 'file' not in request.files:
        return jsonify({'error': 'No file provided'}), 400
    
    doc_file = request.files['file']
    
    if not doc_file or not doc_file.filename:
        return jsonify({'error': 'Invalid file'}), 400
    
    filename = doc_file.filename.lower()
    if not (filename.endswith('.docx') or filename.endswith('.doc')):
        return jsonify({'error': 'File must be a .docx or .doc file'}), 400
    
    try:
        print(f"📄 Processing Word document: {doc_file.filename}")
        
        file_bytes = doc_file.read()
        print(f"  📏 File size: {len(file_bytes)} bytes")
        
        result = process_docx_to_markdown(file_bytes, doc_file.filename)
        
        # --- AI Powered Smart Reconstruction & Section Tagging ---
        smart_blocks = process_document_smartly(result.get('markdown_blocks', []), result.get('metadata', {}))
        
        block_count = len(smart_blocks)
        image_count = sum(1 for b in smart_blocks if b.get('type') == 'image')
        text_count = block_count - image_count
        
        print(f"✅ Word document processed & reconstructed: {block_count} blocks ({text_count} text, {image_count} images)")
        
        return jsonify({
            'success': True,
            'filename': doc_file.filename,
            'metadata': result.get('metadata', {}),
            'blocks': smart_blocks
        })
        
    except Exception as e:
        import traceback
        traceback.print_exc()
        return jsonify({'error': str(e)}), 500