updated_word.py

import json
from docx import Document
from docx.shared import RGBColor
import re

def load_json(filepath):
    with open(filepath, 'r') as file:
        return json.load(file)

def flatten_json_new_system(json_data):
    """Flatten your new JSON structure to work with replacement logic"""
    flat_json = {}
    
    for schema_name, schema_data in json_data.items():
        if isinstance(schema_data, dict):
            for field_name, values in schema_data.items():
                # Handle list values (your system returns lists)
                if isinstance(values, list) and values:
                    value = values[0] if len(values) == 1 else values
                else:
                    value = values
                
                # Add multiple key variations for better matching
                flat_json[field_name] = value
                flat_json[field_name.lower()] = value
                flat_json[field_name.lower().strip()] = value
                
                # Add schema-prefixed keys
                flat_json[f"{schema_name}.{field_name}"] = value
                flat_json[f"{schema_name.lower()}.{field_name.lower()}"] = value
                
                # Special mappings for common cases
                if "print name" in field_name.lower():
                    flat_json["print name"] = value
                    flat_json["operator name"] = value
                    flat_json["name"] = value
                    
                if "position title" in field_name.lower():
                    flat_json["position title"] = value
                    flat_json["position"] = value
                    flat_json["title"] = value
                    
                if "accreditation number" in field_name.lower():
                    flat_json["accreditation number"] = value
                    flat_json["nhvas accreditation no"] = value
                    
                if "expiry date" in field_name.lower():
                    flat_json["expiry date"] = value
                    flat_json["expiry"] = value
    
    return flat_json

def is_red(run):
    """Detect red colored text"""
    color = run.font.color
    return color and (color.rgb == RGBColor(255, 0, 0) or getattr(color, "theme_color", None) == 1)

def get_value_as_string(value, field_name=""):
    """Convert value to string, handling lists appropriately"""
    if isinstance(value, list):
        if len(value) == 0:
            return ""
        elif len(value) == 1:
            return str(value[0])
        else:
            if "australian company number" in field_name.lower() or "company number" in field_name.lower():
                return value  # Return as list for ACN processing
            else:
                return " ".join(str(v) for v in value)
    else:
        return str(value)

def find_matching_json_value(field_name, flat_json):
    """Enhanced matching for your new JSON structure"""
    field_name = field_name.strip()
    
    # Direct match (exact)
    if field_name in flat_json:
        print(f"    ✅ Direct match found for key '{field_name}'")
        return flat_json[field_name]
    
    # Case-insensitive exact match
    for key, value in flat_json.items():
        if key.lower() == field_name.lower():
            print(f"    ✅ Case-insensitive match found for key '{field_name}' with JSON key '{key}'")
            return value
    
    # Partial matching for common field names
    field_lower = field_name.lower().strip()
    
    # Handle common variations
    if "print name" in field_lower:
        for key in ["Print Name", "print name", "operator name", "name"]:
            if key in flat_json:
                print(f"    ✅ Print name match: '{field_name}' -> '{key}'")
                return flat_json[key]
    
    if "position title" in field_lower:
        for key in ["Position Title", "position title", "position", "title"]:
            if key in flat_json:
                print(f"    ✅ Position title match: '{field_name}' -> '{key}'")
                return flat_json[key]
    
    if "accreditation number" in field_lower:
        for key in flat_json.keys():
            if "accreditation" in key.lower() and "number" in key.lower():
                print(f"    ✅ Accreditation number match: '{field_name}' -> '{key}'")
                return flat_json[key]
    
    if "expiry date" in field_lower:
        for key in flat_json.keys():
            if "expiry" in key.lower():
                print(f"    ✅ Expiry date match: '{field_name}' -> '{key}'")
                return flat_json[key]
    
    # Fuzzy matching
    field_words = set(word.lower() for word in re.findall(r'\b\w+\b', field_name) if len(word) > 2)
    if not field_words:
        return None
    
    best_match = None
    best_score = 0
    best_key = None
    
    for key, value in flat_json.items():
        key_words = set(word.lower() for word in re.findall(r'\b\w+\b', key) if len(word) > 2)
        if not key_words:
            continue
            
        common_words = field_words.intersection(key_words)
        if common_words:
            similarity = len(common_words) / len(field_words.union(key_words))
            coverage = len(common_words) / len(field_words)
            final_score = (similarity * 0.6) + (coverage * 0.4)
            
            if final_score > best_score:
                best_score = final_score
                best_match = value
                best_key = key
    
    if best_match and best_score >= 0.25:
        print(f"    ✅ Fuzzy match found for key '{field_name}' with JSON key '{best_key}' (score: {best_score:.2f})")
        return best_match
    
    print(f"    ❌ No match found for '{field_name}'")
    return None

def get_clean_text(cell):
    """Extract clean text from cell"""
    text = ""
    for paragraph in cell.paragraphs:
        for run in paragraph.runs:
            text += run.text
    return text.strip()

def has_red_text(cell):
    """Check if cell has red text"""
    for paragraph in cell.paragraphs:
        for run in paragraph.runs:
            if is_red(run) and run.text.strip():
                return True
    return False

def replace_red_text_in_cell(cell, replacement_text):
    """Replace red text in cell with new text"""
    replacements_made = 0
    
    for paragraph in cell.paragraphs:
        for run in paragraph.runs:
            if is_red(run) and run.text.strip():
                run.text = replacement_text
                run.font.color.rgb = RGBColor(0, 0, 0)  # Change to black
                replacements_made += 1
                break  # Only replace first red text found
    
    return replacements_made

def handle_australian_company_number(row, company_numbers):
    """Handle ACN digit placement"""
    replacements_made = 0
    for i, digit in enumerate(company_numbers):
        cell_idx = i + 1
        if cell_idx < len(row.cells):
            cell = row.cells[cell_idx]
            if has_red_text(cell):
                cell_replacements = replace_red_text_in_cell(cell, str(digit))
                replacements_made += cell_replacements
                print(f"      -> Placed digit '{digit}' in cell {cell_idx + 1}")
    return replacements_made

def handle_nature_business_section(cell, flat_json):
    """Handle Nature of Business section with sub-fields"""
    if not has_red_text(cell):
        return 0
    
    cell_text = get_clean_text(cell).lower()
    if "nature of the operators business" not in cell_text and "nature of the operator business" not in cell_text:
        return 0
    
    print(f"    🎯 Found Nature of Business section")
    
    # Check for business description
    for key in flat_json.keys():
        if "nature of the operators business" in key.lower():
            business_value = flat_json[key]
            replacement_text = get_value_as_string(business_value)
            cell_replacements = replace_red_text_in_cell(cell, replacement_text)
            if cell_replacements > 0:
                print(f"      ✅ Updated business description")
                return cell_replacements
    
    return 0

def handle_operator_declaration_table(table, flat_json):
    """Handle Operator Declaration table specifically"""
    replacements_made = 0
    
    for row_idx, row in enumerate(table.rows):
        if len(row.cells) >= 2:
            cell1_text = get_clean_text(row.cells[0]).strip()
            cell2_text = get_clean_text(row.cells[1]).strip()
            
            # Check if this is the Print Name / Position Title header row
            if ("print name" in cell1_text.lower() and "position title" in cell2_text.lower()):
                print(f"    🎯 Found Operator Declaration table")
                
                # Look for data row
                if row_idx + 1 < len(table.rows):
                    data_row = table.rows[row_idx + 1]
                    if len(data_row.cells) >= 2:
                        name_cell = data_row.cells[0]
                        position_cell = data_row.cells[1]
                        
                        # Update Print Name
                        if has_red_text(name_cell):
                            name_value = None
                            for key in ["Print Name", "print name", "Operator Declaration.Print Name"]:
                                if key in flat_json:
                                    name_value = flat_json[key]
                                    break
                            
                            if name_value:
                                name_text = get_value_as_string(name_value)
                                cell_replacements = replace_red_text_in_cell(name_cell, name_text)
                                replacements_made += cell_replacements
                                print(f"        ✅ Updated Print Name: '{name_text}'")
                        
                        # Update Position Title
                        if has_red_text(position_cell):
                            position_value = None
                            for key in ["Position Title", "position title", "Operator Declaration.Position Title"]:
                                if key in flat_json:
                                    position_value = flat_json[key]
                                    break
                            
                            if position_value:
                                position_text = get_value_as_string(position_value)
                                cell_replacements = replace_red_text_in_cell(position_cell, position_text)
                                replacements_made += cell_replacements
                                print(f"        ✅ Updated Position Title: '{position_text}'")
                
                break
    
    return replacements_made

def process_tables(document, flat_json):
    """Process all tables in document"""
    replacements_made = 0
    
    for table_idx, table in enumerate(document.tables):
        print(f"\n🔍 Processing table {table_idx + 1}:")
        
        # Check for Operator Declaration table first (priority fix)
        if len(table.rows) <= 4:  # Small tables
            declaration_replacements = handle_operator_declaration_table(table, flat_json)
            if declaration_replacements > 0:
                replacements_made += declaration_replacements
                continue
        
        # Process all rows
        for row_idx, row in enumerate(table.rows):
            if len(row.cells) < 1:
                continue
                
            key_cell = row.cells[0]
            key_text = get_clean_text(key_cell)
            
            if not key_text:
                continue
            
            print(f"  📌 Row {row_idx + 1}: Key = '{key_text}'")
            
            # Handle Nature of Business section
            if "nature of the operators business" in key_text.lower():
                nature_replacements = handle_nature_business_section(key_cell, flat_json)
                replacements_made += nature_replacements
                continue
            
            # Regular field matching
            json_value = find_matching_json_value(key_text, flat_json)
            
            if json_value is not None:
                replacement_text = get_value_as_string(json_value, key_text)
                
                # Handle Australian Company Number specially
                if ("australian company number" in key_text.lower() or "company number" in key_text.lower()) and isinstance(json_value, list):
                    cell_replacements = handle_australian_company_number(row, json_value)
                    replacements_made += cell_replacements
                else:
                    # Handle regular fields
                    for cell_idx in range(len(row.cells)):
                        cell = row.cells[cell_idx]
                        if has_red_text(cell):
                            cell_replacements = replace_red_text_in_cell(cell, replacement_text)
                            replacements_made += cell_replacements
                            if cell_replacements > 0:
                                print(f"    ✅ Updated cell {cell_idx + 1}: '{replacement_text}'")
            else:
                # Process any red text in row cells
                for cell_idx in range(len(row.cells)):
                    cell = row.cells[cell_idx]
                    if has_red_text(cell):
                        # Try to extract red text and match it
                        red_text = ""
                        for paragraph in cell.paragraphs:
                            for run in paragraph.runs:
                                if is_red(run):
                                    red_text += run.text
                        
                        if red_text.strip():
                            json_value = find_matching_json_value(red_text.strip(), flat_json)
                            if json_value is not None:
                                replacement_text = get_value_as_string(json_value)
                                cell_replacements = replace_red_text_in_cell(cell, replacement_text)
                                replacements_made += cell_replacements
                                if cell_replacements > 0:
                                    print(f"    ✅ Replaced red text: '{red_text.strip()}' -> '{replacement_text}'")
    
    return replacements_made

def process_paragraphs(document, flat_json):
    """Process paragraphs for red text"""
    replacements_made = 0
    print(f"\n🔍 Processing paragraphs:")
    
    for para_idx, paragraph in enumerate(document.paragraphs):
        red_text = ""
        red_runs = []
        
        for run in paragraph.runs:
            if is_red(run) and run.text.strip():
                red_text += run.text
                red_runs.append(run)
        
        if red_text.strip():
            print(f"  📌 Paragraph {para_idx + 1}: Found red text: '{red_text.strip()}'")
            
            json_value = find_matching_json_value(red_text.strip(), flat_json)
            
            if json_value is not None:
                replacement_text = get_value_as_string(json_value)
                print(f"    ✅ Replacing with: '{replacement_text}'")
                
                # Replace in first red run only
                if red_runs:
                    red_runs[0].text = replacement_text
                    red_runs[0].font.color.rgb = RGBColor(0, 0, 0)
                    # Clear other red runs
                    for run in red_runs[1:]:
                        run.text = ''
                    replacements_made += 1
    
    return replacements_made

def process_hf(json_file, docx_file, output_file):
    """Main processing function compatible with your new system"""
    try:
        # Load JSON
        if hasattr(json_file, "read"):
            json_data = json.load(json_file)
        else:
            with open(json_file, 'r', encoding='utf-8') as f:
                json_data = json.load(f)
        
        # Flatten your new JSON structure
        flat_json = flatten_json_new_system(json_data)
        print("📄 Available JSON keys (sample):")
        for i, (key, value) in enumerate(sorted(flat_json.items())):
            if i < 10:
                print(f"  - {key}: {value}")
        print(f"  ... and {len(flat_json) - 10} more keys\n")

        # Load DOCX
        if hasattr(docx_file, "read"):
            doc = Document(docx_file)
        else:
            doc = Document(docx_file)

        # Process document
        print("🚀 Starting processing compatible with your new system...")
        
        table_replacements = process_tables(doc, flat_json)
        paragraph_replacements = process_paragraphs(doc, flat_json)
        
        total_replacements = table_replacements + paragraph_replacements

        # Save output
        if hasattr(output_file, "write"):
            doc.save(output_file)
        else:
            doc.save(output_file)
            
        print(f"\n✅ Document saved as: {output_file}")
        print(f"✅ Total replacements: {total_replacements}")
        print(f"   📊 Tables: {table_replacements}")
        print(f"   📝 Paragraphs: {paragraph_replacements}")
        print(f"🎉 Processing complete!")

    except FileNotFoundError as e:
        print(f"❌ File not found: {e}")
    except Exception as e:
        print(f"❌ Error: {e}")
        import traceback
        traceback.print_exc()

if __name__ == "__main__":
    import sys
    if len(sys.argv) != 4:
        print("Usage: python compatible_pipeline.py <input_docx> <updated_json> <output_docx>")
        exit(1)
    docx_path = sys.argv[1]
    json_path = sys.argv[2]
    output_path = sys.argv[3]
    process_hf(json_path, docx_path, output_path)