import csv
import json
import re
import random
from pathlib import Path

def extract_pos(hmr_text):
    """Extracts part of speech from strings like 'word (pos)'."""
    if not hmr_text:
        return hmr_text, None
    match = re.search(r'\s*\(([^)]+)\)$', hmr_text)
    if match:
        pos = match.group(1)
        hmr_clean = hmr_text[:match.start()].strip()
        return hmr_clean, pos
    return hmr_text.strip(), None

def convert():
    data_dir = Path('data')
    processed_dir = Path('processed')
    processed_dir.mkdir(exist_ok=True)
    
    all_data = []
    
    csv_files = sorted(list(data_dir.rglob('*.csv')))
    
    for csv_file in csv_files:
        try:
            with open(csv_file, mode='r', encoding='utf-8') as f:
                reader = csv.DictReader(f)
                for row in reader:
                    en = (row.get('en') or '').strip()
                    hmr = (row.get('hmr') or '').strip()
                    if not en and not hmr:
                        continue
                    
                    hmr_clean, pos = extract_pos(hmr)
                    all_data.append({
                        'hmr': hmr_clean,
                        'en': en,
                        'pos': pos
                    })
        except Exception as e:
            print(f"Error processing {csv_file}: {e}")

    # Shuffle for unbiased splitting
    random.seed(42) # For reproducibility
    random.shuffle(all_data)
    
    # Split 95/5
    split_idx = int(len(all_data) * 0.95)
    train_data = all_data[:split_idx]
    test_data = all_data[split_idx:]
    
    # Save full JSON
    with open('hmar_data.json', 'w', encoding='utf-8') as f:
        json.dump(all_data, f, indent=2, ensure_ascii=False)
    
    # Save JSONL files for training
    def save_jsonl(data, filename):
        with open(processed_dir / filename, 'w', encoding='utf-8') as f:
            for entry in data:
                f.write(json.dumps(entry, ensure_ascii=False) + '\n')

    save_jsonl(train_data, 'train.jsonl')
    save_jsonl(test_data, 'test.jsonl')
    
    print(f"Total entries: {len(all_data)}")
    print(f"Saved {len(train_data)} to processed/train.jsonl")
    print(f"Saved {len(test_data)} to processed/test.jsonl")

if __name__ == '__main__':
    convert()