"""Integrate the self-licensed contemporary medical calendar notes into
polocrbench-train-pool-v1 (handwriting-mednotes source).

License holder: Piotr Styła (declared CC BY 4.0, 2026-10-23).
Content: handwritten medical study/calendar notes (mostly page fragments
with cut edges). Transcriptions are AI pre-annotation with [ucięte] (cut),
[?], [skreślone] markers. Deterministic PII scan found no e-mail/phone/
PESEL/account strings; lecturer surnames appear as professional references.
Content is study/training material with medical knowledge; no personal
health records.
"""
import collections
import hashlib
import json
import shutil
from pathlib import Path

BASE = Path('C:/Users/Hipek/OCR_external_data')
WORK = BASE / 'skany-jadwiga-work'
POOL = BASE / 'polocrbench-train-pool-v1'


def sha(data):
    return hashlib.sha256(data).hexdigest()


def main():
    trans = {}
    for line in (WORK / 'transcriptions.jsonl').read_text(encoding='utf-8').splitlines():
        row = json.loads(line)
        trans[row['page_id']] = row['text']
    originals = {p.stem: sha(p.read_bytes()) for p in (WORK / 'originals').glob('*.jpg')}
    assert len(trans) == 49

    rows = []
    for stem in sorted(trans):
        src = WORK / 'pages' / f'{stem}.jpg'
        pool_id = 'hwmed_' + stem.lower()
        data = src.read_bytes()
        shutil.copyfile(src, POOL / 'images' / f'{pool_id}.jpg')
        rows.append({'id': pool_id, 'source': 'handwriting-mednotes',
                     'source_ref': 'self-licensed medical calendar notes '
                                   '(license holder: Piotr Styła, CC BY 4.0, 2026-10-23)',
                     'image': f'images/{pool_id}.jpg', 'image_sha256': sha(data),
                     'text': trans[stem], 'text_sha256': sha(trans[stem].encode()),
                     'width': 700, 'height': 1000, 'split': 'train',
                     'license': 'cc-by-4.0', 'human_verified': False, 'gold': False,
                     'page_fragment': True,
                     'original_image_sha256': originals.get(stem),
                     'transcription': 'ai-preannotation-cut-markers'})

    manifest_path = POOL / 'manifest.jsonl'
    existing = manifest_path.read_text(encoding='utf-8')
    manifest_path.write_text(existing + ''.join(
        json.dumps(r, ensure_ascii=False) + '\n' for r in rows), encoding='utf-8')

    report = json.loads((POOL / 'report.json').read_text(encoding='utf-8'))
    all_rows = [json.loads(s) for s in manifest_path.read_text(encoding='utf-8').splitlines()]
    report['schema'] = 'polocrbench-train-pool-v1.4'
    report['pages'] = len(all_rows)
    report['by_source'] = dict(collections.Counter(r['source'] for r in all_rows))
    report['by_split'] = dict(collections.Counter(r['split'] for r in all_rows))
    report['handwriting_mednotes_pages'] = len(rows)
    report['handwriting_mednotes_license'] = 'CC BY 4.0 (license holder: Piotr Styła)'
    report['handwriting_mednotes_content'] = 'study/training notes with medical knowledge (dosage schedules, disease patterns as taught); no personal health records; mostly page fragments with cut edges'
    report['licenses']['handwriting-mednotes'] = 'CC BY 4.0 (license holder: Piotr Styła)'
    (POOL / 'report.json').write_text(json.dumps(report, ensure_ascii=False, indent=2),
                                      encoding='utf-8')

    sums = {p.relative_to(POOL).as_posix(): sha(p.read_bytes())
            for p in sorted(POOL.rglob('*')) if p.is_file() and p.name != 'checksums.json'}
    (POOL / 'checksums.json').write_text(json.dumps(sums, indent=2), encoding='utf-8')
    print(json.dumps({'mednotes_rows': len(rows), 'pool_pages': len(all_rows),
                      'by_source': report['by_source'], 'checksum_entries': len(sums)},
                     ensure_ascii=False, indent=2))


if __name__ == '__main__':
    main()