#!/usr/bin/env python3
"""Append a frozen, sourced and reviewed 500-question supplement to unchanged v6.2."""
import hashlib
import json
import unicodedata
from collections import Counter
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
BASE_SHA = 'aaceb71c48331b813049f35bdb103d630f4acd46caeea2db831108f962f17630'
AUTHOR = 'Claude Opus 5.5 (Anthropic), via parallel authoring agents'
DATE = '2026-10-14'
SELECTION = ('Authored and reviewed before any model was evaluated on these additions; '
             'no performance-based item selection')


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


def build():
    base = ROOT / 'data/v6.2/test.jsonl'
    assert sha(base.read_bytes()) == BASE_SHA
    rows = [json.loads(s) for s in base.read_text().splitlines()]
    source = [json.loads(s) for s in (ROOT / 'source/v6.3-additions.jsonl').read_text().splitlines()]
    assert len(source) == 500
    audit = []
    for line, item in enumerate(source, 1):
        question = unicodedata.normalize('NFC', item['question']).strip()
        qid = 'aussieqa-' + sha(question.encode())[:20]
        rows.append({'id': qid, 'question': question, 'answers': [item['answer']]})
        audit.append({'id': qid, 'source_version': '6.3-additions', 'source_line': line,
                      'topic': item['topic'], 'subtopic': item['subtopic'],
                      'difficulty_estimate': item['difficulty_estimate'], 'source_url': item['source_url'],
                      'author': AUTHOR, 'authored_date': DATE, 'answer_source_checked_date': DATE,
                      'review': item['review'], 'selection': SELECTION})
    assert len(rows) == len({r['id'] for r in rows}) == len({r['question'].casefold() for r in rows}) == 1500
    for path, data in [('data/v6.3/test.jsonl', rows), ('metadata/v6.3/additions.jsonl', audit)]:
        p = ROOT / path
        p.parent.mkdir(parents=True, exist_ok=True)
        p.write_text(''.join(json.dumps(r, ensure_ascii=False, separators=(',', ':')) + '\n' for r in data))
    assert (ROOT / 'data/v6.3/test.jsonl').read_bytes().startswith(base.read_bytes())
    outcomes = Counter(item['review']['outcome'] for item in source)
    manifest = {'dataset': 'Aussie-1k', 'version': '0.4', 'source_build_identifier': '6.3', 'release_date': DATE,
                'base_version': '0.3', 'unchanged_base_questions': 1000, 'new_questions': 500,
                'test_records': 1500, 'reference_answers': sum(len(r['answers']) for r in rows),
                'answer_count_distribution': dict(Counter(len(r['answers']) for r in rows)),
                'addition_topic_counts': dict(Counter(r['topic'] for r in source)),
                'addition_subtopic_slices': dict(Counter(r['slice'] for r in source)),
                'addition_difficulty_estimates': dict(sorted(Counter(r['difficulty_estimate'] for r in source).items())),
                'review_outcomes': dict(outcomes),
                'review_protocol': ('Claude authored each item and checked it against the cited source. MiniMax-M3 and '
                                    'GLM-5.3-Flash (SCX.ai) independently rated fit (1-5), reference correctness, ambiguity '
                                    'and time-stability. Items accepted by both judges with no flags passed review; every '
                                    'flagged item was adjudicated by Claude against sources and kept unchanged, revised and '
                                    're-reviewed by both judges, or dropped. Claude then read every remaining candidate and '
                                    'dropped overlapping, answer-leaking or weakly attested items.'),
                'selection_rule': ('From the reviewed candidates, 45 items per authoring slice (50 for geography); within '
                                   'each slice, difficulty levels keep proportional shares and items are ranked by the '
                                   'judges\' summed fit scores. No evaluated-model answers were used.'),
                'candidate_counts': {'drafted': 608, 'dropped_as_duplicates_or_unstable_before_review': 14,
                                     'dropped_in_adjudication_or_manual_review': 12, 'reserve_not_selected': 82,
                                     'selected': 500},
                'duplicate_review': ('Exact and case-insensitive uniqueness checked; semantic near-duplicates against '
                                     'v6.2 and within the supplement flagged with E5-Mistral-7B-Instruct embeddings '
                                     '(cosine >= 0.82) and resolved by hand. No claim of exhaustive semantic deduplication.'),
                'ordering': 'Unchanged v6.2 questions followed by 500 additions in frozen source order',
                'files': {}}
    for name in ['data/v6.2/test.jsonl', 'source/v6.3-additions.jsonl', 'data/v6.3/test.jsonl',
                 'metadata/v6.3/additions.jsonl']:
        b = (ROOT / name).read_bytes()
        manifest['files'][name] = {'sha256': sha(b), 'bytes': len(b)}
    (ROOT / 'metadata/v6.3/manifest.json').write_text(json.dumps(manifest, indent=2) + '\n')
    print(json.dumps(manifest, indent=2))


if __name__ == '__main__':
    build()