#!/usr/bin/env python3
"""Compare an automated cast against a manually-corrected one (ground truth).

  python3 scripts/compare_casts.py <manual.json> <auto.json>

Matches segments by normalised text rather than index (a recast splits and
merges segments, so indices never line up), then reports where the automation
disagrees with the human — which is the input for improving the rules.
"""
import json, re, sys, collections

def norm(t):
    t = re.sub(r'[»«„“”"\'`]', '', str(t or ''))
    return re.sub(r'\s+', ' ', t).strip().lower()

def load(p):
    d = json.load(open(p, encoding='utf-8'))
    return d.get('segments') or []

def is_unknown(s):
    sp = str(s.get('speaker') or '')
    return s.get('type') == 'dialogue' and (not sp or sp.lower().startswith(('unknown', 'unbekannt')))

def summarise(segs, label):
    dia = [s for s in segs if s.get('type') == 'dialogue']
    fused = [s for s in dia if re.search(r'\n\s*\n', (s.get('text') or '').strip())]
    print(f"{label:10s} segments={len(segs):5d} dialogue={len(dia):5d} "
          f"unknown={sum(1 for s in segs if is_unknown(s)):4d} fused={len(fused):3d} "
          f"speakers={len({s.get('speaker') for s in dia if s.get('speaker')}):3d}")

def main(man_path, auto_path):
    man, auto = load(man_path), load(auto_path)
    print("=" * 78)
    summarise(man, "MANUAL"); summarise(auto, "AUTO")
    print("=" * 78)

    # index the manual cast by normalised text
    mi = collections.defaultdict(list)
    for i, s in enumerate(man):
        k = norm(s.get('text'))
        if k: mi[k].append(i)

    agree = disagree = only_auto = 0
    unknown_in_auto_known_in_man = []
    wrong_speaker = []
    type_diff = []
    for s in auto:
        k = norm(s.get('text'))
        if not k: continue
        hits = mi.get(k)
        if not hits:
            only_auto += 1
            continue
        m = man[hits[0]]
        if m.get('type') != s.get('type'):
            type_diff.append((s.get('text', '')[:60], m.get('type'), s.get('type')))
        ms, as_ = str(m.get('speaker') or ''), str(s.get('speaker') or '')
        if ms == as_:
            agree += 1
        else:
            disagree += 1
            if is_unknown(s) and not is_unknown(m):
                unknown_in_auto_known_in_man.append((s.get('text', '')[:60], ms))
            elif not is_unknown(s) and not is_unknown(m) and m.get('type') == 'dialogue':
                wrong_speaker.append((s.get('text', '')[:60], ms, as_))

    tot = agree + disagree
    print(f"\nmatched segments: {tot}  agree={agree} ({100*agree//max(tot,1)}%)  disagree={disagree}")
    print(f"segments only in AUTO (split/reworded): {only_auto}")

    print(f"\n--- AUTO left Unknown where the human knew the speaker ({len(unknown_in_auto_known_in_man)}) ---")
    for t, who in unknown_in_auto_known_in_man[:25]:
        print(f"  should be {who:18s} | {t!r}")

    print(f"\n--- AUTO picked a DIFFERENT speaker than the human ({len(wrong_speaker)}) ---")
    for t, who, got in wrong_speaker[:25]:
        print(f"  human={who:16s} auto={got:16s} | {t!r}")

    print(f"\n--- type disagreements narration vs dialogue ({len(type_diff)}) ---")
    for t, mt, at in type_diff[:20]:
        print(f"  human={mt:9s} auto={at:9s} | {t!r}")

if __name__ == '__main__':
    if len(sys.argv) != 3:
        print(__doc__); sys.exit(1)
    main(sys.argv[1], sys.argv[2])