"""Re-test the 12 case-study candidates' sync variants on Gemini.

Pipeline:
  1. Read /home/ubuntu/case_study_candidates.jsonl (12 base videos).
  2. Filter the master test jsonl to the 36 rows that belong to those 12 bases
     (each base + its delay + early variant).
  3. Invoke scripts/eval_gemini_mute_sync_swap.py --task sync --openai-parse-sync.
  4. Read the Gemini sync results and report which of the 36 are wrong, using
     the same correctness rule as find_case_study.py:
        wrong = (gt_synced != pred_synced) OR
                (not gt_synced AND pred_direction != gt_direction)

Usage:
  GEMINI_API_KEY=... OPENAI_API_KEY=... python3 /home/ubuntu/case_study_gemini_sync.py
or pass --gemini-key / --openai-key.
"""

import argparse
import json
import os
import re
import subprocess
import sys
from pathlib import Path

REPO          = Path("/home/ubuntu/CleverHans-Evaluation")
TEST_JSONL    = REPO / "data" / "kto_training_data_v2_test.jsonl"
EVAL_SCRIPT   = REPO / "scripts" / "eval_gemini_mute_sync_swap.py"
DATA_ROOT     = Path("/opt/dlami/nvme/video_source")
CANDIDATES    = Path("/home/ubuntu/case_study_pool.jsonl")  # 45-video pool

OUT_ROOT      = Path("/home/ubuntu/eval_results/case_study_pool")
FILTERED_JSON = OUT_ROOT / "sync_test.jsonl"
LABEL         = "case_study_pool_gemini_sync"
GEMINI_RESULT = OUT_ROOT / "sync" / LABEL / "eval_results.jsonl"
WRONG_OUT     = OUT_ROOT / "gemini_wrong.jsonl"

SYNC_SUFFIX_RE = re.compile(r"_(delay|early)_\d+(?:\.\d+)?s(?=\.mp4$)")


def base_of(name: str) -> str:
    return SYNC_SUFFIX_RE.sub("", name)


def load_jsonl(path):
    with open(path) as f:
        for line in f:
            line = line.strip()
            if line:
                yield json.loads(line)


def step_filter():
    bases = {row["video"] for row in load_jsonl(CANDIDATES)}
    print(f"[filter] {len(bases)} base videos from {CANDIDATES}")

    OUT_ROOT.mkdir(parents=True, exist_ok=True)
    kept = []
    for row in load_jsonl(TEST_JSONL):
        if base_of(row["video"]) in bases:
            kept.append(row)

    with open(FILTERED_JSON, "w") as f:
        for row in kept:
            f.write(json.dumps(row, ensure_ascii=False) + "\n")
    print(f"[filter] kept {len(kept)} rows -> {FILTERED_JSON}")
    if len(kept) != 3 * len(bases):
        print(f"[warn] expected {3*len(bases)} rows (3 per base), got {len(kept)}")


def step_run_gemini(gemini_key: str, openai_key: str, model: str, workers: int):
    env = os.environ.copy()
    env["GEMINI_API_KEY"] = gemini_key
    env["OPENAI_API_KEY"] = openai_key

    cmd = [
        sys.executable, str(EVAL_SCRIPT),
        "--task", "sync",
        "--model", model,
        "--data-root", str(DATA_ROOT),
        "--test-jsonl", str(FILTERED_JSON),
        "--output-dir", str(OUT_ROOT),
        "--label", LABEL,
        "--openai-parse-sync",
        "--workers", str(workers),
    ]
    print(f"[run] {' '.join(cmd)}")
    subprocess.run(cmd, env=env, check=True)


def step_report():
    if not GEMINI_RESULT.exists():
        sys.exit(f"[error] expected results at {GEMINI_RESULT}; eval did not produce one")

    rows = list(load_jsonl(GEMINI_RESULT))
    wrong = []
    for r in rows:
        gt_synced = bool(r["gt_synced"])
        pred_synced = bool(r["pred_synced"])
        is_wrong = (gt_synced != pred_synced) or (
            (not gt_synced) and r.get("pred_direction") != r.get("gt_direction")
        )
        if is_wrong:
            wrong.append({
                "video": r["video"],
                "base": base_of(r["video"]),
                "gt": (r["gt_direction"], r["gt_offset_sec"]),
                "pred_synced": pred_synced,
                "pred": (r.get("pred_direction"), r.get("pred_offset_sec")),
                "raw": r.get("raw_output", "")[:200],
            })

    by_base = {}
    for w in wrong:
        by_base.setdefault(w["base"], []).append(w)

    print(f"\n[report] {len(rows)} sync samples evaluated, {len(wrong)} wrong")
    print(f"[report] wrong distribution by base video:")
    for base in sorted(by_base):
        hits = by_base[base]
        print(f"\n  {base}  ({len(hits)} variant(s) wrong)")
        for h in hits:
            print(f"    - {h['video']}")
            print(f"        gt={h['gt']}  pred_synced={h['pred_synced']}  pred={h['pred']}")

    with open(WRONG_OUT, "w") as f:
        for w in wrong:
            f.write(json.dumps(w, ensure_ascii=False) + "\n")
    print(f"\n[saved] wrong rows -> {WRONG_OUT}")

    bases_total = {base_of(r["video"]) for r in rows}
    bases_any_wrong = set(by_base)
    bases_all_three_wrong = {b for b, hs in by_base.items()
                             if len(hs) == 3}
    print(f"\n[summary]")
    print(f"  candidates with >=1 wrong sync : {len(bases_any_wrong)} / {len(bases_total)}")
    print(f"  candidates with all 3 wrong    : {len(bases_all_three_wrong)} / {len(bases_total)}")
    if bases_all_three_wrong:
        print(f"  perfect-fail candidates:")
        for b in sorted(bases_all_three_wrong):
            print(f"    - {b}")


def main():
    p = argparse.ArgumentParser()
    p.add_argument("--gemini-key", default=os.environ.get("GEMINI_API_KEY"))
    p.add_argument("--openai-key", default=os.environ.get("OPENAI_API_KEY"))
    p.add_argument("--model", default="gemini-3.1-pro-preview")
    p.add_argument("--workers", type=int, default=4)
    p.add_argument("--skip-run", action="store_true",
                   help="Skip the Gemini call (use existing results to re-report).")
    args = p.parse_args()

    step_filter()
    if not args.skip_run:
        if not args.gemini_key:
            sys.exit("[error] need --gemini-key or GEMINI_API_KEY env")
        if not args.openai_key:
            sys.exit("[error] need --openai-key or OPENAI_API_KEY env")
        step_run_gemini(args.gemini_key, args.openai_key, args.model, args.workers)
    step_report()


if __name__ == "__main__":
    main()