# Copyright (c) 2026 The Anuvani-Diarization authors
# SPDX-License-Identifier: MIT OR Apache-2.0
"""The release, unchanged, from audio to RTTM with the stand-in networks of tests/fake_nn.py (CPU only): for each
input, `load_audio` -> `analyse` -> `indic_mode`, saving the record and the RTTM, or the error.

  python -s tests/ref_fake_run.py INPUTS_JSON OUT_DIR
"""
import json
import os
import sys
from pathlib import Path

os.environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np

HERE = Path(__file__).resolve().parent
sys.path.insert(0, str(HERE))
import refpkg  # noqa: E402

refpkg.load()
import fake_nn  # noqa: E402
from anuvani_diar_ref.frontend import load_bundle, load_audio, analyse  # noqa: E402
from anuvani_diar_ref.modes import indic_mode, write_rttm_indic  # noqa: E402
from anuvani_diar_ref.decoder import load_decoder  # noqa: E402

REL = refpkg.REL


def main():
    items = json.loads(Path(sys.argv[1]).read_text())
    out = Path(sys.argv[2]); out.mkdir(parents=True, exist_ok=True)
    modes = json.loads((REL / "bundle/MANIFEST.json").read_text())["modes"]
    model = load_bundle(REL / "bundle", "cpu", 8, 2)
    fake_nn.patch_release(model)
    decoder = load_decoder(REL / "bundle" / modes["indic"]["decoder"])
    log = {}
    for it in items:
        sid, rec = it["sid"], {}
        try:
            audio, sr = load_audio(Path(it["path"]))
            d = analyse(model, audio, sr)
            np.savez(out / f"{sid}.npz", **d)
            write_rttm_indic(out / f"{sid}.rttm", sid, indic_mode(d, modes["indic"]["clustering"], decoder))
        except Exception as e:
            rec["error"] = f"{type(e).__name__}: {e}"
        log[sid] = rec
    (out / "log.json").write_text(json.dumps(log, indent=1))


if __name__ == "__main__":
    main()