Remove legacy file

make_kimi_train.py

@@ -1,107 +0,0 @@
-#!/usr/bin/env python3
-"""
-Step 2: metadata.tsv → FLAC-to-WAV conversion + metadata_kimi_train.jsonl
-
-WARNING: This script converts all .flac files to .wav IN-PLACE and deletes the .flac.
-         WAV files are approximately 2-3x larger than FLAC.
-         Purpose: produce training data in Kimi-Audio conversation format.
-
-Output: metadata_kimi_train.jsonl  (same directory as this script)
-        Each pair produces two entries:
-          1. EN→ZH: user gives EN audio, assistant responds with ZH audio + ZH text
-          2. ZH→EN: user gives ZH audio, assistant responds with EN audio + EN text
-"""
-
-import csv
-import json
-import os
-import soundfile as sf
-from tqdm import tqdm
-
-BASE_DIR     = os.path.dirname(__file__)
-INPUT_TSV    = os.path.join(BASE_DIR, "metadata.tsv")
-OUTPUT_JSONL = os.path.join(BASE_DIR, "metadata_kimi_train.jsonl")
-
-
-def flac_to_wav(flac_path: str) -> str:
-    """Convert a .flac file to .wav in-place (deletes .flac). Returns .wav path."""
-    wav_path = flac_path[:-5] + ".wav"
-    data, sr = sf.read(flac_path)
-    sf.write(wav_path, data, sr)
-    os.remove(flac_path)
-    return wav_path
-
-
-def flac_rel_to_wav_rel(p: str) -> str:
-    return p[:-5] + ".wav" if p.endswith(".flac") else p
-
-
-def main():
-    with open(INPUT_TSV, "r", encoding="utf-8") as f:
-        rows = list(csv.DictReader(f, delimiter="\t"))
-    print(f"Loaded {len(rows)} pairs from {INPUT_TSV}")
-    print("Converting FLAC → WAV (in-place) and writing metadata_kimi_train.jsonl ...")
-
-    ok = skip = fail = 0
-    out_f = open(OUTPUT_JSONL, "w", encoding="utf-8")
-
-    for row in tqdm(rows, unit="pairs"):
-        zh_flac = os.path.join(BASE_DIR, row["zh_path"])
-        en_flac = os.path.join(BASE_DIR, row["en_path"])
-        zh_text = row["zh_text"]
-        en_text = row["en_text"]
-
-        # Convert FLAC → WAV for both files
-        converted = {}
-        for key, flac_abs in [("zh", zh_flac), ("en", en_flac)]:
-            wav_abs = flac_abs[:-5] + ".wav"
-            if os.path.exists(wav_abs):
-                converted[key] = wav_abs
-            elif os.path.exists(flac_abs):
-                try:
-                    converted[key] = flac_to_wav(flac_abs)
-                except Exception as e:
-                    print(f"\n  FAILED converting {flac_abs}: {e}")
-                    fail += 1
-                    break
-            else:
-                print(f"\n  MISSING: {flac_abs}")
-                fail += 1
-                break
-        else:
-            # Both converted successfully — write two conversation entries
-            en_rel = flac_rel_to_wav_rel(row["en_path"])
-            zh_rel = flac_rel_to_wav_rel(row["zh_path"])
-
-            # EN → ZH
-            out_f.write(json.dumps({
-                "task_type": "s-s",
-                "conversation": [
-                    {"role": "user",      "message_type": "text",       "content": "Translate the given English speech into Chinese while preserving its expressiveness."},
-                    {"role": "user",      "message_type": "audio",      "content": en_rel},
-                    {"role": "assistant", "message_type": "audio-text", "content": [zh_rel, zh_text]},
-                ]
-            }, ensure_ascii=False) + "\n")
-
-            # ZH → EN
-            out_f.write(json.dumps({
-                "task_type": "s-s",
-                "conversation": [
-                    {"role": "user",      "message_type": "text",       "content": "Translate the given Chinese speech into English while preserving its expressiveness."},
-                    {"role": "user",      "message_type": "audio",      "content": zh_rel},
-                    {"role": "assistant", "message_type": "audio-text", "content": [en_rel, en_text]},
-                ]
-            }, ensure_ascii=False) + "\n")
-
-            ok += 1
-            continue
-
-        skip += 1
-
-    out_f.close()
-    print(f"\nDone: {ok} pairs converted, {skip} skipped/missing, {fail} errors")
-    print(f"Output: {OUTPUT_JSONL}  ({ok * 2} total conversation entries)")
-
-
-if __name__ == "__main__":
-    main()