Spaces:
Running on Zero
Running on Zero
File size: 6,965 Bytes
c759578 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | #!/usr/bin/env python3
"""Run a small live Urdu S2S batch from a benchmark manifest."""
from __future__ import annotations
import argparse
import csv
import json
from pathlib import Path
import sys
import traceback
ROOT = Path(__file__).resolve().parents[1]
for path in (ROOT / "src", ROOT / "scripts"):
if str(path) not in sys.path:
sys.path.insert(0, str(path))
from urdu_s2s.asr_providers import FasterWhisperASRProvider # noqa: E402
from urdu_s2s.live_providers import ( # noqa: E402
OpenAIBridgeProvider,
OpenAICompatibleChatClient,
OpenAIReplyProvider,
)
from urdu_s2s.pipeline import SpeechToSpeechPipeline # noqa: E402
from urdu_s2s.schemas import SpeechToSpeechRequest # noqa: E402
from urdu_s2s.tts_providers import ChatterboxPraxyTTSProvider # noqa: E402
from run_s2s_live import DEFAULT_PRAXY_ANCHOR, result_to_payload, write_json_result # noqa: E402
DEFAULT_MANIFEST = ROOT / "artifacts/live_s2s_smoke10_manifest.csv"
def read_manifest(path: Path) -> list[dict[str, str]]:
with path.open(newline="", encoding="utf-8") as handle:
return list(csv.DictReader(handle))
def parse_ids(raw_ids: str) -> set[str] | None:
ids = {part.strip() for part in raw_ids.split(",") if part.strip()}
return ids or None
def resolve_repo_path(path: Path) -> Path:
return path if path.is_absolute() else ROOT / path
def write_summary_csv(path: Path, rows: list[dict[str, object]]) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
fieldnames = [
"id",
"status",
"audio_path",
"prompt_roman_urdu",
"asr_transcript",
"assistant_reply_urdu",
"devanagari_tts_text",
"tts_audio_path",
"json_path",
"error",
]
with path.open("w", newline="", encoding="utf-8") as handle:
writer = csv.DictWriter(handle, fieldnames=fieldnames)
writer.writeheader()
for row in rows:
writer.writerow({field: row.get(field, "") for field in fieldnames})
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST)
parser.add_argument("--ids", default="", help="Comma-separated IDs. Defaults to every row.")
parser.add_argument("--output-dir", type=Path, default=ROOT / "reports/evals/s2s_live_smoke10")
parser.add_argument("--summary-csv", type=Path, default=ROOT / "reports/evals/s2s_live_smoke10_summary.csv")
parser.add_argument("--model", default="")
parser.add_argument("--base-url", default="")
parser.add_argument("--whisper-model", default="large-v3")
parser.add_argument("--whisper-language", default="ur")
parser.add_argument("--whisper-device", default="cuda")
parser.add_argument("--whisper-compute-type", default="float16")
parser.add_argument("--voice-prompt-audio-path", type=Path, default=DEFAULT_PRAXY_ANCHOR)
parser.add_argument("--chatterbox-device", default="cuda")
parser.add_argument("--chatterbox-t3-model", default="v3")
parser.add_argument("--fail-fast", action="store_true")
return parser.parse_args()
def main() -> int:
args = parse_args()
manifest_path = resolve_repo_path(args.manifest)
output_dir = resolve_repo_path(args.output_dir)
voice_prompt_audio_path = resolve_repo_path(args.voice_prompt_audio_path)
selected_ids = parse_ids(args.ids)
rows = read_manifest(manifest_path)
if selected_ids is not None:
rows = [row for row in rows if row.get("id") in selected_ids]
if not rows:
raise ValueError(f"No manifest rows selected from {manifest_path}")
chat_client = OpenAICompatibleChatClient(
base_url=args.base_url or None,
model=args.model or None,
)
asr_provider = FasterWhisperASRProvider(
model_name=args.whisper_model,
language=args.whisper_language,
device=args.whisper_device,
compute_type=args.whisper_compute_type,
)
tts_provider = ChatterboxPraxyTTSProvider(
output_audio_path=output_dir / "placeholder.wav",
voice_prompt_audio_path=voice_prompt_audio_path,
device=args.chatterbox_device,
t3_model=args.chatterbox_t3_model,
)
pipeline = SpeechToSpeechPipeline(
asr_provider=asr_provider,
reply_provider=OpenAIReplyProvider(chat_client=chat_client),
bridge_provider=OpenAIBridgeProvider(chat_client=chat_client),
tts_provider=tts_provider,
)
summary_rows: list[dict[str, object]] = []
output_dir.mkdir(parents=True, exist_ok=True)
for index, row in enumerate(rows, start=1):
bench_id = row["id"]
audio_path = resolve_repo_path(Path(row["audio_path"]))
wav_path = output_dir / f"{bench_id}_praxy.wav"
json_path = output_dir / f"{bench_id}.json"
print(f"[{index}/{len(rows)}] {bench_id} -> {wav_path}", flush=True)
try:
tts_provider.output_audio_path = wav_path
request = SpeechToSpeechRequest(
request_id=f"{bench_id}_live_v2",
audio_path=audio_path,
metadata={"prompt_roman_urdu": row.get("prompt_roman_urdu", "")},
)
payload = result_to_payload(pipeline.run(request))
write_json_result(payload, json_path)
summary_rows.append(
{
"id": bench_id,
"status": "ok",
"audio_path": str(audio_path),
"prompt_roman_urdu": row.get("prompt_roman_urdu", ""),
"asr_transcript": payload["asr_transcript"],
"assistant_reply_urdu": payload["assistant_reply_urdu"],
"devanagari_tts_text": payload["devanagari_tts_text"],
"tts_audio_path": payload["tts_audio_path"],
"json_path": str(json_path),
"error": "",
}
)
except Exception as exc: # noqa: BLE001 - batch runner should report per-item failures.
error = "".join(traceback.format_exception_only(type(exc), exc)).strip()
print(f"[{bench_id}] ERROR: {error}", flush=True)
summary_rows.append(
{
"id": bench_id,
"status": "error",
"audio_path": str(audio_path),
"prompt_roman_urdu": row.get("prompt_roman_urdu", ""),
"error": error,
}
)
if args.fail_fast:
break
write_summary_csv(resolve_repo_path(args.summary_csv), summary_rows)
print(f"summary={resolve_repo_path(args.summary_csv)}")
print(f"ok={sum(1 for row in summary_rows if row['status'] == 'ok')} total={len(summary_rows)}")
return 0 if all(row["status"] == "ok" for row in summary_rows) else 1
if __name__ == "__main__":
raise SystemExit(main())
|