| """voice_daemon.py - resident Cantonese TTS server for LYRA. |
| Runs in the isolated `envs/voice` environment (qwen-tts, transformers 4.57.3).""" |
| import json, os, sys, time, traceback |
| from pathlib import Path |
| import numpy as np, soundfile as sf, torch |
| sys.path.insert(0, "/marimo/ai_studio") |
| from studio_core import BASE, JOBS, JOBS_DONE, RESULTS, LOGS, VOICE_MODEL |
|
|
| MODEL = None |
| def log(m): |
| line = f"[{time.strftime('%H:%M:%S')}] {m}" |
| print(line, flush=True) |
| with open(LOGS/"voice_daemon.log", "a") as f: f.write(line + "\n") |
|
|
| def get_model(): |
| global MODEL |
| if MODEL is None: |
| from qwen_tts import Qwen3TTSModel |
| log("load Qwen3-TTS + Cantonese LoRA ...") |
| MODEL = Qwen3TTSModel.from_pretrained(str(VOICE_MODEL), device_map="cuda", dtype=torch.bfloat16) |
| log(f"voice ready | speakers={MODEL.get_supported_speakers()} | langs={MODEL.get_supported_languages()}") |
| return MODEL |
|
|
| def job_tts(j): |
| m = get_model() |
| spk = j.get("speaker") or (m.get_supported_speakers() or [None])[0] |
| kw = dict(text=j["text"], speaker=spk, language=j.get("language") or "chinese") |
| if j.get("instruct"): kw["instruct"] = j["instruct"] |
| log(f"tts '{j['name']}' spk={spk} :: {j['text'][:30]}") |
| t0 = time.time() |
| wavs, sr = m.generate_custom_voice(**kw) |
| out = BASE/"assets"/"audio"/j["name"] |
| sf.write(str(out), np.asarray(wavs[0]), sr) |
| dur = len(np.asarray(wavs[0]))/sr |
| log(f"wrote {out.name} {dur:.2f}s in {time.time()-t0:.1f}s") |
| return {"files": [str(out)], "seconds": round(dur,2), "speaker": spk} |
|
|
| HANDLERS = {"tts": job_tts, "ping": lambda j: {"pong": True}} |
|
|
| def main(): |
| log(f"voice daemon up pid={os.getpid()}") |
| while True: |
| found = False |
| for f in sorted(JOBS.glob("*.json")): |
| try: j = json.loads(f.read_text()) |
| except Exception: continue |
| if j.get("type") not in HANDLERS: |
| continue |
| found = True; jid = j.get("id", f.stem) |
| try: |
| res = {"id": jid, "status": "ok", **(HANDLERS[j["type"]](j) or {})} |
| except Exception as e: |
| res = {"id": jid, "status": "error", "error": f"{type(e).__name__}: {e}", |
| "trace": traceback.format_exc()[-1200:]} |
| log("FAILED " + res["error"]) |
| tmp = RESULTS/f".{res['id']}.tmp"; tmp.write_text(json.dumps(res, ensure_ascii=False, indent=2)) |
| tmp.rename(RESULTS/f"{res['id']}.json"); f.rename(JOBS_DONE/f.name) |
| log(f"done {res['id']} status={res['status']}") |
| if not found: time.sleep(1) |
|
|
| if __name__ == "__main__": |
| main() |
|
|
