110b2298b7
- stt_local: Whisper large-v3-turbo MLX, transcript + timestamped json - lipsync_local: Rhubarb visemes (CPU lane), dialog-guided - voice_clone_local: Chatterbox on MPS (needs setuptools<81 for perth/pkg_resources) - wan_video: Wan 2.2 TI2V-5B t2v/i2v via resident ComfyUI, frames->mp4 - llm_local: Qwen3-30B-A3B-4bit dialogue writer (primary-only) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import argparse
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import json
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import re
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import sys
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import time
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from pathlib import Path
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ap = argparse.ArgumentParser()
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ap.add_argument("--input", action="append", default=[])
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ap.add_argument("--outdir", required=True)
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ap.add_argument("--params", default="{}")
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a = ap.parse_args()
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p = json.loads(a.params)
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prompt = (p.get("prompt") or "").strip()
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if not prompt:
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print("ERROR: prompt is required")
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sys.exit(1)
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from mlx_lm import load, generate # noqa: E402
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from mlx_lm.sample_utils import make_sampler # noqa: E402
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MODEL = "mlx-community/Qwen3-30B-A3B-4bit"
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t0 = time.time()
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model, tokenizer = load(MODEL)
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print(f"model loaded in {time.time() - t0:.1f}s", flush=True)
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messages = []
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if (p.get("system") or "").strip():
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messages.append({"role": "system", "content": p["system"].strip()})
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messages.append({"role": "user", "content": prompt})
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chat = tokenizer.apply_chat_template(
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messages, add_generation_prompt=True, tokenize=False, enable_thinking=False)
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t1 = time.time()
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text = generate(model, tokenizer, prompt=chat,
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max_tokens=int(p.get("max_tokens", 1024)),
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sampler=make_sampler(temp=float(p.get("temperature", 0.7))))
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text = re.sub(r"<think>.*?</think>", "", text, flags=re.S).strip()
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out = Path(a.outdir) / "llm_output.txt"
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out.write_text(text + "\n")
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print(f"done in {time.time() - t1:.1f}s, {len(text)} chars:\n{text[:400]}", flush=True)
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