59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
#!/usr/bin/env python3
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"""Robo Pest STT relay — faster-whisper on nightmare's RTX 4080 SUPER.
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POST /transcribe (body: raw PCM 16kHz s16le mono bytes) -> {"text": "..."}
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GET /health -> {"status": "ok", ...}
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Auth: X-Auth-Token header required (set via STT_AUTH_TOKEN env var).
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Health endpoint is open (no secrets).
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"""
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import io
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import os
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import struct
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import numpy as np
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from fastapi import FastAPI, Request, HTTPException
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from faster_whisper import WhisperModel
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MODEL_NAME = os.environ.get("STT_MODEL", "small.en")
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DEVICE = os.environ.get("STT_DEVICE", "cuda")
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AUTH_TOKEN = os.environ.get("STT_AUTH_TOKEN", "")
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app = FastAPI()
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model = WhisperModel(MODEL_NAME, device=DEVICE, compute_type="float16")
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def check_auth(request: Request):
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if not AUTH_TOKEN:
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return
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token = request.headers.get("X-Auth-Token", "")
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if token != AUTH_TOKEN:
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raise HTTPException(status_code=401, detail="bad token")
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def pcm16_to_float32(data: bytes) -> np.ndarray:
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n = len(data) // 2
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ints = struct.unpack(f"<{n}h", data[: n * 2])
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return np.array(ints, dtype=np.float32) / 32768.0
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@app.get("/health")
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def health():
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return {"status": "ok", "model": MODEL_NAME, "device": DEVICE}
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@app.post("/transcribe")
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async def transcribe(request: Request):
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check_auth(request)
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body = await request.body()
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if not body:
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return {"text": ""}
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audio = pcm16_to_float32(body)
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segments, info = model.transcribe(audio, language="en", beam_size=1, vad_filter=True)
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text = " ".join(s.text.strip() for s in segments).strip()
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return {"text": text, "duration": round(info.duration, 2)}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8765)
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