koko210Serve
8ca716029e
Voice conversion pipeline (Soprano TTS → RVC) with Docker support. Previously tracked as bare gitlink; removed .git/ directories and absorbed into main repo for unified tracking. Includes: Soprano TTS, RVC WebUI integration, Docker configs, WebSocket API, and benchmark scripts. Updated .gitignore to exclude large model weights (*.pth, *.pt, *.onnx, *.index). 287 files (3.1GB of ML weights properly excluded via gitignore).
48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
import base64
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import io
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import json
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from typing import Generator
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import numpy as np
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from fastapi import FastAPI, HTTPException
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from fastapi.responses import Response
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from scipy.io.wavfile import write
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from torch import Tensor
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from soprano.tts import SopranoTTS
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# Load model at startup
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tts = SopranoTTS(cache_size_mb = 100)
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app = FastAPI(title="Soprano TTS API")
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def _tensor_to_wav_bytes(tensor: Tensor) -> bytes:
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"""
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Convert a 1D fp32 torch tensor to a WAV byte stream.
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"""
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# convert to int16
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audio_int16 = (np.clip(tensor.numpy(), -1.0, 1.0) * 32767).astype(np.int16)
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wav_io = io.BytesIO()
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write(wav_io, 32000, audio_int16) # 32kHz sample rate
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wav_io.seek(0)
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return wav_io.read()
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@app.post("/v1/audio/speech")
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async def create_speech(payload: dict):
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"""
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Minimal implementation of OpenAI's Speech endpoint.
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Fields:
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- input: string - text to synthesize
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- model, voice, etc. are accepted but ignored.
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- response_format: str - ignored, only support wav.
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"""
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text = payload.get("input")
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if not isinstance(text, str) or not text.strip():
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raise HTTPException(status_code=400, detail="`input` field must be a non-empty string.")
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audio_tensor = tts.infer(text)
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wav_bytes = _tensor_to_wav_bytes(audio_tensor)
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return Response(content=wav_bytes, media_type="audio/wav", headers={"Content-Disposition": 'attachment; filename="speech.wav"'})
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