vh
01eedd8d27
Two-container stack serving MrDragonFox/mOrpheus (uncensored Orpheus TTS, Llama-3.2-3B -> SNAC 24kHz). vllm-morpheus (GPU/3090) emits Orpheus audio tokens; morpheus-tts (CPU) SNAC-decodes them to WAV and exposes POST /tts (baddy voice + zero-shot cloning). Deployed + tested end-to-end (28/28 valid frames, valid WAV, reachable over WG). Hard-won config, all encoded in compose/README: - bf16 REQUIRED: --quantization fp8 destroys audio-token generation (0 valid SNAC frames even at greedy). Footprint ~7.9GB. - Image PINNED to v0.23.0: 'latest' ships Blackwell oink/aiter kernels that crash on Ampere import. - 3090 (not the comfy-contended A6000); --enforce-eager to fit the shared card. - RTF ~1.0 end-to-end (gen ~98 tok/s / RTF 0.84 + CPU decode + HTTP). INTERNAL RESEARCH ONLY (CC-BY-NC-4.0); do not expose externally.
15 lines
582 B
Docker
15 lines
582 B
Docker
# mOrpheus TTS wrapper — CPU-only (SNAC decode + FastAPI /tts). Calls the vLLM engine.
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FROM python:3.11-slim
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RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1 && rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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COPY requirements.txt .
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# CPU torch (SNAC decode is small; keeps this container off the GPU / out of contention)
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RUN pip install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu \
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&& pip install --no-cache-dir -r requirements.txt
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COPY app.py .
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EXPOSE 8000
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CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
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