| # SN59 babelbit ARENA miner — gist S2S (whisper-large-v3 → Qwen2.5-7B gist → Kokoro) | |
| # Validated qualifying score 0.7397 (place #1). Models are DOWNLOADED AT STARTUP (not baked) | |
| # to keep the image small enough for the arena registry size check (~8 GB vs 28 GB baked). | |
| # Server self-warms (downloads + loads whisper+Qwen+Kokoro) at startup; serves /v1/predict + /predict + health. | |
| FROM nvidia/cuda:12.6.0-cudnn-runtime-ubuntu22.04 | |
| ENV DEBIAN_FRONTEND=noninteractive PIP_NO_CACHE_DIR=1 \ | |
| HF_HOME=/models/hf PIP_BREAK_SYSTEM_PACKAGES=1 | |
| RUN apt-get update && apt-get install -y --no-install-recommends \ | |
| python3 python3-pip espeak-ng ffmpeg ca-certificates && \ | |
| rm -rf /var/lib/apt/lists/* | |
| # torch (CUDA 12.x) + serving + model deps (gist pipeline) | |
| RUN pip3 install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cu124 && \ | |
| pip3 install --no-cache-dir \ | |
| faster-whisper transformers accelerate bitsandbytes sentencepiece \ | |
| kokoro "misaki[en]" espeakng-loader phonemizer-fork \ | |
| soundfile numpy huggingface_hub fastapi "uvicorn[standard]" | |
| WORKDIR /app | |
| # Models are NOT baked (would make the image ~28 GB and fail the arena size check). | |
| # whisper-large-v3 + Qwen2.5-7B + Kokoro-82M download at startup into HF_HOME on first warm. | |
| RUN mkdir -p /models/hf | |
| COPY server.py model.py gist_model.py /app/ | |
| # Winning config (validated). Managed/arena predict path is /predict; health is GET /health. | |
| # Babelbit arena contract: port 8000, serves /v1/predict + /predict + /healthz + /health. | |
| ENV BB_MINER_MODEL=gist \ | |
| BB_ASR_MODEL=large-v3 BB_ASR_BEAMS=5 \ | |
| BB_GIST_LLM=Qwen/Qwen2.5-7B-Instruct BB_GIST_SPEED=1.15 BB_GIST_VOICE=af_heart \ | |
| PORT=8000 | |
| EXPOSE 8000 | |
| # Server self-warms (loads whisper+Qwen+Kokoro) on startup before accepting traffic. | |
| CMD ["sh","-c","uvicorn server:app --host 0.0.0.0 --port ${PORT} --log-level info"] | |