Download Dockerfile from nxdev-org/tts: direct link, hf CLI and curl.
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curl -L -o Dockerfile https://huggingface.co/spaces/nxdev-org/tts/resolve/main/Dockerfile
1.45 kB
| FROM python:3.11-slim | |
| # ffmpeg and deno are for the podcast module (yt-dlp converts audio and solves YouTube's JS challenges) | |
| RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg && rm -rf /var/lib/apt/lists/* | |
| COPY --from=denoland/deno:bin /deno /usr/local/bin/deno | |
| # Hugging Face Spaces run the container as user 1000 | |
| RUN useradd -m -u 1000 user | |
| USER user | |
| ENV HOME=/home/user \ | |
| PATH=/home/user/.local/bin:$PATH \ | |
| HF_HOME=/home/user/.cache/huggingface \ | |
| PYTHONUNBUFFERED=1 \ | |
| CACHE_DIR=/home/user/cache | |
| WORKDIR /home/user/app | |
| COPY --chown=user requirements.txt . | |
| RUN pip install --no-cache-dir --user -r requirements.txt | |
| # Bake both models and all voices into the image so a waking Space doesn't download them. | |
| RUN python -c "from huggingface_hub import snapshot_download as d; d('hexgrad/Kokoro-82M'); d('hexgrad/Kokoro-82M-v1.1-zh')" | |
| # Same for the Whisper model (change both this and the WHISPER_MODEL variable to use another size) | |
| ARG WHISPER_MODEL=small | |
| RUN python -c "from faster_whisper import download_model; download_model('${WHISPER_MODEL}')" | |
| # app.py mounts the modules listed in MODULES: kokoro_tts.py (TTS), whisper_stt.py (STT), podcast.py (YouTube podcasts) | |
| COPY --chown=user *.py ./ | |
| EXPOSE 7860 | |
| # Refresh yt-dlp on every start so YouTube changes don't break podcast downloads; keep going if offline. | |
| CMD pip install --no-cache-dir --user -q -U "yt-dlp[default]" || true; exec python app.py | |