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# Base Image
FROM python:3.10-slim
# Build argument for Hugging Face token
ARG HF_TOKEN
ENV DEBIAN_FRONTEND=noninteractive \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
HF_TOKEN=${HF_TOKEN}
WORKDIR /code
# System Dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
git \
curl \
libopenblas-dev \
libomp-dev \
ffmpeg \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Hugging Face + model tools
RUN pip install --no-cache-dir huggingface-hub sentencepiece accelerate fasttext
# Hugging Face cache environment
ENV HF_HOME=/models/huggingface \
TRANSFORMERS_CACHE=/models/huggingface \
HUGGINGFACE_HUB_CACHE=/models/huggingface \
HF_HUB_CACHE=/models/huggingface
# Created cache dir and set permissions
RUN mkdir -p /models/huggingface && chmod -R 777 /models/huggingface
RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='facebook/mms-tts-hau')" \
&& python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='facebook/mms-tts-eng')" \
&& python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='facebook/mms-tts-yor')" \
&& find /models/huggingface -name '*.lock' -delete
RUN python -c "from transformers import pipeline; pipeline('text-to-speech', model='facebook/mms-tts-hau')" \
&& python -c "from transformers import pipeline; pipeline('text-to-speech', model='facebook/mms-tts-eng')" \
&& python -c "from transformers import pipeline; pipeline('text-to-speech', model='facebook/mms-tts-yor')"
# Models will be downloaded at runtime when HF_TOKEN is available
# Copy project files
COPY . .
EXPOSE 7860
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]
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