38 lines
1.1 KiB
Docker
38 lines
1.1 KiB
Docker
FROM python:3.11-slim as requirements-stage
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WORKDIR /tmp
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RUN pip install poetry
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COPY pyproject.toml ./poetry.lock* /tmp/
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RUN poetry export -f requirements.txt --output requirements.txt --without-hashes
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FROM python:3.11-slim
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# Allow statements and log messages to immediately appear in the logs
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ENV PYTHONUNBUFFERED True
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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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COPY . ./
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COPY --from=requirements-stage /tmp/requirements.txt /app/requirements.txt
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RUN apt update && apt install -y ffmpeg
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RUN pip install openai-whisper
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# openai-whisper model in not compatible with the newer 2.0.0 numpy release
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RUN pip install --upgrade numpy<2
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RUN pip install --no-cache-dir -r /app/requirements.txt
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EXPOSE 8000
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# Run the web service on container startup. Here we use the gunicorn
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# webserver, with one worker process and 8 threads.
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# For environments with multiple CPU cores, increase the number of workers
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# to be equal to the cores available.
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# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
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CMD exec uvicorn --bind 0.0.0.0:8000 --workers 1 --threads 8 --timeout 0 app.server:app
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