SurfSense/surfsense_backend/Dockerfile

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FROM python:3.12-slim
WORKDIR /app
# Install system dependencies including SSL tools, CUDA dependencies, and Tesseract OCR
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
python3-dev \
ca-certificates \
curl \
wget \
unzip \
gnupg2 \
espeak-ng \
libsndfile1 \
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libgl1 \
libglib2.0-0 \
libsm6 \
libxext6 \
libxrender1 \
dos2unix \
git \
&& rm -rf /var/lib/apt/lists/*
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# Install Pandoc 3.x from GitHub as a fallback for Linux where pypandoc_binary
# may not bundle pandoc (apt ships 2.17 which has broken table rendering).
# pypandoc_binary bundles pandoc on Windows/macOS; on Linux it picks this up.
RUN ARCH=$(dpkg --print-architecture) && \
wget -qO /tmp/pandoc.deb "https://github.com/jgm/pandoc/releases/download/3.9/pandoc-3.9-1-${ARCH}.deb" && \
dpkg -i /tmp/pandoc.deb && \
rm /tmp/pandoc.deb
# Update certificates and install SSL tools
RUN update-ca-certificates
RUN pip install --upgrade certifi pip-system-certs
# Copy requirements
COPY pyproject.toml .
COPY uv.lock .
# Install PyTorch based on architecture
RUN if [ "$(uname -m)" = "x86_64" ]; then \
pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121; \
else \
pip install --no-cache-dir torch torchvision torchaudio; \
fi
# Install python dependencies
RUN pip install --no-cache-dir uv && \
uv pip install --system --no-cache-dir -e .
# Set SSL environment variables dynamically
RUN CERTIFI_PATH=$(python -c "import certifi; print(certifi.where())") && \
echo "Setting SSL_CERT_FILE to $CERTIFI_PATH" && \
echo "export SSL_CERT_FILE=$CERTIFI_PATH" >> /root/.bashrc && \
echo "export REQUESTS_CA_BUNDLE=$CERTIFI_PATH" >> /root/.bashrc
ENV SSL_CERT_FILE=/usr/local/lib/python3.12/site-packages/certifi/cacert.pem
ENV REQUESTS_CA_BUNDLE=/usr/local/lib/python3.12/site-packages/certifi/cacert.pem
# Pre-download EasyOCR models to avoid runtime SSL issues
RUN mkdir -p /root/.EasyOCR/model
RUN wget --no-check-certificate https://github.com/JaidedAI/EasyOCR/releases/download/v1.3/english_g2.zip -O /root/.EasyOCR/model/english_g2.zip || true
RUN wget --no-check-certificate https://github.com/JaidedAI/EasyOCR/releases/download/pre-v1.1.6/craft_mlt_25k.zip -O /root/.EasyOCR/model/craft_mlt_25k.zip || true
RUN cd /root/.EasyOCR/model && (unzip -o english_g2.zip || true) && (unzip -o craft_mlt_25k.zip || true)
# Pre-download Docling models
RUN python -c "try:\n from docling.document_converter import DocumentConverter\n conv = DocumentConverter()\nexcept:\n pass" || true
# Install Playwright browsers for web scraping if needed
RUN pip install playwright && \
playwright install chromium --with-deps
# Copy source code
COPY . .
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# Copy and set permissions for entrypoint script
# Use dos2unix to ensure LF line endings (fixes CRLF issues from Windows checkouts)
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COPY scripts/docker/entrypoint.sh /app/scripts/docker/entrypoint.sh
RUN dos2unix /app/scripts/docker/entrypoint.sh && chmod +x /app/scripts/docker/entrypoint.sh
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# Shared temp directory for file uploads between API and Worker containers.
# Python's tempfile module uses TMPDIR, so uploaded files land here.
# Mount the SAME volume at /shared_tmp on both API and Worker in Coolify.
RUN mkdir -p /shared_tmp
ENV TMPDIR=/shared_tmp
# Prevent uvloop compatibility issues
ENV PYTHONPATH=/app
ENV UVICORN_LOOP=asyncio
# Tune glibc malloc to return freed memory to the OS more aggressively.
# Without these, Python's gc.collect() frees objects but the underlying
# C heap pages stay mapped (RSS never drops) due to sbrk fragmentation.
ENV MALLOC_MMAP_THRESHOLD_=65536
ENV MALLOC_TRIM_THRESHOLD_=131072
ENV MALLOC_MMAP_MAX_=65536
# SERVICE_ROLE controls which process this container runs:
# api FastAPI backend only (runs migrations on startup)
# worker Celery worker only
# beat Celery beat scheduler only
# all All three (legacy / dev default)
ENV SERVICE_ROLE=all
# Celery worker tuning (only used when SERVICE_ROLE=worker or all)
ENV CELERY_MAX_WORKERS=10
ENV CELERY_MIN_WORKERS=2
ENV CELERY_MAX_TASKS_PER_CHILD=50
# CELERY_QUEUES: comma-separated queues to consume (empty = all queues)
# "surfsense" fast tasks only (file uploads, podcasts, etc.)
# "surfsense.connectors" slow connector indexing tasks only
# "" both queues (default, for single-worker setups)
ENV CELERY_QUEUES=""
# Run
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EXPOSE 8000-8001
CMD ["/app/scripts/docker/entrypoint.sh"]