Dockerfile.finrl

# QuantStack FinRL Worker — includes torch + RL dependencies
# Separate image to avoid bloating graph services with ~4GB of CUDA libs.

FROM python:3.11-slim-bookworm

LABEL maintainer="QuantStack"
LABEL description="QuantStack FinRL worker (torch + stable-baselines3)"

ARG EXTRA_CA_CERT=""
RUN if [ -n "$EXTRA_CA_CERT" ]; then \
        printf '%s\n' "$EXTRA_CA_CERT" >> /usr/local/share/ca-certificates/corporate.crt \
        && update-ca-certificates; \
    fi

RUN apt-get update && apt-get install -y --no-install-recommends \
    gcc \
    g++ \
    git \
    curl \
    wget \
    make \
    && rm -rf /var/lib/apt/lists/*

# Build TA-Lib from source (not in Debian repos)
RUN wget -q https://github.com/ta-lib/ta-lib/releases/download/v0.6.4/ta-lib-0.6.4-src.tar.gz \
    && tar xzf ta-lib-0.6.4-src.tar.gz \
    && cd ta-lib-0.6.4 \
    && ./configure --prefix=/usr/local \
    && make -j$(nproc) \
    && make install \
    && ldconfig \
    && cd .. \
    && rm -rf ta-lib-0.6.4 ta-lib-0.6.4-src.tar.gz

RUN pip install --no-cache-dir "uv>=0.5.0"

WORKDIR /app

COPY pyproject.toml uv.lock ./
COPY src/ ./src/

# Install with RL + data extras (torch, gymnasium, stable-baselines3, finrl, TA-Lib).
# CPU-only torch to avoid CUDA bloat on non-GPU hosts.
RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install --system \
    --index-url https://download.pytorch.org/whl/cpu \
    --extra-index-url https://pypi.org/simple/ \
    -e ".[langgraph,data,rl]"

COPY scripts/ ./scripts/

RUN mkdir -p /data/quantstack

ENV KILL_SWITCH_SENTINEL=/data/quantstack/KILL_SWITCH_ACTIVE

COPY scripts/docker-entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh

ENTRYPOINT ["/entrypoint.sh"]
CMD ["api"]