# CPU-only Hugging Face Space image.
# Serving uses llama.cpp + a pre-merged GGUF (Q4_K_M), so there is no torch /
# transformers / bitsandbytes in the production image. This keeps the image small,
# cold starts fast, and RAM well under the 16 GB free-tier ceiling.
FROM python:3.11-slim

# System deps. build-essential + cmake are a safety net in case pip falls back to
# building llama-cpp-python from source; normally the prebuilt CPU wheel is used.
RUN apt-get update && apt-get install -y --no-install-recommends \
    git \
    curl \
    build-essential \
    cmake \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /app

# Build llama-cpp-python from source against THIS image's glibc toolchain.
# Why not a prebuilt wheel: the abetlen CPU "wheel index" ships musl-linked wheels
# for every version recent enough to support the phi3 architecture (>=0.2.63), which
# fail to load on this Debian/glibc image with:
#   "libc.musl-x86_64.so.1: cannot open shared object file".
# The only glibc wheels there (<=0.2.62) predate phi3 support. So we compile.
# GGML_NATIVE=OFF -> portable CPU binary (the build host CPU may differ from the
# cpu-basic runtime CPU; -march=native would risk an illegal-instruction crash).
# Version note: 0.3.2's bundled llama.cpp SEGFAULTs (exit 139) at inference time on
# this GGUF (produced by a much newer llama.cpp). 0.3.19 is verified to load and
# generate correct SQL against the exact production GGUF, so we pin to it.
ENV CMAKE_ARGS="-DGGML_NATIVE=OFF"
# Compile ONE translation unit at a time. A parallel compile (default = all cores)
# OOM-killed the build runner (exit 137). Single-threaded keeps peak RAM ~1-2 GB.
# Slower build, but reliable on the memory-limited HF build runner.
ENV CMAKE_BUILD_PARALLEL_LEVEL=1
RUN pip install --no-cache-dir --no-binary=llama-cpp-python "llama-cpp-python==0.3.19"

# Install the slim CPU-serving dependencies.
COPY requirements-space.txt .
RUN pip install --no-cache-dir -r requirements-space.txt

# Copy project source
COPY . .

# HF Spaces requires the app to listen on port 7860
EXPOSE 7860

# Create dirs that may not exist in the repo
RUN mkdir -p data models templates static

# HF Spaces runs containers as a non-root user
RUN useradd -m -u 1000 appuser && chown -R appuser /app
USER appuser

# Point HF cache to a writable location inside the container (GGUF is cached here)
ENV HF_HOME=/app/.cache/huggingface

CMD ["python", "src/server.py"]