Dockerfile

# --- 1. Use a standard, reliable Python base ---
FROM python:3.12-slim

WORKDIR /app

# --- 2. Install C/C++ build tools & venv ---
RUN apt-get update && apt-get install -y \
    build-essential \
    cmake \
    python3-venv \
    && rm -rf /var/lib/apt/lists/*

# --- 3. Download the model first ---
# This uses a safe, isolated venv just for downloading
COPY download_model.py .
RUN --mount=type=secret,id=HF_TOKEN \
    sh -c 'python3 -m venv /tmp/downloader-venv && \
           . /tmp/downloader-venv/bin/activate && \
           pip install huggingface_hub && \
           python3 download_model.py'

# --- 4. Build llama-cpp-python (CPU-ONLY) ---
# This is the CRITICAL FIX.
# This forces a fast, CPU-only build that will not time out.
ENV CMAKE_ARGS="-DLLAMA_CUDA=OFF"

# This build step will now be fast (1-2 minutes)
RUN pip install "llama-cpp-python[server]"

# --- 5. Set the runtime command ---
# Expose the port (matches README.md)
EXPOSE 8000

# This command runs the server
CMD [ \
    "python", \
    "-m", "llama_cpp.server", \
    "--model", "prem-1B-SQL.Q8_0.gguf", \
    "--n_gpu_layers", "0", \
    "--port", "8000", \
    "--host", "0.0.0.0", \
    "--api_key_env_var", "API_KEY" \
]