FROM python:3.11-slim

# 1. Install OS build dependencies and curl
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential \
    curl \
    git \
    && rm -rf /var/lib/apt/lists/*

# 2. Set up user 1000 (required by Hugging Face Spaces)
RUN useradd -m -u 1000 user
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH \
    PYTHONUNBUFFERED=1 \
    HF_HOME=/home/user/.cache/huggingface

WORKDIR $HOME/app

# 3. Install Python dependencies as user
COPY --chown=user:user requirements.txt .
USER user
RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
    pip install --no-cache-dir -r requirements.txt

# 4. Pre-download model & tokenizer into image layer so startup is instant
RUN python -c "from transformers import AutoModelForCausalLM, AutoTokenizer; \
    AutoModelForCausalLM.from_pretrained('dejanseo/reverse-prompter'); \
    AutoTokenizer.from_pretrained('dejanseo/reverse-prompter')"

# 5. Copy application source
COPY --chown=user:user . .

EXPOSE 7860

# 6. Streamlit startup flags configured for HF Spaces iframe and port 7860
CMD ["streamlit", "run", "src/streamlit_app.py", \
     "--server.port=7860", \
     "--server.address=0.0.0.0", \
     "--server.headless=true", \
     "--server.enableCORS=false", \
     "--server.enableXsrfProtection=false"]