# Use a slim Python image for smaller size and faster downloads
FROM python:3.9-slim

# Set environment variables for non-interactive commands
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1

# --- NEW LINE: Set Hugging Face cache directory ---
# This ensures that the user inside the container has write permissions for the cache.
ENV HF_HOME="/tmp/.cache/huggingface"

# Set the working directory in the container
WORKDIR /app

# Install system dependencies
# build-essential for compiling C extensions if needed by Python packages
# libgl1-mesa-glx for PyTorch if using certain functionalities (though often not needed for CPU-only inference)
# Other packages can be added as needed by your specific dependencies.
RUN apt-get update && \
    apt-get install -y --no-install-recommends \
    build-essential \
    libgl1-mesa-glx \
    git \
    && rm -rf /var/lib/apt/lists/*

# Copy only the requirements file first to leverage Docker's build cache
# This ensures that if your app code changes but dependencies don't,
# the pip install step isn't re-run every time.
COPY requirements.txt .

# Install Python dependencies
# Use --no-cache-dir to save space
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of your application code and model files
# This includes app.py, your model's state_dict, tokenizer files, etc.
# The '.' indicates copying everything from the current host directory into the container's /app directory.
COPY . .

# Expose the port your FastAPI application will listen on
# FastAPI typically runs on port 8000
EXPOSE 8000

# Command to run your FastAPI application using Uvicorn
# 0.0.0.0 makes the server accessible from outside the container
# app:app refers to the 'app' FastAPI instance within 'app.py'
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]