| # 1. Start with a lean and official Python base image | |
| FROM python:3.10-slim | |
| # Install dependencies for psycopg2 (libpq-dev is still needed) | |
| # ffmpeg is NO LONGER needed for this version | |
| RUN apt-get update && apt-get install -y libpq-dev && rm -rf /var/lib/apt/lists/* | |
| # 2. Set the working directory inside the container | |
| WORKDIR /app | |
| # 3. Create a non-root user and set up cache | |
| RUN useradd -m -u 1000 user | |
| RUN mkdir -p /app/.cache && chown -R user:user /app/.cache | |
| ENV HF_HOME="/app/.cache" | |
| USER user | |
| # Add local bin directory to PATH | |
| ENV PATH="/home/user/.local/bin:${PATH}" | |
| # 4. Copy and install dependencies | |
| COPY --chown=user:user requirements.txt . | |
| RUN pip install --no-cache-dir -r requirements.txt | |
| # 5. Copy the app source code | |
| COPY --chown=user:user . . | |
| # 6. Expose the port used by Hugging Face Spaces | |
| EXPOSE 7860 | |
| # 7. Run the FastAPI app using Uvicorn | |
| # This assumes your file is named "main.py". If you named it "browser_main.py", | |
| # change "main:app" to "browser_main:app" | |
| CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"] |