Dockerfile

# FROM python:3.10-slim

# # Install system dependencies
# RUN apt-get update && apt-get install -y \
#     tesseract-ocr \
#     poppler-utils \
#     ffmpeg \
#     && rm -rf /var/lib/apt/lists/*

# # Set working directory
# WORKDIR /app

# # Copy requirements first to leverage Docker cache
# COPY requirements.txt .

# # Install Python dependencies
# RUN pip install --no-cache-dir -r requirements.txt

# # Copy application code
# COPY . .

# # Create necessary directories with proper permissions
# RUN mkdir -p /data/uploads /tmp/huggingface /tmp/torch /tmp/whisper && \
#     chmod -R 777 /data /tmp

# # Set environment variables
# ENV PYTHONUNBUFFERED=1
# ENV HF_HOME=/tmp/huggingface
# ENV HF_HOME=/tmp/huggingface
# ENV XDG_CACHE_HOME=/tmp
# ENV TORCH_HOME=/tmp/torch
# ENV WHISPER_CACHE=/tmp/whisper
# ENV PYTHONPATH=/app

# # Expose port
# EXPOSE 7860

# # Run the application with gunicorn
# CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "1", "--threads", "8", "--timeout", "0", "ai_med_extract.app:app"]







# # Multi-arch/mode Dockerfile that supports both GPU and CPU builds via build-args.
# # Defaults to CPU runtime suitable for Hugging Face Spaces Basic.

# ARG BASE_IMAGE=python:3.10-slim

# # Stage 1: builder (installs Python deps into a venv with build tooling)
# FROM ${BASE_IMAGE} AS builder

# ARG DEBIAN_FRONTEND=noninteractive
# ENV TZ=Etc/UTC

# # Install build tools only in builder
# RUN apt-get update && apt-get install -y --no-install-recommends \
#     tzdata \
#     build-essential \
#     python3 \
#     python3-pip \
#     python3-venv \
#     python3-dev \
#     tesseract-ocr \
#     poppler-utils \
#     ffmpeg \
#     && ln -fs /usr/share/zoneinfo/$TZ /etc/localtime \
#     && dpkg-reconfigure -f noninteractive tzdata \
#     && rm -rf /var/lib/apt/lists/*

# # Create virtual environment
# ENV VIRTUAL_ENV=/opt/venv
# RUN python3 -m venv "$VIRTUAL_ENV"
# ENV PATH="$VIRTUAL_ENV/bin:$PATH"

# WORKDIR /app
# COPY requirements.txt ./

# # Upgrade pip and install dependencies
# RUN pip install --upgrade pip && \
#     pip install --prefer-binary -r requirements.txt

# # Stage 2: runtime (minimal runtime deps + venv from builder)
# FROM ${BASE_IMAGE} AS runtime

# ARG DEBIAN_FRONTEND=noninteractive
# ENV TZ=Etc/UTC

# # Install only runtime system packages; keep minimal
# RUN apt-get update && apt-get install -y --no-install-recommends \
#     tzdata \
#     tesseract-ocr \
#     poppler-utils \
#     ffmpeg \
#     && ln -fs /usr/share/zoneinfo/$TZ /etc/localtime \
#     && dpkg-reconfigure -f noninteractive tzdata \
#     && rm -rf /var/lib/apt/lists/*

# # Copy Python environment from builder
# COPY --from=builder /opt/venv /opt/venv
# ENV PATH="/opt/venv/bin:$PATH"

# # App
# WORKDIR /app
# COPY . .

# # Reasonable cache dirs at runtime (kept outside image layers)
# ENV HF_HOME=/tmp/huggingface \
#     XDG_CACHE_HOME=/tmp \
#     TORCH_HOME=/tmp/torch \
#     WHISPER_CACHE=/tmp/whisper \
#     PYTHONUNBUFFERED=1 \
#     PYTHONPATH=/app \
#     GGUF_N_THREADS=2 \
#     GGUF_N_BATCH=64 \
#     OMP_NUM_THREADS=2 \
#     MKL_NUM_THREADS=2 \
#     NUMEXPR_NUM_THREADS=2

# # Ensure writable directories exist (works on Spaces read-only root)
# RUN mkdir -p /tmp/uploads /tmp/huggingface /tmp/torch /tmp/whisper && \
#     chmod -R 777 /tmp

# EXPOSE 7860

# CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "1", "--threads", "8", "--timeout", "0", "ai_med_extract.app:app"]


# Multi-arch/mode Dockerfile that supports both GPU and CPU builds via build-args.
# Defaults to CPU runtime suitable for Hugging Face Spaces Basic.
# NOTE: This Dockerfile is for local development and custom deployments.
# Hugging Face Spaces uses .huggingface.yaml configuration instead.

ARG BASE_IMAGE=python:3.10-slim

# Stage 1: builder (installs Python deps into a venv with build tooling)
FROM ${BASE_IMAGE} AS builder

ARG DEBIAN_FRONTEND=noninteractive
ENV TZ=Etc/UTC

# Install build tools only in builder
RUN apt-get update && apt-get install -y --no-install-recommends \
    tzdata \
    build-essential \
    python3 \
    python3-pip \
    python3-venv \
    python3-dev \
    tesseract-ocr \
    poppler-utils \
    ffmpeg \
    && ln -fs /usr/share/zoneinfo/$TZ /etc/localtime \
    && dpkg-reconfigure -f noninteractive tzdata \
    && rm -rf /var/lib/apt/lists/*

# Create virtual environment
ENV VIRTUAL_ENV=/opt/venv
RUN python3 -m venv "$VIRTUAL_ENV"
ENV PATH="$VIRTUAL_ENV/bin:$PATH"

WORKDIR /app
COPY requirements.txt ./

# Upgrade pip and install dependencies
RUN pip install --upgrade pip && \
    pip install --prefer-binary -r requirements.txt

# Stage 2: runtime (minimal runtime deps + venv from builder)
FROM ${BASE_IMAGE} AS runtime

ARG DEBIAN_FRONTEND=noninteractive
ENV TZ=Etc/UTC

# Install only runtime system packages; keep minimal
RUN apt-get update && apt-get install -y --no-install-recommends \
    tzdata \
    tesseract-ocr \
    poppler-utils \
    ffmpeg \
    && ln -fs /usr/share/zoneinfo/$TZ /etc/localtime \
    && dpkg-reconfigure -f noninteractive tzdata \
    && rm -rf /var/lib/apt/lists/*

# Copy Python environment from builder
COPY --from=builder /opt/venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

# App
WORKDIR /app
COPY . .

# Runtime cache dirs (kept in /tmp, auto-cleared on restart)
ENV HF_HOME=/tmp/huggingface \
    XDG_CACHE_HOME=/tmp \
    TORCH_HOME=/tmp/torch \
    WHISPER_CACHE=/tmp/whisper \
    PYTHONUNBUFFERED=1 \
    PYTHONPATH=/app \
    GGUF_N_THREADS=2 \
    GGUF_N_BATCH=64 \
    OMP_NUM_THREADS=2 \
    MKL_NUM_THREADS=2 \
    NUMEXPR_NUM_THREADS=2

# Ensure writable directories exist
RUN mkdir -p /tmp/uploads /tmp/huggingface /tmp/torch /tmp/whisper && \
    chmod -R 777 /tmp

# Add entrypoint script that clears cache/models before app starts
RUN echo '#!/bin/bash\n\
echo "[ENTRYPOINT] Clearing Hugging Face / Torch / tmp cache..."\n\
rm -rf /tmp/* ~/.cache/huggingface ~/.cache/torch || true\n\
mkdir -p /tmp/uploads /tmp/huggingface /tmp/torch /tmp/whisper\n\
chmod -R 777 /tmp\n\
exec "$@"' > /entrypoint.sh && chmod +x /entrypoint.sh

ENTRYPOINT ["/entrypoint.sh"]

EXPOSE 7860

# Use uvicorn for FastAPI (ASGI) instead of gunicorn (WSGI)
# Or use gunicorn with uvicorn workers for ASGI support
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]