Dockerfile.prod

# Stage 1: Build environment
FROM python:3.9-slim-buster AS builder

# Set work directory
WORKDIR /app

# Install system build dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    cmake \
    git \
    wget \
    && rm -rf /var/lib/apt/lists/*

# Install Miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
    && bash miniconda.sh -b -p /opt/conda \
    && rm miniconda.sh
ENV PATH="/opt/conda/bin:${PATH}"

# Create a conda environment
RUN conda create -n pipeline python=3.9 -y
SHELL ["conda", "run", "-n", "pipeline", "/bin/bash", "-c"]

# Copy only requirements, to cache them in docker layer
COPY requirements.txt /app/

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

# Stage 2: Runtime environment
FROM python:3.9-slim-buster AS runtime

# Set work directory
WORKDIR /app

# Install runtime system dependencies
RUN apt-get update && apt-get install -y \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libglib2.0-0 \
    libgl1-mesa-glx \
    ffmpeg \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Copy conda environment from builder
COPY --from=builder /opt/conda /opt/conda
ENV PATH="/opt/conda/bin:${PATH}"
SHELL ["conda", "run", "-n", "pipeline", "/bin/bash", "-c"]

# Copy application code
COPY . /app

# Install Ollama
RUN curl https://ollama.ai/install.sh | sh

# Make port 8080 available to the world outside this container
EXPOSE 8080

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1

# Run the application
CMD ["conda", "run", "--no-capture-output", "-n", "pipeline", "python", "main.py"]