# ============================================================
# CCPA Compliance Analyzer
# Base: NVIDIA CUDA 12.1 + Ubuntu 22.04 for GPU support
# Falls back gracefully to CPU if no GPU is available
# ============================================================
FROM nvidia/cuda:12.1.0-base-ubuntu22.04

# ── Build args ───────────────────────────────────────────────
ARG MODEL_NAME=llama3.2:3b
ARG DEBIAN_FRONTEND=noninteractive

# ── System dependencies ──────────────────────────────────────
RUN apt-get update && apt-get install -y \
    python3.11 \
    python3.11-dev \
    python3-pip \
    curl \
    ca-certificates \
    && rm -rf /var/lib/apt/lists/*

# Make python3.11 the default python
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1 && \
    update-alternatives --install /usr/bin/python  python  /usr/bin/python3.11 1

# ── Install Ollama ───────────────────────────────────────────
RUN curl -fsSL https://ollama.com/install.sh | sh

# ── Working directory ────────────────────────────────────────
WORKDIR /app

# ── Python dependencies (cached layer) ──────────────────────
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# ── Application code ─────────────────────────────────────────
COPY app.py .
COPY ccpa_knowledge.py .

# ── Pre-download model weights into the image ────────────────
# Ollama needs to be running to pull; we start it, pull, then stop.
# OLLAMA_MODELS sets a consistent path for the weights.
ENV OLLAMA_MODELS=/root/.ollama/models
RUN ollama serve & \
    SERVER_PID=$! && \
    echo "Waiting for Ollama daemon..." && \
    timeout 60 sh -c 'until curl -sf http://localhost:11434/api/tags; do sleep 2; done' && \
    echo "Pulling model: ${MODEL_NAME}" && \
    ollama pull ${MODEL_NAME} && \
    echo "Model pull complete." && \
    kill $SERVER_PID && \
    wait $SERVER_PID 2>/dev/null || true

# ── Startup script ───────────────────────────────────────────
COPY start.sh .
RUN chmod +x start.sh

# ── Runtime environment ──────────────────────────────────────
ENV MODEL_NAME=${MODEL_NAME}
ENV OLLAMA_HOST=http://localhost:11434
ENV PYTHONUNBUFFERED=1

# ── Port ─────────────────────────────────────────────────────
EXPOSE 8000

# ── Health check ─────────────────────────────────────────────
HEALTHCHECK --interval=15s --timeout=10s --start-period=120s --retries=5 \
    CMD curl -sf http://localhost:8000/health || exit 1

# ── Entrypoint ───────────────────────────────────────────────
CMD ["./start.sh"]
# Use a suitable base image (e.g., Ubuntu, Alpine, Node.js)
FROM alpine:latest

# Install unzip since Docker does not natively support extracting .zip files with ADD
# and clean up package cache in a single RUN command to keep the image small
RUN apk update && apk add unzip && rm -rf /var/cache/apk/*

# Set the working directory inside the container
WORKDIR /app

# Copy the local zip file into the container
COPY app.zip .

# Unzip the file and then remove the zip file to keep the final image clean
RUN unzip app.zip && rm app.zip

# Define the command to run when the container starts (replace with your application's start command)
CMD ["your_app_start_command"]