# =============================================================================
# FOXHUNT ML TRAINING SERVICE - DEVELOPMENT CONTAINER
# =============================================================================
# This Dockerfile creates a development container with ML development tools
# and model experimentation capabilities

# =============================================================================
# BUILDER STAGE - Development Build
# =============================================================================
FROM rust:1.75-slim as ml-dev-builder

# Install build dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    pkg-config \
    libssl-dev \
    ca-certificates \
    libpq-dev \
    protobuf-compiler \
    libblas-dev \
    liblapack-dev \
    git \
    && rm -rf /var/lib/apt/lists/*

# Development Cargo configuration
ENV CARGO_NET_GIT_FETCH_WITH_CLI=true
ENV CARGO_INCREMENTAL=1
ENV CARGO_PROFILE_DEV_DEBUG=true

WORKDIR /workspace

# Copy workspace files
COPY Cargo.toml Cargo.lock ./
COPY trading_engine ./trading_engine
COPY risk ./risk
COPY ml ./ml
COPY data ./data
COPY common ./common
COPY storage ./storage
COPY crates/config ./crates/config
COPY crates/model_loader ./crates/model_loader
COPY services/ml_training_service ./services/ml_training_service

# Build in development mode
RUN cargo build \
    --package ml_training_service \
    --features minimal

# =============================================================================
# DEVELOPMENT RUNTIME - Ubuntu with ML Tools
# =============================================================================
FROM ubuntu:22.04-slim

# Install runtime dependencies and ML development tools
RUN apt-get update && apt-get install -y \
    ca-certificates \
    libssl3 \
    libpq5 \
    curl \
    wget \
    netcat-openbsd \
    # Mathematical libraries
    libblas3 \
    liblapack3 \
    # Python ML ecosystem
    python3 \
    python3-pip \
    python3-dev \
    # Development tools
    git \
    vim \
    htop \
    # AWS CLI for S3 operations
    awscli \
    && rm -rf /var/lib/apt/lists/*

# Install Python ML packages for experimentation
RUN pip3 install \
    numpy \
    pandas \
    matplotlib \
    seaborn \
    jupyter \
    plotly \
    scikit-learn \
    tensorboard \
    mlflow \
    wandb \
    && rm -rf /root/.cache/pip

# Create app user and directories
RUN groupadd -r foxhunt && useradd -r -g foxhunt -s /bin/bash foxhunt
RUN mkdir -p /app/config /app/models /app/data /app/checkpoints /app/cache /app/logs \
    /app/experiments /app/notebooks \
    && chown -R foxhunt:foxhunt /app

# Copy debug binary from builder
COPY --from=ml-dev-builder /workspace/target/debug/ml_training_service /app/ml_training_service
RUN chmod +x /app/ml_training_service

# Copy configuration templates
COPY services/ml_training_service/config/ /app/config/ || true

USER foxhunt
WORKDIR /app

# Expose ports for service, health check, TensorBoard, and Jupyter
EXPOSE 50053 8083 6006 8888

# Development environment variables
ENV RUST_LOG=debug
ENV RUST_BACKTRACE=full
ENV FOXHUNT_CONFIG=/app/config/development.toml
ENV FOXHUNT_ENV=development
ENV MODEL_CACHE_DIR=/app/cache
ENV JUPYTER_ENABLE_LAB=yes
ENV WANDB_MODE=disabled

# Health check for development
HEALTHCHECK --interval=30s --timeout=15s --start-period=60s --retries=3 \
    CMD curl -f http://localhost:8083/health || exit 1

# Development startup
CMD ["./ml_training_service"]