# syntax=docker/dockerfile:1
#
# Single GPU runtime for train + SwanLab client + eval.
# Build:  docker build -t kda:<tag> .
#
# Does not bake data, checkpoints, or API keys. Mount them at run time.
# Host: NVIDIA driver >= 570, nvidia-container-toolkit. See README.

FROM pytorch/pytorch:2.9.0-cuda12.8-cudnn9-devel

ENV DEBIAN_FRONTEND=noninteractive \
    PIP_NO_CACHE_DIR=1 \
    PYTHONUNBUFFERED=1 \
    PYTHONPATH=/workspace/kda \
    HF_HOME=/cache/huggingface \
    HUGGINGFACE_HUB_CACHE=/cache/huggingface \
    HF_HUB_DISABLE_TELEMETRY=1

RUN apt-get update && apt-get install -y --no-install-recommends \
        git \
        ca-certificates \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /workspace/kda

# Layer cache: install deps from pyproject before the rest of the tree.
COPY pyproject.toml ./
COPY kda ./kda
# Base image already has torch/cuda/triton; do not let pip re-resolve torch.
RUN pip install --no-cache-dir --no-deps -e . && \
    pip install --no-cache-dir \
        "einops>=0.7.0" \
        "packaging>=23.0" \
        "sentencepiece>=0.2.0" \
        "datasets>=3.0.0" \
        "transformers>=4.51.0" \
        "swanlab>=0.6.0" \
        "sacrebleu>=2.4.0" \
        "langdetect>=1.0.9" \
        "pytest>=7.0"

COPY . /workspace/kda
RUN pip install --no-cache-dir --no-deps -e . && \
    mkdir -p /cache/huggingface /workspace/kda/ckpts /workspace/kda/swanlog \
             /data/pretrain /data/eval /data/sft

# Require an explicit entry (train / eval / pytest / swanlab ping).
CMD ["python", "scripts/container_help.py"]