# Nori multi-policy inference image (INFERENCE_ENDPOINT_PLAN step 5).
#
# ONE Dockerfile, per-kind requirements via build arg:
#   docker build --build-arg MODEL_KIND=molmoact2 -t nori-serve-molmoact2 .
#   docker build --build-arg MODEL_KIND=pi05      -t nori-serve-pi05 .
# Run with env MODEL_KIND matching the build arg (the arg only picks which
# requirements file is installed; the env picks the adapter at boot).
#
# Base per kind (BUILD_BASE arg):
#   molmoact2 -> pytorch/pytorch:2.5.1-cuda12.1 (the proven Space stack; never
#     reinstall torch/torchvision/torchaudio on top — ABI break, space/Dockerfile)
#   pi05      -> python:3.12-slim (the pinned lerobot REQUIRES py>=3.12, which no
#     pytorch/pytorch image ships; lerobot's own dep spec then installs the torch
#     it wants — CUDA-bundled pip wheels, host driver via the endpoint runtime.
#     This mirrors lelab's local venv, the combo the pi05 load path was proven on.)
ARG BUILD_BASE=python:3.12-slim
FROM ${BUILD_BASE}

ARG MODEL_KIND=groot

ENV HOME=/home/user \
    PYTHONUNBUFFERED=1 \
    HF_HOME=/home/user/.cache/huggingface \
    HF_HUB_ENABLE_HF_TRANSFER=1 \
    MODEL_KIND=${MODEL_KIND}

# ffmpeg for av decode; git for the pinned lerobot install (pi05 kind).
RUN apt-get update && apt-get install -y --no-install-recommends \
        ffmpeg libgl1 libglib2.0-0 git && \
    rm -rf /var/lib/apt/lists/*

RUN useradd -m -u 1000 user
WORKDIR /app

COPY --chown=user:user requirements-${MODEL_KIND}.txt ./requirements.txt
RUN pip install --no-cache-dir -r requirements.txt hf_transfer

COPY --chown=user:user server.py rtc.py ./
COPY --chown=user:user adapters/ ./adapters/

RUN mkdir -p /home/user/.cache/huggingface && chown -R user:user /home/user /app
USER user

# PORT: Spaces route to 7860; Inference Endpoints take the port from the
# endpoint config — declare 7860 there, or set PORT. health_route=/ready.
EXPOSE 7860
CMD ["sh", "-c", "uvicorn server:app --host 0.0.0.0 --port ${PORT:-7860}"]