space: add root Dockerfile for trainer Space

Dockerfile

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+# DrugEnv trainer Space (Docker, single H200 GPU)
+# Serves the FastAPI control panel (space.training.app:app) on port 8000,
+# matched by README YAML app_port: 8000.
+FROM nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1 \
+    HF_HOME=/home/user/.cache/huggingface \
+    TRANSFORMERS_CACHE=/home/user/.cache/huggingface/transformers \
+    PYTHONPATH=/home/user/app \
+    PORT=8000
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        python3.11 python3.11-venv python3.11-dev python3-pip \
+        git curl ca-certificates build-essential \
+    && rm -rf /var/lib/apt/lists/* \
+    && ln -sf /usr/bin/python3.11 /usr/local/bin/python \
+    && ln -sf /usr/bin/python3.11 /usr/local/bin/python3
+
+RUN useradd -ms /bin/bash user
+USER user
+ENV PATH="/home/user/.local/bin:${PATH}"
+WORKDIR /home/user/app
+
+# Copy the entire repo first so relative -r references inside the
+# trainer requirements file (-r ../../requirements-train.txt etc.)
+# resolve correctly. Only after the tree is in place do we install.
+COPY --chown=user:user . /home/user/app
+
+RUN python -m pip install --upgrade pip && \
+    python -m pip install --user -r /home/user/app/space/training/requirements.txt
+
+EXPOSE 8000
+
+CMD ["python", "-m", "uvicorn", "space.training.app:app", "--host", "0.0.0.0", "--port", "8000"]