File size: 4,158 Bytes
3dbff85 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | # Riprap — Hugging Face Spaces deployment for the personal Space
# (msradam/riprap-nyc) on L4 hardware.
#
# Differences from the canonical Dockerfile:
#
# 1. L4 has 24 GB VRAM (vs 16 GB on T4 small), so we co-host the
# riprap-models service inside the same container instead of
# proxying to the AMD MI300X droplet. No external dependency.
#
# 2. We bake granite4.1:8b at *build* time. The build sandbox could
# not previously fit Granite + EO toolchain together; this Dockerfile
# keeps the EO install at runtime (entrypoint.l4.sh) and frees the
# sandbox budget for the 8B pull.
#
# 3. CUDA + ROCm-free torch — the inline riprap-models service uses
# the cu124 wheels installed via requirements.txt + the additional
# delta in services/riprap-models/requirements.txt.
#
# DO NOT push this image to the lablab Space — that one stays pointed
# at the MI300X droplet for AMD-judging continuity.
FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04 AS base
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
python3 python3-pip python3-venv python-is-python3 \
curl ca-certificates zstd procps git \
gdal-bin libgdal-dev libgeos-dev libproj-dev \
libgl1 libglib2.0-0 \
&& rm -rf /var/lib/apt/lists/*
RUN useradd -m -u 1000 user
ENV HOME=/home/user \
PATH=/home/user/.local/bin:/usr/local/bin:/usr/bin:/bin \
PYTHONUNBUFFERED=1 \
HF_HOME=/home/user/.cache/huggingface \
OLLAMA_HOST=127.0.0.1:11434 \
OLLAMA_NUM_PARALLEL=1 \
OLLAMA_KEEP_ALIVE=24h \
OLLAMA_MAX_LOADED_MODELS=2 \
OLLAMA_FLASH_ATTENTION=1 \
OLLAMA_KV_CACHE_TYPE=q8_0 \
OLLAMA_DEBUG=1 \
OLLAMA_MODELS=/home/user/.ollama/models \
RIPRAP_OLLAMA_3B_TAG=granite4.1:8b \
RIPRAP_LLM_PRIMARY=ollama \
RIPRAP_LLM_BASE_URL=http://127.0.0.1:11434/v1 \
RIPRAP_ML_BACKEND=remote \
RIPRAP_ML_BASE_URL=http://127.0.0.1:7861
RUN curl -fsSL https://ollama.com/install.sh | sh
WORKDIR /home/user/app
# Web app deps (torch cu124 lands via sentence-transformers / etc.).
COPY --chown=user:user requirements.txt ./
RUN pip install --no-cache-dir --upgrade pip && \
pip install --no-cache-dir -r requirements.txt
# riprap-models delta deps. Use the existing requirements.txt at the
# *service* level, but skip requirements-full.txt — its ROCm-frozen
# torch pin would clobber the cu124 wheels installed above.
COPY --chown=user:user services/riprap-models/requirements.txt /tmp/req-models.txt
RUN pip install --no-cache-dir -r /tmp/req-models.txt
# Bake torchvision (CUDA 12.4 wheel) and peft at build time. The
# canonical entrypoint.sh runtime-installs torchvision via the EO
# toolchain path because the canonical CPU Space's build sandbox is
# too tight; L4 builds have more room, and a properly matched
# torchvision avoids the `torchvision::nms does not exist` runtime
# error the canonical setup hits. peft is required by the riprap-
# models service for the TerraMind LoRA inference path.
RUN pip install --no-cache-dir \
--index-url https://download.pytorch.org/whl/cu124 \
torchvision \
&& pip install --no-cache-dir peft==0.18.1
# Bake Granite 4.1 weights into the image (EO toolchain is installed
# at runtime — see entrypoint.l4.sh — to keep the build sandbox under
# its disk threshold).
RUN mkdir -p $OLLAMA_MODELS && \
ollama serve & \
OPID=$! && \
for i in $(seq 1 30); do curl -sf http://127.0.0.1:11434/ > /dev/null && break; sleep 1; done && \
ollama pull granite4.1:8b && \
kill $OPID 2>/dev/null || true && \
sleep 2
# App code, fixtures, and inline model service.
COPY --chown=user:user app/ ./app/
COPY --chown=user:user web/ ./web/
COPY --chown=user:user scripts/ ./scripts/
COPY --chown=user:user data/ ./data/
COPY --chown=user:user corpus/ ./corpus/
COPY --chown=user:user services/riprap-models/main.py ./riprap_models.py
COPY --chown=user:user agent.py riprap.py ./
COPY --chown=user:user entrypoint.sh ./entrypoint.sh
RUN chmod +x ./entrypoint.sh
RUN chown -R user:user /home/user
USER user
EXPOSE 7860
CMD ["./entrypoint.sh"]
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