tdpeuter/open-webui
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Optimize Dockerfile for CUDA support

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Refactored the Dockerfile to better organize and streamline environment variable settings, emphasizing support for a CUDA-based WebUI backend while retaining the ability to build a CPU-only image. Consolidated ENV commands to reduce layers, improving build efficiency, and set a default PORT environment to enhance container usability. Enabled exposure of the backend service on port 8080 and leveraged combined RUN directives to minimize the image footprint. These changes facilitate a more robust deployment process, catering to both CPU and CUDA environments.
This commit is contained in:
Joseph Young 2024-03-17 01:55:37 -04:00
parent 75a40dead6
commit f6cef312f2
1 changed files with 36 additions and 33 deletions
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67
Dockerfile-cuda
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@ -11,48 +11,53 @@ RUN npm ci
COPY . .
RUN npm run build
######## WebUI backend ########
######## CPU-only WebUI backend ########
# To support both CPU and GPU backend, we need to keep the ability to build the CPU-only image.
#FROM python:3.11-slim-bookworm as base
#FROM --platform=linux/amd64 ubuntu:22.04 AS cpu-builder-amd64
#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
#RUN OPENWEBUI_CPU_TARGET="cpu" sh gen_linux.sh
#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
#RUN OPENWEBUI_CPU_TARGET="cpu_avx" sh gen_linux.sh
#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
#RUN OPENWEBUI_CPU_TARGET="cpu_avx2" sh gen_linux.sh
######## CUDA WebUI backend ########
ARG CUDA_VERSION=12.3.2
#FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu22.04 as base
FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-ubuntu22.04 AS cuda-build-amd64
# Set environment variables for NVIDIA Container Toolkit
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
ENV NVIDIA_DRIVER_CAPABILITIES=all
ENV NVIDIA_VISIBLE_DEVICES=all
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 \
NVIDIA_DRIVER_CAPABILITIES=all \
NVIDIA_VISIBLE_DEVICES=all
# Install NVIDIA CUDA toolkit and libraries in the container
#RUN apt-get update && \
# apt-get install -y --no-install-recommends nvidia-cuda-toolkit nvidia-cuda-dev nvidia-cudnn-dev
ENV ENV=prod \
PORT=8080
ENV ENV=prod
ENV PORT ""
## Base URL Config ##
ENV OLLAMA_BASE_URL="/ollama" \
OPENAI_API_BASE_URL=""
ENV OLLAMA_BASE_URL "/ollama"
ENV OPENAI_API_BASE_URL ""
ENV OPENAI_API_KEY ""
ENV WEBUI_SECRET_KEY ""
ENV SCARF_NO_ANALYTICS true
ENV DO_NOT_TRACK true
## API Key and Security Config ##
ENV OPENAI_API_KEY="" \
WEBUI_SECRET_KEY="" \
SCARF_NO_ANALYTICS=true \
DO_NOT_TRACK=true
######## Preloaded models ########
# whisper TTS Settings
ENV WHISPER_MODEL="base"
ENV WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
ENV WHISPER_MODEL="base" \
WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
# RAG Embedding Model Settings
# any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers
# Leaderboard: https://huggingface.co/spaces/mteb/leaderboard
# for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB)
# IMPORTANT: If you change the default model (all-MiniLM-L6-v2) and vice versa, you aren't able to use RAG Chat with your previous documents loaded in the WebUI! You need to re-embed them.
ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2"
ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
# device type for whisper tts and embedding models - "cpu" (default), "cuda" (NVIDIA GPU and CUDA required), or "mps" (apple silicon) - choosing this right can lead to better performance
ENV RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda"
ENV RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models"
ENV SENTENCE_TRANSFORMERS_HOME $RAG_EMBEDDING_MODEL_DIR
RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda" \
RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
SENTENCE_TRANSFORMERS_HOME=$RAG_EMBEDDING_MODEL_DIR
######## Preloaded models ########
WORKDIR /app/backend
@ -63,12 +68,8 @@ RUN apt-get update && \
rm -rf /var/lib/apt/lists/*
COPY ./backend/requirements.txt ./requirements.txt
RUN pip3 install torch torchvision torchaudio --no-cache-dir
RUN pip3 install -r requirements.txt --no-cache-dir
# copy embedding weight from build
RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2
COPY --from=build /app/onnx /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx
RUN pip3 install torch torchvision torchaudio --no-cache-dir && \
pip3 install -r requirements.txt --no-cache-dir
# copy built frontend files
COPY --from=build /app/build /app/build
@ -78,4 +79,6 @@ COPY --from=build /app/package.json /app/package.json
# copy backend files
COPY ./backend .
EXPOSE 8080
CMD [ "bash", "start.sh"]