open-webui/Dockerfile-cuda
Joseph Young f6cef312f2 Optimize Dockerfile for CUDA support
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.
2024-03-17 01:55:37 -04:00

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# syntax=docker/dockerfile:1
######## WebUI frontend ########
FROM node:21-alpine3.19 as build
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci
COPY . .
RUN npm run build
######## 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 --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-ubuntu22.04 AS cuda-build-amd64
# Set environment variables for NVIDIA Container Toolkit
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 \
NVIDIA_DRIVER_CAPABILITIES=all \
NVIDIA_VISIBLE_DEVICES=all
ENV ENV=prod \
PORT=8080
## Base URL Config ##
ENV OLLAMA_BASE_URL="/ollama" \
OPENAI_API_BASE_URL=""
## API Key and Security Config ##
ENV OPENAI_API_KEY="" \
WEBUI_SECRET_KEY="" \
SCARF_NO_ANALYTICS=true \
DO_NOT_TRACK=true
######## Preloaded models ########
# whisper TTS Settings
ENV WHISPER_MODEL="base" \
WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
# RAG Embedding Model Settings
# any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers
# Leaderboard: https://huggingface.co/spaces/mteb/leaderboard
# for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB)
# IMPORTANT: If you change the default model (all-MiniLM-L6-v2) and vice versa, you aren't able to use RAG Chat with your previous documents loaded in the WebUI! You need to re-embed them.
ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
# device type for whisper tts and embedding models - "cpu" (default), "cuda" (NVIDIA GPU and CUDA required), or "mps" (apple silicon) - choosing this right can lead to better performance
RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda" \
RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
SENTENCE_TRANSFORMERS_HOME=$RAG_EMBEDDING_MODEL_DIR
######## Preloaded models ########
WORKDIR /app/backend
# Install Python & dependencies in the container
RUN apt-get update && \
apt-get install -y --no-install-recommends python3.11 python3-pip ffmpeg libsm6 libxext6 pandoc netcat-openbsd && \
rm -rf /var/lib/apt/lists/*
COPY ./backend/requirements.txt ./requirements.txt
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
COPY --from=build /app/CHANGELOG.md /app/CHANGELOG.md
COPY --from=build /app/package.json /app/package.json
# copy backend files
COPY ./backend .
EXPOSE 8080
CMD [ "bash", "start.sh"]