open-webui/Dockerfile-cuda
Joseph Young e3b1cbbb86 Parametrize CUDA_VERSION in Dockerfile
Standardized CUDA_VERSION as a global ARG to ensure consistency and facilitate version updates across the Dockerfile. This change allows the CUDA version to be defined once at the beginning and reused, reducing the chance of mismatched versions and easing maintenance when changing CUDA versions. It further streamlines the build process for potential multi-stage builds with varying CUDA dependencies.

Refs #nvidia-update
2024-03-17 02:27:06 -04:00

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# syntax=docker/dockerfile:1
ARG CUDA_VERSION=12.3.2
######## 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 ########
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"]