forked from open-webui/open-webui
c004ecdccc
Switched to Chainguard images as base for both CPU and CUDA backend builds for improved security and compatibility. Replaced Ubuntu base with Chainguard's Python image for the CPU builds and PyTorch CUDA image for GPU acceleration, resolving python requirements conflicts. Updated package installation commands to align with the new Redhat-compatible base images. The Dockerfile now installs only the necessary dependencies, as Python is provided by the base image. These changes will facilitate a more secure and streamlined build process with better dependency management across different platforms.
101 lines
3.8 KiB
Text
101 lines
3.8 KiB
Text
# syntax=docker/dockerfile:1
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ARG CUDA_VERSION=12.3.2
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######## WebUI frontend ########
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FROM node:21-alpine3.19 as build
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WORKDIR /app
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COPY package.json package-lock.json ./
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RUN npm ci
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COPY . .
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RUN npm run build
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######## CPU-only WebUI backend ########
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# To support both CPU and GPU backend, we need to keep the ability to build the CPU-only image.
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#FROM python:3.11-slim-bookworm as base
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FROM --platform=linux/amd64 cgr.dev/chainguard/python:latest-dev AS cpu-build-amd64
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#FROM --platform=linux/amd64 ubuntu:22.04 AS cpu-builder-amd64
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#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
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#RUN OPENWEBUI_CPU_TARGET="cpu" sh gen_linux.sh
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#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
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#RUN OPENWEBUI_CPU_TARGET="cpu_avx" sh gen_linux.sh
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#FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
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#RUN OPENWEBUI_CPU_TARGET="cpu_avx2" sh gen_linux.sh
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######## CUDA WebUI backend ########
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#FROM --platform=linux/amd64 nvidia/cuda:"$CUDA_VERSION"-devel-ubuntu22.04 AS cuda-build-amd64
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#FROM --platform=linux/amd64 cgr.dev/chainguard/pytorch-cuda12:latest AS cuda-build-amd64 # fails with python requirements conflicts
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# Set environment variables for NVIDIA Container Toolkit
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ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 \
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NVIDIA_DRIVER_CAPABILITIES=all \
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NVIDIA_VISIBLE_DEVICES=all
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ENV ENV=prod \
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PORT=8080
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## Base URL Config ##
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ENV OLLAMA_BASE_URL="/ollama" \
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OPENAI_API_BASE_URL=""
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## API Key and Security Config ##
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ENV OPENAI_API_KEY="" \
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WEBUI_SECRET_KEY="" \
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SCARF_NO_ANALYTICS=true \
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DO_NOT_TRACK=true
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######## Preloaded models ########
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# whisper TTS Settings
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ENV WHISPER_MODEL="base" \
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WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
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# RAG Embedding Model Settings
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# any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers
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# Leaderboard: https://huggingface.co/spaces/mteb/leaderboard
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# for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB)
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# 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.
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ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
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# 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
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RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda" \
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RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
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SENTENCE_TRANSFORMERS_HOME=$RAG_EMBEDDING_MODEL_DIR
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######## Preloaded models ########
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WORKDIR /app/backend
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# Install Python & dependencies in the container
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# Used for Debian
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#RUN apt-get update && \
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# apt-get install -y --no-install-recommends python3.11 python3-pip ffmpeg libsm6 libxext6 pandoc netcat-openbsd && \
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# rm -rf /var/lib/apt/lists/*
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# Used for Redhat
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#RUN apk update && \
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# apk add --no-install-recommends python3.11 python3-pip ffmpeg libsm6 libxext6 pandoc netcat-openbsd && \
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# apk del /var/cache/apk/*.tbz2
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# Install only the dependencies in the container, python will come from the base image used
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RUN apk update && \
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apk add --no-install-recommends ffmpeg libsm6 libxext6 pandoc netcat-openbsd && \
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apk del /var/cache/apk/*.tbz2
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COPY ./backend/requirements.txt ./requirements.txt
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RUN pip3 install torch torchvision torchaudio --no-cache-dir && \
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pip3 install -r requirements.txt --no-cache-dir
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# copy built frontend files
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COPY --from=build /app/build /app/build
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COPY --from=build /app/CHANGELOG.md /app/CHANGELOG.md
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COPY --from=build /app/package.json /app/package.json
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# copy backend files
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COPY ./backend .
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EXPOSE 8080
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CMD [ "bash", "start.sh"]
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