mirror of
https://github.com/open-webui/open-webui
synced 2025-06-26 18:26:48 +00:00
177 lines
6.6 KiB
Docker
177 lines
6.6 KiB
Docker
# syntax=docker/dockerfile:1
|
|
# Initialize device type args
|
|
# use build args in the docker build command with --build-arg="BUILDARG=true"
|
|
ARG USE_CUDA=false
|
|
ARG USE_OLLAMA=false
|
|
# Tested with cu117 for CUDA 11 and cu121 for CUDA 12 (default)
|
|
ARG USE_CUDA_VER=cu121
|
|
# 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 embedding model (sentence-transformers/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.
|
|
ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
|
|
ARG USE_RERANKING_MODEL=""
|
|
|
|
# Tiktoken encoding name; models to use can be found at https://huggingface.co/models?library=tiktoken
|
|
ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base"
|
|
|
|
ARG BUILD_HASH=dev-build
|
|
# Override at your own risk - non-root configurations are untested
|
|
ARG UID=0
|
|
ARG GID=0
|
|
|
|
######## WebUI frontend ########
|
|
FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build
|
|
ARG BUILD_HASH
|
|
|
|
WORKDIR /app
|
|
|
|
COPY package.json package-lock.json ./
|
|
RUN npm ci
|
|
|
|
COPY . .
|
|
ENV APP_BUILD_HASH=${BUILD_HASH}
|
|
RUN npm run build
|
|
|
|
######## WebUI backend ########
|
|
FROM python:3.11-slim-bookworm AS base
|
|
|
|
# Use args
|
|
ARG USE_CUDA
|
|
ARG USE_OLLAMA
|
|
ARG USE_CUDA_VER
|
|
ARG USE_EMBEDDING_MODEL
|
|
ARG USE_RERANKING_MODEL
|
|
ARG UID
|
|
ARG GID
|
|
|
|
## Basis ##
|
|
ENV ENV=prod \
|
|
PORT=8080 \
|
|
# pass build args to the build
|
|
USE_OLLAMA_DOCKER=${USE_OLLAMA} \
|
|
USE_CUDA_DOCKER=${USE_CUDA} \
|
|
USE_CUDA_DOCKER_VER=${USE_CUDA_VER} \
|
|
USE_EMBEDDING_MODEL_DOCKER=${USE_EMBEDDING_MODEL} \
|
|
USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL}
|
|
|
|
## Basis URL Config ##
|
|
ENV OLLAMA_BASE_URL="/ollama" \
|
|
OPENAI_API_BASE_URL=""
|
|
|
|
## API Key and Security Config ##
|
|
ENV OPENAI_API_KEY="" \
|
|
WEBUI_SECRET_KEY="" \
|
|
SCARF_NO_ANALYTICS=true \
|
|
DO_NOT_TRACK=true \
|
|
ANONYMIZED_TELEMETRY=false
|
|
|
|
#### Other models #########################################################
|
|
## whisper TTS model settings ##
|
|
ENV WHISPER_MODEL="base" \
|
|
WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
|
|
|
|
## RAG Embedding model settings ##
|
|
ENV RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL_DOCKER" \
|
|
RAG_RERANKING_MODEL="$USE_RERANKING_MODEL_DOCKER" \
|
|
SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"
|
|
|
|
## Tiktoken model settings ##
|
|
ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \
|
|
TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken"
|
|
|
|
## Hugging Face download cache ##
|
|
ENV HF_HOME="/app/backend/data/cache/embedding/models"
|
|
|
|
## Torch Extensions ##
|
|
# ENV TORCH_EXTENSIONS_DIR="/.cache/torch_extensions"
|
|
|
|
#### Other models ##########################################################
|
|
|
|
WORKDIR /app/backend
|
|
|
|
ENV HOME=/root
|
|
# Create user and group if not root
|
|
RUN if [ $UID -ne 0 ]; then \
|
|
if [ $GID -ne 0 ]; then \
|
|
addgroup --gid $GID app; \
|
|
fi; \
|
|
adduser --uid $UID --gid $GID --home $HOME --disabled-password --no-create-home app; \
|
|
fi
|
|
|
|
RUN mkdir -p $HOME/.cache/chroma
|
|
RUN echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id
|
|
|
|
# Make sure the user has access to the app and root directory
|
|
RUN chown -R $UID:$GID /app $HOME
|
|
|
|
RUN if [ "$USE_OLLAMA" = "true" ]; then \
|
|
apt-get update && \
|
|
# Install pandoc and netcat
|
|
apt-get install -y --no-install-recommends git build-essential pandoc netcat-openbsd curl && \
|
|
apt-get install -y --no-install-recommends gcc python3-dev && \
|
|
# for RAG OCR
|
|
apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \
|
|
# install helper tools
|
|
apt-get install -y --no-install-recommends curl jq && \
|
|
# install ollama
|
|
curl -fsSL https://ollama.com/install.sh | sh && \
|
|
# cleanup
|
|
rm -rf /var/lib/apt/lists/*; \
|
|
else \
|
|
apt-get update && \
|
|
# Install pandoc, netcat and gcc
|
|
apt-get install -y --no-install-recommends git build-essential pandoc gcc netcat-openbsd curl jq && \
|
|
apt-get install -y --no-install-recommends gcc python3-dev && \
|
|
# for RAG OCR
|
|
apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \
|
|
# cleanup
|
|
rm -rf /var/lib/apt/lists/*; \
|
|
fi
|
|
|
|
# install python dependencies
|
|
COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt
|
|
|
|
RUN pip3 install uv && \
|
|
if [ "$USE_CUDA" = "true" ]; then \
|
|
# If you use CUDA the whisper and embedding model will be downloaded on first use
|
|
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \
|
|
uv pip install --system -r requirements.txt --no-cache-dir && \
|
|
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
|
|
python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
|
|
python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
|
|
else \
|
|
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
|
|
uv pip install --system -r requirements.txt --no-cache-dir && \
|
|
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
|
|
python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
|
|
python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
|
|
fi; \
|
|
chown -R $UID:$GID /app/backend/data/
|
|
|
|
|
|
|
|
# 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
|
|
|
|
# copy built frontend files
|
|
COPY --chown=$UID:$GID --from=build /app/build /app/build
|
|
COPY --chown=$UID:$GID --from=build /app/CHANGELOG.md /app/CHANGELOG.md
|
|
COPY --chown=$UID:$GID --from=build /app/package.json /app/package.json
|
|
|
|
# copy backend files
|
|
COPY --chown=$UID:$GID ./backend .
|
|
|
|
EXPOSE 8080
|
|
|
|
HEALTHCHECK CMD curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1
|
|
|
|
USER $UID:$GID
|
|
|
|
ARG BUILD_HASH
|
|
ENV WEBUI_BUILD_VERSION=${BUILD_HASH}
|
|
ENV DOCKER=true
|
|
|
|
CMD [ "bash", "start.sh"]
|