mirror of
https://github.com/open-webui/open-webui.git
synced 2025-12-13 12:55:19 +00:00
632aaff608
When Python runs in Docker containers without PYTHONUNBUFFERED=1, stdout and stderr output is buffered. If the application crashes before the buffer is flushed, critical log output is lost, making debugging and error reporting difficult. This change ensures that Python output is unbuffered so that all logs are captured immediately, regardless of whether the application crashes or exits normally. Fixes issue #19844
192 lines
7.1 KiB
Docker
192 lines
7.1 KiB
Docker
# syntax=docker/dockerfile:1
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# Initialize device type args
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# use build args in the docker build command with --build-arg="BUILDARG=true"
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ARG USE_CUDA=false
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ARG USE_OLLAMA=false
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ARG USE_SLIM=false
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ARG USE_PERMISSION_HARDENING=false
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# Tested with cu117 for CUDA 11 and cu121 for CUDA 12 (default)
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ARG USE_CUDA_VER=cu128
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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 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.
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ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
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ARG USE_RERANKING_MODEL=""
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# Tiktoken encoding name; models to use can be found at https://huggingface.co/models?library=tiktoken
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ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base"
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ARG BUILD_HASH=dev-build
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# Override at your own risk - non-root configurations are untested
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ARG UID=0
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ARG GID=0
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######## WebUI frontend ########
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FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build
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ARG BUILD_HASH
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# Set Node.js options (heap limit Allocation failed - JavaScript heap out of memory)
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# ENV NODE_OPTIONS="--max-old-space-size=4096"
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WORKDIR /app
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# to store git revision in build
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RUN apk add --no-cache git
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COPY package.json package-lock.json ./
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RUN npm ci --force
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COPY . .
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ENV APP_BUILD_HASH=${BUILD_HASH}
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RUN npm run build
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######## WebUI backend ########
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FROM python:3.11-slim-bookworm AS base
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# Use args
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ARG USE_CUDA
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ARG USE_OLLAMA
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ARG USE_CUDA_VER
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ARG USE_SLIM
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ARG USE_PERMISSION_HARDENING
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ARG USE_EMBEDDING_MODEL
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ARG USE_RERANKING_MODEL
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ARG UID
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ARG GID
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## Basis ##
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ENV ENV=prod \
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PYTHONUNBUFFERED=1 \
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PORT=8080 \
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# pass build args to the build
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USE_OLLAMA_DOCKER=${USE_OLLAMA} \
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USE_CUDA_DOCKER=${USE_CUDA} \
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USE_SLIM_DOCKER=${USE_SLIM} \
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USE_CUDA_DOCKER_VER=${USE_CUDA_VER} \
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USE_EMBEDDING_MODEL_DOCKER=${USE_EMBEDDING_MODEL} \
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USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL}
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## Basis 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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ANONYMIZED_TELEMETRY=false
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#### Other models #########################################################
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## whisper TTS model 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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ENV RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL_DOCKER" \
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RAG_RERANKING_MODEL="$USE_RERANKING_MODEL_DOCKER" \
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SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"
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## Tiktoken model settings ##
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ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \
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TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken"
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## Hugging Face download cache ##
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ENV HF_HOME="/app/backend/data/cache/embedding/models"
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## Torch Extensions ##
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# ENV TORCH_EXTENSIONS_DIR="/.cache/torch_extensions"
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#### Other models ##########################################################
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WORKDIR /app/backend
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ENV HOME=/root
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# Create user and group if not root
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RUN if [ $UID -ne 0 ]; then \
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if [ $GID -ne 0 ]; then \
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addgroup --gid $GID app; \
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fi; \
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adduser --uid $UID --gid $GID --home $HOME --disabled-password --no-create-home app; \
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fi
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RUN mkdir -p $HOME/.cache/chroma
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RUN echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id
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# Make sure the user has access to the app and root directory
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RUN chown -R $UID:$GID /app $HOME
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# Install common system dependencies
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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git build-essential pandoc gcc netcat-openbsd curl jq \
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python3-dev \
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ffmpeg libsm6 libxext6 \
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&& rm -rf /var/lib/apt/lists/*
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# install python dependencies
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COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt
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RUN pip3 install --no-cache-dir uv && \
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if [ "$USE_CUDA" = "true" ]; then \
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# If you use CUDA the whisper and embedding model will be downloaded on first use
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \
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uv pip install --system -r requirements.txt --no-cache-dir && \
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python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
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python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
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python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
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else \
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
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uv pip install --system -r requirements.txt --no-cache-dir && \
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if [ "$USE_SLIM" != "true" ]; then \
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python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
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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'])"; \
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python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
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fi; \
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fi; \
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mkdir -p /app/backend/data && chown -R $UID:$GID /app/backend/data/ && \
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rm -rf /var/lib/apt/lists/*;
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# Install Ollama if requested
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RUN if [ "$USE_OLLAMA" = "true" ]; then \
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date +%s > /tmp/ollama_build_hash && \
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echo "Cache broken at timestamp: `cat /tmp/ollama_build_hash`" && \
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curl -fsSL https://ollama.com/install.sh | sh && \
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rm -rf /var/lib/apt/lists/*; \
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fi
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# copy embedding weight from build
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# RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2
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# COPY --from=build /app/onnx /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx
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# copy built frontend files
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COPY --chown=$UID:$GID --from=build /app/build /app/build
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COPY --chown=$UID:$GID --from=build /app/CHANGELOG.md /app/CHANGELOG.md
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COPY --chown=$UID:$GID --from=build /app/package.json /app/package.json
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# copy backend files
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COPY --chown=$UID:$GID ./backend .
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EXPOSE 8080
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HEALTHCHECK CMD curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1
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# Minimal, atomic permission hardening for OpenShift (arbitrary UID):
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# - Group 0 owns /app and /root
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# - Directories are group-writable and have SGID so new files inherit GID 0
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RUN if [ "$USE_PERMISSION_HARDENING" = "true" ]; then \
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set -eux; \
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chgrp -R 0 /app /root || true; \
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chmod -R g+rwX /app /root || true; \
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find /app -type d -exec chmod g+s {} + || true; \
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find /root -type d -exec chmod g+s {} + || true; \
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fi
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USER $UID:$GID
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ARG BUILD_HASH
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ENV WEBUI_BUILD_VERSION=${BUILD_HASH}
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ENV DOCKER=true
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CMD [ "bash", "start.sh"]
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