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| # 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"] | |