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ARG USE_CUDA=false |
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ARG USE_OLLAMA=false |
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ARG USE_CUDA_VER=cu121 |
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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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ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base" |
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ARG BUILD_HASH=dev-build |
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ARG UID=0 |
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ARG GID=0 |
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FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build |
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ARG BUILD_HASH |
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WORKDIR /app |
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COPY package.json package-lock.json ./ |
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RUN npm ci |
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COPY . . |
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ENV APP_BUILD_HASH=${BUILD_HASH} |
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RUN npm run build |
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FROM python:3.11-slim-bookworm AS base |
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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_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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ENV ENV=prod \ |
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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_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=${USE_RERANKING_MODEL} |
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ENV OLLAMA_BASE_URL="/ollama" \ |
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OPENAI_API_BASE_URL="" |
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ENV OPENAI_API_KEY="" \ |
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WEBUI_SECRET_KEY="" \ |
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SCARF_NO_ANALYTICS=true \ |
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DO_NOT_TRACK=true \ |
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ANONYMIZED_TELEMETRY=false |
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ENV WHISPER_MODEL="base" \ |
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WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models" |
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ENV RAG_EMBEDDING_MODEL="$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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ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \ |
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TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken" |
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ENV HF_HOME="/app/backend/data/cache/embedding/models" |
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WORKDIR /app/backend |
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ENV HOME=/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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RUN chown -R $UID:$GID /app $HOME |
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RUN if [ "$USE_OLLAMA" = "true" ]; then \ |
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apt-get update && \ |
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# Install pandoc and netcat |
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apt-get install -y --no-install-recommends git build-essential pandoc netcat-openbsd curl && \ |
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apt-get install -y --no-install-recommends gcc python3-dev && \ |
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# for RAG OCR |
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apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \ |
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# install helper tools |
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apt-get install -y --no-install-recommends curl jq && \ |
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# install ollama |
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curl -fsSL https://ollama.com/install.sh | sh && \ |
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# cleanup |
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rm -rf /var/lib/apt/lists/*; \ |
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else \ |
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apt-get update && \ |
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# Install pandoc, netcat and gcc |
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apt-get install -y --no-install-recommends git build-essential pandoc gcc netcat-openbsd curl jq && \ |
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apt-get install -y --no-install-recommends gcc python3-dev && \ |
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# for RAG OCR |
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apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \ |
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# cleanup |
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rm -rf /var/lib/apt/lists/*; \ |
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fi |
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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 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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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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chown -R $UID:$GID /app/backend/data/ |
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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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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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