128 lines
4.0 KiB
Docker
128 lines
4.0 KiB
Docker
# syntax=docker/dockerfile:1
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# Argumenty budowania
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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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# Etap budowania frontendu
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FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build
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ARG TARGETPLATFORM
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ARG BUILDPLATFORM
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ARG BUILD_HASH
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WORKDIR /app
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COPY package.json package-lock.json ./
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RUN npm ci
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COPY . .
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ENV APP_BUILD_HASH=${BUILD_HASH}
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RUN npm run build
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# Etap budowania backendu
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FROM --platform=$TARGETPLATFORM python:3.11-slim-bookworm AS base
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# Użyj argumentów
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ARG TARGETPLATFORM
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ARG USE_CUDA
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ARG USE_OLLAMA
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ARG USE_CUDA_VER
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ARG USE_EMBEDDING_MODEL
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ARG USE_RERANKING_MODEL
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ARG UID
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ARG GID
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# Ustawienia środowiskowe
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ENV ENV=prod \
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PORT=8080 \
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USE_OLLAMA_DOCKER=${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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OLLAMA_BASE_URL="/ollama" \
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OPENAI_API_BASE_URL="" \
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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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WHISPER_MODEL="base" \
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WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models" \
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RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL" \
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RAG_RERANKING_MODEL="$USE_RERANKING_MODEL" \
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SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models" \
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TIKTOKEN_ENCODING_NAME="cl100k_base" \
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TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken" \
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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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# Tworzenie użytkownika i grupy, jeśli nie 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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# Upewnij się, że użytkownik ma dostęp do katalogów
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RUN chown -R $UID:$GID /app $HOME
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# Instalacja zależności systemowych
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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git build-essential pandoc gcc netcat-openbsd curl jq \
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python3-dev ffmpeg libsm6 libxext6 && \
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if [ "$USE_OLLAMA" = "true" ]; then \
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curl -fsSL https://ollama.com/install.sh | sh; \
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fi && \
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rm -rf /var/lib/apt/lists/*
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# Instalacja zależności Pythona
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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 [ "$USE_CUDA" = "true" ]; then \
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir; \
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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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fi && \
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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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chown -R $UID:$GID /app/backend/data/
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# Kopiowanie plików frontendowych
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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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# Kopiowanie plików backendowych
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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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