mirror of
https://github.com/open-webui/open-webui
synced 2024-11-06 00:32:05 +00:00
92 lines
3.5 KiB
Docker
92 lines
3.5 KiB
Docker
# syntax=docker/dockerfile:1
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######## WebUI frontend ########
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FROM node:21-alpine3.19 as build
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WORKDIR /app
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#RUN apt-get update \
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# && apt-get install -y --no-install-recommends wget \
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# # cleanup
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# && rm -rf /var/lib/apt/lists/*
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# wget embedding model weight from alpine (does not exist from slim-buster)
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#RUN wget "https://chroma-onnx-models.s3.amazonaws.com/all-MiniLM-L6-v2/onnx.tar.gz" -O - | \
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# tar -xzf - -C /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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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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## Basis ##
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ENV ENV=prod \
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PORT=8080
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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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#### Preloaded models ##########################################################
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## whisper TTS 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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# 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 persormance 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 default model (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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ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
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# device type for whisper tts and embbeding models - "cpu" (default), "cuda" (nvidia gpu and CUDA required) or "mps" (apple silicon) - choosing this right can lead to better performance
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RAG_EMBEDDING_MODEL_DEVICE_TYPE="cpu" \
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RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
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SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"
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#### Preloaded models ##########################################################
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WORKDIR /app/backend
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# install python dependencies
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COPY ./backend/requirements.txt ./requirements.txt
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RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir \
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&& pip3 install -r requirements.txt --no-cache-dir
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# install required packages
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RUN apt-get update \
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# Install pandoc and netcat
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&& apt-get install -y --no-install-recommends pandoc netcat-openbsd \
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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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# preload embedding model
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RUN python -c "import os; from chromadb.utils import embedding_functions; sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=os.environ['RAG_EMBEDDING_MODEL'], device=os.environ['RAG_EMBEDDING_MODEL_DEVICE_TYPE'])"
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# preload tts model
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RUN python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='auto', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"
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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 --from=build /app/build /app/build
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COPY --from=build /app/CHANGELOG.md /app/CHANGELOG.md
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COPY --from=build /app/package.json /app/package.json
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# copy backend files
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COPY ./backend .
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CMD [ "bash", "start.sh"]
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