forked from open-webui/open-webui
8ce48dc7d1
Okay, this was driving my OCD crazy. Corrected a spelling error in the Dockerfile's comment section to enhance documentation clarity. The typo 'persormance' was updated to 'performance,' ensuring accurate guidance on using multilingual sentence transformer models for better performance and language support.
116 lines
No EOL
5.1 KiB
Docker
116 lines
No EOL
5.1 KiB
Docker
# syntax=docker/dockerfile:1
|
|
# Initialize device type args
|
|
ARG USE_CUDA=false
|
|
ARG USE_MPS=false
|
|
|
|
######## WebUI frontend ########
|
|
FROM node:21-alpine3.19 as build
|
|
|
|
WORKDIR /app
|
|
|
|
#RUN apt-get update \
|
|
# && apt-get install -y --no-install-recommends wget \
|
|
# # cleanup
|
|
# && rm -rf /var/lib/apt/lists/*
|
|
|
|
# wget embedding model weight from alpine (does not exist from slim-buster)
|
|
#RUN wget "https://chroma-onnx-models.s3.amazonaws.com/all-MiniLM-L6-v2/onnx.tar.gz" -O - | \
|
|
# tar -xzf - -C /app
|
|
|
|
COPY package.json package-lock.json ./
|
|
RUN npm ci
|
|
|
|
COPY . .
|
|
RUN npm run build
|
|
|
|
######## WebUI backend ########
|
|
FROM python:3.11-slim-bookworm as base
|
|
|
|
# Use args
|
|
ARG USE_CUDA
|
|
ARG USE_MPS
|
|
|
|
## Basis ##
|
|
ENV ENV=prod \
|
|
PORT=8080
|
|
|
|
## 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
|
|
|
|
#### Preloaded models #########################################################
|
|
## whisper TTS Settings ##
|
|
ENV WHISPER_MODEL="base" \
|
|
WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
|
|
|
|
## RAG Embedding Model Settings ##
|
|
# 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 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.
|
|
ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
|
|
RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
|
|
SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models" \
|
|
# device type for whisper tts and embbeding models - "cpu" (default) or "mps" (apple silicon) - choosing this right can lead to better performance
|
|
# Important:
|
|
# If you want to use CUDA you need to install the nvidia-container-toolkit (https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
|
|
# you can set this to "cuda" but its recomended to use --build-arg CUDA_ENABLED=true flag when building the image
|
|
RAG_EMBEDDING_MODEL_DEVICE_TYPE="cpu" \
|
|
DEVICE_COMPUTE_TYPE="int8"
|
|
# 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
|
|
#### Preloaded models ##########################################################
|
|
|
|
WORKDIR /app/backend
|
|
# install python dependencies
|
|
COPY ./backend/requirements.txt ./requirements.txt
|
|
|
|
RUN if [ "$USE_CUDA" = "true" ]; then \
|
|
export DEVICE_TYPE="cuda" && \
|
|
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 --no-cache-dir && \
|
|
pip3 install -r requirements.txt --no-cache-dir; \
|
|
elif [ "$USE_MPS" = "true" ]; then \
|
|
export DEVICE_TYPE="mps" && \
|
|
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
|
|
pip3 install -r requirements.txt --no-cache-dir && \
|
|
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; from chromadb.utils import embedding_functions; sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=os.environ['RAG_EMBEDDING_MODEL'], device=os.environ['DEVICE_TYPE'])"; \
|
|
else \
|
|
export DEVICE_TYPE="cpu" && \
|
|
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
|
|
pip3 install -r requirements.txt --no-cache-dir && \
|
|
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; from chromadb.utils import embedding_functions; sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=os.environ['RAG_EMBEDDING_MODEL'], device=os.environ['DEVICE_TYPE'])"; \
|
|
fi
|
|
|
|
# install required packages
|
|
RUN apt-get update \
|
|
# Install pandoc and netcat
|
|
&& apt-get install -y --no-install-recommends pandoc netcat-openbsd \
|
|
# for RAG OCR
|
|
&& apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 \
|
|
# cleanup
|
|
&& rm -rf /var/lib/apt/lists/*
|
|
|
|
|
|
|
|
# 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 --from=build /app/build /app/build
|
|
COPY --from=build /app/CHANGELOG.md /app/CHANGELOG.md
|
|
COPY --from=build /app/package.json /app/package.json
|
|
|
|
# copy backend files
|
|
COPY ./backend .
|
|
|
|
EXPOSE 8080
|
|
|
|
CMD [ "bash", "start.sh"] |