Create Dockerfile-cuda

+Dockerfile-cuda

I created this file to help add CUDA support to open-webui for access to a GPU during embedding operations.

Dockerfile-cuda

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+# syntax=docker/dockerfile:1
+
+######## WebUI frontend ########
+FROM node:21-alpine3.19 as build
+
+WORKDIR /app
+
+COPY package.json package-lock.json ./
+RUN npm ci
+
+COPY . .
+RUN npm run build
+
+######## WebUI backend ########
+ARG CUDA_VERSION=12.3.2
+#FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu22.04 as base
+FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-ubuntu22.04 AS cuda-build-amd64
+
+# Set environment variables for NVIDIA Container Toolkit
+ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+ENV NVIDIA_DRIVER_CAPABILITIES=all
+ENV NVIDIA_VISIBLE_DEVICES=all
+
+# Install NVIDIA CUDA toolkit and libraries in the container
+#RUN apt-get update && \
+#    apt-get install -y --no-install-recommends nvidia-cuda-toolkit nvidia-cuda-dev nvidia-cudnn-dev
+
+ENV ENV=prod
+ENV PORT ""
+
+ENV OLLAMA_BASE_URL "/ollama"
+
+ENV OPENAI_API_BASE_URL ""
+ENV OPENAI_API_KEY ""
+
+ENV WEBUI_SECRET_KEY ""
+
+ENV SCARF_NO_ANALYTICS true
+ENV DO_NOT_TRACK true
+
+######## Preloaded models ########
+# whisper TTS Settings
+ENV WHISPER_MODEL="base"
+ENV 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"
+# device type for whisper tts and embedding models - "cpu" (default), "cuda" (NVIDIA GPU and CUDA required), or "mps" (apple silicon) - choosing this right can lead to better performance
+ENV RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda"
+ENV RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models"
+ENV SENTENCE_TRANSFORMERS_HOME $RAG_EMBEDDING_MODEL_DIR
+
+######## Preloaded models ########
+WORKDIR /app/backend
+
+# Install Python & dependencies in the container
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends python3.11 python3-pip ffmpeg libsm6 libxext6 pandoc netcat-openbsd && \
+    rm -rf /var/lib/apt/lists/*
+
+COPY ./backend/requirements.txt ./requirements.txt
+RUN pip3 install torch torchvision torchaudio --no-cache-dir
+RUN pip3 install -r requirements.txt --no-cache-dir
+
+# 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 .
+
+CMD [ "bash", "start.sh"]