Dockerfile optimisation

Dockerfile

@@ -1,12 +1,18 @@
 # syntax=docker/dockerfile:1
 
-FROM node:alpine as build
+######## WebUI frontend ########
+FROM node:21-bullseye-slim 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 - | \
+#RUN wget "https://chroma-onnx-models.s3.amazonaws.com/all-MiniLM-L6-v2/onnx.tar.gz" -O - | \
-    tar -xzf - -C /app
+#    tar -xzf - -C /app
 
 COPY package.json package-lock.json ./
 RUN npm ci
@@ -14,54 +20,55 @@ RUN npm ci
 COPY . .
 RUN npm run build
 
-
+######## WebUI backend ########
 FROM python:3.11-slim-bookworm as base
 
-ENV ENV=prod
+## Basis ##
-ENV PORT ""
+ENV ENV=prod \
+    PORT=8080
 
-ENV OLLAMA_BASE_URL "/ollama"
+## Basis URL Config ##
+ENV OLLAMA_BASE_URL="/ollama" \
+    OPENAI_API_BASE_URL=""
 
-ENV OPENAI_API_BASE_URL ""
+## API Key and Security Config ##
-ENV OPENAI_API_KEY ""
+ENV OPENAI_API_KEY="" \
+    WEBUI_SECRET_KEY="" \
+    SCARF_NO_ANALYTICS=true \
+    DO_NOT_TRACK=true
 
-ENV WEBUI_SECRET_KEY ""
+#### Preloaded models ##########################################################
+## whisper TTS Settings ##
+ENV WHISPER_MODEL="base" \
+    WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
 
-ENV SCARF_NO_ANALYTICS true
+## RAG Embedding Model Settings ##
-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 persormance 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"
+ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
     # 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
-ENV RAG_EMBEDDING_MODEL_DEVICE_TYPE="cpu"
+    RAG_EMBEDDING_MODEL_DEVICE_TYPE="cpu" \
-ENV RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models"
+    RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
-ENV SENTENCE_TRANSFORMERS_HOME $RAG_EMBEDDING_MODEL_DIR
+    SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"
-
+#### Preloaded models ##########################################################
-######## Preloaded models ########
 
 WORKDIR /app/backend
 
 # install python dependencies
 COPY ./backend/requirements.txt ./requirements.txt
 
-RUN apt-get update && apt-get install ffmpeg libsm6 libxext6  -y
+RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir \
+    && pip3 install -r requirements.txt --no-cache-dir
 
-RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir
+#  install required packages
-RUN pip3 install -r requirements.txt --no-cache-dir
-
-# Install pandoc and netcat
-# RUN python -c "import pypandoc; pypandoc.download_pandoc()"
 RUN apt-get update \
-    && apt-get install -y pandoc netcat-openbsd \
+    # 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/*
 
 # preload embedding model
@@ -70,8 +77,8 @@ RUN python -c "import os; from chromadb.utils import embedding_functions; senten
 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'])"
 
 # copy embedding weight from build
-RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2
+# 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 --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