Speed up Docker image builds using multi-stage parallel pipelines

Decouple web app, server builds in parallel to speed up Docker
builds

Dockerfile

@@ -1,5 +1,5 @@
 # syntax=docker/dockerfile:1
-FROM ubuntu:jammy
+FROM ubuntu:jammy AS base
 LABEL homepage="https://khoj.dev"
 LABEL repository="https://github.com/khoj-ai/khoj"
 LABEL org.opencontainers.image.source="https://github.com/khoj-ai/khoj"
@@ -10,44 +10,46 @@ RUN apt update -y && apt -y install \
     python3-pip \
     swig \
     curl \
-    # Required by llama-cpp-python pre-built wheels. See #1628
-    musl-dev \
     # Required by RapidOCR
     libgl1 \
     libglx-mesa0 \
-    libglib2.0-0 && \
+    libglib2.0-0 \
-    # Required by Next.js Web app
-    curl -sL https://deb.nodesource.com/setup_20.x | bash - && \
-    curl -sS https://dl.yarnpkg.com/debian/pubkey.gpg | apt-key add - && \
-    echo "deb https://dl.yarnpkg.com/debian/ stable main" | tee /etc/apt/sources.list.d/yarn.list && \
-    apt update -y && apt -y --no-install-recommends install nodejs yarn && \
-    apt clean && rm -rf /var/lib/apt/lists/* && \
     # Required by llama-cpp-python pre-built wheels. See #1628
-    ln -s /usr/lib/x86_64-linux-musl/libc.so /lib/libc.musl-x86_64.so.1
+    musl-dev && \
+    ln -s /usr/lib/x86_64-linux-musl/libc.so /lib/libc.musl-x86_64.so.1 && \
+    # Clean up
+    apt clean && rm -rf /var/lib/apt/lists/*
 
-# Install Application
+# Build Server
+FROM base AS server-deps
 WORKDIR /app
 COPY pyproject.toml .
 COPY README.md .
 ARG VERSION=0.0.0
+# use the pre-built llama-cpp-python cpu wheel
 ENV PIP_EXTRA_INDEX_URL=https://abetlen.github.io/llama-cpp-python/whl/cpu
 RUN sed -i "s/dynamic = \\[\"version\"\\]/version = \"$VERSION\"/" pyproject.toml && \
     pip install --no-cache-dir .
 
-# Copy Source Code
+# Build Web App
-COPY . .
+FROM node:20-alpine AS web-app
-
+COPY src/interface/web /app/src/interface/web
-# Set the PYTHONPATH environment variable in order for it to find the Django app.
-ENV PYTHONPATH=/app/src:$PYTHONPATH
-
-# Go to the directory src/interface/web and export the built Next.js assets
 WORKDIR /app/src/interface/web
-RUN bash -c "yarn install --frozen-lockfile && yarn ciexport && yarn cache clean"
+RUN yarn install --frozen-lockfile && \
+    yarn build
+
+# Merge the Server and Web App into a Single Image
+FROM base
+ENV PYTHONPATH=/app/src
 WORKDIR /app
+COPY --from=server-deps /usr/local/lib/python3.10/dist-packages /usr/local/lib/python3.10/dist-packages
+COPY --from=web-app /app/src/interface/web/out ./src/khoj/interface/built
+COPY . .
+RUN cd src && python3 khoj/manage.py collectstatic --noinput
 
 # Run the Application
 # There are more arguments required for the application to run,
-# but these should be passed in through the docker-compose.yml file.
+# but those should be passed in through the docker-compose.yml file.
 ARG PORT
 EXPOSE ${PORT}
 ENTRYPOINT ["python3", "src/khoj/main.py"]

prod.Dockerfile

@@ -1,5 +1,5 @@
 # syntax=docker/dockerfile:1
-FROM ubuntu:jammy
+FROM ubuntu:jammy AS base
 LABEL homepage="https://khoj.dev"
 LABEL repository="https://github.com/khoj-ai/khoj"
 LABEL org.opencontainers.image.source="https://github.com/khoj-ai/khoj"
@@ -16,38 +16,40 @@ RUN apt update -y && apt -y install \
     curl \
     # Required by llama-cpp-python pre-built wheels. See #1628
     musl-dev && \
-    # Required by Next.js Web app
+    ln -s /usr/lib/x86_64-linux-musl/libc.so /lib/libc.musl-x86_64.so.1 && \
-    curl -sL https://deb.nodesource.com/setup_20.x | bash - && \
+    # Clean up
-    curl -sS https://dl.yarnpkg.com/debian/pubkey.gpg | apt-key add - && \
+    apt clean && rm -rf /var/lib/apt/lists/*
-    echo "deb https://dl.yarnpkg.com/debian/ stable main" | tee /etc/apt/sources.list.d/yarn.list && \
-    apt update -y && apt -y --no-install-recommends install nodejs yarn && \
-    apt clean && rm -rf /var/lib/apt/lists/* && \
-    # Required by llama-cpp-python pre-built wheels. See #1628
-    ln -s /usr/lib/x86_64-linux-musl/libc.so /lib/libc.musl-x86_64.so.1
 
-# Install Application
+# Build Server
+FROM base AS server-deps
 WORKDIR /app
 COPY pyproject.toml .
 COPY README.md .
 ARG VERSION=0.0.0
+# use the pre-built llama-cpp-python cpu wheel
 ENV PIP_EXTRA_INDEX_URL=https://abetlen.github.io/llama-cpp-python/whl/cpu
 RUN sed -i "s/dynamic = \\[\"version\"\\]/version = \"$VERSION\"/" pyproject.toml && \
-    pip install --no-cache-dir -e .[prod]
+    pip install --no-cache-dir .[prod]
 
-# Copy Source Code
+# Build Web App
-COPY . .
+FROM node:20-alpine AS web-app
-
+COPY src/interface/web /app/src/interface/web
-# Set the PYTHONPATH environment variable in order for it to find the Django app.
-ENV PYTHONPATH=/app/src:$PYTHONPATH
-
-# Go to the directory src/interface/web and export the built Next.js assets
 WORKDIR /app/src/interface/web
-RUN bash -c "yarn install --frozen-lockfile && yarn ciexport && yarn cache clean"
+RUN yarn install --frozen-lockfile && \
+    yarn build
+
+# Merge the Server and Web App into a Single Image
+FROM base
+ENV PYTHONPATH=/app/src
 WORKDIR /app
+COPY --from=server-deps /usr/local/lib/python3.10/dist-packages /usr/local/lib/python3.10/dist-packages
+COPY --from=web-app /app/src/interface/web/out ./src/khoj/interface/built
+COPY . .
+RUN cd src && python3 khoj/manage.py collectstatic --noinput
 
 # Run the Application
 # There are more arguments required for the application to run,
-# but these should be passed in through the docker-compose.yml file.
+# but those should be passed in through the docker-compose.yml file.
 ARG PORT
 EXPOSE ${PORT}
 ENTRYPOINT ["gunicorn", "-c", "gunicorn-config.py", "src.khoj.main:app"]