mirror of
https://github.com/khoaliber/khoj.git
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42 lines
1.6 KiB
Docker
42 lines
1.6 KiB
Docker
ARG PYTHON_VERSION=3.10
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FROM mcr.microsoft.com/devcontainers/python:${PYTHON_VERSION}
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# Install Node.js and Yarn
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RUN curl -fsSL https://deb.nodesource.com/setup_lts.x | bash - && \
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apt-get install -y nodejs
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# Setup working directory
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WORKDIR /workspace
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# --- Python Server App Dependencies ---
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# Create Python virtual environment
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RUN python3 -m venv /opt/venv
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# Add venv to PATH for subsequent RUN commands and for the container environment
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ENV PATH="/opt/venv/bin:${PATH}"
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# Copy files required for Python dependency installation.
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COPY pyproject.toml README.md ./
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# Setup python environment
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# Use the pre-built llama-cpp-python, torch cpu wheel
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ENV PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu https://abetlen.github.io/llama-cpp-python/whl/cpu" \
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# Avoid downloading unused cuda specific python packages
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CUDA_VISIBLE_DEVICES="" \
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# Use static version to build app without git dependency
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VERSION=0.0.0
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# Install Python dependencies from pyproject.toml in editable mode
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RUN sed -i "s/dynamic = \\[\"version\"\\]/version = \"$VERSION\"/" pyproject.toml && \
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pip install --no-cache-dir ".[dev]"
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# --- Web App Dependencies ---
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# Copy web app manifest files
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COPY src/interface/web/package.json src/interface/web/yarn.lock /tmp/web/
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# Install web app dependencies
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# note: yarn will be available from the "features" in devcontainer.json
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RUN yarn install --cwd /tmp/web --cache-folder /opt/yarn-cache
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# The .venv and node_modules are now populated in the image.
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# The rest of the source code will be mounted by VS Code from your local checkout,
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# overlaying any files copied here if they are part of the workspace mount.
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