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Add Rust to Docker image, update requirements.txt
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@ -18,6 +18,12 @@ RUN apt-get update && \
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apt-get clean && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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rm -rf /var/lib/apt/lists/*
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# Install Rust
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RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
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# Set up the Rust environment
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ENV PATH="/root/.cargo/bin:${PATH}"
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RUN rustup default stable
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WORKDIR /app
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WORKDIR /app
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@ -1,58 +0,0 @@
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FROM python:3.11-slim-bookworm as base
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# Use args
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ARG USE_CUDA
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ARG USE_CUDA_VER
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## Basis ##
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ENV ENV=prod \
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PORT=9099 \
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# pass build args to the build
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USE_CUDA_DOCKER=${USE_CUDA} \
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USE_CUDA_DOCKER_VER=${USE_CUDA_VER}
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# Install GCC and build tools
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RUN apt-get update && \
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apt-get install -y gcc build-essential curl git && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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# Install Python dependencies
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COPY ./requirements.txt .
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RUN pip3 install uv && \
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if [ "$USE_CUDA" = "true" ]; then \
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \
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uv pip install --system -r requirements.txt --no-cache-dir; \
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else \
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
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uv pip install --system -r requirements.txt --no-cache-dir; \
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fi
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# Copy the application code
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COPY . .
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# Install Rust compiler and ddtrace which are required for DataDog components
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RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
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# Set up the Rust environment
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ENV PATH="/root/.cargo/bin:${PATH}"
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RUN /root/.cargo/bin/rustup default stable
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# DEBUG - check that Rust installed correctly
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RUN cargo --version
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# Set the working directory to the Pipelines app dir
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WORKDIR /app
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# Install Python dependencies
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RUN pip3 install git+https://github.com/DataDog/dd-trace-py.git@main
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# Expose the port
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ENV HOST="0.0.0.0"
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ENV PORT="9099"
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ENTRYPOINT [ "bash", "start.sh" ]
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@ -27,8 +27,9 @@ redis
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sqlmodel
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sqlmodel
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chromadb
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chromadb
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# Deployment
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# Observability
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langfuse
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langfuse
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git+https://github.com/DataDog/dd-trace-py.git@main
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# ML libraries
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# ML libraries
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torch
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torch
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