This is a legacy deployment system implementation — before moving to GitHub Actions — for PureCPP an open-source modular RAG (Retrieval-Augmented Generation) system developed by PureAI, to which I contributed during my internship, integrating C++ and Python, deploying to PyPI, and optimizing for high-performance vector processing and queries.
It also includes careful memory control strategies to maximize performance, culminating in the development of a functional and scalable vector database engine.
In addition to its modular architecture, the project features orchestration and optimization through build and deploy pipeline scripts, reducing processes that originally took ~3 hours down to just 30 minutes
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Note:
As this project is extensive and contains many modular components, this documentation will initially focus on explaining the parts I developed in the about the deploy system, as well as their integration with the pipLater sections will extend the documentation to cover:
- the C++ <-> Python bindings,
- the modular CMake architecture,
- How the VDB internals AND optimized memory management work