GSoC 2024 Contributor
email: atharun05@gmail.com
Education: B.Tech in Computer Science and Engineering, National Institute of Technology, Tiruchirapalli, Tamil Nadu, India
Completed project:
Integrate a Large Language Model with the xeus-cpp Jupyter kernel
Xeus-cpp, a Jupyter kernel for C++, is built upon the native implementation of the Jupyter protocol, xeus. This setup empowers users to interactively write and execute C++ code, providing immediate visibility into the results.With its REPL (read-eval-print-loop) functionality, users can rapidly prototype and iterate without the need to compile and run separate C++ programs. Additionally, this integration facilitates seamless interaction between C++ and Python within the same Jupyter environment. With the ever growing popularity of large language models, this project aims to integrate a large language model with the xeus-cpp Jupyter kernel. This integration will enable users to interactively generate and execute code in C++ leveraging the assistance of the language model.
Project Proposal: URL
Mentors: Anutosh Bhat, Johan Mabille, Aaron Jomy, David Lange, Vassil Vassilev
We are part of the
Princeton Department of Physics
and
Princeton Institute for Computational Science and Engineering
(PICSciE).
Contact: David Lange; Vassil Vassilev
This project is supported by the National Science Foundation under Grant OAC-1931408 (2020-2023) and OAC-2311471(2023-2026). Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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