Hey Everyone, I'm Kannav Sethi, a 4th Year Software Engineering Student at Seneca Polytechnic, I'm taking DPS909 - Topics In Open Source Development which is one of the professional options as one of my courses this semester. I am taking this course to enhance my credibility and explore different technologies through different projects in the open-source domain.

By the time I complete this course, I intend to be proficient in navigating and understanding large codebases, as well as contributing meaningfully to projects that utilize technologies currently unfamiliar to me. I aspire to work on projects that involve developing new frameworks or tools in TypeScript/Python, which will enhance my expertise in backend development.

I was exploring the trending repositories on GitHub this week and came across a fantastic project that offers a user interface for RAG (Retrieval-Augmented Generation). For those unfamiliar with RAG, it's essentially a technique where AI is prompted to retrieve the most relevant information from a database—often a vector database—based on similar content, to provide the best possible response. The project is called Kotaemon. What I find most impressive about this project is its versatility; it acts like an abstraction layer, allowing different AI agents and documents to be used while still effectively performing RAG. I think this project is a powerful tool for anyone working with AI and large datasets. I think going through this project would increase the knowledge that I have of working with RAG-based applications.

That was all for my first blog post, hope you enjoyed it !!