Let's Transform Ideas into Reality

PersonaRAG is a production-grade Retrieval-Augmented Generation (RAG) system that acts as a conversational AI twin of my professional profile. It answers questions about my experience, projects, research, and education in my own voice, grounded strictly in my resume and personal website. Unlike standard RAG pipelines, PersonaRAG is optimized for multi-turn conversations and resume-style content, where users expect complete sections (e.g., “Work Experience”) and coherent follow-ups rather than isolated text snippets.

Implementation of RAG method to perform question answering on PDF documents. HuggingFace embeddings in addition to the Groq API were used for efficient and accurate information retrieval. Session management was done to ensure embeddings are computed once per document upload to optimize performance by avoiding redundant computations.

Development of Web App that uses open source LLMs to answer user queries based on its own knowledge as well as any reference provided in the form of external webpages.