vidiptvashist/Q-A-Chatbot-using-RAG-Retrieval-Augmented-Generation-

This project is a classic example of an academic/MTech capstone project. While it addresses a real-world use case (private data extraction via RAG), it utilizes standard patterns that have since been commoditized by both open-source frameworks and frontier model providers. With only 5 stars and 1 fork over a 2.5-year period, the project lacks the community momentum required to build a moat. From a competitive standpoint, the 'Chat with your PDF' functionality has been natively integrated into ChatGPT (GPTs), Claude (Artifacts/Uploads), and Google Gemini (NotebookLM). These platform-level features offer superior parsing, embedding, and reasoning capabilities with zero setup. Furthermore, professional-grade RAG frameworks like LangChain and LlamaIndex provide more robust versions of this specific architecture. The 'web scraping' component is also a standard feature in most modern LLM toolchains. The project is effectively obsolete in the current fast-moving AI landscape and serves primarily as a personal portfolio piece or a historical reference implementation of early RAG patterns.