Mav Chatbot is a conversational assistant designed to provide accurate and context-aware answers about the University of Texas at Arlington (UTA). This chatbot leverages a Retrieval-Augmented Generation (RAG) pipeline to ensure that users receive up-to-date and relevant information.
The system integrates Google Custom Search to fetch real-time web results, followed by web scraping to extract the most relevant content from the pages. The extracted text is then transformed into vector embeddings for efficient retrieval. Using LangChain, the project orchestrates the interaction between components — from search and retrieval to response generation. Finally, a powerful language model (via Groq API) is used to generate natural, context-rich answers based on the retrieved content.
Built With
- language
- python
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