Gen-AI Based Chatbot on Top of Llama for SSR Documents
Data Institutions generate vast amounts of information, making efficient access challenging. The proposed institutional chatbot integrates Llama, a conversational AI, into the institution’s website to provide real-time access to Self- Study Reports (SSR) and other documents. Using natural language processing (NLP), the chatbot streamlines communication, minimizes manual searches, and enhances transparency and accessibility. By leveraging machine learning, it interprets queries, retrieves relevant data, and generates human-like responses. A feedback loop ensures continuous learning, while Llama’s scalability enables accurate responses to complex queries. This AI-driven system modernizes institutional knowledge management and improves efficiency. Keywords - Data Institutional chatbot, Llama, natural language processing (NLP), Self-Study Reports (SSR), machine learning, information retrieval, feedback loop, knowledge management.
Authors
- Anjali Mishra (ORCID: https://orcid.org/0000-0001-6269-5424)
- Aaryan Singh
- Deepika Shekhawat (ORCID: https://orcid.org/0000-0002-6271-4602)
- Anjali Singh (ORCID: https://orcid.org/0009-0007-3640-2457)
Publication Details
- Journal
- INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
- Published
- 2025-03-31
- DOI
- https://doi.org/10.55041/ijsrem43414
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00