International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 186 - Number 55 |
Year of Publication: 2024 |
Authors: Rishi Kumar Sharma |
10.5120/ijca2024924277 |
Rishi Kumar Sharma . Power of Design Documents: Building a Feature-Rich Gen-AI Chatbot with Python, OpenSearch, and LLMs. International Journal of Computer Applications. 186, 55 ( Dec 2024), 47-52. DOI=10.5120/ijca2024924277
OpenAI - the name of the latest breakthroughs in artificial intelligence (AI) research - has captured the imagination since its announcement at the end of 2015.[1] This non-profit research organization, unlike its for-profit rivals, has an ambitious vision: to ensure that Artificial General Intelligence (AGI), the highest form of AI development where machines can outperform humans in a variety of applications, works for humanity at large. This paper discusses the ability to turn design papers into a knowledge-base via Generative AI (Gen-AI). Using LLMs and a strong search engine like OpenSearch, lets explore how to create a robust chatbot that can answer questions and provide insight right from the design document. Lets walk through all the key components, starting with data preparation and indexing to model selection and integration. Lets understand how to mine valuable data from design files, preprocess them for optimal LLM performance, and provide a slick search solution with OpenSearch. Hopefully, will learn enough to create own intelligent chatbot that will help teams effectively access and make sense of important design information at the end of this article.