I recently built an "Agentic AI Knowledge Assistant" that combines "Retrieval-Augmented Generation (RAG), hybrid search, and an LLM agent" to answer questions strictly from a predefined knowledge base.
One of the main goals of this project was to address a common problem with LLM applications: the model should not answer questions using its general pretrained knowledge when the required information is not available in the knowledge base.
How it works
The system follows a retrieval-first approach:
User Question → Hybrid Retrieval → Relevant Context → AI Agent → Final Answer:
