This guide details the architecture of an AI chatbot, emphasizing the roles of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and orchestration frameworks. It explains how components like LangChain and LangGraph connect to manage agent goals, tool selection, and memory. The system utilizes a MCP Server with tools such as PostgreSQL and Google Drive, interacting with a React-based chatbot application via FastAPI, and incorporates security guardrails and Ragas for evaluation. AI
IMPACT Provides a technical overview of building AI chatbots, detailing component interactions and frameworks.
RANK_REASON The item describes the architecture and components of an AI chatbot, which falls under AI tooling.
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