This episode discusses an AI Multi-Agent Simulation Project, exemplified by an "AI Debate Simulator." It utilizes Large Language Models (LLMs), grounded by Retrieval-Augmented Generation (RAG) with a Pinecone vector database, to simulate discussions among AI personas representing various individuals. The system allows users to configure simulations with different participants and topics, observe the multi-round interactions, review the knowledge sources used, and pose follow-up questions. Built using Langchain, LangGraph, and Streamlit, the application features a user interface for setup and review, and leverages backend services like Google Generative AI for language processing and Pinecone for knowledge storage.

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