EPISODE · Mar 28, 2025 · 5 MIN
AI Multi-Agent Debate Simulation with Great Minds
from AI in Action · host Terresa P
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.
What this episode covers
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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AI Multi-Agent Debate Simulation with Great Minds
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