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Description

Welcome to the official presentation of AgentMonitor, an advanced AI project developed by Kumaraswamy Bakkashetti from Keshav Memorial Institute of Technology. AgentMonitor is a plug-and-play framework designed to make Large Language Model (LLM)-based Multi-Agent Systems (MAS) more predictive, safe, and transparent. It integrates real-time agent-wise monitoring, LLM-based safety enhancement, and XGBoost performance prediction, with an interactive React-based visualization dashboard. 🚀 Key Highlights: ✅ Real-time agent-wise safety checks using JudgeLLM ✅ Dynamic output refinement using Code Enhancer ✅ Predictive performance modeling with XGBoost ✅ Interactive visualization of agent communication & safety metrics ✅ 6.2% reduction in harmful outputs and improved overall reliability 🧩 Tech Stack: Python | LangChain | AutoGen | XGBoost | OpenAI GPT | React.js | HTML | CSS | JavaScript 📈 Objective: To ensure safe, interpretable, and efficient collaboration among AI agents in complex multi-agent systems. 💬 Future Vision: Scaling to larger agent networks, adaptive safety thresholds, and cross-task generalization for next-generation AI ecosystems. 🎓 Presented by: Kumaraswamy Bakkashetti 🏫 Institution: Keshav Memorial Institute of Technology 📅 Year: 2025 #AIProject #AgentMonitor #MultiAgentSystem #XGBoost #LangChain #LLM #ArtificialIntelligence #MachineLearning #ReactJS #PythonProjects #FinalYearProject