Post by Shearman Chua

🚀 Introducing A2A Multimodal DeepAgent Chat I'm excited to share a project I've been working on — a full-stack multimodal AI agent system that brings together several cutting-edge technologies: 🤖 What it does: Chat with AI agents using text, images, and videos Agents can detect and classify objects in images/videos using YOLO and Vision Language Models Built on Google's A2A (Agent-to-Agent) protocol for standardized agent communication Supports streaming responses for real-time interaction 🛠️ Tech Stack: Frontend: React + Vite + Tailwind CSS Agent: Python + LangGraph DeepAgent + LangChain Tools: FastMCP (Model Context Protocol) for extensible tool integration Storage: MinIO for media handling with pre-signed URLs Observability: Arize Phoenix for tracing and debugging ✨ Key Features: 📸 Upload images/videos and get AI-powered analysis 🎯 Target detection & classification with threat assessment 🔍 Web search integration via DuckDuckGo 📡 Real-time streaming via Server-Sent Events 🐳 Fully containerized with Docker Compose Why A2A Protocol? The A2A protocol enables standardized communication between AI agents, making it easier to build interoperable multi-agent systems. This project demonstrates how to build a production-ready A2A agent with multimodal capabilities. Check out the repo: https://lnkd.in/grgQx-dH Would love to hear your thoughts and feedback! 💬 #AI #MachineLearning #LLM #MultimodalAI #AgentAI #OpenSource #Python #React #Docker #Langgraph #A2A #arizephoenix

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