End-to-End Agentic AI Automation Lab
Explore real-world projects and advanced implementations of agentic AI systems, multi-agent frameworks, RAG pipelines, and AI workflow automation.
关于
This repository serves as a comprehensive, hands-on portfolio of projects demonstrating advanced agentic AI systems. Explore real-world implementations of multi-agent frameworks, Retrieval-Augmented Generation (RAG) pipelines, and AI workflow automation. It offers developers, researchers, and enthusiasts the resources to build, deploy, and manage intelligent AI agents at scale using tools like LangChain, CrewAI, and deployment strategies with Docker and AWS.
主要功能
- Multi-Agent Collaboration & Memory Management
- Model Context Protocol (MCP) Integration
- Adaptive & Agentic RAG Systems
- 1 GitHub stars
- AI Agent Frameworks (LangChain, LangGraph, CrewAI, AutoGen)
- End-to-End Deployment with CI/CD
使用案例
- Integrating standardized protocols like MCP into AI pipelines
- Building scalable and intelligent multi-agent applications
- Automating and monitoring AI workflows