MDalamin5/End-to-End-Agentic-Ai-Automation-Lab
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.
This project helps AI developers and researchers build and deploy intelligent AI systems that can automate complex tasks. It provides practical examples and code for creating multi-agent systems and integrating them with workflow automation tools. Developers can use these resources to build scalable AI applications, from initial concept to cloud deployment.
Use this if you are an AI developer or researcher looking for hands-on experience and code examples to build, deploy, and manage intelligent AI agents and multi-agent systems at scale.
Not ideal if you are looking for a ready-to-use AI application and do not have programming or AI development experience.
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50
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26
Language
Jupyter Notebook
License
MIT
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Last pushed
Mar 09, 2026
Commits (30d)
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