{"repo":"MDalamin5/End-to-End-Agentic-Ai-Automation-Lab","free":true,"listed":false,"github":"https://github.com/MDalamin5/End-to-End-Agentic-Ai-Automation-Lab","clone":"git clone https://github.com/MDalamin5/End-to-End-Agentic-Ai-Automation-Lab.git","description":"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.","language":"Jupyter Notebook","stars":91,"topics":["agentic-ai","agentic-rag","autogen","docker","langchain","langgraph","mcp-server","langsmit","ambient-ai","deep-agents"],"license":"MIT","category":"ai-agents","readme_excerpt":"🤖 End-to-End Agentic AI & Automation Lab A comprehensive, production-grade repository for building, deploying, and managing intelligent AI agents, RAG pipelines, and automated workflows. Overview • Key Highlights • Project Architecture • Tech Stack • Getting Started --- 📖 Overview Welcome to the End-to-End Agentic AI Automation Lab . This repository is a massive, hands-on engineering playbook demonstrating how to transition from basic LLM API calls to complex, multi-agent autonomous systems and production-ready AI products . Whether you are looking to build highly reliable Agentic workflows using LangGraph , orchestrate multi-agent collaboration via AutoGen , implement cutting-edge Model Context Protocol (MCP) , or serve fine-tuned local models using vLLM and Unsloth , this repository has you covered. --- 🚀 Key Highlights Advanced Agentic Frameworks : Deep dives into LangGraph (StateGraphs, subgraphs, memory, HITL) and AutoGen (RoundRobin, Swarm, custom tools). Model Context Protocol (MCP) : Industry-grade implementations of Anthropic's MCP for tool execution, web search, and Notion integration. Production RAG Systems : Implementation of Hybrid Search, BM25, LlamaParse, Semantic Routing, and Long/Short-Term Memory (Mem0). AI Workflow Automation : Zero-code/low-code multi-agent orchestration using n8n and LangFlow . LLM Fine-Tuning & Serving : Hands-on pipelines for fine-tuning with LoRA/Unsloth and deploying high-throughput inference endpoints with vLLM . End-to-End Produc","default_branch":null,"files":null,"tree":[],"storefront":"/r/MDalamin5","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MDalamin5/End-to-End-Agentic-Ai-Automation-Lab/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}