LangChainHandsOn vs End-to-End-Agentic-Ai-Automation-Lab

This repository is dedicated to learning and experimenting with LangChain. It contains hands-on examples, notes, and mini-projects that explore concepts like prompt engineering, LLM orchestration, RAG (Retrieval-Augmented Generation), agentic workflows, and tool integrations.

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.

MCP Servers

MCP Servers

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Jupyter Notebook

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MIT

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