Simple Chatbot using LangChain just Q & A Generative AI Application.

Understand about RAG using Langchain How Rag Works and with practical implimentation

Core Agentic AI implementation using the OpenAI Agent SDK in Python. This repository demonstrates how to build intelligent, tool-using AI agents

Learn ABout Prompt Engineering In Structured Way

MCP crash course in which you will learn how to build client and server and interact them

A smart PDF summarization tool built with AI to convert large documents into meaningful summaries.

Latest langchain version tutorial which is v1

Master the power of MCP (Model Context Protocol) with this beginner-to-advanced repository! This repo is designed to help developers understand how MCP enables seamless communication between AI models, tools, and external systems.

A structured collection of real-world projects built using LangGraph — covering everything from basic workflows to advanced multi-agent systems, RAG pipelines, and autonomous AI agents. Perfect for beginners to advanced developers exploring graph-based AI architectures.

Learn MCP by building clients and servers that connect AI apps to tools, data, and workflows

Learn prompt engineering patterns to craft better AI prompts, guide LLMs, and improve output quality with clear examples and methods

Learn MCP with practical projects for beginner to advanced use, connecting AI models, tools, and external systems

Explore a LangChain document pipeline for RAG, from ingestion and embeddings to retrieval and LLM response generation