Langgraph Course AI Agent

LangGraph🦜🕸️ – Develop LLM-Powered AI Agents

   

Build production-grade AI agents—fast. This repository is the hands-on companion to my Udemy bestseller. Every branch is a project, every commit is a lesson. Clone it, code along, and ship your own LangGraph agents.

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🚀 What You'll Build

• Agentic RAG – Retrieval-Augmented Generation with self-correction & adaptive routing
• ReAct Agent – Reasoning + Acting loop implemented in LangGraph
• Reflection & Reflexion Agents – Agents that critique and improve themselves
• Multi-Step Graphs – Complex flows with conditionals, parallelism, and web-search tools

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🗂️ Repository Map

Branch	Project Snapshot	Live Code
project/agentic-rag	Advanced RAG pipeline with grading, web-search & adaptive routing	link
project/ReAct-agent	Classic ReAct (Reason + Act) agent in LangGraph	link
project/reflection	Minimal reflection demo – the why before the wow	link
project/reflection-agent	Full reflection agent that revises its own output	link
project/reflexion-agent	Reflexion agent that learns from past runs	link

✨ Tip: Checkout a branch, then use git log --oneline to watch the lessons unfold commit-by-commit.

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📚 Lesson-By-Lesson: Agentic RAG Branch

#	Commit	Lesson Title	Key Skill
1	5b2b18e	Project Kick-Off	Repo & env setup
2	2693185	Folder Structure 101	Clean project scaffolding
3	513e3cf	Ingestion Pipeline	Load & embed data
4	03f79ae	Graph State	Passing memory between nodes
5	c2d71c7	Retrieve Node	Context fetching with LangGraph
6	9107e7a	Grade Docs Node	Structured relevance filtering
7	6d4fdc4	Web Search Node	Tavily API integration
8	bc57b63	Generation Node	Prompting & LLM calls
9	a450f9b	Wiring the Graph	Fan-in, fan-out, conditionals
10	5400fb7	Self-RAG	Let the LLM critique itself
11	034e53f	Adaptive Router	Dynamic tool selection

Feel free to cherry-pick commits or rewind with git checkout <hash> to experiment.

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⚡ Quick Start

# 1. Clone & enter
$ git clone https://github.com/emarco177/langgaph-course.git
$ cd langgaph-course

# 2. Choose a project branch
$ git checkout project/agentic-rag  # for example

# 3. Install deps (Poetry)
$ poetry install

# 4. Run
$ poetry run python main.py

Create a .env file:

OPENAI_API_KEY=...
TAVILY_API_KEY=...          # optional – for web-search lessons
LANGCHAIN_API_KEY=...       # optional – for LangSmith tracing
LANGCHAIN_TRACING_V2=true   # optional
PYTHONPATH=$(pwd)

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💼 Level-Up Your Career: LangJobs🦜

Looking for your next role building Agents, RAG apps, or LangGraph integrations? Check the LangJobs.dev board—built for the 150 000-strong AI-Engineering community.
Post a job or explore openings that use the exact tech stack you're mastering here.

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🤝 Join the Community

• 💬 Discord – Private server for Q&A and project feedback
• 🐙 GitHub Issues – Bugs, ideas, PRs welcome!
• 🛠️ Bonus Repos – Extra templates & utilities for course alumni

All future updates are free. Your one-time enrollment grows with the ecosystem.

Enjoy the course & happy coding! 🎉

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🙏 Acknowledgements

Big thanks to the LangChain / LangGraph team and their excellent documentation and tutorials that make this course possible.

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