LangGraph Learning Path

This repository contains a comprehensive set of Jupyter notebooks for learning LangGraph, from beginner to advanced levels.

📚 Learning Path

Beginner Level

1. 01_Introduction_to_LangGraph.ipynb - Basic concepts and setup
2. 02_Simple_State_Machines.ipynb - Understanding state management
3. 03_Basic_Agents.ipynb - Creating your first agent

Intermediate Level

4. 04_Advanced_State_Management.ipynb - Complex state patterns
5. 05_Multi_Agent_Systems.ipynb - Working with multiple agents
6. 06_Conditional_Flows.ipynb - Dynamic routing and conditions
7. 07_Memory_and_Context.ipynb - Managing conversation history

Advanced Level

8. 08_Complex_Workflows.ipynb - Real-world workflow examples
9. 09_Custom_Components.ipynb - Building custom nodes and edges
10. 10_Production_Patterns.ipynb - Deployment and optimization
11. 11_Advanced_Integration.ipynb - External APIs and tools
12. 12_Real_World_Projects.ipynb - Complete project examples

🚀 Getting Started

Prerequisites

pip install langgraph langchain langchain-openai jupyter

Setup

1. Clone this repository
2. Install dependencies: pip install -r requirements.txt
3. Start Jupyter: jupyter notebook
4. Follow the notebooks in order

📖 What You'll Learn

Beginner Concepts

• LangGraph fundamentals
• State management basics
• Simple agent creation
• Basic workflow patterns

Intermediate Skills

• Complex state management
• Multi-agent coordination
• Conditional logic and routing
• Memory and context handling

Advanced Techniques

• Custom component development
• Production deployment patterns
• External tool integration
• Real-world project implementation

🛠️ Requirements

Create a requirements.txt file with:

langgraph>=0.2.0
langchain>=0.2.0
langchain-openai>=0.1.0
jupyter>=1.0.0
python-dotenv>=1.0.0

🔧 Environment Setup

1. Create a .env file with your OpenAI API key:

OPENAI_API_KEY=your_api_key_here

2. Install dependencies:

pip install -r requirements.txt

📝 Notebook Structure

Each notebook follows a consistent structure:

• Theory: Conceptual explanation
• Examples: Practical code examples
• Exercises: Hands-on practice
• Challenges: Advanced problems to solve

🤝 Contributing

Feel free to contribute improvements, additional examples, or new notebooks!

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.