{"id":24401641,"url":"https://github.com/jkmaina/langgraphprojects","last_synced_at":"2025-12-24T18:40:08.593Z","repository":{"id":272004340,"uuid":"913639572","full_name":"jkmaina/LangGraphProjects","owner":"jkmaina","description":"This is the official companion repository for the book The Complete LangGraph Blueprint: Build 50+ AI Agents for Business Success. 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This book guides you through creating 50+ AI agents for real-world business applications using LangGraph and other cutting-edge AI tools.\n\n---\n\n## About the Book 📚\n\nThis project is a comprehensive guide to building AI agents using LangGraph, an open-source framework for graph-based AI workflows. It covers fundamental programming concepts, LangGraph principles, and step-by-step tutorials to develop intelligent, autonomous systems. Whether you're a beginner or an experienced developer, this book provides everything you need to harness AI for innovation and success.\n\n---\n\n## Why Buy This Book? 🎯\n\n- **Exclusive Knowledge**: Master the techniques for building 50+ AI agents.\n- **Hands-On Learning**: Follow detailed examples and exercises to build your AI agents step by step.\n- **Real-World Applications**: Learn how to solve practical business problems with AI.\n- **Expert Guidance**: Written by an industry expert with a wealth of experience in AI and automation.\n\n👉 [Get your copy now on Amazon!](https://www.amazon.com/Complete-LangGraph-Blueprint-Business-Success-ebook/dp/B0DP69QV7K)\n\n---\n\n## Key Features 🚀\n\n- **50+ AI Agents**: Build and customize AI agents with dynamic decision-making and tool integration.\n- **Graph-Based AI Workflows**: Learn how to create workflows using nodes, edges, states, and conditions.\n- **LLM Integration**: Leverage Large Language Models like GPT-4 for natural language understanding.\n- **Tool Nodes**: Integrate APIs and external systems into your AI agents.\n- **Memory \u0026 Persistence**: Implement short-term and long-term memory for enhanced user experiences.\n- **Use Cases**: Apply your skills across industries like customer service, healthcare, and finance.\n- **Practical Exercises**: Reinforce learning with hands-on coding examples.\n\n---\n\n## Project Structure 🗂\n\nThe repository is organized as follows:\n\n```\nLANGGRAPHPROJECTS/\n├── chapter1/             # Code for Chapter 1\n├── chapter2/             # Code for Chapter 2\n├── chapter3/             # Code for Chapter 3\n├── chapter4/             # Code for Chapter 4\n├── chapter5/             # Code for Chapter 5\n├── chapter6/             # Code for Chapter 6\n├── chapter7/             # Code for Chapter 7\n├── chapter8/             # Code for Chapter 8\n├── chapter9/             # Code for Chapter 9\n├── chapter10/            # Code for Chapter 10\n├── chapter11/            # Code for Chapter 11\n├── chapter12/            # Code for Chapter 12\n├── chapter13/            # Code for Chapter 13\n├── chapter15/            # Code for Chapter 15\n├── chapter16/            # Code for Chapter 16\n├── chapter17/            # Code for Chapter 17\n├── chapter18/            # Code for Chapter 18\n├── chapter19/            # Code for Chapter 19\n├── chapter20/            # Code for Chapter 20\n├── output/               # Generated outputs and artifacts\n├── testing/              # Unit tests and experimental workflows\n├── .env                  # Environment configuration file\n├── .gitignore            # Git ignored files\n├── data.json             # Sample data for workflows\n├── display_graph.py      # Visualization script for LangGraph workflows\n├── graph_24371.png       # Example graph visualization\n├── graph_80385.png       # Example graph visualization\n├── lesson4.py            # Lesson 4 code file\n├── lesson5.py            # Lesson 5 code file\n└── README.md             # Project documentation (this file)\n```\n\n---\n\n## Getting Started 🚦\n\n### Prerequisites\n\n- **Python 3.10+**: Install from [python.org](https://www.python.org/downloads/).\n- **Dependencies**: Install required libraries like `langgraph`, `langchain`, and `openai`.\n\n```bash\npip install langgraph langchain_openai python-dotenv\n```\n\n---\n\n### Setting Up Your Environment\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/jkmaina/LangGraphProjects.git\n   cd langgraph-blueprint\n   ```\n\n2. Create a virtual environment:\n   ```bash\n   python -m venv langgraph_env\n   source langgraph_env/bin/activate  # On Linux/macOS\n   langgraph_env\\Scripts\\activate     # On Windows\n   ```\n\n3. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n4. Add your OpenAI API key:\n   - Create a `.env` file in the root directory:\n     ```\n     OPENAI_API_KEY=your-api-key-here\n     ```\n\n---\n\n### Running Your First AI Agent\n\n- Navigate to the `/chapter1/lesson1a.py` directory.\n- Run the Hello World LangGraph workflow:\n   ```bash\n   python lesson1a.py\n   ```\n\n---\n\n## Contributing 🤝\n\nContributions are welcome! Submit issues, feature requests, or pull requests to improve this project.\n\n---\n\n## License 📝\n\nThis repository is licensed under the Apache 2.0 License. See the `LICENSE` file for details.\n\n---\n\n## Support and Resources 📚\n\n- **Book Updates and Code Samples**: Subscribe for updates and new content at [james.karanja@zavora.ai](mailto:james.karanja@zavora.ai).\n- **Community Discussions**: Join the conversation on LangGraph workflows, agent designs, and AI tools.\n- **LangGraph Documentation**: [Official LangGraph Docs](https://langgraph.docs.example)\n\nHappy Coding! 🎉\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjkmaina%2Flanggraphprojects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjkmaina%2Flanggraphprojects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjkmaina%2Flanggraphprojects/lists"}