A practical exploration of LangGraph through conversational AI implementations. This repository contains chatbot implementations built with LangGraph, demonstrating progressive complexity in conversational AI architecture. Each implementation explores different aspects of LangGraph's capabilities for building stateful, multi-actor LLM applications.
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├── Chatbot.py # Core chatbot implementation
├── Simple_Bot.py # Foundational bot structure
├── .gitignore
└── README.md
- LangGraph – Stateful multi-actor LLM application framework
- Python 3.9+ – Primary programming language
- LangChain – LLM application development framework
- Clone the repository:
git clone https://github.com/Ahla22-19/learning-langgraph.git cd learning-langgraph
2. **Install dependencies:**
```bash
pip install langgraph langchain python-dotenv
- Configure environment variables:
# Create .env file with your API credentials
OPENAI_API_KEY=your_api_key_hereBasic chatbot implementation demonstrating core LangGraph concepts including graph structure, nodes, and basic conversation flow.
Enhanced implementation featuring:
- State management
- Conversation memory
- Improved response handling
- Error management
Run individual bot implementations:
# Execute basic bot
python Simple_Bot.py
# Run enhanced chatbot
python Chatbot.pyAhla22-19 – Exploring LangGraph through conversational AI implementations.
🔗 GitHub: @Ahla22-19
2024
If you find this project interesting, please consider:
- ⭐ Starring the repository
- 🍴 Forking to experiment with your own chatbot implementations
Ahlam Zeynu – Developer
- 📧 Email: zeynuahlam@gmail.com
- 💻 GitHub: @Ahla22-19
Project Link: https://github.com/Ahla22-19/learning-langgraph
MIT License – see LICENSE file for details
© 2024 – LangGraph Chatbot Development