🧩 LangGraph Examples

This repository contains a collection of Jupyter notebooks that demonstrate how to build AI workflows and agents using LangGraph.
The examples go step by step, starting from simple graphs to full-featured agents.

---

📂 Notebooks

1. 1_simple_graph.ipynb
   Introduction to building a minimal LangGraph. Learn how nodes and edges work.

2. 2_graph_with_condition.ipynb
   Add conditional logic and branching inside your LangGraph.

3. 3_chatbot.ipynb
   Create a basic chatbot agent with LangGraph.

4. 4_tool_calls.ipynb
   Connect your agent to external tools (e.g., search, APIs) using LangGraph.

5. 5_memory.ipynb
   Add short-term and long-term memory to your chatbot agent.

6. 6_langsmith_tracing.ipynb
   Use LangSmith for tracing, debugging, and evaluating your LangGraph runs.

7. 7_car_buyer_agent.ipynb
   End-to-end example: An AI agent that helps simulate a car buyer assistant.

8. 8_custom_support_service.ipynb
   Build a customer support service agent that answers FAQs and routes queries.

---

🚀 Getting Started

1. Clone the repo

git clone https://github.com/your-username/langgraph-examples.git
cd langgraph-examples

---

📦 Requirements

This project uses Python 3.9+ and the following libraries. You can install them via requirements.txt:

Install dependencies

uv pip install -r requirements.txt

⭐ Star this repo if you found it helpful! ⭐