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This project demonstrates a multi-agent chatbot system built using LangGraph, LangChain, and Azure OpenAI GPT-4o. It enables intelligent routing of user queries to specialized agents .

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shaadclt/Multi-Agent-System-LangGraph

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💬 LangGraph Multi-Agent Chatbot with Azure OpenAI (GPT-4o)

This project demonstrates a multi-agent chatbot system built using LangGraph, LangChain, and Azure OpenAI GPT-4o. It enables intelligent routing of user queries to specialized agents that can handle:

  • 📦 Product Q&A (e.g., laptop features, specifications)
  • 📑 Order Management (e.g., order status, updates)
  • 💬 Small Talk (greetings, goodbyes)

The chatbot is designed to operate inside Google Colab, using userdata for secure credential handling and modular notebooks for agent logic.


🚀 Features

  • Agent Routing with LangGraph
  • 🤖 GPT-4o via Azure OpenAI API
  • 🛍️ Product Q&A Agent
  • 📦 Order Management Agent
  • 🗨️ Small Talk Handler
  • 🧠 Memory Management via thread_id
  • 📈 Visualize Agent Flow using Mermaid.js

📁 Project Structure

├── product_qna_agentic_chatbot.ipynb       # Defines Product QnA agent
├── orders_chatbot_custom_agent_langgraph.ipynb  # Defines Order management agent
├── multi_agent_system_langgraph.ipynb           # Main router agent and orchestrator
├── README.md                               # You are here

🔧 Setup Instructions

1. Clone the Repository

git clone https://github.com/shaadclt/Multi-Agent-System-LangGraph.git
cd Multi-Agent-System-LangGraph

2. Open multi_agent_system_langgraph.ipynb in Google Colab

3. Add Azure Credentials to Colab userdata

import os
from google.colab import userdata

os.environ["AZURE_OPENAI_API_KEY"] = userdata.get('AZURE_OPENAI_API_KEY')
os.environ["AZURE_OPENAI_ENDPOINT"] = userdata.get('AZURE_OPENAI_ENDPOINT')

4. Run the Notebook Cells

🧠 Conversation Flow Example


USER : How are you doing?

AGENT : Hello! I’m here to assist you with laptop features or order updates.

USER : Please show me the details of the order ORD-7311

AGENT : Your order ORD-7311 is currently being processed and will ship soon.

USER : Tell me about the features of SpectraBook laptop

AGENT : SpectraBook features include a 13” OLED display, 16GB RAM, and a 512GB SSD.

🧱 Built With

  • LangGraph

  • LangChain

  • Azure OpenAI

  • Python 3.10+

  • Google Colab

📜 License

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

✨ Acknowledgements

Thanks to:

  • LangChain & LangGraph Teams

  • Microsoft Azure OpenAI

  • OpenAI GPT-4o for powering intelligent conversations

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This project demonstrates a multi-agent chatbot system built using LangGraph, LangChain, and Azure OpenAI GPT-4o. It enables intelligent routing of user queries to specialized agents .

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