Multi-agent router pattern

This example demonstrates the router multi-agent pattern using langgraph. It simulates a customer support system that intelligently routes user questions to specialized agents (sales, technical support, or general) based on the query's intent.

Requirements

This project requires Python 3.6+ and the following libraries:

• langchain
• langgraph
• langchain-openai
• python-dotenv

All dependencies are listed in requirements.txt and can be installed from there.

Steps for running this example

1. Install dependencies:

python -m venv .venv

# macOS/Linux:
source .venv/bin/activate

# Windows Command Prompt:
.venv\Scripts\activate.bat

# Windows PowerShell:
.venv\Scripts\Activate.ps1

pip install -r requirements.txt

2. Set environment variables: Ensure your OpenAI API key is set as an environment variable. You can do this by:

OPENAI_API_KEY="YOUR_OPENAI_API_KEY"

Alternatively, create a .env file in the source directory with the content OPENAI_API_KEY="YOUR_OPENAI_API_KEY".

3. Run the script:

python multi_agent_router.py

Output

The script will run three example questions, demonstrating how the system routes each query to the appropriate specialized agent and generates a response.