azure-ai-agentserver-langgraph 1.0.0b2

LangGraph adapter for Azure AI Agent Server

Azure AI Agent Server Adapter for LangGraph Python

Getting started

pip install azure-ai-agentserver-langgraph

Key concepts

Azure AI Agent Server wraps your LangGraph agent, and host it on the cloud.

Examples

# your existing agent
from my_langgraph_agent import my_awesome_agent

# langgraph utils
from azure.ai.agentserver.langgraph import from_langgraph

if __name__ == "__main__":
    # with this simple line, your agent will be hosted on http://localhost:8088
    from_langgraph(my_awesome_agent).run()

Note If your langgraph agent was not using langgraph's builtin MessageState, you should implement your own LanggraphStateConverter and provide to from_langgraph.

Reference this example for more details.

Troubleshooting

First run your agent with azure-ai-agentserver-langgraph locally.

If it works on local but failed on cloud. Check your logs in the application insight connected to your Azure AI Foundry Project.

Next steps

Please visit Samples folder. There are several samples for you to build your agent with azure-ai-agentserver-* packages

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the [Microsoft Open Source Code of Conduct][code_of_conduct]. For more information, see the Code of Conduct FAQ or contact [e-mail] with any additional questions or comments.