Oap Agent Supervisor

Open Agent Platform Supervisor

This project leverages the pre-built [LangGraph Supervisor](https://github.com/langchain-ai/langgraph-supervisor-py) agent to orchestrate specialist agents via a [RemoteGraph](https://langchain-ai.github.io/langgraph/reference/remote_graph/).

Features

• Dynamic Agent Delegation: The supervisor can decide whether to handle a user query itself or delegate it to a configured specialist agent.
• Configurable Agents: Easily define and configure multiple child agents, selecting from the list of existing agents you have deployed and configured in Open Agent Platform (OAP).
• Customizable System Prompt: Tailor the supervisor's behavior and instructions using a configurable system prompt, with a sensible default provided.

Deployments

Local

To run the supervisor locally,

1. Clone this repo

git clone https://github.com/langchain-ai/open-agent-supervisor.git

1. Copy the `.env.example` file into `.env`, and set your environment variables

   *We default to OpenAI to provide the underlying supervisor agent LLM*

cp .env.example .env

1. Create a new virtual environment, and activate it

uv venv
source .venv/bin/activate

1. Install the dependencies, and dev dependencies

uv sync

1. Run the LangGraph server locally

# The --no-browser will disable auto-opening LangGraph studio when the server starts
# optional, but recommended since the studio is not needed for this project
uv run langgraph dev --no-browser

For more info, see our [LangGraph CLI docs](https://langchain-ai.github.io/langgraph/cloud/reference/cli/#dev)

Open Agent Platform

[!IMPORTANT] **Prerequisites**: Have at least one supervisor deployed to your instance of LangGraph Platform (LGP) that matches or extends the base implementation provided in this repo

To add a supervisor agent to the platform:

1. Navigate to the `