- ✨ Start from an idea -> copilot builds your multi-agent workflows
- E.g. "Build me an assistant for a food delivery company to handle delivery status and missing items. Include the necessary tools."
- 🌐 Connect MCP servers
- Add the MCP servers in settings -> import the tools into Rowboat.
- 📞 Integrate into your app using the HTTP API or Python SDK
- Grab the project ID and generated API key from settings and use the API.
Powered by OpenAI's Agents SDK, Rowboat is the fastest way to build multi-agents!
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Set your OpenAI key
export OPENAI_API_KEY=your-openai-api-key
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Clone the repository and start Rowboat docker
git clone [email protected]:rowboatlabs/rowboat.git cd rowboat docker-compose up --build
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Access the app at http://localhost:3000.
There are 2 ways to integrate with the agents you create in Rowboat
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HTTP API
- You can use the API directly at http://localhost:3000/api/v1/
- See API Docs for details
curl --location 'http://localhost:3000/api/v1/<PROJECT_ID>/chat' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer <API_KEY>' \ --data '{ "messages": [ { "role": "user", "content": "tell me the weather in london in metric units" } ], "state": null }'
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Python SDK You can use the included Python SDK to interact with the Agents
pip install rowboat
See SDK Docs for details. Here is a quick example:
from rowboat import Client, StatefulChat from rowboat.schema import UserMessage, SystemMessage # Initialize the client client = Client( host="http://localhost:3000", project_id="<PROJECT_ID>", api_key="<API_KEY>" ) # Create a stateful chat session (recommended) chat = StatefulChat(client) response = chat.run("What's the weather in London?") print(response) # Or use the low-level client API messages = [ SystemMessage(role='system', content="You are a helpful assistant"), UserMessage(role='user', content="Hello, how are you?") ] # Get response response = client.chat(messages=messages) print(response.messages[-1].content)
Refer to Docs to learn how to start building agents with Rowboat.