Reasoning Agent

Stream an Agno reasoning agent’s thinking to the frontend over AG-UI.

Code

cookbook/05_agent_os/interfaces/agui/reasoning_agent.py

from agno.agent.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.os.interfaces.agui import AGUI
from agno.tools.websearch import WebSearchTools

chat_agent = Agent(
    name="Assistant",
    model=OpenAIResponses(id="o4-mini"),
    instructions="You are a helpful AI assistant.",
    add_datetime_to_context=True,
    add_history_to_context=True,
    add_location_to_context=True,
    timezone_identifier="Etc/UTC",
    markdown=True,
    tools=[WebSearchTools()],
)

agent_os = AgentOS(
    agents=[chat_agent],
    interfaces=[AGUI(agent=chat_agent)],
)
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="reasoning_agent:app", reload=True, port=9001)

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
2. Set Environment Variables

   export OPENAI_API_KEY=your_openai_api_key
   
3. Install Dependencies

   uv pip install 'agno[agui]' ddgs
   
4. Run Example

   python cookbook/05_agent_os/interfaces/agui/reasoning_agent.py
   

Key Features

• Native Reasoning: o4-mini streams its reasoning as AG-UI REASONING_* events
• Visible Thinking: The frontend renders the agent’s reasoning steps in real time
• Web Search: WebSearchTools pulls in current information
• Context Aware: Date, time, and location are added to the agent’s context

Setup Frontend

1. Clone the AG-UI repository: git clone https://github.com/ag-ui-protocol/ag-ui.git
2. Install the TypeScript SDK: cd ag-ui/typescript-sdk && pnpm install
3. Build the Agno integration: cd integrations/agno && pnpm run build
4. Start Dojo: cd ../../apps/dojo && pnpm run dev
5. Open http://localhost:3000 and select the Agno integration