Connect Agno to the AI Gateway

Send requests from your Agno agents through the Logfire AI Gateway.

Agno is a Python framework for building multimodal and multi-agent AI systems. The example keeps the agent in Agno and points its OpenAIChat model at an OpenAI-compatible gateway route.

Before you start

• Complete the AI Gateway prerequisites, including setting LOGFIRE_GATEWAY_API_KEY in your terminal.
• Use an existing Agno project with the packages imported below installed.

Model data passes through Logfire

This configuration sends prompts, tool inputs, and model responses through the Logfire AI Gateway and the selected model provider. If gateway telemetry is enabled, Logfire stores the conversation content in your selected project. Calls to built-in providers count toward your gateway spend.

Configure Agno

Set api_key to your gateway key and base_url to the OpenAI-compatible gateway route. Copy the route and a supported model name from the Gateway Connect tab.

agno-gateway.py

import os

from agno.agent import Agent
from agno.models.openai import OpenAIChat

agent = Agent(
    name='Weather Agent',
    model=OpenAIChat(
        id='gpt-5.4-mini',
        api_key=os.environ['LOGFIRE_GATEWAY_API_KEY'],
        base_url='https://gateway-us.pydantic.dev/proxy/openai',
    ),
)

agent.print_response('What is the weather in London?')

Verify it worked

Run the example from your terminal. It prints the model response. That confirms the client reached the gateway. Organization admins can also open AI Engineering > Gateway > Spending to see usage for the key. If telemetry is enabled, open the selected project’s Live view to inspect the request trace.

Troubleshooting

• Python raises KeyError: 'LOGFIRE_GATEWAY_API_KEY': set the environment variable in the same terminal where you run the example.
• The request returns an authentication or model error: copy the URL and model name again from the Gateway Connect tab, and confirm that the selected route supports the OpenAI request format.