> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Basic

> Use Agno with Tuning Engines as an OpenAI-compatible endpoint.

```python basic.py theme={null}
"""Use Agno with Tuning Engines as an OpenAI-compatible endpoint."""

from os import getenv

from agno.agent import Agent
from agno.models.tuning_engines import TuningEngines

agent = Agent(
    model=TuningEngines(
        id=getenv("TUNING_ENGINES_MODEL", "gpt-4o"),
    ),
    markdown=True,
)

agent.print_response(
    "Explain how governance, traces, and usage reporting help production AI agents.",
    stream=True,
)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Export your API keys">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export TUNING_ENGINES_API_KEY="your_tuning_engines_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:TUNING_ENGINES_API_KEY="your_tuning_engines_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `basic.py`, then run:

    ```bash theme={null}
    python basic.py
    ```
  </Step>
</Steps>

Full source: [cookbook/90\_models/tuning\_engines/basic.py](https://github.com/agno-agi/agno/blob/main/cookbook/90_models/tuning_engines/basic.py)