> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/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-5.6-luna"),
    ),
    markdown=True,
)

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

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**2. Export your API keys**

```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"
```

**3. Run the example**

Save the code above as `basic.py`, then run:

```bash theme={null}
python basic.py
```

Full source: [cookbook/90\_models/tuning\_engines/basic.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/tuning_engines/basic.py)


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