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

# AI Suite integration guide

AI Suite simplifies access to multiple large language models (LLMs) through a unified interface. Use the following steps to integrate and interact with the SambaNova API using the AI Suite interface.

## Prerequisites

Before you begin, ensure you have:

* A SambaCloud API key. Get one by creating a [SambaCloud](https://cloud.sambanova.ai) account and navigating to the API keys tab.
* Python 3.9 or newer installed on your machine.

<Steps>
  <Step title="Setup your API key">
    ```bash theme={null}
    export SAMBANOVA_API_KEY="your-api-key"
    ```
  </Step>

  <Step title="Run the command to install the package">
    ```bash theme={null}
    pip install aisuite
    ```
  </Step>

  <Step title="Make a request">
    Include an import statement for the `aisuite` library in your file. To access the SambaNova API, prefix the model name with `sambanova:` followed by the specific model identifier. For example: `sambanova:Llama-4-Maverick-17B-128E-Instruct`. You can now make requests to any [Supported model](/en/models/sambacloud-models).
  </Step>
</Steps>

## Example code

```python theme={null}
import aisuite as ai
client = ai.Client()

models = ["sambanova:Llama-4-Maverick-17B-128E-Instruct", "sambanova:DeepSeek-V3.1"]

messages = [
    {"role": "system", "content": "Respond in Pirate English."},
    {"role": "user", "content": "Tell me a joke."},
]

for model in models:
    response = client.chat.completions.create(
        model=model,
        messages=messages,
        temperature=0.75
    )
    print(response.choices[0].message.content)
```

This is helpful because it allows you to compare speed and accuracy across different providers using the same codebase. For instance, you can include `openai:gpt-4o` alongside other models in your list.

For more information, see the [AI Suite README](https://github.com/andrewyng/aisuite/tree/main) on Github.