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

# Vercel

Vercel is a platform for deploying and hosting web applications, which developers can use to easily manage their websites and serverless functions.

## Setup

The SambaNova provider is available via the `sambanova-ai-provider` module. You can install it with:

<CodeGroup>
  ```npm npm
  npm install sambanova-ai-provider
  ```

  ```yarn yarn
  yarn add sambanova-ai-provider
  ```

  ```pnpm pnpm
  pnpm add sambanova-ai-provider
  ```
</CodeGroup>

### **Environment variables**

Create a `.env` file with a `SAMBANOVA_API_KEY` variable.

## Provider Instance

You can import the default provider instance `sambanova` from `sambanova-ai-provider`:

```
import { sambanova } from 'sambanova-ai-provider';
```

If you need a customized setup, you can import `createSambaNova` from `sambanova-ai-provider` and create a provider instance with your settings:

```
import { createSambaNova } from 'sambanova-ai-provider';

const sambanova = createSambaNova({
  // Optional settings
});
```

You can use the following optional settings to customize the SambaNova provider instance:

* **baseURL** *string*

  Use a different URL prefix for API calls, e.g. to use proxy servers. The default prefix is `https://api.sambanova.ai/v1`.
* **apiKey** *string*

  API key that is being sent using the `Authorization` header. It defaults to the `SAMBANOVA_API_KEY` environment variable.
* **headers** *Record\<string,string>*

  Custom headers to include in the requests.
* **fetch** *(input: RequestInfo, init?: RequestInit) => Promise\<Response>*

  Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation. Defaults to the global `fetch` function. You can use it as a middleware to intercept requests, or to provide a custom fetch implementation for e.g. testing.

## **Models**

You can use any of [our SambaCloud models](https://docs.sambanova.ai/cloud/docs/models/sambacloud-models) on a provider instance. The first argument is the model id, e.g. `Meta-Llama-3.3-70B-Instruct`.

```
const model = sambanova('Meta-Llama-3.3-70B-Instruct');
```

## **Example Usage**

Basic demonstration of text generation using the SambaNova provider.

```
import { createSambaNova } from 'sambanova-ai-provider';
import { generateText } from 'ai';

const sambanova = createSambaNova({
  apiKey: 'YOUR_API_KEY',
});

const model = sambanova('Meta-Llama-3.3-70B-Instruct');

const { text } = await generateText({
  model,
  prompt: 'Hello, nice to meet you.',
});

console.log(text);
```

You’ll receive an output similar to the following:

```
Hello. Nice to meet you too. Is there something I can help you with or would you like to chat?
```

## **Intercepting Fetch Requests**

Intercepting fetch requests is supported. You can find more details [here](https://sdk.vercel.ai/examples/providers/intercepting-fetch-requests).

### Example

```
import { createSambaNova } from 'sambanova-ai-provider';
import { generateText } from 'ai';

const sambanovaProvider = createSambaNova({
  apiKey: 'YOUR_API_KEY',
  fetch: async (url, options) => {
    console.log('URL', url);
    console.log('Headers', JSON.stringify(options.headers, null, 2));
    console.log(`Body ${JSON.stringify(JSON.parse(options.body), null, 2)}`);
    return await fetch(url, options);
  },
});

const model = sambanovaProvider('Meta-Llama-3.3-70B-Instruct');

const { text } = await generateText({
  model,
  prompt: 'Hello, nice to meet you.',
});
```

### Example output

```
URL https://api.sambanova.ai/v1/chat/completions
Headers {
  "Content-Type": "application/json",
  "Authorization": "Bearer YOUR_API_KEY"
}
Body {
  "model": "Meta-Llama-3.3-70B-Instruct",
  "temperature": 0,
  "messages": [
    {
      "role": "user",
      "content": "Hello, nice to meet you."
    }
  ]
}
```