Feat (docs): Add SambaNova provider

content/providers/03-community-providers/96-sambanova.md

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+---
+title: SambaNova
+description: Learn how to use the SambaNova provider for the AI SDK.
+---
+# SambaNova Provider
+
+[sambanova-ai-provider](https://github.com/sambanova/sambanova-ai-provider) contains language model support for the SambaNova API.
+
+API keys can be obtained from the [SambaNova Cloud Platform](https://cloud.sambanova.ai/apis).
+
+## Setup
+
+The SambaNova provider is available via the `sambanova-ai-provider` module. You can install it with:
+
+<Tabs items={['pnpm', 'npm', 'yarn']}>
+  <Tab>
+    <Snippet text="pnpm add sambanova-ai-provider" dark />
+  </Tab>
+  <Tab>
+    <Snippet text="npm install sambanova-ai-provider" dark />
+  </Tab>
+  <Tab>
+    <Snippet text="yarn add sambanova-ai-provider" dark />
+  </Tab>
+</Tabs>
+
+### 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`:
+
+```ts
+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:
+
+```ts
+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&lt;string,string&gt;_
+
+  Custom headers to include in the requests.
+
+- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise&lt;Response&gt;_
+
+  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 [SambaNova models](https://docs.sambanova.ai/cloud/docs/get-started/supported-models) on a provider instance.
+The first argument is the model id, e.g. `Meta-Llama-3.1-70B-Instruct`.
+
+```ts
+const model = sambanova('Meta-Llama-3.1-70B-Instruct');
+```
+
+## Tested models and capabilities
+
+This provider is capable of generating and streaming text, and interpreting image inputs.
+
+At least it has been tested with the following features (which use the `/chat/completion` endpoint):
+
+| Chat completion     | Image input         |
+| ------------------- | ------------------- |
+| <Check size={18} /> | <Check size={18} /> |
+
+### Image input
+
+You need to use any of the following models for visual understanding:
+
+- Llama3.2-11B-Vision-Instruct
+- Llama3.2-90B-Vision-Instruct
+
+SambaNova does not support URLs, but the ai-sdk is able to download the file and send it to the model.
+
+## Example Usage
+
+Basic demonstration of text generation using the SambaNova provider.
+
+```ts
+import { createSambaNova } from 'sambanova-ai-provider';
+import { generateText } from 'ai';
+
+const sambanova = createSambaNova({
+  apiKey: 'YOUR_API_KEY',
+});
+
+const model = sambanova('Meta-Llama-3.1-70B-Instruct');
+
+const { text } = await generateText({
+  model,
+  prompt: 'Hello, nice to meet you.',
+});
+
+console.log(text);
+```
+
+You will get an output text similar to this one:
+
+```
+Hello. Nice to meet you too. Is there something I can help you with or would you like to chat?
+```
+
+## Intercepting Fetch Requests
+
+This provider supports [Intercepting Fetch Requests](https://sdk.vercel.ai/examples/providers/intercepting-fetch-requests).
+
+### Example
+
+```ts
+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-3.1-70B-Instruct');
+
+const { text } = await generateText({
+  model,
+  prompt: 'Hello, nice to meet you.',
+});
+```
+
+And you will get an output like this:
+
+```bash
+URL https://api.sambanova.ai/v1/chat/completions
+Headers {
+  "Content-Type": "application/json",
+  "Authorization": "Bearer YOUR_API_KEY"
+}
+Body {
+  "model": "Meta-Llama-3.1-70B-Instruct",
+  "temperature": 0,
+  "messages": [
+    {
+      "role": "user",
+      "content": "Hello, nice to meet you."
+    }
+  ]
+}
+```