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

# SambaNova

> Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including [SambaNova AI](https://sambanova.ai/).

With Portkey, you can take advantage of features like fast AI gateway access, observability, prompt management, and more, all while ensuring the secure management of your LLM API keys through a [virtual key](/product/ai-gateway/virtual-keys) system.

<Note>
  Provider Slug: `sambanova`
</Note>

## Portkey SDK Integration with SambaNova Models

### **1. Install the Portkey SDK**

Add the Portkey SDK to your application to interact with SambaNova's API through Portkey's gateway.

<Tabs>
  <Tab title="NodeJS">
    ```sh theme={"system"}
    npm install --save portkey-ai
    ```
  </Tab>

  <Tab title="Python">
    ```sh theme={"system"}
    pip install portkey-ai
    ```
  </Tab>
</Tabs>

### **2. Initialize Portkey with the Virtual Key**

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={"system"}
    import Portkey from 'portkey-ai'

    const portkey = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        virtualKey: "VIRTUAL_KEY" // Your SambaNova Virtual Key
    })
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={"system"}
    from portkey_ai import Portkey
    portkey = Portkey(
        api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
        virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for SambaNova AI
    )
    ```
  </Tab>
</Tabs>

### **3. Invoke Chat Completions**

Use the Portkey instance to send requests to the SambaNova API. You can also override the virtual key directly in the API call if needed.

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={"system"}
    const chatCompletion = await portkey.chat.completions.create({
        messages: [{ role: 'user', content: 'Say this is a test' }],
        model: 'Meta-Llama-3.1-405B-Instruct',
    });
    console.log(chatCompletion.choices);
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={"system"}
    completion = portkey.chat.completions.create(
        messages= [{ "role": 'user', "content": 'Say this is a test' }],
        model= 'Meta-Llama-3.1-405B-Instruct'
    )
    print(completion)
    ```
  </Tab>
</Tabs>

## Managing SambaNova Prompts

You can manage all prompts to SambaNova models in the [Prompt Library](/product/prompt-library). All the current models of SambaNova are supported and you can easily start testing different prompts.

Once you're ready with your prompt, you can use the `portkey.prompts.completions.create` interface to use the prompt in your application.

The complete list of supported models are available here:

<Card title="Supported Models" icon="list" href="https://community.sambanova.ai/t/supported-models/193">
  View the list of supported SambaNova models
</Card>

You'll find more information in the relevant sections:

1. [Add metadata to your requests](/product/observability/metadata)
2. [Add gateway configs to your SambaNova requests](/product/ai-gateway/configs)
3. [Tracing SambaNova requests](/product/observability/traces)
4. [Setup a fallback from OpenAI to SambaNova APIs](/product/ai-gateway/fallbacks)