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

# Implement audio‑input features

For developers requiring audio support, SambaNova provides OpenAI’s Whisper large-v3 model, which enables real-time transcriptions and translations.

<Warning>
  This feature is available for SambaStack users only. Whisper-Large-v3 is not available on SambaCloud.
</Warning>

## Whisper-Large-v3

* **Model**: Whisper-Large-v3
* **Description**: State-of-the-art automatic speech recognition (ASR) and translation model. Developed by OpenAI and trained on 5M+ hours of labeled audio. Excels in multilingual and zero-shot speech tasks across diverse domains.
* **Model ID**: `Whisper-Large-v3`
* **Supported languages**: Multilingual

### Core capabilities

* Transcribes and translates extended audio inputs (up to 25 MB).
* Demonstrates high accuracy in speech recognition and translation tasks.
* Provides OpenAI-compatible endpoints for transcriptions and translations.

### Request parameters

| Parameter | Type | Description | Default | Endpoints |
| :- | :- | :- | :- | :- |
| `model` | String | The ID of the model to use. | Required | `transcriptions`, `translations` |
| `file` | File | Audio file in FLAC, MP3, MP4, MPEG, MPGA, M4A, Ogg, WAV, or WebM format. File size limit: 25MB. | Required | `transcriptions`, `translations` |
| `prompt` | String | Prompt to influence transcription style or vocabulary. Example: "Please transcribe carefully, including pauses and hesitations." | Optional | `transcriptions`, `translations` |
| `response_format` | String | Output format. `json` and `text` are the only supported values. | `json` | `transcriptions`, `translations` |
| `language` | String | The language of the input audio. Using ISO-639-1 format (e.g., `en`) improves accuracy and latency. | Optional | `transcriptions`, `translations` |
| `stream` | Boolean | Enables streaming responses. | `false` | `transcriptions`, `translations` |
| `stream_options` | Object | Additional streaming configuration (e.g., `{"include_usage": true}`). | Optional | `transcriptions`, `translations` |

<Note>
  Whisper-Large-v3 supports the `response_format` values `json` and `text` only.

  * `verbose_json`, `srt`, and `vtt` are not currently supported - requesting them returns plain text.
  * `timestamp_granularities` is not supported and returns `{"error":{"message":"Unknown parameter: 'timestamp_granularities'."}}`.
</Note>

### Example usage

<CodeGroup>
  ```python Python (SambaNova) theme={}
  from sambanova import SambaNova
  import base64

  client = SambaNova(
      base_url="your-sambanova-base-url",
      api_key="your-sambanova-api-key",
  )

  audio_path="audio_path"
  with open(audio_path, "rb") as audio_file:
     bin_audio = audio_file.read()

  response = client.audio.transcriptions.create(
      model="Whisper-Large-v3",
      file=(audio_path,bin_audio),
  )
  print(str(response))
  ```

  ```python Python (OpenAI) theme={}
  from openai import OpenAI
  import base64

  client = OpenAI(
      base_url="your-sambanova-base-url",
      api_key="your-sambanova-api-key",
  )

  audio_path="audio_path"
  with open(audio_path, "rb") as audio_file:
     bin_audio = audio_file.read()

  response = client.audio.transcriptions.create(
      model="Whisper-Large-v3",
      file=(audio_path,bin_audio),
  )
  print(str(response))
  ```

  ```javascript Javascript (SambaNova) theme={}
  import SambaNova from "sambanova";

  const client = new SambaNova({
    baseURL: 'your-sambanova-base-url',
    apiKey: 'your-sambanova-api-key'
  });

  async function run() {
    const audioPath = 'audio_path';
    const binAudio = fs.createReadStream(audioPath);

    const response = await client.audio.transcriptions.create({
      model: 'Whisper-Large-v3',
      file: binAudio,
    });

    console.log('Full Response:');
    console.dir(response, { depth: null });
  }

  run().catch(console.error);
  ```
</CodeGroup>

## Translations

The translations endpoint transcribes audio in any supported language and returns the output in English. Use the `language` parameter to specify the language of the input audio in ISO 639-1 format (for example, `"es"` for Spanish) to improve accuracy and reduce latency.

### Example usage

<CodeGroup>
  ```python Python (SambaNova) theme={}
  from sambanova import SambaNova

  client = SambaNova(
      base_url="your-sambanova-base-url",
      api_key="your-sambanova-api-key",
  )

  audio_path = "audio_path"
  with open(audio_path, "rb") as audio_file:
      bin_audio = audio_file.read()

  response = client.audio.translations.create(
      model="Whisper-Large-v3",
      file=(audio_path, bin_audio),
      language="es",
  )
  print(str(response))
  ```

  ```python Python (OpenAI) theme={}
  from openai import OpenAI

  client = OpenAI(
      base_url="your-sambanova-base-url",
      api_key="your-sambanova-api-key",
  )

  audio_path = "audio_path"
  with open(audio_path, "rb") as audio_file:
      bin_audio = audio_file.read()

  response = client.audio.translations.create(
      model="Whisper-Large-v3",
      file=(audio_path, bin_audio),
      language="es",
  )
  print(str(response))
  ```

  ```javascript Javascript (SambaNova) theme={}
  import SambaNova from "sambanova";

  const client = new SambaNova({
    baseURL: 'your-sambanova-base-url',
    apiKey: 'your-sambanova-api-key'
  });

  async function run() {
    const audioPath = 'audio_path';
    const binAudio = fs.createReadStream(audioPath);

    const response = await client.audio.translations.create({
      model: 'Whisper-Large-v3',
      file: binAudio,
      language: 'es',
    });

    console.log('Full Response:');
    console.dir(response, { depth: null });
  }

  run().catch(console.error);
  ```
</CodeGroup>

### Example response

```json theme={}
{
  "text": "It is the sound effect of a bell ringing, specifically a church bell."
}
```