Converts audio to text in the specified language.
Endpoint
POST https://api.sambanova.ai/v1/audio/transcriptions
For SambaStack, developers should check with their system administrator for the correct URL.
Request parameters
The following tables outline the parameters required to make a transcription request, parameter type, description, and default values.
For improved accuracy, we strongly recommend specifying the language parameter when using any audio model.
Whisper Large v3
| Parameter | Type | Description | Default |
|---|
model | String | The ID of the model to use. | Required |
file | File | Audio file in FLAC, MP3, MP4, MPEG, MPGA, M4A, Ogg, WAV, or WebM format. File size limit is 25MB. | Required |
prompt | String | Prompt provided to influence transcription style or vocabulary. Example: “Please transcribe carefully, including pauses and hesitations.” | Optional |
response_format | String | Output format: JSON or text. | json |
language | String | The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency. | Optional |
stream | Boolean | Enables streaming responses. | false |
stream_options | Object | Additional streaming configuration (e.g., {“include_usage”: true}). | Optional |
CURL
This section provides examples of how to send a request using different methods.
curl --location 'https://api.sambanova.ai/v1/audio/transcriptions' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--form 'model="Whisper-Large-v3"' \
--form 'language="spanish"' \
--form 'response_format="json"' \
--form 'file=@"/path/to/audio/file.mp3"' \
--form 'stream="true"'
Python
import requests
def transcribe_audio(audio_file_path, api_key, language="english"):
headers = {"Authorization": f"Bearer {api_key}"}
files = {"file": open(audio_file_path, "rb")}
data = {
"model": "Whisper-Large-v3",
"language": language,
"response_format": "json",
"stream": true, # Optional
}
response = requests.post(
"https://api.sambanova.ai/v1/audio/transcriptions",
headers=headers,
files=files,
data=data,
)
return response.json()
JSON
{
"text": "It's a sound effect of a bell chiming, specifically a church bell."
}
Text
It's a sound effect of a bell chiming, specifically a church bell.
