Speech to text

POST /v1/audio/transcriptions turns a recording into text. It has the shape of OpenAI’s audio transcriptions, so an OpenAI SDK’s audio.transcriptions.create works by changing base_url alone.

It runs on a dedicated deployment

Speech-to-text models are offered as dedicated deployments: create a deployment of a model that transcribes, then send its full name as model:

accounts/<your-account>/deployments/<your-asr-deployment>

A bare model name, or a deployment of a model that does not transcribe, returns MODEL_CAPABILITY_UNSUPPORTED. The other way round is refused too: a speech-to-text deployment does not answer /v1/chat/completions.

Sending audio

curl https://compute.prentis.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $PRENTIS_API_KEY" \
  -F file=@recording.wav \
  -F model=accounts/<your-account>/deployments/<your-asr-deployment> \
  -F language=en

import os
from openai import OpenAI

client = OpenAI(base_url="https://compute.prentis.ai/v1", api_key=os.environ["PRENTIS_API_KEY"])

with open("recording.wav", "rb") as f:
    resp = client.audio.transcriptions.create(
        model="accounts/<your-account>/deployments/<your-asr-deployment>",
        file=f,
        language="en",
    )
print(resp.text)

Field
`file`	A WAV file: PCM, 16, 24 or 32-bit, any sample rate, mono or stereo. Up to 25 MB and 10 minutes.
`model`	The deployment’s full name, as above.
`language`	Optional. An ISO-639-1 code such as `en` or `zh`; leave it out and the model detects the language.
`prompt`	Optional. Names and terms the recording is likely to contain, which steers spelling. UTF-8 text, up to 64 KB.
`temperature`	Optional, 0 to 1. 0 is the usual choice for transcription.
`response_format`	`json` (the default) or `text`.
`stream`	Optional. `true` streams the text as it is recognised.

Other formats (mp3, ogg, webm) return MEDIA_UNSUPPORTED: convert them to WAV first. A recording of 16 kHz mono 16-bit PCM — what voice pipelines usually produce — is about 32 KB per second.

What comes back

With response_format: json:

{
  "text": "Can you move my three o'clock meeting to Thursday morning?",
  "usage": { "type": "duration", "seconds": 4 }
}

usage.seconds is the recording’s length read from the WAV header, rounded up to whole seconds. With response_format: text the body is the transcript alone, as text/plain. With stream: true the answer is text/event-stream: one transcript.text.delta event per new piece of text, then a single transcript.text.done carrying the whole text and the usage, which ends the stream. There is no [DONE] line — unlike chat streaming.

data: {"type":"transcript.text.delta","delta":"Can you move my"}

data: {"type":"transcript.text.delta","delta":" three o'clock meeting to Thursday morning?"}

data: {"type":"transcript.text.done","text":"Can you move my three o'clock meeting to Thursday morning?","usage":{"type":"duration","seconds":4}}

Using it from a voice agent

Pipecat’s OpenAI speech-to-text service takes a base URL and a model, which is all it needs:

import os
from pipecat.services.openai.stt import OpenAISTTService

stt = OpenAISTTService(
    api_key=os.environ["PRENTIS_API_KEY"],
    base_url="https://compute.prentis.ai/v1",
    model="accounts/<your-account>/deployments/<your-asr-deployment>",
)

The API key needs the audio operation if you restrict its operations; a key with no operation restrictions can already call this endpoint.

Cost

A dedicated deployment is billed for the GPU time it holds, whether or not you send anything. Transcription calls are not billed on top of that: each one appears on the Usage and Requests pages with its audio length, at no charge.

Get started

Guides

Platform

Reference

It runs on a dedicated deployment

Sending audio

What comes back

Using it from a voice agent

Cost

​It runs on a dedicated deployment

​Sending audio

​What comes back

​Using it from a voice agent

​Cost

It runs on a dedicated deployment

Sending audio

What comes back

Using it from a voice agent

Cost