Speech to Text

API Overview

To simplify the integration of different speech-to-text-transcription models (stt)、speech-to-text-translation models (stt), OneRouter provides a unified image API.

API Specification

speech-to-text-translation models (stt)

Translates audio into English.

curl https://audio.onerouter.pro/v1/audio/translations \
    -H "Content-Type: multipart/form-data" \
    -H "Authorization: <API_KEY>" \
    --form 'file=@/path/to/file/speech.m4a' \
    --form 'model="whisper-1"'

from openai import OpenAI
import base64
import os

client = OpenAI(
    api_key="<API_KEY>", # Replace with your Key "sk-***"
    base_url="https://audio.onerouter.pro/v1"
)

audio_file = open("/path/to/file/speech.m4a", "rb")

transcript = client.audio.translations.create(
  model="whisper-1",
  file=audio_file
)

print(transcript)

import os
import requests

API_URL = "https://audio.onerouter.pro/v1/audio/translations"
API_KEY = os.getenv("ONEROUTER_API_KEY")

if not API_KEY:
    raise RuntimeError("Please set the ONEROUTER_API_KEY")

file_path = os.path.join(os.path.dirname(__file__), "tts-output.mp3")

with open(file_path, "rb") as f:
    files = {"file": ("tts-output.mp3", f, "audio/mpeg")}
    data = {
        "model": "whisper-1",
        "prompt": "loudly",
        "response_format": "json",
        "temperature": 0.8,
    }
    headers = {"Authorization": API_KEY}

    response = requests.post(API_URL, headers=headers, files=files, data=data)
    response.raise_for_status()
    print(response.json())

<API_KEY> is your API Key generated in API page.
model is the model name, such as whisper-1, available model list can be access in Model page.
file is the audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

Example response

{
  "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}

speech-to-text-transcription models (stt)

Transcribes audio into the input language.

curl https://audio.onerouter.pro/v1/speech/transcriptions \
    -H "Content-Type: multipart/form-data" \
    -H "Authorization: <API_KEY>" \
    --form 'file=@/path/to/file/speech.m4a' \
    --form 'model="whisper-1"

from openai import OpenAI
import base64
import os

client = OpenAI(
    api_key="<API_KEY>", # Replace with your Key "sk-***"
    base_url="https://audio.onerouter.pro/v1"
)

audio_file = open("/path/to/file/speech.m4a", "rb")

transcription = client.audio.transcriptions.create(
  model="gpt-4o-transcribe",
  file=audio_file
)

print(transcription)

import os
import requests

API_URL = "https://audio.onerouter.pro/v1/audio/transcriptions"
API_KEY = os.getenv("ONEROUTER_API_KEY")

if not API_KEY:
    raise RuntimeError("Please set the ONEROUTER_API_KEY")

file_path = os.path.join(os.path.dirname(__file__), "tts-output.mp3")

with open(file_path, "rb") as f:
    files = {"file": ("tts-output.mp3", f, "audio/mpeg")}
    data = {
        "model": "gpt-4o-transcribe",
        "prompt": "loudly",
        "response_format": "json",
        "temperature": 0.8,
    }
    headers = {"Authorization": API_KEY}

    response = requests.post(API_URL, headers=headers, files=files, data=data)
    response.raise_for_status()
    print(response.json())

<API_KEY> is your API Key generated in API page.
model is the model name, such as whisper-1, available model list can be access in Model page.
file is the audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

Example response


{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.",
  "usage": {
    "type": "tokens",
    "input_tokens": 14,
    "input_token_details": {
      "text_tokens": 0,
      "audio_tokens": 14
    },
    "output_tokens": 45,
    "total_tokens": 59
  }
}

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Last updated 2 months ago