axonrouter-stt

name	axonrouter-stt
description	Speech-to-text via AxonRouter /v1/audio/transcriptions using OpenAI Whisper / Groq / Gemini / Deepgram / AssemblyAI / NVIDIA / HuggingFace models. Use when the user wants to transcribe audio, convert speech to text, or get subtitles from audio files.

AxonRouter — Speech-to-Text

Requires AXONROUTER_URL (and AXONROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/rickicode/axonrouter/refs/heads/main/skills/axonrouter/SKILL.md for setup.

Discover

curl $AXONROUTER_URL/v1/models/stt | jq '.data[].id'
# Per-model params (language, response_format, prompt, temperature support)
curl "$AXONROUTER_URL/v1/models/info?id=openai/whisper-1"

model = STT model ID (e.g. openai/whisper-1, groq/whisper-large-v3, deepgram/nova-3, gemini/gemini-2.5-flash).

Endpoint

POST $AXONROUTER_URL/v1/audio/transcriptions (OpenAI Whisper compatible, multipart/form-data)

Field	Required	Notes
model	yes	from /v1/models/stt
file	yes	audio file (mp3, wav, m4a, webm, ogg, flac)
language	no	ISO-639-1 (e.g. en, vi)
prompt	no	hint text to guide transcription
response_format	no	json (default) / text / verbose_json / srt / vtt
temperature	no	0–1

Examples

curl -X POST "$AXONROUTER_URL/v1/audio/transcriptions" \
  -H "Authorization: Bearer $AXONROUTER_KEY" \
  -F "model=openai/whisper-1" \
  -F "file=@audio.mp3" \
  -F "language=vi"

JS (Node):

const form = new FormData();
form.append("model", "groq/whisper-large-v3-turbo");
form.append("file", new Blob([await (await import("node:fs/promises")).readFile("audio.mp3")]), "audio.mp3");
const r = await fetch(`${process.env.AXONROUTER_URL}/v1/audio/transcriptions`, {
  method: "POST",
  headers: { "Authorization": `Bearer ${process.env.AXONROUTER_KEY}` },
  body: form,
});
const { text } = await r.json();
console.log(text);

Python:

from openai import OpenAI
import os

client = OpenAI(base_url=f"{os.environ['AXONROUTER_URL']}/v1", api_key=os.environ["AXONROUTER_KEY"])
with open("audio.mp3", "rb") as f:
    transcript = client.audio.transcriptions.create(model="openai/whisper-1", file=f, language="en")
print(transcript.text)

Response shape

Default (response_format=json):

{ "text": "Xin chào, đây là bản ghi âm." }

verbose_json adds language, duration, segments[] with timestamps. srt / vtt return subtitle text.

Provider quirks

Provider	model format	Notes
openai	whisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribe	Native OpenAI shape
groq	whisper-large-v3, whisper-large-v3-turbo, distil-whisper-large-v3-en	Fastest; OpenAI shape
gemini	gemini-2.5-flash, gemini-2.5-pro, gemini-2.5-flash-lite	Server converts to generateContent with audio inline
deepgram	nova-3, nova-2, whisper-large	Token auth; server adapts response
assemblyai	universal-3-pro, universal-2	Async upload+poll handled server-side
nvidia	nvidia/parakeet-ctc-1.1b-asr	NIM endpoint
huggingface	openai/whisper-large-v3, openai/whisper-small	HF Inference API