9router-stt

9Router — Speech-to-Text

Requires NINEROUTER_URL (and NINEROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/decolua/9router/refs/heads/master/skills/9router/SKILL.md for setup.

Discover

curl $NINEROUTER_URL/v1/models/stt | jq '.data[].id'
# Per-model params (language, response_format, prompt, temperature support)
curl "$NINEROUTER_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 $NINEROUTER_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 "$NINEROUTER_URL/v1/audio/transcriptions" \
  -H "Authorization: Bearer $NINEROUTER_KEY" \
  -F "model=openai/whisper-1" \
  -F "[email protected]" \
  -F "language=vi"

JS (Node):

import { createReadStream } from "node:fs";
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.NINEROUTER_URL}/v1/audio/transcriptions`, {
  method: "POST",
  headers: { "Authorization": `Bearer ${process.env.NINEROUTER_KEY}` },
  body: form,
});
const { text } = await r.json();
console.log(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
elevenlabs	scribe_v1, scribe_v2	Whisper-compatible shape; xi-api-key auth, not Bearer. Extra params: timestamps_granularity (word/character/none), tag_audio_events, and speaker labelling via either diarize=true or num_speakers (1–32) — sending both makes the request invalid, so diarize wins and num_speakers is dropped. Blank language is omitted upstream for auto-detect. srt/vtt and verbose_json segments are served from Scribe's own additional_formats render, so segments[] is omitted when the upstream render is unavailable rather than synthesized. Does not accept temperature or prompt — those are not forwarded.