About 9router-stt
9router-stt is a skill for sending audio to 9Router’s transcription endpoint. It supports model discovery, optional transcription settings, and several output formats across providers.
Key features
- 01Discover available transcription models
- 02Transcribe audio through an API
- 03Set language and prompt hints
- 04Return JSON, text, or subtitles
Use cases
- 01Transcribe an audio recording
- 02Create SRT or VTT subtitles
Install
Copy the command and run it in a terminal.
npx skills add https:/After installing, type/9router-sttin Claude Code to confirm it loaded.
Details
From the project README9Router — 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. |