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9router-stt

The 9router-stt skill transcribes audio files to text using multiple speech-to-text providers including OpenAI Whisper, Groq, Gemini, Deepgram, AssemblyAI, NVIDIA, and HuggingFace through a unified 9Router API endpoint. Use this skill when users need to convert audio files (mp3, wav, m4a, webm, ogg, flac) into text transcriptions, optionally specifying language, output format (json, text, srt, vtt), or providing transcription hints via prompt parameters.

View source Repository: 9router

Install in Claude Code

Copy

git clone --depth 1 https://github.com/decolua/9router /tmp/9router-stt && cp -r /tmp/9router-stt/skills/9router-stt ~/.claude/skills/9router-stt

Then start a new Claude Code session; the skill loads automatically.

Definition

SKILL.md

# 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

```bash
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

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

JS (Node):

```js
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`):
```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 |