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9router-stt

Transcribe audio files through 9Router using models from providers such as OpenAI, Groq, and Deepgram. Receive plain text, structured results with timestamps, or SRT and VTT subtitles, depending on the selected model’s support.

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原文查看原文说明

Speech-to-text via 9Router /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.

查看安装方法

适用场景

  • Transcribing recorded meetings or interviews
  • Creating SRT or VTT subtitles from audio
  • Getting transcriptions with timestamps

包含的文件(1)

  • SKILL.md3.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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)

FieldRequiredNotes
modelyesfrom /v1/models/stt
fileyesaudio file (mp3, wav, m4a, webm, ogg, flac)
languagenoISO-639-1 (e.g. en, vi)
promptnohint text to guide transcription
response_formatnojson (default) / text / verbose_json / srt / vtt
temperatureno0–1

Examples

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):

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

Providermodel formatNotes
openaiwhisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribeNative OpenAI shape
groqwhisper-large-v3, whisper-large-v3-turbo, distil-whisper-large-v3-enFastest; OpenAI shape
geminigemini-2.5-flash, gemini-2.5-pro, gemini-2.5-flash-liteServer converts to generateContent with audio inline
deepgramnova-3, nova-2, whisper-largeToken auth; server adapts response
assemblyaiuniversal-3-pro, universal-2Async upload+poll handled server-side
nvidianvidia/parakeet-ctc-1.1b-asrNIM endpoint
huggingfaceopenai/whisper-large-v3, openai/whisper-smallHF Inference API
elevenlabsscribe_v1, scribe_v2Whisper-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.

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