skills/ veniceai/skills

venice-audio-transcription

Transcribe audio files to text via POST /audio/transcriptions. Covers supported models (Parakeet, Whisper, Wizper, Scribe, xAI STT), accepted containers (wav/flac/m4a/aac/mp4/mp3/ogg/webm), response formats (json/text only), per-model timestamps (word/segment/char), language hints, the 25 MB cap, an

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Venice Transcription (`/audio/transcriptions`)

POST /api/v1/audio/transcriptions takes an audio file and returns text. It's OpenAI-compatible with multipart/form-data — the OpenAI SDK's audio.transcriptions.create() works unchanged.

Method	Path	Auth	Notes
`POST`	`/api/v1/audio/transcriptions`	Bearer key or x402 (SIWX)	`multipart/form-data`, file field `file`, max 25 MB. Billed per second of audio.

Use when

You need STT (speech-to-text) for voice notes, meetings, podcasts, short audio.
You need word/segment timestamps for subtitles or chapters.
You want to pick between Venice-hosted Parakeet, Whisper-family models, ElevenLabs Scribe, or xAI STT.

For video, there is no transcription endpoint any more — POST /video/transcriptions is retired and returns 410. Extract the audio track and send it here, or ask a video-capable chat model via venice-chat.

Minimal request

curl https://api.venice.ai/api/v1/audio/transcriptions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -F "file=@./meeting.m4a" \
  -F "model=nvidia/parakeet-tdt-0.6b-v3" \
  -F "response_format=json" \
  -F "timestamps=false"

{ "text": "Alright everyone, let's kick off the meeting...", "duration": 184.2 }

With timestamps=true, the JSON also carries a timestamps object (see below).

Request (`multipart/form-data`)

Only the fields below are read; anything else in the form is ignored.

Field	Type	Default	Notes
`file`	binary	—	Required. Real file part (no base64). Accepted: `wav`/`wave`, `flac`, `m4a`, `aac`, `mp4`, `mp3`, `ogg`/`oga`, `webm`. Checked by extension/MIME and then by binary signature. Max 25 MB.
`model`	string	—	Send it. The OpenAPI schema lists `nvidia/parakeet-tdt-0.6b-v3` as default, but that default is never applied: omitting `model` returns `400 "model is required"`.
`response_format`	`json` / `text`	`json`	Only these two. `text` returns a `text/plain` body with just the transcript.
`timestamps`	bool (`true`/`false` as form string)	`false`	Adds `timestamps` to the JSON response.
`language`	string	—	ISO 639-1 hint (`en`, `ja`, …). Forwarded by Whisper, Wizper, Scribe and xAI STT; ignored by Parakeet (auto-detects).

Response

{
  "text": "…",
  "duration": 184.2,
  "timestamps": {
    "word":    [{ "word": "Alright", "start": 0.12, "end": 0.48 }],
    "segment": [{ "text": "Alright everyone…", "start": 0.12, "end": 4.9 }],
    "char":    [{ "char": "A", "start": 0.12, "end": 0.15 }]
  }
}

duration (seconds) and timestamps are optional. Which timestamp arrays appear depends on the model:

Model	Timestamp granularity
`openai/whisper-large-v3`	`segment` + `word`
`fal-ai/wizper`	`segment`
`elevenlabs/scribe-v2`	`word`
`stt-xai-v1`	`word`
`nvidia/parakeet-tdt-0.6b-v3`	may include `segment`, `word` and/or `char`

Models

All five are in the live GET /models?type=asr list. Price is model_spec.pricing.per_audio_second.usd.

Model ID	Privacy	Notes
`nvidia/parakeet-tdt-0.6b-v3`	private	Venice-hosted, fast. Ignores `language`.
`openai/whisper-large-v3`	private	Multilingual; `language` hint; segment + word timestamps.
`fal-ai/wizper`	private	Whisper v3 variant; `language` hint; segment timestamps.
`elevenlabs/scribe-v2`	anonymized	`language` hint; word timestamps.
`stt-xai-v1`	anonymized	`language` hint; word timestamps.

A key with modelPrivacy: PRIVATE_ONLY gets 403 on the anonymized ones (PRIVATE_TEXT keys are not restricted here). Failed transcriptions are not charged.

OpenAI SDK

import OpenAI from 'openai'
import fs from 'node:fs'

const client = new OpenAI({
  apiKey: process.env.VENICE_API_KEY,
  baseURL: 'https://api.venice.ai/api/v1',
})

const out = await client.audio.transcriptions.create({
  file: fs.createReadStream('meeting.m4a'),
  model: 'openai/whisper-large-v3',
  response_format: 'json',
  language: 'en',
  // @ts-expect-error — Venice-specific extra, passes through multipart
  timestamps: true,
})

console.log(out.text)

Long files

There's no server-side chunking, and uploads are capped at 25 MB. Split long recordings client-side (on silence, or fixed segments), transcribe each chunk, then concatenate with offset timestamps.

ffmpeg -i long.mp3 -f segment -segment_time 600 -c copy chunk_%03d.mp3

Errors

Code	Meaning
`400`	Missing `model`, bad params (e.g. `response_format` not `json`/`text`), no `file` part (including a JSON body instead of multipart → `"No audio file provided"`), unsupported extension/MIME, or unrecognized binary signature.
`401`	Authentication failed.
`402`	Insufficient balance. Bearer → `{"error":"Insufficient USD or Diem balance…"}`, or `"API key USD
`403`	A `PRIVATE_ONLY` key calling an `anonymized` model, or region restriction.
`404`	Unknown `model`.
`413`	File larger than 25 MB (`{"code":"PAYLOAD_TOO_LARGE","error":"File exceeds the maximum allowed size of 25 MB."}`).
`422`	Upstream provider couldn't process the audio (zero-length, silent, corrupt, unsupported format or language, provider-side refusal). No `suggested_prompt`.
`429`	Rate limited.
`500`	Inference failure.
`502`	Temporary upstream ASR failure — `{"error":"Audio transcription failed due to a temporary upstream error. Please retry."}` (no `code` field). Retry with backoff.
`503`	Model temporarily offline — retry with jitter.

See venice-errors for body shapes and retry strategy.

Gotchas

Always send model — the documented default never applies.
file must be a real multipart file part. JSON + base64 is not supported.
There is no verbose_json, srt or vtt. For subtitles, use response_format=json + timestamps=true and render the timings yourself. text drops timestamps entirely.
Check which granularity your model returns before building on timestamps.word vs timestamps.segment.
A file with a valid extension but a non-audio binary signature is rejected; re-encode to a standard profile (e.g. MP3 44.1 kHz or 16 kHz).
On 429, back off; throttle big batches rather than firing everything in parallel.

Files

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SKILL.md

Venice Transcription (/audio/transcriptions)

Use when

Minimal request

Request (multipart/form-data)

Response

Models

OpenAI SDK

Long files

Errors

Gotchas

Files

Agent reviews

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Related tooling skillsscan passed

Venice Transcription (`/audio/transcriptions`)

Request (`multipart/form-data`)