Required fields
model? provider/model pair (e.g.openai/whisper-1).audio? multipart file upload oraudio_base64string.- Optional:
filename,mime_typewhen using base64.
If you send both audio and audio_base64, the file upload wins.
The audio transcription API streams files to providers such as OpenAI Whisper, records token usage, and emits normalized responses that work inside n8n or your own apps.
Send audio through POST /audio/transcribe and receive structured text plus usage metadata.
https://luntrex.com/api/v1
model ? provider/model pair (e.g. openai/whisper-1).audio ? multipart file upload or audio_base64 string.filename, mime_type when using base64.If you send both audio and audio_base64, the file upload wins.
curl -X POST https://luntrex.com/api/v1/audio/transcribe \
-H "Authorization: Bearer <API_KEY>" \
-F "model=openai/whisper-1" \
-F "audio=@Recording.m4a"
Use this mode from n8n?s HTTP Request node (?Send Binary Data?).
POST /audio/transcribe
{
"model": "openai/whisper-1",
"audio_base64": "<base64 string>",
"filename": "meeting.m4a",
"mime_type": "audio/x-m4a"
}
Ideal when you already have base64 bytes coming from a form or browser.
{
"text": "Are you ready for help me?",
"status": "success",
"raw": {
"text": "Are you ready for help me?",
"usage": {
"type": "duration",
"seconds": 4
}
}
}
The raw block mirrors the provider response for troubleshooting.
usage row with input_tokens,
output_tokens, and total_cost_tokens.input_tokens from audio duration and output_tokens from transcript length.
price_input / price_output on the selected model.POST > URL
https://luntrex.com/api/v1/audio/transcribe.sdfsd).model=openai/whisper-1, optional filename,
mime_type with expressions
{{ $binary.sdfsd.fileName }}, {{ $binary.sdfsd.mimeType }}.Authorization: Bearer <API_KEY>.text; use it downstream in Slack, email, etc.401 api_key_missing ? invalid or missing bearer token.403 insufficient credits ? user balance is 0.415 ? unsupported MIME type (ensure audio matches allowed list).5xx ? provider error; check raw response.filename parameter to keep transcripts organized in logs.