Short answer: Drop the "OpenAI → Transcribe Audio (Whisper)" action anywhere in your workflow, map the inputs from upstream nodes, and publish.
Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.
| Field | Type | Required | Description |
|---|---|---|---|
Audio File URL file_url | string | Required | Public URL of the audio file to transcribe (mp3, mp4, mpeg, mpga, m4a, wav, webm) |
Model model | options | Required | Model. Options: Whisper v1 |
Language language | options | Optional | Language of the audio (improves accuracy). Leave empty for auto-detect. |
Prompt prompt | string | Optional | Optional text to guide the model's style or continue a previous segment |
Response Format response_format | options | Optional | Response Format. Options: JSON, Plain Text, SRT (subtitles), VTT (subtitles), Verbose JSON (with timestamps) |
{"file_url": "https://example.com/audio.mp3","model": "{{trigger.model}}","language": "{{trigger.language}}","prompt": "e.g. Technical discussion about cloud computing","response_format": "{{trigger.response_format}}"}
{"text": "Hello, this is a sample transcription of the audio file."}
Use these fields in downstream nodes for routing, logging, or error handling.
Any of these apps can fire this action as part of a workflow.
Triggered by anything in the catalog. Free tier available. No credit card.