---

name: venice-transcribe description: Transcribe audio to text using Venice AI's Whisper-based speech recognition. Supports WAV, MP3, FLAC, M4A, AAC formats with optional timestamps. homepage: https://venice.ai metadata: { "openclaw": { "emoji": "🎤", "requires": { "bins": ["uv"], "env": ["VENICE_API_KEY"] }, "primaryEnv": "VENICE_API_KEY", "install": [ { "id": "uv-brew", "kind": "brew", "formula": "uv", "bins": ["uv"], "label": "Install uv (brew)", }, ], }, }

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Venice Transcribe

Transcribe audio files to text using Venice AI's speech recognition (Whisper-based). API Base URL: https://api.venice.ai/api/v1 Documentation: docs.venice.ai

Setup

• Get your API key from venice.ai → Settings → API Keys

• Set the environment variable:

``bash export VENICE_API_KEY="your_api_key_here" `

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Transcribe Audio

Convert audio files to text. `bash uv run {baseDir}/scripts/transcribe.py --file recording.mp3 ` Options:

• --file (required): Audio file path

• --output: Save transcription to file (default: prints to stdout)

• --model: ASR model (default: openai/whisper-large-v3)

• --format: Output format: json or text (default: json)

• --timestamps: Include word/segment timestamps

• --language: Language hint (ISO 639-1 code, e.g., en, es, fr)

Supported audio formats:

• WAV, WAVE

• MP3

• FLAC

• M4A, AAC

• MP4 (audio track)

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Examples

Basic transcription: `bash uv run {baseDir}/scripts/transcribe.py --file meeting.mp3 ` Get just the text (no JSON): `bash uv run {baseDir}/scripts/transcribe.py --file audio.wav --format text ` With timestamps: `bash uv run {baseDir}/scripts/transcribe.py --file podcast.mp3 --timestamps ` Spanish audio with language hint: `bash uv run {baseDir}/scripts/transcribe.py --file spanish.mp3 --language es ` Save to file: `bash uv run {baseDir}/scripts/transcribe.py --file interview.mp3 --output transcript.json `

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Output Format

JSON format (default): `json { "text": "Hello, this is a transcription test.", "duration": 3.5 } ` JSON with timestamps: `json { "text": "Hello world", "duration": 2.1, "timestamps": { "word": [ {"word": "Hello", "start": 0.0, "end": 0.5}, {"word": "world", "start": 0.6, "end": 1.0} ], "segment": [ {"text": "Hello world", "start": 0.0, "end": 1.0} ] } } ` Text format: ` Hello, this is a transcription test. `

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Runtime Note

This skill uses uv run which automatically installs Python dependencies (httpx) via PEP 723 inline script metadata. No manual Python package installation required - uv handles everything.

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API Reference

| Endpoint | Description | Method | |----------|-------------|--------| | /audio/transcriptions` | Transcribe audio to text | POST (multipart) | Full API docs: docs.venice.ai