A powerful CLI tool for transcribing audio files to text using Venice AI high-accuracy Whisper models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install venice-transcribe
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install venice-transcribe using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Venice Transcribe?
Venice Transcribe is a specialized technical implementation for speech recognition, allowing users to convert diverse audio formats into structured JSON or plain text. As part of the Openclaw Skills collection, it provides a privacy-conscious way to handle media processing by leveraging Venice AI. The skill utilizes the OpenAI Whisper-large-v3 model to ensure high fidelity for technical, medical, or casual conversations, making it an ideal choice for developers who need robust transcription capabilities without the overhead of local model management.
Venice Transcribe Use Cases
- Automating meeting minutes by transcribing recorded calls for documentation.
- Generating closed captions for video content using detailed segment timestamps.
- Creating searchable databases of voice recordings, interviews, and lectures.
- Enhancing automated AI workflows that require speech-to-text conversion within Openclaw Skills pipelines.
How Venice Transcribe Works
- The command-line interface accepts an audio file in formats like MP3, WAV, or FLAC.
- The system validates the existence of the required VENICE_API_KEY and the presence of the uv package manager.
- The audio data is transmitted securely to the Venice AI API for inference using Whisper-based models.
- Optional parameters like language hints and timestamp flags are applied to refine the transcription output.
- The transcribed text and associated metadata are returned and either printed to the terminal or saved to a designated output file.
Venice Transcribe Setup
First, secure an API key from the Venice AI settings dashboard. Next, configure your local environment variable:
export VENICE_API_KEY="your_api_key_here"
Ensure you have the uv tool installed, as it is the optimized runner for Openclaw Skills to handle dependencies automatically:
brew install uv
Run the transcription command directly against your audio file:
uv run scripts/transcribe.py --file your_audio.mp3
Venice Transcribe Data Schema & Taxonomy
The output defaults to a structured JSON object but can be toggled to plain text. The data is organized as follows:
| Property | Type | Description |
|---|---|---|
text |
string | The full transcription of the audio file content. |
duration |
float | Total duration of the processed audio in seconds. |
timestamps |
object | (Optional) Contains arrays for word-level and segment-level start/end times. |
When timestamps are enabled, the JSON includes a nested array of objects identifying the exact start and end for every word recognized in the stream, which is critical for syncing with other Openclaw Skills.
Venice Transcribe Advanced Features
- Multi-format support including MP4 audio tracks and FLAC for high-fidelity lossless processing.
- Word-level timestamp extraction for precise media indexing and video editing workflows.
- ISO 639-1 language hints to improve transcription accuracy for non-English audio files.
- Seamless integration with other Openclaw Skills via standardized CLI output flags and JSON pipes.
SKILL.md
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