A high-performance speech-to-text skill that transcribes Telegram voice messages using the Groq Whisper API for lightning-fast AI processing.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install groq-voice-transcriber
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 groq-voice-transcriber 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 Groq Voice Transcriber?
The Groq Voice Transcriber is a specialized tool designed to bridge the gap between spoken communication and LLM processing. By leveraging the ultra-fast Groq Whisper API, this skill allows your AI agents to "hear" and understand voice messages within platforms like Telegram. It is an essential component of the Openclaw Skills ecosystem for users who prefer hands-free interaction with their personal AI assistants.
This skill does more than just convert audio to text; it facilitates a complete feedback loop where transcribed content is passed to a Large Language Model for context-aware responses. This ensures that voice-driven workflows are as seamless and intelligent as text-based ones, allowing for a natural conversation flow with your automated agents.
Groq Voice Transcriber Use Cases
- Transcribing Telegram voice messages on the fly for immediate readability.
- Integrating speech-to-text capabilities into automated AI agent workflows.
- Processing voice-based commands for Large Language Model interaction.
- Archiving spoken notes as structured text within your personal knowledge management system.
How Groq Voice Transcriber Works
- The skill intercepts incoming audio files or voice messages from the Telegram interface.
- Captured audio data is sent to the Groq Whisper API for near-instant transcription.
- The resulting text is then passed to a connected LLM to generate a relevant response.
- The final AI-generated message is returned to the user through the communication channel.
Groq Voice Transcriber Setup
- Install the necessary Python dependencies:
pip install -r requirements.txt
- Configure your environment variables by creating a
.envfile and adding your Groq API key:
GROQ_API_KEY=your_api_key_here
- Install the skill into your environment using the CLI tool:
clawhub install ./skills/groq-voice-transcriber
Groq Voice Transcriber Data Schema & Taxonomy
The skill manages audio data and text metadata through the following structure:
| Attribute | Source | Description |
|---|---|---|
| GROQ_API_KEY | .env | Authentication for the Whisper API. |
| Audio Input | Telegram | Incoming .ogg or .mp3 voice files. |
| Transcription | Groq API | The plaintext output of the speech-to-text process. |
| LLM Response | Agent | The final text generated based on the transcription. |
Groq Voice Transcriber Advanced Features
- Ultra-low latency transcription powered by Groq LPU hardware acceleration.
- Seamless Telegram integration for real-time voice-to-agent communication.
- Direct pipeline support for passing transcribed text to multiple Openclaw Skills.
- Support for various audio formats commonly used in mobile messaging apps.
SKILL.md
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