Gemini Stt
Documentsgemini-sttGemini Stt is an Agent Skill for documents published in the sundial-org/awesome-openclaw-skills repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.
Transcribe audio files using Google's Gemini API or Vertex AI
How to use this skill
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- Open your project in Codex.
- Copy and paste the prompt below.
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Inspect the Agent Skill at https://github.com/sundial-org/awesome-openclaw-skills/blob/HEAD/skills/gemini-stt/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/gemini-stt, but wait for my approval before writing files or running scripts.
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Gemini Speech-to-Text Skill
Transcribe audio files using Google's Gemini API or Vertex AI. Default model is gemini-2.0-flash-lite for fastest transcription.
Authentication (choose one)
Option 1: Vertex AI with Application Default Credentials (Recommended)
gcloud auth application-default login
gcloud config set project YOUR_PROJECT_ID
The script will automatically detect and use ADC when available.
Option 2: Direct Gemini API Key
Set GEMINI_API_KEY in environment (e.g., ~/.env or ~/.clawdbot/.env)
Requirements
- Python 3.10+ (no external dependencies)
- Either GEMINI_API_KEY or gcloud CLI with ADC configured
Supported Formats
.ogg/.opus(Telegram voice messages).mp3.wav.m4a
Usage
# Auto-detect auth (tries ADC first, then GEMINI_API_KEY)
python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg
# Force Vertex AI
python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex
# With a specific model
python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro
# Vertex AI with specific project and region
python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex --project my-project --region us-central1
# With Clawdbot media
python ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg
Options
| Option | Description |
|---|---|
<audio_file> | Path to the audio file (required) |
--model, -m | Gemini model to use (default: gemini-2.0-flash-lite) |
--vertex, -v | Force use of Vertex AI with ADC |
--project, -p | GCP project ID (for Vertex, defaults to gcloud config) |
--region, -r | GCP region (for Vertex, default: us-central1) |
Supported Models
Any Gemini model that supports audio input can be used. Recommended models:
| Model | Notes |
|---|---|
gemini-2.0-flash-lite | Default. Fastest transcription speed. |
gemini-2.0-flash | Fast and cost-effective. |
gemini-2.5-flash-lite | Lightweight 2.5 model. |
gemini-2.5-flash | Balanced speed and quality. |
gemini-2.5-pro | Higher quality, slower. |
gemini-3-flash-preview | Latest flash model. |
gemini-3-pro-preview | Latest pro model, best quality. |
See Gemini API Models for the latest list.
How It Works
- Reads the audio file and base64 encodes it
- Auto-detects authentication:
- If ADC is available (gcloud), uses Vertex AI endpoint
- Otherwise, uses GEMINI_API_KEY with direct Gemini API
- Sends to the selected Gemini model with transcription prompt
- Returns the transcribed text
Example Integration
For Clawdbot voice message handling:
# Transcribe incoming voice message
TRANSCRIPT=$(python ~/.claude/skills/gemini-stt/transcribe.py "$AUDIO_PATH")
echo "User said: $TRANSCRIPT"
Error Handling
The script exits with code 1 and prints to stderr on:
- No authentication available (neither ADC nor GEMINI_API_KEY)
- File not found
- API errors
- Missing GCP project (when using Vertex)
Notes
- Uses Gemini 2.0 Flash Lite by default for fastest transcription
- No external Python dependencies (uses stdlib only)
- Automatically detects MIME type from file extension
- Prefers Vertex AI with ADC when available (no API key management needed)