--- name: gemini-stt description: Transcribe audio files using Google's Gemini API or Vertex AI metadata: {"clawdbot":{"emoji":"🎤","os":["linux","darwin"]}} ---

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 | |--------|-------------| | | 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

1. Reads the audio file and base64 encodes it
2. Auto-detects authentication:

- If ADC is available (gcloud), uses Vertex AI endpoint - Otherwise, uses GEMINI_API_KEY with direct Gemini API

1. Sends to the selected Gemini model with transcription prompt
2. 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)