Skills gemini-stt

Name: gemini-stt
Author: clawdbot

Transcribe audio files using Google's Gemini API or Vertex AI

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/araa47/gemini-stt" ~/.claude/skills/clawdbot-skills-gemini-stt && rm -rf "$T"

manifest: skills/araa47/gemini-stt/SKILL.md

source content

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

~/.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)