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Now supports both GEMINI_API_KEY and gcloud ADC authentication methods. Auto-detects authentication method.\n\nv1.0.0 | 2026-01-13T18:18:30.222Z | user\n\nInitial release of Gemini-based Speech-to-Text skill. Optimized for speed with gemini-2.0-flash-lite default.\n\nArchive index:\n\nArchive v1.1.0: 3 files, 4469 bytes\n\nFiles: SKILL.md (3571b), transcribe.py (8588b), _meta.json (129b)\n\nFile v1.1.0:SKILL.md\n\n---\nname: gemini-stt\ndescription: Transcribe audio files using Google's Gemini API or Vertex AI\nmetadata: {\"clawdbot\":{\"emoji\":\"🎤\",\"os\":[\"linux\",\"darwin\"]}}\n---\n\n# Gemini Speech-to-Text Skill\n\nTranscribe audio files using Google's Gemini API or Vertex AI. Default model is `gemini-2.0-flash-lite` for fastest transcription.\n\n## Authentication (choose one)\n\n### Option 1: Vertex AI with Application Default Credentials (Recommended)\n\n```bash\ngcloud auth application-default login\ngcloud config set project YOUR_PROJECT_ID\n```\n\nThe script will automatically detect and use ADC when available.\n\n### Option 2: Direct Gemini API Key\n\nSet `GEMINI_API_KEY` in environment (e.g., `~/.env` or `~/.clawdbot/.env`)\n\n## Requirements\n\n- Python 3.10+ (no external dependencies)\n- Either GEMINI_API_KEY or gcloud CLI with ADC configured\n\n## Supported Formats\n\n- `.ogg` / `.opus` (Telegram voice messages)\n- `.mp3`\n- `.wav`\n- `.m4a`\n\n## Usage\n\n```bash\n# Auto-detect auth (tries ADC first, then GEMINI_API_KEY)\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg\n\n# Force Vertex AI\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex\n\n# With a specific model\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro\n\n# Vertex AI with specific project and region\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex --project my-project --region us-central1\n\n# With Clawdbot media\npython ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg\n```\n\n## Options\n\n| Option | Description |\n|--------|-------------|\n| `<audio_file>` | Path to the audio file (required) |\n| `--model`, `-m` | Gemini model to use (default: `gemini-2.0-flash-lite`) |\n| `--vertex`, `-v` | Force use of Vertex AI with ADC |\n| `--project`, `-p` | GCP project ID (for Vertex, defaults to gcloud config) |\n| `--region`, `-r` | GCP region (for Vertex, default: `us-central1`) |\n\n## Supported Models\n\nAny Gemini model that supports audio input can be used. Recommended models:\n\n| Model | Notes |\n|-------|-------|\n| `gemini-2.0-flash-lite` | **Default.** Fastest transcription speed. |\n| `gemini-2.0-flash` | Fast and cost-effective. |\n| `gemini-2.5-flash-lite` | Lightweight 2.5 model. |\n| `gemini-2.5-flash` | Balanced speed and quality. |\n| `gemini-2.5-pro` | Higher quality, slower. |\n| `gemini-3-flash-preview` | Latest flash model. |\n| `gemini-3-pro-preview` | Latest pro model, best quality. |\n\nSee [Gemini API Models](https://ai.google.dev/gemini-api/docs/models) for the latest list.\n\n## How It Works\n\n1. Reads the audio file and base64 encodes it\n2. Auto-detects authentication:\n   - If ADC is available (gcloud), uses Vertex AI endpoint\n   - Otherwise, uses GEMINI_API_KEY with direct Gemini API\n3. Sends to the selected Gemini model with transcription prompt\n4. Returns the transcribed text\n\n## Example Integration\n\nFor Clawdbot voice message handling:\n\n```bash\n# Transcribe incoming voice message\nTRANSCRIPT=$(python ~/.claude/skills/gemini-stt/transcribe.py \"$AUDIO_PATH\")\necho \"User said: $TRANSCRIPT\"\n```\n\n## Error Handling\n\nThe script exits with code 1 and prints to stderr on:\n- No authentication available (neither ADC nor GEMINI_API_KEY)\n- File not found\n- API errors\n- Missing GCP project (when using Vertex)\n\n## Notes\n\n- Uses Gemini 2.0 Flash Lite by default for fastest transcription\n- No external Python dependencies (uses stdlib only)\n- Automatically detects MIME type from file extension\n- Prefers Vertex AI with ADC when available (no API key management needed)\n\nFile v1.1.0:_meta.json\n\n{\n  \"ownerId\": \"kn74rm3nhtpv387m12frad6bws7z5kqr\",\n  \"slug\": \"gemini-stt\",\n  \"version\": \"1.1.0\",\n  \"publishedAt\": 1768651581889\n}\n\nArchive v1.0.0: 3 files, 2987 bytes\n\nFiles: SKILL.md (2557b), transcribe.py (3531b), _meta.json (129b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: gemini-stt\ndescription: Transcribe audio files using Google's Gemini API\nmetadata: {\"clawdbot\":{\"emoji\":\"🎤\",\"os\":[\"linux\",\"darwin\"],\"requires\":{\"env\":[\"GEMINI_API_KEY\"]}}}\n---\n\n# Gemini Speech-to-Text Skill\n\nTranscribe audio files using Google's Gemini API. Default model is `gemini-2.0-flash-lite` for fastest transcription.\n\n## Requirements\n\n- **GEMINI_API_KEY**: Set in environment (e.g., `~/.env` or `~/.clawdbot/.env`)\n- Python 3.x (no external dependencies)\n\n## Supported Formats\n\n- `.ogg` / `.opus` (Telegram voice messages)\n- `.mp3`\n- `.wav`\n- `.m4a`\n\n## Usage\n\n```bash\n# Basic usage (uses default model: gemini-2.0-flash-lite)\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg\n\n# With a specific model\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro\n\n# Short form\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg -m gemini-2.5-flash\n\n# With Clawdbot media\npython ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg\n```\n\n## Options\n\n| Option | Description |\n|--------|-------------|\n| `<audio_file>` | Path to the audio file (required) |\n| `--model`, `-m` | Gemini model to use (default: `gemini-2.0-flash-lite`) |\n\n## Supported Models\n\nAny Gemini model that supports audio input can be used. Recommended models:\n\n| Model | Notes |\n|-------|-------|\n| `gemini-2.0-flash-lite` | **Default.** Fastest transcription speed. |\n| `gemini-2.0-flash` | Fast and cost-effective. |\n| `gemini-2.5-flash-lite` | Lightweight 2.5 model. |\n| `gemini-2.5-flash` | Balanced speed and quality. |\n| `gemini-2.5-pro` | Higher quality, slower. |\n| `gemini-3-flash-preview` | Latest flash model. |\n| `gemini-3-pro-preview` | Latest pro model, best quality. |\n\nSee [Gemini API Models](https://ai.google.dev/gemini-api/docs/models) for the latest list.\n\n## How It Works\n\n1. Reads the audio file and base64 encodes it\n2. Sends to the selected Gemini model with transcription prompt\n3. 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Auto-detects authentication method. v1.0.0 | 2026-01-13T18:18:30.222Z | user Initial release of Gemini-","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"gcloud auth application-default login\ngcloud config set project YOUR_PROJECT_ID"},{"language":"bash","snippet":"# Auto-detect auth (tries ADC first, then GEMINI_API_KEY)\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg\n\n# Force Vertex AI\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex\n\n# With a specific model\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro\n\n# Vertex AI with specific project and region\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex --project my-project --region us-central1\n\n# With Clawdbot media\npython ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg"},{"language":"bash","snippet":"# Transcribe incoming voice message\nTRANSCRIPT=$(python ~/.claude/skills/gemini-stt/transcribe.py \"$AUDIO_PATH\")\necho \"User said: $TRANSCRIPT\""},{"language":"bash","snippet":"# Basic usage (uses default model: gemini-2.0-flash-lite)\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg\n\n# With a specific model\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro\n\n# Short form\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg -m gemini-2.5-flash\n\n# With Clawdbot media\npython ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg"},{"language":"bash","snippet":"# Transcribe incoming voice message\nTRANSCRIPT=$(python ~/.claude/skills/gemini-stt/transcribe.py \"$AUDIO_PATH\")\necho \"User said: $TRANSCRIPT\""}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: gemini-stt\ndescription: Transcribe audio files using Google's Gemini API or Vertex AI\nmetadata: {\"clawdbot\":{\"emoji\":\"🎤\",\"os\":[\"linux\",\"darwin\"]}}\n---\n\n# Gemini Speech-to-Text Skill\n\nTranscribe audio files using Google's Gemini API or Vertex AI. Default model is `gemini-2.0-flash-lite` for fastest transcription.\n\n## Authentication (choose one)\n\n### Option 1: Vertex AI with Application Default Credentials (Recommended)\n\n```bash\ngcloud auth application-default login\ngcloud config set project YOUR_PROJECT_ID\n```\n\nThe script will automatically detect and use ADC when available.\n\n### Option 2: Direct Gemini API Key\n\nSet `GEMINI_API_KEY` in environment (e.g., `~/.env` or `~/.clawdbot/.env`)\n\n## Requirements\n\n- Python 3.10+ (no external dependencies)\n- Either GEMINI_API_KEY or gcloud CLI with ADC configured\n\n## Supported Formats\n\n- `.ogg` / `.opus` (Telegram voice messages)\n- `.mp3`\n- `.wav`\n- `.m4a`\n\n## Usage\n\n```bash\n# Auto-detect auth (tries ADC first, then GEMINI_API_KEY)\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg\n\n# Force Vertex AI\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex\n\n# With a specific model\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro\n\n# Vertex AI with specific project and region\npython ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex --project my-project --region us-central1\n\n# With Clawdbot media\npython ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg\n```\n\n## Options\n\n| Option | Description |\n|--------|-------------|\n| `<audio_file>` | Path to the audio file (required) |\n| `--model`, `-m` | Gemini model to use (default: `gemini-2.0-flash-lite`) |\n| `--vertex`, `-v` | Force use of Vertex AI with ADC |\n| `--project`, `-p` | GCP project ID (for Vertex, defaults to gcloud config) |\n| `--region`, `-r` | GCP region (for Vertex, default: `us-central1`) |\n\n## Supported Models\n\nAny Gemini model that supports audio input can be used. Recommended models:\n\n| Model | Notes |\n|-------|-------|\n| `gemini-2.0-flash-lite` | **Default.** Fastest transcription speed. |\n| `gemini-2.0-flash` | Fast and cost-effective. |\n| `gemini-2.5-flash-lite` | Lightweight 2.5 model. |\n| `gemini-2.5-flash` | Balanced speed and quality. |\n| `gemini-2.5-pro` | Higher quality, slower. |\n| `gemini-3-flash-preview` | Latest flash model. |\n| `gemini-3-pro-preview` | Latest pro model, best quality. |\n\nSee [Gemini API Models](https://ai.google.dev/gemini-api/docs/models) for the latest list.\n\n## How It Works\n\n1. Reads the audio file and base64 encodes it\n2. Auto-detects authentication:\n   - If ADC is available (gcloud), uses Vertex AI endpoint\n   - Otherwise, uses GEMINI_API_KEY with direct Gemini API\n3. Sends to the selected Gemini model with transcription prompt\n4. Returns the transcribed text\n\n## Example Integration\n\nFor Clawdbot voice message handling:\n\n```bash\n# Transcribe incoming voice message\nTRANSCRIP"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn74rm3nhtpv387m12frad6bws7z5kqr\",\n  \"slug\": \"gemini-stt\",\n  \"version\": \"1.1.0\",\n  \"publishedAt\": 1768651581889\n}"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Transcribe audio files using Google's Gemini API or Vertex AI Skill: Gemini STT Summary: Transcribe audio files using Google's Gemini API or Vertex AI Tags: latest:1.1.0 Version history: v1.1.0 | 2026-01-17T12:06:21.889Z | user Added support for Google Vertex AI with Application Default Credentials (ADC). Now supports both GEMINI_API_KEY and gcloud ADC authentication methods. 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