ai-multimodal
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Best use case
ai-multimodal is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Teams using ai-multimodal should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ai-multimodal/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ai-multimodal Compares
| Feature / Agent | ai-multimodal | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# AI Multimodal Processing Skill Process audio, images, videos, documents, and generate images using Google Gemini's multimodal API. Unified interface for all multimedia content understanding and generation. ## Core Capabilities ### Audio Processing - Transcription with timestamps (up to 9.5 hours) - Audio summarization and analysis - Speech understanding and speaker identification - Music and environmental sound analysis - Text-to-speech generation with controllable voice ### Image Understanding - Image captioning and description - Object detection with bounding boxes (2.0+) - Pixel-level segmentation (2.5+) - Visual question answering - Multi-image comparison (up to 3,600 images) - OCR and text extraction ### Video Analysis - Scene detection and summarization - Video Q&A with temporal understanding - Transcription with visual descriptions - YouTube URL support - Long video processing (up to 6 hours) - Frame-level analysis ### Document Extraction - Native PDF vision processing (up to 1,000 pages) - Table and form extraction - Chart and diagram analysis - Multi-page document understanding - Structured data output (JSON schema) - Format conversion (PDF to HTML/JSON) ### Image Generation - Text-to-image generation - Image editing and modification - Multi-image composition (up to 3 images) - Iterative refinement - Multiple aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4) - Controllable style and quality ## Capability Matrix | Task | Audio | Image | Video | Document | Generation | |------|:-----:|:-----:|:-----:|:--------:|:----------:| | Transcription | ✓ | - | ✓ | - | - | | Summarization | ✓ | ✓ | ✓ | ✓ | - | | Q&A | ✓ | ✓ | ✓ | ✓ | - | | Object Detection | - | ✓ | ✓ | - | - | | Text Extraction | - | ✓ | - | ✓ | - | | Structured Output | ✓ | ✓ | ✓ | ✓ | - | | Creation | TTS | - | - | - | ✓ | | Timestamps | ✓ | - | ✓ | - | - | | Segmentation | - | ✓ | - | - | - | ## Model Selection Guide ### Gemini 2.5 Series (Recommended) - **gemini-2.5-pro**: Highest quality, all features, 1M-2M context - **gemini-2.5-flash**: Best balance, all features, 1M-2M context - **gemini-2.5-flash-lite**: Lightweight, segmentation support - **gemini-2.5-flash-image**: Image generation only ### Gemini 2.0 Series - **gemini-2.0-flash**: Fast processing, object detection - **gemini-2.0-flash-lite**: Lightweight option ### Feature Requirements - **Segmentation**: Requires 2.5+ models - **Object Detection**: Requires 2.0+ models - **Multi-video**: Requires 2.5+ models - **Image Generation**: Requires flash-image model ### Context Windows - **2M tokens**: ~6 hours video (low-res) or ~2 hours (default) - **1M tokens**: ~3 hours video (low-res) or ~1 hour (default) - **Audio**: 32 tokens/second (1 min = 1,920 tokens) - **PDF**: 258 tokens/page (fixed) - **Image**: 258-1,548 tokens based on size ## Quick Start ### Prerequisites **API Key Setup**: Supports both Google AI Studio and Vertex AI. The skill checks for `GEMINI_API_KEY` in this order: 1. Process environment: `export GEMINI_API_KEY="your-key"` 2. Project root: `.env` 3. `.claude/.env` 4. `.claude/skills/.env` 5. `.claude/skills/ai-multimodal/.env` **Get API key**: https://aistudio.google.com/apikey **For Vertex AI**: ```bash export GEMINI_USE_VERTEX=true export VERTEX_PROJECT_ID=your-gcp-project-id export VERTEX_LOCATION=us-central1 # Optional ``` **Install SDK**: ```bash pip install google-genai python-dotenv pillow ``` ### Common Patterns **Transcribe Audio**: ```bash python scripts/gemini_batch_process.py \ --files audio.mp3 \ --task transcribe \ --model gemini-2.5-flash ``` **Analyze Image**: ```bash python scripts/gemini_batch_process.py \ --files image.jpg \ --task analyze \ --prompt "Describe this image" \ --output docs/assets/<output-name>.md \ --model gemini-2.5-flash ``` **Process Video**: ```bash python scripts/gemini_batch_process.py \ --files video.mp4 \ --task analyze \ --prompt "Summarize key points with timestamps" \ --output docs/assets/<output-name>.md \ --model gemini-2.5-flash ``` **Extract from PDF**: ```bash python scripts/gemini_batch_process.py \ --files document.pdf \ --task extract \ --prompt "Extract table data as JSON" \ --output docs/assets/<output-name>.md \ --format json ``` **Generate Image**: ```bash python scripts/gemini_batch_process.py \ --task generate \ --prompt "A futuristic city at sunset" \ --output docs/assets/<output-file-name> \ --model gemini-2.5-flash-image \ --aspect-ratio 16:9 ``` **Optimize Media**: ```bash # Prepare large video for processing python scripts/media_optimizer.py \ --input large-video.mp4 \ --output docs/assets/<output-file-name> \ --target-size 100MB # Batch optimize multiple files python scripts/media_optimizer.py \ --input-dir ./videos \ --output-dir docs/assets/optimized \ --quality 85 ``` **Convert Documents to Markdown**: ```bash # Convert to PDF python scripts/document_converter.py \ --input document.docx \ --output docs/assets/document.md # Extract pages python scripts/document_converter.py \ --input large.pdf \ --output docs/assets/chapter1.md \ --pages 1-20 ``` ## Supported Formats ### Audio - WAV, MP3, AAC, FLAC, OGG Vorbis, AIFF - Max 9.5 hours per request - Auto-downsampled to 16 Kbps mono ### Images - PNG, JPEG, WEBP, HEIC, HEIF - Max 3,600 images per request - Resolution: ≤384px = 258 tokens, larger = tiled ### Video - MP4, MPEG, MOV, AVI, FLV, MPG, WebM, WMV, 3GPP - Max 6 hours (low-res) or 2 hours (default) - YouTube URLs supported (public only) ### Documents - PDF only for vision processing - Max 1,000 pages - TXT, HTML, Markdown supported (text-only) ### Size Limits - **Inline**: <20MB total request - **File API**: 2GB per file, 20GB project quota - **Retention**: 48 hours auto-delete ## Reference Navigation For detailed implementation guidance, see: ### Audio Processing - `references/audio-processing.md` - Transcription, analysis, TTS - Timestamp handling and segment analysis - Multi-speaker identification - Non-speech audio analysis - Text-to-speech generation ### Image Understanding - `references/vision-understanding.md` - Captioning, detection, OCR - Object detection and localization - Pixel-level segmentation - Visual question answering - Multi-image comparison ### Video Analysis - `references/video-analysis.md` - Scene detection, temporal understanding - YouTube URL processing - Timestamp-based queries - Video clipping and FPS control - Long video optimization ### Document Extraction - `references/document-extraction.md` - PDF processing, structured output - Table and form extraction - Chart and diagram analysis - JSON schema validation - Multi-page handling ### Image Generation - `references/image-generation.md` - Text-to-image, editing - Prompt engineering strategies - Image editing and composition - Aspect ratio selection - Safety settings ## Cost Optimization ### Token Costs **Input Pricing**: - Gemini 2.5 Flash: $1.00/1M input, $0.10/1M output - Gemini 2.5 Pro: $3.00/1M input, $12.00/1M output - Gemini 1.5 Flash: $0.70/1M input, $0.175/1M output **Token Rates**: - Audio: 32 tokens/second (1 min = 1,920 tokens) - Video: ~300 tokens/second (default) or ~100 (low-res) - PDF: 258 tokens/page (fixed) - Image: 258-1,548 tokens based on size **TTS Pricing**: - Flash TTS: $10/1M tokens - Pro TTS: $20/1M tokens ### Best Practices 1. Use `gemini-2.5-flash` for most tasks (best price/performance) 2. Use File API for files >20MB or repeated queries 3. Optimize media before upload (see `media_optimizer.py`) 4. Process specific segments instead of full videos 5. Use lower FPS for static content 6. Implement context caching for repeated queries 7. Batch process multiple files in parallel ## Rate Limits **Free Tier**: - 10-15 RPM (requests per minute) - 1M-4M TPM (tokens per minute) - 1,500 RPD (requests per day) **YouTube Limits**: - Free tier: 8 hours/day - Paid tier: No length limits - Public videos only **Storage Limits**: - 20GB per project - 2GB per file - 48-hour retention ## Error Handling Common errors and solutions: - **400**: Invalid format/size - validate before upload - **401**: Invalid API key - check configuration - **403**: Permission denied - verify API key restrictions - **404**: File not found - ensure file uploaded and active - **429**: Rate limit exceeded - implement exponential backoff - **500**: Server error - retry with backoff ## Scripts Overview All scripts support unified API key detection and error handling: **gemini_batch_process.py**: Batch process multiple media files - Supports all modalities (audio, image, video, PDF) - Progress tracking and error recovery - Output formats: JSON, Markdown, CSV - Rate limiting and retry logic - Dry-run mode **media_optimizer.py**: Prepare media for Gemini API - Compress videos/audio for size limits - Resize images appropriately - Split long videos into chunks - Format conversion - Quality vs size optimization **document_converter.py**: Convert documents to PDF - Convert DOCX, XLSX, PPTX to PDF - Extract page ranges - Optimize PDFs for Gemini - Extract images from PDFs - Batch conversion support Run any script with `--help` for detailed usage. ## Resources - [Audio API Docs](https://ai.google.dev/gemini-api/docs/audio) - [Image API Docs](https://ai.google.dev/gemini-api/docs/image-understanding) - [Video API Docs](https://ai.google.dev/gemini-api/docs/video-understanding) - [Document API Docs](https://ai.google.dev/gemini-api/docs/document-processing) - [Image Gen Docs](https://ai.google.dev/gemini-api/docs/image-generation) - [Get API Key](https://aistudio.google.com/apikey) - [Pricing](https://ai.google.dev/pricing)
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