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media-creation

Creates images and video via Alibaba Wan 2.6 (DashScope), Google Gemini/Veo, and OpenAI GPT Image 1.5 APIs, plus background extraction workflows. Trigger terms: image generation, video generation, dashscope, wan 2.6, alibaba, gemini, veo, gpt image, openai images, background removal, alpha extraction, transparent png.

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Th0rgal/sandboxed-library-template
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SKILL.md
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name
media-creation
description
Creates images and video via Alibaba Wan 2.6 (DashScope), Google Gemini/Veo, and OpenAI GPT Image 1.5 APIs, plus background extraction workflows. Trigger terms: image generation, video generation, dashscope, wan 2.6, alibaba, gemini, veo, gpt image, openai images, background removal, alpha extraction, transparent png.
## Use when - Generate images or video via Alibaba Wan, Google Gemini/Veo, or OpenAI GPT Image APIs. - Create transparent PNGs (prefer GPT Image 1.5 for native transparency support). - Convert consistent renders (3D, compositing) with different backgrounds into a transparent RGBA output. - Prefer Gemini for general image generation; use Wan when content is restricted (e.g., babies). ## Don't use when - If API access or credentials are not available. - If the task does not involve media generation or background extraction. ## Outputs - Generated media files in `artifacts/` (PNG, WEBP, MP4, etc.) or API JSON responses when requested. ## Templates or Examples - Use the API request examples below as templates. ## Transparent Image Generation (Recommended Approach) ### Option 1: GPT Image 1.5 Native Transparency (BEST) GPT Image 1.5 supports native transparency output. This is the simplest and most reliable method: ```bash curl -X POST "https://api.openai.com/v1/images/generations" \ -H "Authorization: Bearer ${OPENAI_API_KEY}" \ -H "Content-Type: application/json" \ -d '{ "model": "gpt-image-1.5", "prompt": "A cute cartoon cat mascot", "size": "1024x1024", "quality": "high", "background": "transparent", "output_format": "png" }' ``` Notes: - `background: "transparent"` requires `output_format: "png"` or `"webp"` - Returns base64 data in `data[0].b64_json` - This is the only method that produces TRUE transparency from a single generation ### Option 2: Three-Background Extraction (For Consistent Renders Only) **⚠️ IMPORTANT LIMITATION**: This workflow ONLY works when you have control over the exact pixel output: - ✅ 3D renders (Blender, Maya, etc.) - ✅ Compositing software with controlled backgrounds - ✅ Screenshots with different desktop backgrounds - ❌ Generative AI (each generation produces different results) The algorithm requires IDENTICAL foreground pixels across all three images. Generative AI models produce different outputs even with the same prompt. For 3D/compositing use: ```bash python3 scripts/extract_transparency.py \ --black render_black.png \ --white render_white.png \ --colored render_red.png \ --output result.png ``` ### Option 3: AI Image + Manual Background Removal For AI-generated images that need transparency: 1. Generate the image with any provider 2. Use a dedicated background removal tool (rembg, remove.bg API, etc.) ## Inputs the Agent Should Ask For (only if missing; otherwise proceed) - Provider: Alibaba Wan (DashScope), Google (Gemini/Veo), or OpenAI (GPT Image). - Model ID and task type (T2I, I2V, T2V). - Prompt text and any input image path (for I2V). - Output size/resolution and aspect ratio. - Desired output format and count. - For transparency: whether native transparency (GPT Image) or background extraction is needed. - For background extraction: paths to black/white/red background images and the colored background RGB (0-1). ## API Keys The following environment variables should be set for API access: - `OPENAI_API_KEY` - For GPT Image 1.5 generations - `GOOGLE_GENAI_API_KEY` - For Gemini image/Veo video generation - `DASHSCOPE_API_KEY` - For Alibaba Wan 2.6 image/video generation ## Outputs / Definition of Done - A clear, credential-safe request plan or script snippet. - For generation: task submission, polling, and decode/download steps. - For background removal: algorithm steps and expected RGBA output. ## Procedure - Use `references/alibaba-wan-api.md` for Wan 2.6 endpoints and parameters (image, T2V, I2V). - Use `references/gemini-banana-api.md` for Gemini image and Veo video in the Gemini API. - Use `references/openai-gpt-image-api.md` for GPT Image 1.5 endpoints and parameters. - Use `references/background-removal-3-bg.md` for the three-background alpha extraction algorithm. - API keys in code examples are stored encrypted using `<encrypted>` tags. ## Model Quick Reference | Provider | Model | Use Case | |----------|-------|----------| | OpenAI | `gpt-image-1.5` | Best for transparent images, high quality | | OpenAI | `gpt-image-1` | Image edits/inpainting | | Google | `gemini-2.5-flash-image` | Fast image generation | | Google | `veo-3.1-generate-preview` | Video generation | | Alibaba | `wan2.6-t2v` | Text-to-video | | Alibaba | `wan2.6-i2v` | Image-to-video | | Alibaba | `wan2.6-image` | Image generation (fewer restrictions) | ## Checks & Guardrails - API keys must be wrapped in `<encrypted>` tags; they are encrypted at rest. - Validate image sizes/formats and rate limits. - Ensure base64 encoding formats match API expectations. - For transparency: verify the workflow matches the source type (render vs. AI). ## References - references/alibaba-wan-api.md - references/gemini-banana-api.md - references/openai-gpt-image-api.md - references/background-removal-3-bg.md ## Scripts - `scripts/extract_transparency.py` - Extract RGBA from black/white/red background images. Usage: `python3 scripts/extract_transparency.py --black img_black.png --white img_white.png --colored img_red.png --output result.png`
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