media-creation

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:

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:

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:

• OPENAIAPIKEY - For GPT Image 1.5 generations
• GOOGLEGENAIAPI_KEY - For Gemini image/Veo video generation
• DASHSCOPEAPIKEY - 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

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/extracttransparency.py --black imgblack.png --white imgwhite.png --colored imgred.png --output result.png