Enhance documentation for AI generation: update image and video generation scenarios, integrate OpenRouter API details, and clarify submit-and-poll patterns for video generation.

Co-authored-by: Copilot <copilot@github.com>
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2026-04-27 19:33:43 +02:00
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### Future: AI Generation History
AI generation metadata (model, prompt, cost, result URLs) can be stored as JSON columns in a future `generation_history` table in DuckDB, enabling per-user analytics and usage dashboards at zero extra infrastructure cost.
## OpenRouter API Integration
### Image Generation
Image generation uses two different OpenRouter endpoints depending on the model:
- **Legacy endpoint** (`/images/generations`): Used by DALL-E 3 and similar models. Returns `data[].url` and `data[].b64_json`.
- **Chat completions** (`/chat/completions` with `modalities: ["image"]`): Used by FLUX.2 Klein 4B and GPT-5 Image Mini. Returns `choices[0].message.images[].image_url.url` as base64 data URLs.
The router auto-detects the model type and routes accordingly. Image configuration (`aspect_ratio`, `image_size`) is passed via `image_config` for chat-based models.
### Video Generation
Video generation uses OpenRouter's `/api/v1/videos` endpoint with a **submit-and-poll** pattern:
1. `POST /api/v1/videos` with `model`, `prompt`, `aspect_ratio`, `resolution`, `duration_seconds`
2. Response: `{"id": "job_id", "polling_url": "https://..."}` with `status: "queued"`
3. Poll `GET polling_url` every 5 seconds until `status` is `"completed"` or `"failed"`
4. Completed response includes `unsigned_urls: [str]` array with video download URLs
Supported models: `openai/sora-2-pro`, `google/veo-3.1-fast`. Both text-to-video and image-to-video use the same `/api/v1/videos` endpoint (image-to-video includes `image_url` in the request body).