ai.allucanget.biz/docs/8.1-openrouter.md

OpenRouter API Integration

Text Generation

Warning

TODO: Add more details on how the backend integrates with OpenRouter for text generation, including chat completions and single-prompt generation flows.

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 orchestrated by a background worker:

1. User submits a video request via POST /generate/video (or /generate/video/from-image)
2. Backend inserts a row into generated_videos with status: "queued" and returns immediately
3. Background worker (video_worker.py) picks up queued jobs every 15 seconds:
   • Calls POST /api/v1/videos with model, prompt, aspect_ratio, resolution, duration
   • Receives {"id": "job_id", "polling_url": "https://..."} and updates DB to status: "processing"
   • Polls GET polling_url every 15 seconds until status is "completed" or "failed"
   • Updates DB with final status, video_url, and any error message
4. Frontend polls GET /generate/video/{db_id}/status every 5 seconds to show live updates
5. Completed response includes video_url — the video is displayed in a <video> element

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 frame_images with first_frame in the request body).