Text to image
Describe the subject, scene, composition, lighting, and style to create a new image.
AI image generation workflow
Organize text-to-image and reference-image creation as a reusable local-first workflow. Keep subjects, scenes, styles, prompts, and generated results with your project while choosing the model for each task.
Describe the subject, scene, composition, lighting, and style to create a new image.
Use one source image to guide a new result when the selected model supports it.
Combine several reference images for visual direction or style with models verified for that input.
Every model below has passed Orqra capability verification. The labels show the specific text or reference-image inputs verified for each model.
Add the subject, scene, style, and any reference images the task needs.
Keep reusable creative content separate from the instruction for this image.
Select a model that matches the input mode, review its settings, then save and reuse the result.
Prompt Fabric keeps reusable creative content separate from task instructions. Save recurring descriptions and directions as templates, insert them when needed, and adjust each copy for the shot. It organises the request; it does not guarantee model output quality.
Learn Prompt FabricConnect OpenRouter, add text or supported image inputs, choose a verified image model, write the prompt, and run the node.
The current verified list includes GPT Image 2.5, Nano Banana, FLUX.2, and Recraft models. Text and reference-image modes differ by model.
No. Standard image generation does not require S3-compatible storage. Storage is optional for workflows where a provider needs a public media URL, such as some video tasks.