Stability AI Image Generation

Class: StabilityAIImageGenBlockV1

Source: inference.core.workflows.core_steps.models.foundation.stability_ai.image_gen.v1.StabilityAIImageGenBlockV1

The block wraps Stability AI image generation API and let users generate new images from text, or create variations of existing images.

Type identifier

Use the following identifier in step "type" field: roboflow_core/stability_ai_image_gen@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
strength	float	controls how much influence the image parameter has on the generated image. A value of 0 would yield an image that is identical to the input. A value of 1 would be as if you passed in no image at all..	✅
prompt	str	Prompt to generate new images from text (what you wish to see).	✅
negative_prompt	str	Negative prompt to image generation model (what you do not wish to see).	✅
model	str	choose one of {'core', 'ultra', 'sd3'}. Default 'core' .	✅
api_key	str	Your Stability AI API key.	✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to Stability AI Image Generation in version v1.

• inputs: LMM, Depth Estimation, Classification Label Visualization, Camera Calibration, Stitch OCR Detections, LMM For Classification, Clip Comparison, CSV Formatter, Instance Segmentation Model, Stitch Images, CogVLM, Image Slicer, Roboflow Dataset Upload, Absolute Static Crop, Twilio SMS Notification, Florence-2 Model, OpenAI, Label Visualization, Single-Label Classification Model, Roboflow Dataset Upload, Bounding Box Visualization, Llama 3.2 Vision, Model Comparison Visualization, Slack Notification, Object Detection Model, VLM as Classifier, Detections Consensus, Grid Visualization, Image Convert Grayscale, Halo Visualization, Triangle Visualization, Model Monitoring Inference Aggregator, Keypoint Detection Model, Reference Path Visualization, Perspective Correction, Dynamic Crop, Camera Focus, Identify Changes, VLM as Detector, Florence-2 Model, Local File Sink, OpenAI, Google Vision OCR, Stability AI Image Generation, Ellipse Visualization, SIFT, Blur Visualization, Circle Visualization, Dot Visualization, Image Blur, Background Color Visualization, Multi-Label Classification Model, Color Visualization, Pixelate Visualization, Identify Outliers, Google Gemini, Stability AI Inpainting, Polygon Zone Visualization, Relative Static Crop, OCR Model, Keypoint Visualization, Mask Visualization, Image Preprocessing, Line Counter Visualization, Roboflow Custom Metadata, Anthropic Claude, Webhook Sink, SIFT Comparison, Trace Visualization, Corner Visualization, Polygon Visualization, Crop Visualization, Email Notification, Image Contours, Image Slicer, Image Threshold
• outputs: LMM, Depth Estimation, Classification Label Visualization, Camera Calibration, LMM For Classification, Clip Comparison, Instance Segmentation Model, Stitch Images, CogVLM, Image Slicer, Roboflow Dataset Upload, Absolute Static Crop, Multi-Label Classification Model, Object Detection Model, Florence-2 Model, QR Code Detection, OpenAI, Label Visualization, Single-Label Classification Model, Qwen2.5-VL, Roboflow Dataset Upload, Detections Stitch, Bounding Box Visualization, Llama 3.2 Vision, Model Comparison Visualization, Pixel Color Count, Object Detection Model, VLM as Classifier, Moondream2, Image Convert Grayscale, Halo Visualization, Buffer, Triangle Visualization, Time in Zone, Keypoint Detection Model, Reference Path Visualization, Perspective Correction, Dynamic Crop, Camera Focus, VLM as Detector, Florence-2 Model, OpenAI, Google Vision OCR, VLM as Detector, Stability AI Image Generation, Ellipse Visualization, SIFT, Blur Visualization, Circle Visualization, Image Blur, Dot Visualization, CLIP Embedding Model, Background Color Visualization, Gaze Detection, Multi-Label Classification Model, Single-Label Classification Model, Byte Tracker, Color Visualization, Pixelate Visualization, Dominant Color, Clip Comparison, Google Gemini, Keypoint Detection Model, Stability AI Inpainting, VLM as Classifier, Polygon Zone Visualization, Relative Static Crop, Detections Stabilizer, OCR Model, Keypoint Visualization, Template Matching, Mask Visualization, SmolVLM2, Image Preprocessing, Line Counter Visualization, Anthropic Claude, SIFT Comparison, YOLO-World Model, Trace Visualization, Instance Segmentation Model, Corner Visualization, Polygon Visualization, Segment Anything 2 Model, Barcode Detection, Crop Visualization, Image Contours, Image Slicer, Image Threshold

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Stability AI Image Generation in version v1 has.

Bindings

• input

  • image (image): The image to use as the starting point for the generation..
  • strength (float_zero_to_one): controls how much influence the image parameter has on the generated image. A value of 0 would yield an image that is identical to the input. A value of 1 would be as if you passed in no image at all..
  • prompt (string): Prompt to generate new images from text (what you wish to see).
  • negative_prompt (string): Negative prompt to image generation model (what you do not wish to see).
  • model (string): choose one of {'core', 'ultra', 'sd3'}. Default 'core' .
  • api_key (Union[string, secret]): Your Stability AI API key.

• output

  • image (image): Image in workflows.

Example JSON definition of step Stability AI Image Generation in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/stability_ai_image_gen@v1",
    "image": "$inputs.image",
    "strength": 0.3,
    "prompt": "my prompt",
    "negative_prompt": "my prompt",
    "model": "my prompt",
    "api_key": "xxx-xxx"
}