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

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"
}