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

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"
}