Roboflow Custom Metadata

Class: RoboflowCustomMetadataBlockV1

Source: inference.core.workflows.core_steps.sinks.roboflow.custom_metadata.v1.RoboflowCustomMetadataBlockV1

Block allows users to add custom metadata to each inference result in Roboflow Model Monitoring dashboard.

This is useful for adding information specific to your use case. For example, if you want to be able to filter inferences by a specific label such as location, you can attach those labels to each inference with this block.

For more information on Model Monitoring at Roboflow, see https://docs.roboflow.com/deploy/model-monitoring.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
field_value	str	This is the name of the metadata field you are creating.	✅
field_name	str	Name of the field to be updated..	❌
fire_and_forget	bool	Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..	✅

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 Roboflow Custom Metadata in version v1.

• inputs: Detection Offset, LMM, Roboflow Custom Metadata, VLM as Detector, Multi-Label Classification Model, Detections Classes Replacement, Gaze Detection, OCR Model, Keypoint Detection Model, Instance Segmentation Model, SIFT Comparison, Object Detection Model, Path Deviation, Line Counter, Detections Stabilizer, Detections Transformation, Multi-Label Classification Model, Byte Tracker, Google Vision OCR, Roboflow Dataset Upload, Dynamic Zone, Llama 3.2 Vision, Clip Comparison, Perspective Correction, Object Detection Model, Webhook Sink, Identify Changes, Detections Filter, Email Notification, Instance Segmentation Model, Slack Notification, Detections Merge, Time in Zone, Time in Zone, Local File Sink, CogVLM, Keypoint Detection Model, Overlap Filter, JSON Parser, OpenAI, Moondream2, Path Deviation, Florence-2 Model, Twilio SMS Notification, Bounding Rectangle, Detections Stitch, Template Matching, Byte Tracker, LMM For Classification, Stitch OCR Detections, OpenAI, Google Gemini, Single-Label Classification Model, SIFT Comparison, YOLO-World Model, VLM as Detector, Velocity, Roboflow Dataset Upload, Segment Anything 2 Model, Single-Label Classification Model, VLM as Classifier, CSV Formatter, Model Monitoring Inference Aggregator, VLM as Classifier, Anthropic Claude, Florence-2 Model, Identify Outliers, Byte Tracker, Dynamic Crop, Detections Consensus
• outputs: Size Measurement, Roboflow Custom Metadata, LMM, Multi-Label Classification Model, Distance Measurement, Line Counter Visualization, Gaze Detection, Background Color Visualization, Keypoint Detection Model, Reference Path Visualization, Instance Segmentation Model, SIFT Comparison, Object Detection Model, Triangle Visualization, Path Deviation, Line Counter, Multi-Label Classification Model, Llama 3.2 Vision, Roboflow Dataset Upload, Google Vision OCR, Clip Comparison, Perspective Correction, Object Detection Model, Crop Visualization, Webhook Sink, Dot Visualization, Model Comparison Visualization, Email Notification, Classification Label Visualization, Instance Segmentation Model, Slack Notification, Stability AI Image Generation, Cache Set, Time in Zone, Time in Zone, Trace Visualization, Corner Visualization, Line Counter, Image Threshold, Blur Visualization, Local File Sink, CogVLM, Stability AI Inpainting, Keypoint Detection Model, Circle Visualization, OpenAI, Path Deviation, Florence-2 Model, Twilio SMS Notification, Label Visualization, Image Preprocessing, Detections Stitch, Template Matching, Polygon Zone Visualization, Keypoint Visualization, LMM For Classification, Bounding Box Visualization, Image Blur, OpenAI, Halo Visualization, CLIP Embedding Model, Ellipse Visualization, Color Visualization, Google Gemini, Pixelate Visualization, Single-Label Classification Model, Pixel Color Count, YOLO-World Model, Roboflow Dataset Upload, Polygon Visualization, Segment Anything 2 Model, Single-Label Classification Model, Cache Get, Model Monitoring Inference Aggregator, Mask Visualization, Anthropic Claude, Florence-2 Model, Dynamic Crop, Detections Consensus

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Roboflow Custom Metadata in version v1 has.

Bindings

• input

  • predictions (Union[instance_segmentation_prediction, object_detection_prediction, classification_prediction, keypoint_detection_prediction]): Model predictions to attach custom metadata to..
  • field_value (string): This is the name of the metadata field you are creating.
  • fire_and_forget (boolean): Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..

• output

  • error_status (boolean): Boolean flag.
  • message (string): String value.

Example JSON definition of step Roboflow Custom Metadata in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/roboflow_custom_metadata@v1",
    "predictions": "$steps.my_step.predictions",
    "field_value": "toronto",
    "field_name": "The name of the value of the field",
    "fire_and_forget": true
}