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

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[object_detection_prediction, classification_prediction, keypoint_detection_prediction, instance_segmentation_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
}