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

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, classification_prediction, keypoint_detection_prediction, object_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
}