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: Google Vision OCR, LMM For Classification, Detections Filter, Single-Label Classification Model, CSV Formatter, SAM 3, Seg Preview, Byte Tracker, Overlap Filter, SAM 3, SIFT Comparison, Object Detection Model, Path Deviation, Detections Combine, Email Notification, Anthropic Claude, Object Detection Model, Line Counter, Clip Comparison, Email Notification, Moondream2, VLM as Classifier, Model Monitoring Inference Aggregator, OCR Model, Path Deviation, LMM, Time in Zone, Roboflow Dataset Upload, Gaze Detection, Detections Consensus, OpenAI, SAM 3, VLM as Detector, Multi-Label Classification Model, Florence-2 Model, CogVLM, Roboflow Custom Metadata, Byte Tracker, Keypoint Detection Model, Stitch OCR Detections, Bounding Rectangle, Segment Anything 2 Model, Keypoint Detection Model, SIFT Comparison, Time in Zone, JSON Parser, YOLO-World Model, PTZ Tracking (ONVIF).md), Detection Offset, Detections Classes Replacement, Detections Transformation, Identify Changes, Template Matching, Roboflow Dataset Upload, Anthropic Claude, Florence-2 Model, Google Gemini, Google Gemini, EasyOCR, VLM as Detector, Identify Outliers, Dynamic Zone, Time in Zone, Twilio SMS Notification, Detections Stitch, Llama 3.2 Vision, Velocity, Slack Notification, Byte Tracker, OpenAI, Local File Sink, Instance Segmentation Model, Multi-Label Classification Model, OpenAI, Dynamic Crop, Single-Label Classification Model, Detections Stabilizer, Webhook Sink, Instance Segmentation Model, VLM as Classifier, Perspective Correction, Detections Merge, OpenAI
• outputs: Label Visualization, Blur Visualization, Background Color Visualization, Contrast Equalization, Reference Path Visualization, Stability AI Outpainting, Pixelate Visualization, Single-Label Classification Model, Perception Encoder Embedding Model, Seg Preview, Image Preprocessing, Color Visualization, SIFT Comparison, Email Notification, Cache Set, Circle Visualization, Object Detection Model, Moondream2, Model Monitoring Inference Aggregator, Path Deviation, LMM, Time in Zone, Morphological Transformation, Gaze Detection, Detections Consensus, Crop Visualization, OpenAI, Florence-2 Model, Classification Label Visualization, Segment Anything 2 Model, Time in Zone, YOLO-World Model, PTZ Tracking (ONVIF).md), Icon Visualization, Distance Measurement, Line Counter Visualization, Halo Visualization, Size Measurement, Dynamic Zone, Twilio SMS Notification, Time in Zone, Detections Stitch, Llama 3.2 Vision, Image Blur, Slack Notification, OpenAI, Multi-Label Classification Model, OpenAI, Dynamic Crop, Pixel Color Count, Mask Visualization, Google Vision OCR, LMM For Classification, Keypoint Visualization, Bounding Box Visualization, SAM 3, SAM 3, Object Detection Model, Path Deviation, Anthropic Claude, Polygon Zone Visualization, Ellipse Visualization, Line Counter, Email Notification, Clip Comparison, Roboflow Dataset Upload, SAM 3, CogVLM, Multi-Label Classification Model, Roboflow Custom Metadata, Keypoint Detection Model, Stitch OCR Detections, Keypoint Detection Model, Line Counter, Polygon Visualization, CLIP Embedding Model, Detections Classes Replacement, Cache Get, Triangle Visualization, Template Matching, Roboflow Dataset Upload, Anthropic Claude, Model Comparison Visualization, Corner Visualization, Florence-2 Model, Google Gemini, Google Gemini, Stability AI Image Generation, QR Code Generator, Dot Visualization, Local File Sink, Instance Segmentation Model, Stability AI Inpainting, Single-Label Classification Model, Webhook Sink, Instance Segmentation Model, Image Threshold, Perspective Correction, OpenAI, Trace Visualization

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[classification_prediction, instance_segmentation_prediction, object_detection_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
}