Rate Limiter

Class: RateLimiterBlockV1

Source: inference.core.workflows.core_steps.flow_control.rate_limiter.v1.RateLimiterBlockV1

The Rate Limiter block controls the execution frequency of a branch within a Workflow by enforcing a cooldown period. It ensures that the connected steps do not run more frequently than a specified interval, helping to manage resource usage and prevent over-execution.

Block usage

Rate Limiter is useful when you have two blocks that are directly connected, as shown below:

--- input_a --> ┌───────────┐ ┌───────────┐ --- input_b --> │ step_1 │ --> output_a --> │ step_2 │ --- input_c --> └───────────┘ └───────────┘

If you want to throttle the Step 2 execution rate - you should apply rate limiter in between:

• keep the existing blocks configuration as is (do not change connections)

• set depends_on reference of Rate Limiter into output_a

• set next_steps reference to be a list referring to [$steps.step_2]

• adjust cooldown_seconds to specify what is the number of seconds that must be awaited before next time when step_2 is fired

Cooldown limitations

Current implementation of cooldown is limited to video processing - using this block in context of a Workflow that is run behind HTTP service (Roboflow Hosted API, Dedicated Deployment or self-hosted inference server) will have no effect for processing HTTP requests.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
cooldown_seconds	float	The minimum number of seconds between allowed executions..	❌

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 Rate Limiter in version v1.

• inputs: Model Monitoring Inference Aggregator, Label Visualization, Florence-2 Model, Triangle Visualization, Image Blur, OCR Model, Detections Transformation, Line Counter Visualization, Circle Visualization, Relative Static Crop, Detections Stitch, Trace Visualization, Byte Tracker, Object Detection Model, Clip Comparison, Detection Offset, Detections Consensus, Velocity, Dominant Color, Stitch Images, Bounding Rectangle, Detections Filter, Cosine Similarity, Segment Anything 2 Model, Roboflow Custom Metadata, Single-Label Classification Model, VLM as Classifier, Local File Sink, Crop Visualization, Color Visualization, Image Slicer, Google Gemini, Dynamic Crop, Multi-Label Classification Model, Continue If, Instance Segmentation Model, Keypoint Detection Model, SmolVLM2, Google Vision OCR, Corner Visualization, Overlap Filter, Polygon Zone Visualization, Byte Tracker, Camera Focus, Grid Visualization, Perspective Correction, Stability AI Image Generation, Cache Get, Image Slicer, CSV Formatter, OpenAI, Blur Visualization, Time in Zone, Slack Notification, SIFT Comparison, Pixel Color Count, Detections Stabilizer, Anthropic Claude, QR Code Detection, Buffer, Bounding Box Visualization, Distance Measurement, Twilio SMS Notification, Email Notification, Object Detection Model, LMM For Classification, SIFT Comparison, VLM as Detector, LMM, Florence-2 Model, Depth Estimation, CogVLM, Model Comparison Visualization, Cache Set, First Non Empty Or Default, Data Aggregator, Barcode Detection, Environment Secrets Store, Multi-Label Classification Model, Path Deviation, Rate Limiter, Dimension Collapse, Gaze Detection, Reference Path Visualization, Llama 3.2 Vision, Expression, Detections Merge, Polygon Visualization, Roboflow Dataset Upload, Time in Zone, Identify Outliers, SIFT, Image Threshold, Path Deviation, Property Definition, CLIP Embedding Model, Keypoint Visualization, Ellipse Visualization, JSON Parser, OpenAI, Instance Segmentation Model, Dot Visualization, Roboflow Dataset Upload, Keypoint Detection Model, Stability AI Inpainting, Line Counter, Identify Changes, Single-Label Classification Model, Template Matching, Background Color Visualization, Delta Filter, VLM as Detector, Line Counter, Qwen2.5-VL, Clip Comparison, Dynamic Zone, Classification Label Visualization, Image Convert Grayscale, Image Preprocessing, Byte Tracker, OpenAI, YOLO-World Model, Stability AI Outpainting, Perception Encoder Embedding Model, Size Measurement, Webhook Sink, Moondream2, Camera Calibration, Mask Visualization, Pixelate Visualization, Stitch OCR Detections, PTZ Tracking (ONVIF).md), Image Contours, Detections Classes Replacement, Absolute Static Crop, Halo Visualization, VLM as Classifier
• outputs: None

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Rate Limiter in version v1 has.

Bindings

• input

  • depends_on (*): Step immediately preceding this block..
  • next_steps (step): Steps to execute if allowed by the rate limit..
  • video_reference_image (image): Reference to a video frame to use for timestamp generation (if running faster than realtime on recorded video)..

• output

Example JSON definition of step Rate Limiter in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/rate_limiter@v1",
    "cooldown_seconds": 1.0,
    "depends_on": "$steps.model",
    "next_steps": [
        "$steps.upload"
    ],
    "video_reference_image": "$inputs.image"
}