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: CLIP Embedding Model, Detections Stitch, Circle Visualization, Model Monitoring Inference Aggregator, Time in Zone, QR Code Generator, Dot Visualization, Gaze Detection, Overlap Filter, Single-Label Classification Model, Blur Visualization, Slack Notification, Florence-2 Model, Object Detection Model, Keypoint Detection Model, Llama 3.2 Vision, Delta Filter, Crop Visualization, Barcode Detection, OCR Model, EasyOCR, Velocity, Image Threshold, Relative Static Crop, Triangle Visualization, Reference Path Visualization, QR Code Detection, Model Comparison Visualization, Dimension Collapse, Cache Set, Corner Visualization, Image Slicer, Size Measurement, Image Blur, SIFT Comparison, SmolVLM2, Bounding Box Visualization, Dynamic Zone, Buffer, Stitch OCR Detections, Detections Transformation, First Non Empty Or Default, Multi-Label Classification Model, YOLO-World Model, Distance Measurement, Icon Visualization, SIFT, Stability AI Inpainting, Google Vision OCR, Polygon Zone Visualization, Webhook Sink, CogVLM, Cache Get, Time in Zone, SIFT Comparison, Stability AI Outpainting, Classification Label Visualization, Multi-Label Classification Model, Morphological Transformation, JSON Parser, Depth Estimation, Detections Stabilizer, Instance Segmentation Model, Dominant Color, Segment Anything 2 Model, Continue If, VLM as Classifier, VLM as Detector, Local File Sink, Roboflow Custom Metadata, VLM as Classifier, Pixelate Visualization, CSV Formatter, PTZ Tracking (ONVIF).md), Pixel Color Count, Path Deviation, Byte Tracker, Identify Outliers, Expression, Single-Label Classification Model, Detections Filter, Grid Visualization, Detections Classes Replacement, Path Deviation, Data Aggregator, Template Matching, Roboflow Dataset Upload, Image Slicer, Perception Encoder Embedding Model, Clip Comparison, Perspective Correction, Roboflow Dataset Upload, Anthropic Claude, Background Color Visualization, OpenAI, Bounding Rectangle, Dynamic Crop, Trace Visualization, Keypoint Detection Model, Detection Offset, Polygon Visualization, Identify Changes, Cosine Similarity, Florence-2 Model, Moondream2, Line Counter, Environment Secrets Store, Byte Tracker, Keypoint Visualization, Byte Tracker, Detections Combine, Clip Comparison, Line Counter Visualization, Property Definition, VLM as Detector, OpenAI, Line Counter, Camera Calibration, Instance Segmentation Model, Mask Visualization, Camera Focus, Twilio SMS Notification, Detections Consensus, LMM, Image Preprocessing, Time in Zone, Color Visualization, LMM For Classification, Ellipse Visualization, Stability AI Image Generation, Qwen2.5-VL, Email Notification, Halo Visualization, Rate Limiter, Stitch Images, Absolute Static Crop, Google Gemini, Object Detection Model, Image Contours, Detections Merge, Label Visualization, OpenAI, Contrast Equalization, Image Convert Grayscale
• 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"
}