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