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