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