Webhook Sink¶
Class: WebhookSinkBlockV1
Source: inference.core.workflows.core_steps.sinks.webhook.v1.WebhookSinkBlockV1
The Webhook Sink block enables sending a data from Workflow into external APIs by sending HTTP requests containing workflow results.
How This Block Works¶
It supports multiple HTTP methods (GET, POST, PUT) and can be configured to send:
-
JSON payloads
-
query parameters
-
multipart-encoded files
This block is designed to provide flexibility for integrating workflows with remote systems for data exchange, notifications, or other integrations.
Setting Query Parameters¶
You can easily set query parameters for your request:
query_parameters = {
"api_key": "$inputs.api_key",
}
will send request into the following URL: https://your-host/some/resource?api_key=<API_KEY_VALUE>
Setting headers¶
Setting headers is as easy as setting query parameters:
headers = {
"api_key": "$inputs.api_key",
}
Sending JSON payloads¶
You can set the body of your message to be JSON document that you construct specifying json_payload
and json_payload_operations properties. json_payload works similarly to query_parameters and
headers, but you can optionally apply UQL operations on top of JSON body elements.
Let's assume that you want to send number of bounding boxes predicted by object detection model
in body field named detections_number, then you need to specify configuration similar to the
following:
json_payload = {
"detections_number": "$steps.model.predictions",
}
json_payload_operations = {
"detections_number": [{"type": "SequenceLength"}]
}
Multipart-Encoded Files in POST requests¶
Your endpoint may also accept multipart requests. You can form them in a way which is similar to
JSON payloads - setting multi_part_encoded_files and multi_part_encoded_files_operations.
Let's assume you want to send the image in the request, then your configuration may be the following:
multi_part_encoded_files = {
"image": "$inputs.image",
}
multi_part_encoded_files_operations = {
"image": [{"type": "ConvertImageToJPEG"}]
}
Cooldown¶
The block accepts cooldown_seconds (which defaults to 5 seconds) to prevent unintended bursts of
notifications. Please adjust it according to your needs, setting 0 indicate no cooldown.
During cooldown period, consecutive runs of the step will cause throttling_status output to be set True
and no notification will be sent.
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.
Async execution¶
Configure the fire_and_forget property. Set it to True if you want the request to be sent in the background,
allowing the Workflow to proceed without waiting on data to be sent. In this case you will not be able to rely on
error_status output which will always be set to False, so we recommend setting the fire_and_forget=False for
debugging purposes.
Disabling notifications based on runtime parameter¶
Sometimes it would be convenient to manually disable the Webhook sink block. This is possible
setting disable_sink flag to hold reference to Workflow input. with such setup, caller would be
able to disable the sink when needed sending agreed input parameter.
Common Use Cases¶
- Use this block to [purpose based on block type]
Connecting to Other Blocks¶
The outputs from this block can be connected to other blocks in your workflow.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/webhook_sink@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
url |
str |
URL of the resource to make request. | ✅ |
method |
str |
HTTP method to be used. | ❌ |
query_parameters |
Dict[str, Union[List[Union[bool, float, int, str]], bool, float, int, str]] |
Request query parameters. | ✅ |
headers |
Dict[str, Union[bool, float, int, str]] |
Request headers. | ✅ |
json_payload |
Dict[str, Union[Dict[Any, Any], List[Any], bool, float, int, str]] |
Fields to put into JSON payload. | ✅ |
json_payload_operations |
Dict[str, List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]]] |
UQL definitions of operations to be performed on defined data w.r.t. each value of json_payload parameter. |
❌ |
multi_part_encoded_files |
Dict[str, Union[Dict[Any, Any], List[Any], bool, float, int, str]] |
Data to POST as Multipart-Encoded File. | ✅ |
multi_part_encoded_files_operations |
Dict[str, List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]]] |
UQL definitions of operations to be performed on defined data w.r.t. each value of multi_part_encoded_files parameter. |
❌ |
form_data |
Dict[str, Union[Dict[Any, Any], List[Any], bool, float, int, str]] |
Fields to put into form-data. | ✅ |
form_data_operations |
Dict[str, List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]]] |
UQL definitions of operations to be performed on defined data w.r.t. each value of form_data parameter. |
❌ |
request_timeout |
int |
Number of seconds to wait for remote API response. | ✅ |
fire_and_forget |
bool |
Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling.. | ✅ |
disable_sink |
bool |
Boolean flag to disable block execution.. | ✅ |
cooldown_seconds |
int |
Number of seconds to wait until follow-up notification can be sent.. | ✅ |
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 Webhook Sink in version v1.
- inputs:
Keypoint Detection Model,VLM As Detector,YOLO-World Model,MoonshotAI Kimi,Polygon Zone Visualization,OpenAI-Compatible LLM,Heatmap Visualization,Email Notification,Llama 3.2 Vision,Anthropic Claude,Camera Focus,Label Visualization,Path Deviation,Qwen3.5,SmolVLM2,Rate Limiter,Byte Tracker,Background Color Visualization,Mask Edge Snap,Moondream2,Velocity,Detection Event Log,Florence-2 Model,Barcode Detection,OCR Model,Single-Label Classification Model,VLM As Classifier,Qwen2.5-VL,Detections Stabilizer,LMM For Classification,SIFT,Roboflow Dataset Upload,Segment Anything 2 Model,Multi-Label Classification Model,Halo Visualization,Qwen3.5-VL,Qwen3-VL,Time in Zone,Stitch OCR Detections,Model Comparison Visualization,QR Code Detection,Detections Combine,Bounding Rectangle,ByteTrack Tracker,Stability AI Inpainting,Image Convert Grayscale,Line Counter,OpenAI,Llama 3.2 Vision,Anthropic Claude,Dynamic Crop,Detections Consensus,Size Measurement,Dominant Color,Continue If,Contrast Enhancement,Bounding Box Visualization,Depth Estimation,CLIP Embedding Model,EasyOCR,Relative Static Crop,Polygon Visualization,Google Gemma API,Qwen 3.6 API,Template Matching,Single-Label Classification Model,Image Blur,Anthropic Claude,Triangle Visualization,Roboflow Custom Metadata,Slack Notification,Image Stack,Pixelate Visualization,Image Slicer,Line Counter Visualization,Image Slicer,Cosine Similarity,Cache Get,Expression,Data Aggregator,Google Gemini,Camera Calibration,Ellipse Visualization,Identify Changes,GLM-OCR,Crop Visualization,Circle Visualization,Dimension Collapse,Webhook Sink,MoonshotAI Kimi,S3 Sink,Email Notification,Clip Comparison,Morphological Transformation,Path Deviation,Qwen-VL,SAM 3,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Stitch OCR Detections,OpenAI,VLM As Detector,Keypoint Visualization,Seg Preview,Stability AI Image Generation,Google Vision OCR,SAM 3,Instance Segmentation Model,Overlap Filter,Local File Sink,Multi-Label Classification Model,Google Gemini,Motion Detection,Instance Segmentation Model,Qwen 3.5 API,Google Gemini,Polygon Visualization,SIFT Comparison,Grid Visualization,Delta Filter,Time in Zone,Detections Filter,Detections Merge,First Non Empty Or Default,Keypoint Detection Model,Image Preprocessing,Dynamic Zone,Corner Visualization,Stability AI Outpainting,Semantic Segmentation Model,Detections List Roll-Up,Blur Visualization,Property Definition,Perception Encoder Embedding Model,Distance Measurement,VLM As Classifier,Trace Visualization,Morphological Transformation,Gaze Detection,Reference Path Visualization,Halo Visualization,Dot Visualization,Pixel Color Count,JSON Parser,Background Subtraction,Text Display,Absolute Static Crop,CSV Formatter,Florence-2 Model,Byte Tracker,Identify Outliers,Icon Visualization,Mask Area Measurement,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Object Detection Model,QR Code Generator,OpenRouter,Model Monitoring Inference Aggregator,Image Threshold,OC-SORT Tracker,Clip Comparison,Cache Set,Detection Offset,Keypoint Detection Model,Image Contours,Multi-Label Classification Model,Per-Class Confidence Filter,Object Detection Model,OpenAI,SIFT Comparison,Single-Label Classification Model,OpenAI,Instance Segmentation Model,Buffer,Stitch Images,Environment Secrets Store,Detections Classes Replacement,Semantic Segmentation Model,LMM,Roboflow Dataset Upload,Detections Transformation,Color Visualization,Classification Label Visualization,Camera Focus,Detections Stitch,Byte Tracker,PTZ Tracking (ONVIF),SORT Tracker,Mask Visualization,CogVLM,Inner Workflow,SAM2 Video Tracker,Contrast Equalization,Roboflow Vision Events,Twilio SMS Notification,Google Gemma - outputs:
S3 Sink,Email Notification,Keypoint Detection Model,Morphological Transformation,SAM 3,Path Deviation,Qwen-VL,Clip Comparison,Twilio SMS/MMS Notification,YOLO-World Model,Line Counter,Time in Zone,Polygon Zone Visualization,MoonshotAI Kimi,Stitch OCR Detections,OpenAI-Compatible LLM,OpenAI,Heatmap Visualization,Email Notification,Keypoint Visualization,Llama 3.2 Vision,Anthropic Claude,Stability AI Image Generation,Seg Preview,Google Vision OCR,Label Visualization,SAM 3,Instance Segmentation Model,Path Deviation,Local File Sink,Multi-Label Classification Model,Google Gemini,Motion Detection,Background Color Visualization,Instance Segmentation Model,Qwen 3.5 API,Google Gemini,Polygon Visualization,Moondream2,SIFT Comparison,Florence-2 Model,Time in Zone,Single-Label Classification Model,LMM For Classification,Keypoint Detection Model,Image Preprocessing,Roboflow Dataset Upload,Dynamic Zone,Corner Visualization,Segment Anything 2 Model,Stability AI Outpainting,Multi-Label Classification Model,Halo Visualization,Time in Zone,Semantic Segmentation Model,Blur Visualization,Perception Encoder Embedding Model,Distance Measurement,Morphological Transformation,Trace Visualization,Stitch OCR Detections,Gaze Detection,Reference Path Visualization,Halo Visualization,Model Comparison Visualization,Dot Visualization,Pixel Color Count,Text Display,Florence-2 Model,Icon Visualization,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Stability AI Inpainting,Object Detection Model,Line Counter,QR Code Generator,OpenRouter,Model Monitoring Inference Aggregator,OpenAI,Llama 3.2 Vision,Image Threshold,Anthropic Claude,Dynamic Crop,Detections Consensus,Size Measurement,Cache Set,Bounding Box Visualization,Depth Estimation,Keypoint Detection Model,CLIP Embedding Model,Multi-Label Classification Model,Polygon Visualization,Google Gemma API,Template Matching,Qwen 3.6 API,Single-Label Classification Model,Image Blur,Anthropic Claude,Object Detection Model,Triangle Visualization,Roboflow Custom Metadata,OpenAI,Slack Notification,Image Stack,Pixelate Visualization,Single-Label Classification Model,OpenAI,Instance Segmentation Model,Line Counter Visualization,Detections Classes Replacement,Cache Get,LMM,Roboflow Dataset Upload,Color Visualization,Google Gemini,Classification Label Visualization,Camera Calibration,Detections Stitch,Ellipse Visualization,PTZ Tracking (ONVIF),Mask Visualization,GLM-OCR,Crop Visualization,Circle Visualization,CogVLM,Contrast Equalization,Roboflow Vision Events,Webhook Sink,Twilio SMS Notification,MoonshotAI Kimi,Google Gemma
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Webhook Sink in version v1 has.
Bindings
-
input
url(string): URL of the resource to make request.query_parameters(Union[float_zero_to_one,integer,float,list_of_values,string,roboflow_api_key,roboflow_model_id,roboflow_project,top_class,boolean]): Request query parameters.headers(Union[float_zero_to_one,integer,float,string,roboflow_api_key,roboflow_model_id,roboflow_project,top_class,boolean]): Request headers.json_payload(*): Fields to put into JSON payload.multi_part_encoded_files(*): Data to POST as Multipart-Encoded File.form_data(*): Fields to put into form-data.request_timeout(integer): Number of seconds to wait for remote API response.fire_and_forget(boolean): Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..disable_sink(boolean): Boolean flag to disable block execution..cooldown_seconds(integer): Number of seconds to wait until follow-up notification can be sent..
-
output
Example JSON definition of step Webhook Sink in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/webhook_sink@v1",
"url": "<block_does_not_provide_example>",
"method": "<block_does_not_provide_example>",
"query_parameters": {
"api_key": "$inputs.api_key"
},
"headers": {
"api_key": "$inputs.api_key"
},
"json_payload": {
"field": "$steps.model.predictions"
},
"json_payload_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"multi_part_encoded_files": {
"image": "$steps.visualization.image"
},
"multi_part_encoded_files_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"form_data": {
"field": "$inputs.field_value"
},
"form_data_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"request_timeout": "$inputs.request_timeout",
"fire_and_forget": "$inputs.fire_and_forget",
"disable_sink": false,
"cooldown_seconds": "$inputs.cooldown_seconds"
}