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. 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.
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:
Absolute Static Crop,Relative Static Crop,Expression,LMM For Classification,VLM as Classifier,Seg Preview,Instance Segmentation Model,Color Visualization,Trace Visualization,Polygon Zone Visualization,Camera Focus,Halo Visualization,Identify Changes,VLM as Classifier,Camera Calibration,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,EasyOCR,Distance Measurement,Circle Visualization,Stability AI Outpainting,Byte Tracker,Size Measurement,VLM as Detector,JSON Parser,Byte Tracker,Keypoint Visualization,Object Detection Model,Clip Comparison,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:
Size Measurement,Keypoint Visualization,Object Detection Model,LMM For Classification,Google Vision OCR,Slack Notification,Trace Visualization,Color Visualization,Instance Segmentation Model,Polygon Zone Visualization,Halo Visualization,Dynamic Zone,Triangle Visualization,Single-Label Classification Model,Segment Anything 2 Model,Stability AI Inpainting,Reference Path Visualization,Image Threshold,Corner Visualization,Detections Classes Replacement,Ellipse Visualization,Gaze Detection,OpenAI,Single-Label Classification Model,Time in Zone,Morphological Transformation,Roboflow Custom Metadata,Image Preprocessing,Cache Set,CogVLM,Line Counter Visualization,OpenAI,YOLO-World Model,Florence-2 Model,Roboflow Dataset Upload,Stitch OCR Detections,Path Deviation,Label Visualization,PTZ Tracking (ONVIF).md),Model Comparison Visualization,Multi-Label Classification Model,Multi-Label Classification Model,Roboflow Dataset Upload,Template Matching,OpenAI,Line Counter,Line Counter,Model Monitoring Inference Aggregator,Polygon Visualization,Time in Zone,Instance Segmentation Model,Path Deviation,Llama 3.2 Vision,Icon Visualization,Local File Sink,Time in Zone,Blur Visualization,Clip Comparison,Object Detection Model,Twilio SMS Notification,Bounding Box Visualization,Moondream2,Classification Label Visualization,Background Color Visualization,Webhook Sink,Dynamic Crop,Dot Visualization,Pixelate Visualization,Detections Consensus,Email Notification,CLIP Embedding Model,Crop Visualization,Keypoint Detection Model,Perception Encoder Embedding Model,SIFT Comparison,Mask Visualization,Pixel Color Count,QR Code Generator,Google Gemini,Perspective Correction,Keypoint Detection Model,Stability AI Image Generation,Distance Measurement,Contrast Equalization,Anthropic Claude,Image Blur,Cache Get,Circle Visualization,Stability AI Outpainting,LMM,Detections Stitch,Florence-2 Model
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[roboflow_api_key,float,boolean,roboflow_model_id,float_zero_to_one,top_class,string,integer,roboflow_project,list_of_values]): Request query parameters.headers(Union[float,roboflow_model_id,roboflow_project,float_zero_to_one,top_class,string,integer,roboflow_api_key,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"
}