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@v1
to 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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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:
Environment Secrets Store
,Cache Set
,Object Detection Model
,Object Detection Model
,Detection Offset
,CogVLM
,Ellipse Visualization
,Grid Visualization
,SIFT
,Camera Focus
,Property Definition
,CLIP Embedding Model
,Dot Visualization
,Google Vision OCR
,Clip Comparison
,Identify Changes
,Polygon Zone Visualization
,Gaze Detection
,Classification Label Visualization
,Corner Visualization
,Dynamic Crop
,Label Visualization
,Detections Stabilizer
,Triangle Visualization
,Dynamic Zone
,Dominant Color
,Time in Zone
,Barcode Detection
,Blur Visualization
,Line Counter
,Webhook Sink
,Instance Segmentation Model
,Cosine Similarity
,Path Deviation
,Relative Static Crop
,Detections Consensus
,Twilio SMS Notification
,Crop Visualization
,Qwen2.5-VL
,Distance Measurement
,Circle Visualization
,Velocity
,Keypoint Detection Model
,QR Code Detection
,Size Measurement
,Single-Label Classification Model
,Bounding Box Visualization
,LMM For Classification
,Image Threshold
,OCR Model
,Detections Stitch
,Keypoint Visualization
,Single-Label Classification Model
,Detections Classes Replacement
,Polygon Visualization
,Cache Get
,Image Slicer
,Segment Anything 2 Model
,Stability AI Inpainting
,Clip Comparison
,Perspective Correction
,Roboflow Custom Metadata
,SIFT Comparison
,VLM as Detector
,Image Contours
,Multi-Label Classification Model
,OpenAI
,Absolute Static Crop
,Trace Visualization
,Multi-Label Classification Model
,VLM as Detector
,Identify Outliers
,Roboflow Dataset Upload
,First Non Empty Or Default
,VLM as Classifier
,Llama 3.2 Vision
,Byte Tracker
,Line Counter
,Reference Path Visualization
,Mask Visualization
,Template Matching
,Line Counter Visualization
,Detections Transformation
,Model Monitoring Inference Aggregator
,Anthropic Claude
,SIFT Comparison
,Time in Zone
,Instance Segmentation Model
,Slack Notification
,Detections Filter
,Stitch OCR Detections
,Pixelate Visualization
,Delta Filter
,Dimension Collapse
,VLM as Classifier
,Roboflow Dataset Upload
,Keypoint Detection Model
,Google Gemini
,Rate Limiter
,Model Comparison Visualization
,Halo Visualization
,JSON Parser
,Byte Tracker
,Expression
,Image Blur
,Buffer
,Image Preprocessing
,Background Color Visualization
,Continue If
,Bounding Rectangle
,Pixel Color Count
,Florence-2 Model
,Florence-2 Model
,Local File Sink
,Byte Tracker
,Image Slicer
,Stitch Images
,Stability AI Image Generation
,LMM
,Email Notification
,Color Visualization
,Path Deviation
,YOLO-World Model
,Data Aggregator
,CSV Formatter
,Image Convert Grayscale
,OpenAI
- outputs:
Segment Anything 2 Model
,Cache Get
,Stability AI Inpainting
,Clip Comparison
,Perspective Correction
,Cache Set
,Object Detection Model
,Roboflow Custom Metadata
,Object Detection Model
,SIFT Comparison
,CogVLM
,Ellipse Visualization
,Multi-Label Classification Model
,OpenAI
,Trace Visualization
,CLIP Embedding Model
,Multi-Label Classification Model
,Dot Visualization
,Google Vision OCR
,Roboflow Dataset Upload
,Polygon Zone Visualization
,Gaze Detection
,Classification Label Visualization
,Corner Visualization
,Llama 3.2 Vision
,Line Counter
,Reference Path Visualization
,Dynamic Crop
,Label Visualization
,Mask Visualization
,Triangle Visualization
,Template Matching
,Line Counter Visualization
,Model Monitoring Inference Aggregator
,Time in Zone
,Blur Visualization
,Line Counter
,Anthropic Claude
,Instance Segmentation Model
,Webhook Sink
,Time in Zone
,Instance Segmentation Model
,Slack Notification
,Pixelate Visualization
,Path Deviation
,OpenAI
,Detections Consensus
,Twilio SMS Notification
,Keypoint Detection Model
,Roboflow Dataset Upload
,Google Gemini
,Model Comparison Visualization
,Halo Visualization
,Crop Visualization
,Image Blur
,Distance Measurement
,Circle Visualization
,Keypoint Detection Model
,Image Preprocessing
,Background Color Visualization
,Pixel Color Count
,Size Measurement
,Florence-2 Model
,Single-Label Classification Model
,Bounding Box Visualization
,Florence-2 Model
,Local File Sink
,LMM For Classification
,Stability AI Image Generation
,Image Threshold
,Detections Stitch
,LMM
,Keypoint Visualization
,Email Notification
,Color Visualization
,Path Deviation
,Single-Label Classification Model
,YOLO-World Model
,Polygon Visualization
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
,list_of_values
,float_zero_to_one
,roboflow_model_id
,boolean
,roboflow_project
,string
,integer
,top_class
,float
]): Request query parameters.headers
(Union[roboflow_api_key
,float_zero_to_one
,roboflow_model_id
,boolean
,roboflow_project
,string
,integer
,top_class
,float
]): 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"
}