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