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