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