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