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