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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, RandomNumber, SequenceAggregate, SequenceApply, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, RandomNumber, SequenceAggregate, SequenceApply, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, RandomNumber, SequenceAggregate, SequenceApply, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, 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 dictating if sink is supposed to be executed in the background, not waiting on status of registration before end of workflow run. Use True if best-effort registration is needed, use False while debugging and if error handling is needed. |
✅ |
disable_sink |
bool |
boolean flag that can be also reference to input - to arbitrarily disable data collection for specific request. | ✅ |
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:
Pixelate Visualization
,Gaze Detection
,CLIP Embedding Model
,Blur Visualization
,OCR Model
,Mask Visualization
,Object Detection Model
,SIFT
,Line Counter
,YOLO-World Model
,Cache Get
,Halo Visualization
,Environment Secrets Store
,Grid Visualization
,Google Vision OCR
,Email Notification
,Camera Focus
,Image Threshold
,Byte Tracker
,Template Matching
,Image Preprocessing
,Roboflow Dataset Upload
,Relative Static Crop
,Background Color Visualization
,Bounding Box Visualization
,Image Contours
,Triangle Visualization
,Bounding Rectangle
,Absolute Static Crop
,Distance Measurement
,Time in Zone
,Florence-2 Model
,Detections Stitch
,SIFT Comparison
,Keypoint Detection Model
,Local File Sink
,Expression
,Roboflow Custom Metadata
,Cache Set
,Crop Visualization
,Clip Comparison
,Dynamic Zone
,SIFT Comparison
,Image Convert Grayscale
,Single-Label Classification Model
,Identify Outliers
,Florence-2 Model
,Time in Zone
,OpenAI
,Path Deviation
,Color Visualization
,Multi-Label Classification Model
,Pixel Color Count
,Property Definition
,Multi-Label Classification Model
,Path Deviation
,Stitch Images
,LMM For Classification
,First Non Empty Or Default
,Keypoint Detection Model
,Line Counter
,Instance Segmentation Model
,Rate Limiter
,Single-Label Classification Model
,Detections Filter
,Model Monitoring Inference Aggregator
,Polygon Visualization
,VLM as Detector
,Model Comparison Visualization
,CogVLM
,Keypoint Visualization
,Detections Classes Replacement
,Data Aggregator
,Detection Offset
,Slack Notification
,Stitch OCR Detections
,Identify Changes
,Clip Comparison
,Ellipse Visualization
,Label Visualization
,Classification Label Visualization
,Line Counter Visualization
,Byte Tracker
,LMM
,Stability AI Inpainting
,Reference Path Visualization
,VLM as Detector
,Dynamic Crop
,Dominant Color
,Byte Tracker
,Object Detection Model
,Barcode Detection
,Corner Visualization
,Cosine Similarity
,Perspective Correction
,Polygon Zone Visualization
,VLM as Classifier
,Dimension Collapse
,Continue If
,Twilio SMS Notification
,Size Measurement
,Webhook Sink
,OpenAI
,Detections Consensus
,Image Slicer
,Trace Visualization
,Instance Segmentation Model
,Buffer
,Roboflow Dataset Upload
,VLM as Classifier
,Anthropic Claude
,Image Blur
,Circle Visualization
,Dot Visualization
,Google Gemini
,QR Code Detection
,Segment Anything 2 Model
,JSON Parser
,Detections Stabilizer
,Delta Filter
,CSV Formatter
,Llama 3.2 Vision
,Detections Transformation
- outputs:
Multi-Label Classification Model
,Pixelate Visualization
,Path Deviation
,LMM For Classification
,Keypoint Detection Model
,Gaze Detection
,Line Counter
,Instance Segmentation Model
,CLIP Embedding Model
,Single-Label Classification Model
,Blur Visualization
,Mask Visualization
,Object Detection Model
,Line Counter
,YOLO-World Model
,Model Monitoring Inference Aggregator
,Cache Get
,Polygon Visualization
,Halo Visualization
,Google Vision OCR
,Email Notification
,Model Comparison Visualization
,CogVLM
,Image Threshold
,Keypoint Visualization
,Template Matching
,Image Preprocessing
,Slack Notification
,Roboflow Dataset Upload
,Background Color Visualization
,Bounding Box Visualization
,Label Visualization
,Classification Label Visualization
,Ellipse Visualization
,Line Counter Visualization
,LMM
,Reference Path Visualization
,Stability AI Inpainting
,Dynamic Crop
,Triangle Visualization
,Object Detection Model
,Distance Measurement
,Time in Zone
,Detections Stitch
,Florence-2 Model
,SIFT Comparison
,Keypoint Detection Model
,Corner Visualization
,Perspective Correction
,Local File Sink
,Polygon Zone Visualization
,Twilio SMS Notification
,Trace Visualization
,Webhook Sink
,Detections Consensus
,Size Measurement
,Roboflow Custom Metadata
,OpenAI
,Cache Set
,Instance Segmentation Model
,Crop Visualization
,Roboflow Dataset Upload
,Clip Comparison
,Anthropic Claude
,Image Blur
,Dot Visualization
,Circle Visualization
,Google Gemini
,Segment Anything 2 Model
,Single-Label Classification Model
,Time in Zone
,Florence-2 Model
,Path Deviation
,OpenAI
,Color Visualization
,Multi-Label Classification Model
,Pixel Color Count
,Llama 3.2 Vision
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[boolean
,roboflow_api_key
,roboflow_project
,string
,list_of_values
,integer
,float_zero_to_one
,float
,top_class
,roboflow_model_id
]): Request query parameters.headers
(Union[boolean
,roboflow_api_key
,roboflow_project
,string
,float_zero_to_one
,integer
,float
,top_class
,roboflow_model_id
]): 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 dictating if sink is supposed to be executed in the background, not waiting on status of registration before end of workflow run. UseTrue
if best-effort registration is needed, useFalse
while debugging and if error handling is needed.disable_sink
(boolean
): boolean flag that can be also reference to input - to arbitrarily disable data collection for specific request.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"
}