Slack Notification¶
Class: SlackNotificationBlockV1
Source: inference.core.workflows.core_steps.sinks.slack.notification.v1.SlackNotificationBlockV1
The Slack Notification block 📩 enables sending notifications via Slack, with customizable messages, attachments, and cooldown mechanisms.
The block requires Slack setup - this article may help you configuring everything properly.
✨ Key Features¶
-
📢 Send Messages: Deliver notifications to specified Slack channels.
-
🔗 Dynamic Content: Craft notifications based on outputs from other Workflow steps.
-
📎 Attach Files: Share reports, predictions or visualizations.
-
🕒 Cooldown Control: Prevent duplicate notifications within a set time frame.
-
⚙️ Flexible Execution: Execute in the background or block Workflow execution for debugging.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/slack_notification@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
slack_token |
str |
Visit https://api.slack.com/tutorials/tracks/getting-a-token to find out how to generate a Slack API token.. | ✅ |
channel |
str |
Identifier of Slack channel.. | ✅ |
message |
str |
Content of the message to be sent.. | ❌ |
message_parameters |
Dict[str, Union[bool, float, int, str]] |
Data to be used in the message content.. | ✅ |
message_parameters_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 message parameter. | ❌ |
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. Maximum value: 900 seconds (15 minutes). | ✅ |
cooldown_session_key |
str |
Unique key used internally to implement cooldown. Must be unique for each step in your Workflow.. | ❌ |
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 Slack Notification 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,Pixel Color Count,Multi-Label Classification Model,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,Perspective Correction,Cosine Similarity,Polygon Zone Visualization,VLM as Classifier,Continue If,Dimension Collapse,Twilio SMS Notification,Image Slicer,Webhook Sink,OpenAI,Size Measurement,Detections Consensus,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
Slack Notification in version v1 has.
Bindings
-
input
slack_token(Union[secret,string]): Visit https://api.slack.com/tutorials/tracks/getting-a-token to find out how to generate a Slack API token..channel(string): Identifier of Slack channel..message_parameters(*): Data to be used in the message content..attachments(Union[bytes,string]): Attachments to be sent in the message, such as a csv file or jpg image..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. Maximum value: 900 seconds (15 minutes).
-
output
Example JSON definition of step Slack Notification in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/slack_notification@v1",
"slack_token": "$inputs.slack_token",
"channel": "$inputs.slack_channel_id",
"message": "During last 5 minutes detected {{ $parameters.num_instances }} instances",
"message_parameters": {
"predictions": "$steps.model.predictions",
"reference": "$inputs.reference_class_names"
},
"message_parameters_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"attachments": {
"report.csv": "$steps.csv_formatter.csv_content"
},
"fire_and_forget": "$inputs.fire_and_forget",
"disable_sink": false,
"cooldown_seconds": "$inputs.cooldown_seconds",
"cooldown_session_key": "session-1v73kdhfse"
}