Slack Notification¶
Class: SlackNotificationBlockV1
Source: inference.core.workflows.core_steps.sinks.slack.notification.v1.SlackNotificationBlockV1
Send notifications to Slack channels with customizable message content featuring dynamic workflow data parameters, file attachments, cooldown throttling using cache-based session tracking, and optional async background execution for team alerts, monitoring, and real-time communication workflows.
How This Block Works¶
This block sends notifications to Slack channels using the Slack Web API, integrating workflow execution results into message content. The block:
- Checks if the sink is disabled via
disable_sinkflag (if disabled, returns immediately without sending) - Generates a cache key for cooldown tracking using the Slack token hash and
cooldown_session_key(unique per workflow step) - Validates cooldown period by checking cache for the last notification timestamp (if enabled, throttles notifications within
cooldown_secondsof the last sent notification, returning throttling status) - Creates or retrieves a Slack WebClient instance for the provided token (caches clients by token hash for efficiency)
- Formats the message by processing dynamic parameters (replaces placeholders like
{{ '{{' }} $parameters.parameter_name {{ '}}' }}with actual workflow data frommessage_parameters) - Applies optional UQL operations to transform parameter values before insertion (e.g., extract class names from detections, calculate metrics, filter data) using
message_parameters_operations - Sends the notification to the specified Slack channel:
- Without attachments: Uses
chat_postMessageAPI to send text-only messages - With attachments: Uses
files_upload_v2API to upload files with the message as an initial comment - Updates the cache with the current notification timestamp (expires after 15 minutes)
- Executes synchronously or asynchronously based on
fire_and_forgetsetting: - Synchronous mode (
fire_and_forget=False): Waits for Slack API call completion, returns actual error status for debugging - Asynchronous mode (
fire_and_forget=True): Sends notification in background task, workflow continues immediately, error status always False - Returns status outputs indicating success, throttling, or errors (includes Slack API error details when available)
The block supports dynamic message content through parameter placeholders that are replaced with workflow data at runtime. Message parameters can be raw workflow outputs or transformed using UQL operations (e.g., extract properties, calculate counts, filter values). Attachments are sourced from other workflow blocks that produce string or binary content (e.g., CSV Formatter for reports, image outputs for visualizations). Cooldown prevents notification spam by enforcing minimum time between sends using cache-based tracking with session keys, enabling per-step throttling in distributed or multi-instance environments.
Requirements¶
Slack API Token: Requires a Slack API token (Bot Token or User Token) with appropriate permissions:
- Token must have chat:write scope to send messages to channels
- Token must have files:write scope if using attachments
- Token can be provided via workflow inputs (recommended for security) or stored in workflow definitions
- View Slack API documentation or Roboflow Blog guide for token generation instructions
Channel Configuration: Requires a valid Slack channel identifier (channel ID or channel name starting with #). The bot or user associated with the token must be a member of the channel.
Cooldown Session Key: The cooldown_session_key must be unique for each Slack Notification step in your workflow to enable proper per-step cooldown tracking. The cooldown mechanism uses cache-based storage with a 15-minute expiration time, and cooldown seconds must be between 0 and 900 (15 minutes).
Common Use Cases¶
- Team Alert Notifications: Send Slack alerts to team channels when specific conditions are detected (e.g., alert security team when unauthorized objects detected, notify operations when anomaly detected, send alerts when detection counts exceed thresholds), enabling real-time team collaboration and incident response
- Workflow Execution Updates: Send Slack notifications about workflow execution status and results (e.g., notify team when batch processing completes, send daily summary reports, alert about workflow failures), enabling team visibility into automated processes
- Detection Summaries: Send Slack messages with detection results and aggregated statistics (e.g., share lists of detected objects, send counts and classifications, include detection confidence summaries), enabling stakeholders to stay informed about workflow outputs via team communication channels
- Report Distribution: Upload and share generated reports and data exports via Slack (e.g., attach CSV reports from CSV Formatter, share exported detection data, include formatted analytics summaries), enabling automated data distribution through team channels
- Real-Time Monitoring: Send continuous monitoring updates and status notifications (e.g., notify about system health issues, send periodic performance metrics, alert about processing milestones), enabling real-time visibility for operational monitoring
- Multi-Channel Broadcasting: Send notifications to different Slack channels based on workflow conditions or routing logic (e.g., send alerts to different channels per detection type, route notifications by severity level, distribute reports to department-specific channels), enabling targeted communication and notification routing
Connecting to Other Blocks¶
This block receives data from workflow steps and sends Slack notifications:
- After detection or analysis blocks (e.g., Object Detection, Instance Segmentation, Classification) to send alerts or summaries when objects are detected, classifications are made, or thresholds are exceeded, enabling real-time team notifications and collaboration
- After data processing blocks (e.g., Expression, Property Definition, Detections Filter) to include computed metrics, transformed data, or filtered results in Slack notifications, enabling customized reporting with processed data in team channels
- After formatter blocks (e.g., CSV Formatter) to attach formatted reports and exports to Slack messages, enabling automated distribution of structured data and analytics through team communication channels
- In conditional workflows (e.g., Continue If) to send notifications only when specific conditions are met, enabling event-driven alerting and team communication
- After aggregation blocks (e.g., Data Aggregator) to send periodic analytics summaries and statistical reports to Slack, enabling scheduled team updates and trend analysis
- In monitoring workflows to send status updates, error notifications, or health check reports to team channels, enabling automated system monitoring and incident management through Slack
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 |
Slack API token (Bot Token or User Token) for authenticating with Slack API. Token must have 'chat:write' scope to send messages and 'files:write' scope if using attachments. Token is marked as private for security. Recommended to provide via workflow inputs using SECRET_KIND selectors rather than storing in workflow definitions. Generate tokens via Slack API apps or workspace administration. See Slack API documentation or Roboflow Blog guide for setup instructions.. | ✅ |
channel |
str |
Slack channel identifier where the notification will be sent. Can be a channel ID (e.g., 'C1234567890') or channel name starting with '#' (e.g., '#alerts', '#general'). The bot or user associated with the Slack token must be a member of the channel. Channel names are automatically converted to channel IDs by the Slack API.. | ✅ |
message |
str |
Message content to send to the Slack channel (plain text). Supports dynamic parameters using placeholder syntax: {{ '{{' }} $parameters.parameter_name {{ '}}' }}. Placeholders are replaced with values from message_parameters at runtime. Message can be multi-line text. If attachments are provided, this message becomes the initial comment attached to the file upload. Example: 'Detected {{ '{{' }} $parameters.num_objects {{ '}}' }} objects. Classes: {{ '{{' }} $parameters.classes {{ '}}' }}.'. | ❌ |
message_parameters |
Dict[str, Union[bool, float, int, str]] |
Dictionary mapping parameter names (used in message placeholders) to workflow data sources. Keys are parameter names referenced in message as {{ '{{' }} $parameters.key {{ '}}' }}, values are selectors to workflow step outputs or direct values. These values are substituted into message placeholders at runtime. Can optionally use message_parameters_operations to transform parameter values before substitution.. | ✅ |
message_parameters_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]]] |
Optional dictionary mapping parameter names (from message_parameters) to UQL operation chains that transform parameter values before inserting them into the message. Operations are applied in sequence (e.g., extract class names from detections, calculate counts, filter values). Keys must match parameter names in message_parameters. Leave empty or omit parameters that don't need transformation.. | ❌ |
fire_and_forget |
bool |
Execution mode: True for asynchronous background sending (workflow continues immediately, error_status always False, faster execution), False for synchronous sending (waits for Slack API call completion, returns actual error status for debugging). Set to False during development and debugging to catch Slack API errors. Set to True in production for faster workflow execution when notification delivery timing is not critical.. | ✅ |
disable_sink |
bool |
Flag to disable Slack notification sending at runtime. When True, the block skips sending notification and returns a disabled message. Useful for conditional notification control via workflow inputs (e.g., allow callers to disable notifications for testing, enable/disable based on configuration). Set via workflow inputs for runtime control.. | ✅ |
cooldown_seconds |
int |
Minimum seconds between consecutive Slack notifications to prevent notification spam. Defaults to 5 seconds. Set to 0 to disable cooldown (no throttling). Must be between 0 and 900 (15 minutes). During cooldown period, the block returns throttling_status=True and skips sending. Cooldown is tracked per step using cooldown_session_key with cache-based storage (15-minute expiration). Each Slack Notification step in a workflow should have a unique cooldown_session_key for proper per-step tracking.. | ✅ |
cooldown_session_key |
str |
Unique identifier for this Slack Notification step's cooldown tracking session. Must be unique for each Slack Notification step in your workflow to enable proper per-step cooldown isolation. Used with the Slack token hash to create a cache key for tracking the last notification timestamp. In distributed or multi-instance environments, this ensures cooldown works correctly per step. Typically auto-generated or provided as a workflow input.. | ❌ |
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:
Google Gemini,Mask Visualization,Dimension Collapse,VLM As Detector,Identify Outliers,Single-Label Classification Model,Image Blur,Depth Estimation,Byte Tracker,Cache Set,Clip Comparison,Crop Visualization,SmolVLM2,Property Definition,Data Aggregator,Model Monitoring Inference Aggregator,Cache Get,Multi-Label Classification Model,Anthropic Claude,Keypoint Visualization,Google Gemini,Seg Preview,SORT Tracker,OpenAI,Keypoint Detection Model,Stability AI Inpainting,Perspective Correction,YOLO-World Model,Reference Path Visualization,Trace Visualization,Buffer,Grid Visualization,Polygon Visualization,Polygon Zone Visualization,Stitch OCR Detections,PTZ Tracking (ONVIF),JSON Parser,Stitch OCR Detections,CLIP Embedding Model,Continue If,SAM 3,SIFT Comparison,Detections Combine,Image Slicer,Dynamic Crop,Qwen3-VL,Byte Tracker,Distance Measurement,Image Threshold,OpenAI,Email Notification,SAM 3,Line Counter,Webhook Sink,Instance Segmentation Model,Pixel Color Count,Camera Focus,Roboflow Dataset Upload,Qwen2.5-VL,Time in Zone,Detection Offset,Keypoint Detection Model,Blur Visualization,Contrast Equalization,QR Code Generator,Dot Visualization,Background Subtraction,Roboflow Custom Metadata,Bounding Box Visualization,S3 Sink,Relative Static Crop,Twilio SMS/MMS Notification,Polygon Visualization,Camera Calibration,Detections Classes Replacement,Detections Transformation,Overlap Filter,Email Notification,Circle Visualization,Single-Label Classification Model,Object Detection Model,Detections Merge,Anthropic Claude,Path Deviation,Pixelate Visualization,Google Vision OCR,Google Gemini,Detections Filter,Path Deviation,Image Convert Grayscale,Florence-2 Model,EasyOCR,GLM-OCR,VLM As Detector,Multi-Label Classification Model,Dominant Color,Semantic Segmentation Model,Florence-2 Model,Corner Visualization,Detections Stabilizer,OC-SORT Tracker,Delta Filter,VLM As Classifier,Clip Comparison,VLM As Classifier,Detections Consensus,Triangle Visualization,Stitch Images,Expression,Llama 3.2 Vision,Stability AI Image Generation,Halo Visualization,QR Code Detection,CSV Formatter,CogVLM,Motion Detection,Detections Stitch,Detections List Roll-Up,Time in Zone,Object Detection Model,Template Matching,Identify Changes,Halo Visualization,Size Measurement,Label Visualization,Bounding Rectangle,Perception Encoder Embedding Model,Anthropic Claude,Cosine Similarity,Instance Segmentation Model,Line Counter Visualization,Slack Notification,Time in Zone,Moondream2,Stability AI Outpainting,Heatmap Visualization,Ellipse Visualization,LMM For Classification,First Non Empty Or Default,Icon Visualization,OpenAI,SIFT,Background Color Visualization,SIFT Comparison,Text Display,Velocity,Gaze Detection,LMM,Qwen3.5-VL,Image Contours,Barcode Detection,Mask Area Measurement,Dynamic Zone,Detection Event Log,Roboflow Dataset Upload,Color Visualization,Twilio SMS Notification,Absolute Static Crop,OpenAI,Byte Tracker,OCR Model,ByteTrack Tracker,SAM 3,Segment Anything 2 Model,Model Comparison Visualization,Rate Limiter,Camera Focus,Line Counter,Image Slicer,Classification Label Visualization,Image Preprocessing,Local File Sink,Morphological Transformation,Environment Secrets Store - outputs:
Google Gemini,Mask Visualization,Single-Label Classification Model,Image Blur,Cache Set,Depth Estimation,Crop Visualization,Model Monitoring Inference Aggregator,Cache Get,Multi-Label Classification Model,Anthropic Claude,Keypoint Visualization,Google Gemini,Seg Preview,OpenAI,Keypoint Detection Model,Stability AI Inpainting,Perspective Correction,YOLO-World Model,Reference Path Visualization,Trace Visualization,Polygon Visualization,Polygon Zone Visualization,Stitch OCR Detections,PTZ Tracking (ONVIF),Stitch OCR Detections,CLIP Embedding Model,SAM 3,SIFT Comparison,Dynamic Crop,Distance Measurement,Image Threshold,SAM 3,Email Notification,OpenAI,Line Counter,Webhook Sink,Instance Segmentation Model,Pixel Color Count,Roboflow Dataset Upload,Keypoint Detection Model,Time in Zone,Blur Visualization,Contrast Equalization,QR Code Generator,Dot Visualization,Roboflow Custom Metadata,Bounding Box Visualization,S3 Sink,Polygon Visualization,Twilio SMS/MMS Notification,Camera Calibration,Detections Classes Replacement,Email Notification,Circle Visualization,Single-Label Classification Model,Object Detection Model,Anthropic Claude,Path Deviation,Pixelate Visualization,Google Vision OCR,Google Gemini,Path Deviation,Florence-2 Model,GLM-OCR,Multi-Label Classification Model,Florence-2 Model,Corner Visualization,Clip Comparison,Detections Consensus,Triangle Visualization,Llama 3.2 Vision,Stability AI Image Generation,Halo Visualization,CogVLM,Motion Detection,Detections Stitch,Time in Zone,Object Detection Model,Template Matching,Halo Visualization,Size Measurement,Label Visualization,Perception Encoder Embedding Model,Anthropic Claude,Instance Segmentation Model,Line Counter Visualization,Slack Notification,Time in Zone,Moondream2,Stability AI Outpainting,Heatmap Visualization,Ellipse Visualization,LMM For Classification,Icon Visualization,OpenAI,Background Color Visualization,Text Display,Gaze Detection,LMM,Dynamic Zone,Roboflow Dataset Upload,Color Visualization,Twilio SMS Notification,OpenAI,SAM 3,Segment Anything 2 Model,Model Comparison Visualization,Line Counter,Classification Label Visualization,Image Preprocessing,Local File Sink,Morphological Transformation
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]): Slack API token (Bot Token or User Token) for authenticating with Slack API. Token must have 'chat:write' scope to send messages and 'files:write' scope if using attachments. Token is marked as private for security. Recommended to provide via workflow inputs using SECRET_KIND selectors rather than storing in workflow definitions. Generate tokens via Slack API apps or workspace administration. See Slack API documentation or Roboflow Blog guide for setup instructions..channel(string): Slack channel identifier where the notification will be sent. Can be a channel ID (e.g., 'C1234567890') or channel name starting with '#' (e.g., '#alerts', '#general'). The bot or user associated with the Slack token must be a member of the channel. Channel names are automatically converted to channel IDs by the Slack API..message_parameters(*): Dictionary mapping parameter names (used in message placeholders) to workflow data sources. Keys are parameter names referenced in message as {{ '{{' }} $parameters.key {{ '}}' }}, values are selectors to workflow step outputs or direct values. These values are substituted into message placeholders at runtime. Can optionally use message_parameters_operations to transform parameter values before substitution..attachments(Union[bytes,string]): Optional dictionary mapping attachment filenames to workflow step outputs that provide file content. Keys are the attachment filenames (e.g., 'report.csv', 'image.jpg'), values are selectors to blocks that output string or binary content (e.g., CSV Formatter outputs, image data, generated reports). Files are uploaded to Slack using files_upload_v2 API, and the message becomes the initial comment. Leave empty if no attachments are needed. Requires 'files:write' scope on the Slack token..fire_and_forget(boolean): Execution mode: True for asynchronous background sending (workflow continues immediately, error_status always False, faster execution), False for synchronous sending (waits for Slack API call completion, returns actual error status for debugging). Set to False during development and debugging to catch Slack API errors. Set to True in production for faster workflow execution when notification delivery timing is not critical..disable_sink(boolean): Flag to disable Slack notification sending at runtime. When True, the block skips sending notification and returns a disabled message. Useful for conditional notification control via workflow inputs (e.g., allow callers to disable notifications for testing, enable/disable based on configuration). Set via workflow inputs for runtime control..cooldown_seconds(integer): Minimum seconds between consecutive Slack notifications to prevent notification spam. Defaults to 5 seconds. Set to 0 to disable cooldown (no throttling). Must be between 0 and 900 (15 minutes). During cooldown period, the block returns throttling_status=True and skips sending. Cooldown is tracked per step using cooldown_session_key with cache-based storage (15-minute expiration). Each Slack Notification step in a workflow should have a unique cooldown_session_key for proper per-step tracking..
-
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"
}