Email Notification¶
Class: EmailNotificationBlockV1
Source: inference.core.workflows.core_steps.sinks.email_notification.v1.EmailNotificationBlockV1
The Email Notification block allows users to send email notifications as part of a workflow. It requires SMTP server setup to send the notification
Customizable Email Content¶
-
Subject: Set the subject field to define the subject line of the email.
-
Message: Use the message field to write the body content of the email. Message can be parametrised with data generated during workflow run. See Dynamic Parameters section.
-
Recipients (To, CC, BCC): Define who will receive the email using
receiver_email
,cc_receiver_email
, andbcc_receiver_email
properties. You can input a single email or a list.
Dynamic Parameters¶
Content of the message can be parametrised with Workflow execution outcomes. Take a look at the example message using dynamic parameters:
message = "This is example notification. Predicted classes: {{ $parameters.predicted_classes }}"
Message parameters are delivered by Workflows Execution Engine by setting proper data selectors in
message_parameters
field, for example:
message_parameters = {
"predicted_classes": "$steps.model.predictions"
}
Selecting data is not the only option - data may be processed in the block. In the example below we wish to
extract names of predicted classes. We can apply transformation for each parameter by setting
message_parameters_operations
:
message_parameters_operations = {
"predictions": [
{"type": "DetectionsPropertyExtract", "property_name": "class_name"}
]
}
As a result, in the e-mail that will be sent, you can expect:
This is example notification. Predicted classes: ["class_a", "class_b"].
Configuring SMTP server¶
Those are the parameters configuring SMTP server:
-
smtp_server
- hostname of the SMTP server to use -
sender_email
- e-mail account to be used as sender -
sender_email_password
- password for sender e-mail account -
smtp_port
- port of SMTP service - defaults to465
Block enforces SSL over SMTP.
Typical scenario for using custom SMTP server involves sending e-mail through Google SMTP server. Take a look at Google tutorial to configure the block properly.
GMAIL password will not work if 2-step verification is turned on
GMAIL users choosing custom SMTP server as e-mail service provider must configure application password to avoid problems with 2-step verification protected account. Beware that application password must be kept protected - we recommend sending the password in Workflow input and providing it each time by the caller, avoiding storing it in Workflow definition.
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.
Attachments¶
You may specify attachment files to be send with your e-mail. Attachments can only be generated in runtime by dedicated blocks (for instance CSV Formatter)
To include attachments, simply provide the attachment name and refer to other block outputs:
attachments = {
"report.pdf": "$steps.report_generator.output"
}
Async execution¶
Configure the fire_and_forget
property. Set it to True if you want the email to be sent in the background, allowing the
Workflow to proceed without waiting on e-mail 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 e-mail notifier 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/email_notification@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.. | ❌ |
subject |
str |
Subject of the message.. | ❌ |
sender_email |
str |
E-mail to be used to send the message.. | ✅ |
receiver_email |
Union[List[str], str] |
Destination e-mail address.. | ✅ |
message |
str |
Content of the message to be send.. | ❌ |
message_parameters |
Dict[str, Union[bool, float, int, str]] |
Data to be used inside the message.. | ✅ |
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]]] |
Preprocessing operations to be performed on message parameters.. | ❌ |
cc_receiver_email |
Optional[List[str], str] |
Destination e-mail address.. | ✅ |
bcc_receiver_email |
Optional[List[str], str] |
Destination e-mail address.. | ✅ |
smtp_server |
str |
Custom SMTP server to be used.. | ✅ |
sender_email_password |
str |
Sender e-mail password be used when authenticating to SMTP server.. | ✅ |
smtp_port |
int |
SMTP server port.. | ❌ |
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 until a 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 Email Notification
in version v1
.
- inputs:
Halo Visualization
,OpenAI
,Dimension Collapse
,Buffer
,Email Notification
,Instance Segmentation Model
,Trace Visualization
,Detections Consensus
,Line Counter
,Time in Zone
,Byte Tracker
,Pixelate Visualization
,Byte Tracker
,Webhook Sink
,Google Vision OCR
,Detection Offset
,Image Convert Grayscale
,YOLO-World Model
,Image Slicer
,CogVLM
,Reference Path Visualization
,Cache Set
,Byte Tracker
,Barcode Detection
,Path Deviation
,Detections Stabilizer
,Stability AI Inpainting
,Color Visualization
,Environment Secrets Store
,Clip Comparison
,Classification Label Visualization
,Multi-Label Classification Model
,Clip Comparison
,First Non Empty Or Default
,Detections Stitch
,JSON Parser
,Keypoint Detection Model
,Keypoint Detection Model
,Bounding Rectangle
,Data Aggregator
,Roboflow Dataset Upload
,Rate Limiter
,Bounding Box Visualization
,Detections Transformation
,Continue If
,Depth Estimation
,Detections Merge
,Perspective Correction
,Stitch Images
,Dominant Color
,Identify Outliers
,OCR Model
,CSV Formatter
,Stability AI Image Generation
,Model Comparison Visualization
,Blur Visualization
,Time in Zone
,Image Threshold
,Single-Label Classification Model
,Line Counter Visualization
,Absolute Static Crop
,Image Preprocessing
,Size Measurement
,Mask Visualization
,Expression
,VLM as Detector
,Ellipse Visualization
,Keypoint Visualization
,LMM For Classification
,Camera Focus
,Multi-Label Classification Model
,Template Matching
,Gaze Detection
,VLM as Detector
,SmolVLM2
,Moondream2
,Florence-2 Model
,Velocity
,Stitch OCR Detections
,Anthropic Claude
,Object Detection Model
,Detections Classes Replacement
,Line Counter
,Segment Anything 2 Model
,Single-Label Classification Model
,Qwen2.5-VL
,Object Detection Model
,Overlap Filter
,Model Monitoring Inference Aggregator
,Triangle Visualization
,Local File Sink
,Florence-2 Model
,Relative Static Crop
,OpenAI
,Dynamic Zone
,Twilio SMS Notification
,SIFT Comparison
,Cache Get
,Instance Segmentation Model
,Grid Visualization
,CLIP Embedding Model
,LMM
,Delta Filter
,Property Definition
,Google Gemini
,Roboflow Dataset Upload
,Path Deviation
,Pixel Color Count
,Polygon Visualization
,Polygon Zone Visualization
,Cosine Similarity
,Detections Filter
,VLM as Classifier
,Llama 3.2 Vision
,Background Color Visualization
,Dynamic Crop
,SIFT
,Corner Visualization
,Image Contours
,Label Visualization
,VLM as Classifier
,Image Slicer
,Distance Measurement
,Slack Notification
,Roboflow Custom Metadata
,Dot Visualization
,Circle Visualization
,QR Code Detection
,Image Blur
,Identify Changes
,SIFT Comparison
,Crop Visualization
,Camera Calibration
- outputs:
Line Counter Visualization
,Halo Visualization
,OpenAI
,Image Preprocessing
,Size Measurement
,Mask Visualization
,Email Notification
,Ellipse Visualization
,Keypoint Visualization
,Instance Segmentation Model
,Trace Visualization
,LMM For Classification
,Detections Consensus
,Multi-Label Classification Model
,Time in Zone
,Template Matching
,Gaze Detection
,Line Counter
,Pixelate Visualization
,Florence-2 Model
,Webhook Sink
,Google Vision OCR
,Single-Label Classification Model
,Segment Anything 2 Model
,Object Detection Model
,Anthropic Claude
,Line Counter
,YOLO-World Model
,Object Detection Model
,CogVLM
,Model Monitoring Inference Aggregator
,Triangle Visualization
,Reference Path Visualization
,Local File Sink
,Florence-2 Model
,OpenAI
,Cache Set
,Twilio SMS Notification
,Path Deviation
,SIFT Comparison
,Stability AI Inpainting
,Cache Get
,Color Visualization
,Instance Segmentation Model
,CLIP Embedding Model
,Classification Label Visualization
,LMM
,Multi-Label Classification Model
,Clip Comparison
,Detections Stitch
,Keypoint Detection Model
,Keypoint Detection Model
,Roboflow Dataset Upload
,Google Gemini
,Path Deviation
,Roboflow Dataset Upload
,Bounding Box Visualization
,Polygon Visualization
,Pixel Color Count
,Polygon Zone Visualization
,Perspective Correction
,Stability AI Image Generation
,Model Comparison Visualization
,Llama 3.2 Vision
,Background Color Visualization
,Dynamic Crop
,Blur Visualization
,Corner Visualization
,Label Visualization
,Time in Zone
,Dot Visualization
,Slack Notification
,Roboflow Custom Metadata
,Distance Measurement
,Circle Visualization
,Image Threshold
,Image Blur
,Crop Visualization
,Single-Label Classification Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Email Notification
in version v1
has.
Bindings
-
input
sender_email
(string
): E-mail to be used to send the message..receiver_email
(Union[string
,list_of_values
]): Destination e-mail address..message_parameters
(*
): Data to be used inside the message..cc_receiver_email
(Union[string
,list_of_values
]): Destination e-mail address..bcc_receiver_email
(Union[string
,list_of_values
]): Destination e-mail address..attachments
(Union[string
,bytes
]): Attachments.smtp_server
(string
): Custom SMTP server to be used..sender_email_password
(Union[string
,secret
]): Sender e-mail password be used when authenticating to SMTP server..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 until a follow-up notification can be sent. .
-
output
Example JSON definition of step Email Notification
in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/email_notification@v1",
"subject": "Workflow alert",
"sender_email": "[email protected]",
"receiver_email": "[email protected]",
"message": "During last 5 minutes detected {{ $parameters.num_instances }} instances",
"message_parameters": {
"predictions": "$steps.model.predictions",
"reference": "$inputs.reference_class_names"
},
"message_parameters_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"cc_receiver_email": "[email protected]",
"bcc_receiver_email": "[email protected]",
"attachments": {
"report.cvs": "$steps.csv_formatter.csv_content"
},
"smtp_server": "$inputs.smtp_server",
"sender_email_password": "$inputs.email_password",
"smtp_port": 465,
"fire_and_forget": "$inputs.fire_and_forget",
"disable_sink": false,
"cooldown_seconds": "$inputs.cooldown_seconds"
}