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:
Multi-Label Classification Model
,Dimension Collapse
,Classification Label Visualization
,Background Color Visualization
,Dynamic Crop
,Clip Comparison
,Segment Anything 2 Model
,Absolute Static Crop
,LMM For Classification
,Image Blur
,Roboflow Dataset Upload
,CogVLM
,OCR Model
,Circle Visualization
,Clip Comparison
,Template Matching
,SIFT Comparison
,Multi-Label Classification Model
,Path Deviation
,OpenAI
,Stitch OCR Detections
,Detections Stitch
,QR Code Detection
,Pixel Color Count
,Detections Stabilizer
,Path Deviation
,Line Counter
,VLM as Classifier
,Time in Zone
,Model Comparison Visualization
,Stitch Images
,Keypoint Detection Model
,Bounding Box Visualization
,Moondream2
,Continue If
,Slack Notification
,Color Visualization
,LMM
,Llama 3.2 Vision
,Instance Segmentation Model
,VLM as Detector
,Time in Zone
,Byte Tracker
,Detections Filter
,YOLO-World Model
,Barcode Detection
,Grid Visualization
,SmolVLM2
,Stability AI Inpainting
,Cosine Similarity
,Keypoint Detection Model
,Dot Visualization
,Google Gemini
,Detections Merge
,CLIP Embedding Model
,Dynamic Zone
,Size Measurement
,Property Definition
,Roboflow Custom Metadata
,Data Aggregator
,VLM as Classifier
,Detections Classes Replacement
,Gaze Detection
,Object Detection Model
,Corner Visualization
,Roboflow Dataset Upload
,Image Preprocessing
,Image Slicer
,Byte Tracker
,Line Counter
,Label Visualization
,Bounding Rectangle
,Identify Outliers
,Single-Label Classification Model
,First Non Empty Or Default
,Webhook Sink
,Cache Get
,Mask Visualization
,Delta Filter
,Google Vision OCR
,Twilio SMS Notification
,Buffer
,Detection Offset
,Model Monitoring Inference Aggregator
,Florence-2 Model
,Stability AI Image Generation
,Cache Set
,Identify Changes
,Crop Visualization
,JSON Parser
,VLM as Detector
,Velocity
,OpenAI
,Dominant Color
,Perspective Correction
,SIFT Comparison
,Relative Static Crop
,Ellipse Visualization
,Reference Path Visualization
,Anthropic Claude
,Blur Visualization
,Pixelate Visualization
,Email Notification
,Expression
,CSV Formatter
,Keypoint Visualization
,Camera Focus
,Single-Label Classification Model
,Qwen2.5-VL
,Florence-2 Model
,Detections Transformation
,Image Convert Grayscale
,Image Threshold
,Trace Visualization
,Detections Consensus
,Polygon Visualization
,Triangle Visualization
,Environment Secrets Store
,Halo Visualization
,Polygon Zone Visualization
,Local File Sink
,Rate Limiter
,Instance Segmentation Model
,Camera Calibration
,SIFT
,Image Contours
,Line Counter Visualization
,Image Slicer
,Byte Tracker
,Distance Measurement
,Object Detection Model
- outputs:
Multi-Label Classification Model
,Single-Label Classification Model
,Classification Label Visualization
,Webhook Sink
,Background Color Visualization
,Dynamic Crop
,Cache Get
,Mask Visualization
,Clip Comparison
,Twilio SMS Notification
,Google Vision OCR
,Segment Anything 2 Model
,Model Monitoring Inference Aggregator
,Stability AI Image Generation
,LMM For Classification
,Florence-2 Model
,Image Blur
,Cache Set
,Roboflow Dataset Upload
,CogVLM
,Line Counter
,Circle Visualization
,Crop Visualization
,Template Matching
,Multi-Label Classification Model
,Path Deviation
,OpenAI
,Detections Stitch
,OpenAI
,Pixel Color Count
,Path Deviation
,Line Counter
,Time in Zone
,Model Comparison Visualization
,Bounding Box Visualization
,Keypoint Detection Model
,SIFT Comparison
,Perspective Correction
,Color Visualization
,Slack Notification
,Ellipse Visualization
,Reference Path Visualization
,Blur Visualization
,Pixelate Visualization
,Anthropic Claude
,Email Notification
,LMM
,Llama 3.2 Vision
,Instance Segmentation Model
,Keypoint Visualization
,Time in Zone
,Single-Label Classification Model
,Florence-2 Model
,YOLO-World Model
,Trace Visualization
,Image Threshold
,Polygon Visualization
,Triangle Visualization
,Detections Consensus
,Keypoint Detection Model
,Stability AI Inpainting
,Halo Visualization
,Dot Visualization
,Polygon Zone Visualization
,Google Gemini
,CLIP Embedding Model
,Local File Sink
,Size Measurement
,Instance Segmentation Model
,Roboflow Custom Metadata
,Gaze Detection
,Object Detection Model
,Corner Visualization
,Line Counter Visualization
,Roboflow Dataset Upload
,Image Preprocessing
,Label Visualization
,Distance Measurement
,Object Detection 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[list_of_values
,string
]): Destination e-mail address..message_parameters
(*
): Data to be used inside the message..cc_receiver_email
(Union[list_of_values
,string
]): Destination e-mail address..bcc_receiver_email
(Union[list_of_values
,string
]): 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": "sender@gmail.com",
"receiver_email": "receiver@gmail.com",
"message": "During last 5 minutes detected {{ $parameters.num_instances }} instances",
"message_parameters": {
"predictions": "$steps.model.predictions",
"reference": "$inputs.reference_class_names"
},
"message_parameters_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"cc_receiver_email": "cc-receiver@gmail.com",
"bcc_receiver_email": "bcc-receiver@gmail.com",
"attachments": {
"report.cvs": "$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"
}