Email Notification¶
v2¶
Class: EmailNotificationBlockV2 (there are multiple versions of this block)
Source: inference.core.workflows.core_steps.sinks.email_notification.v2.EmailNotificationBlockV2
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
The Email Notification block allows users to send email notifications as part of a workflow.
Email Provider Options¶
This block supports two email delivery methods via a dropdown selector:
- Roboflow Managed API Key (Default) - No SMTP configuration needed. Emails are sent through Roboflow's proxy service:
- Simplified setup - just provide subject, message, and recipient
- Secure - your workflow API key is used for authentication
-
No SMTP server required
-
Custom SMTP - Use your own SMTP server:
- Full control over email delivery
- Requires SMTP server configuration (host, port, credentials)
- Supports CC and BCC recipients
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_emailproperties. 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"].
Using Custom SMTP Server¶
To use your own SMTP server, select "Custom SMTP" from the email_provider dropdown and configure
the following parameters:
-
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 sent with your e-mail. Attachments can be generated in runtime by dedicated blocks or from image outputs.
Supported attachment types: - CSV/Text files: From blocks like CSV Formatter - Images: Any image output from visualization blocks (automatically converted to JPEG) - Binary data: Any bytes output from compatible blocks
To include attachments, provide the attachment filename as the key and reference the block output:
attachments = {
"report.csv": "$steps.csv_formatter.csv_content",
"detection.jpg": "$steps.bounding_box_visualization.image"
}
Note: Image attachments are automatically converted to JPEG format. If the filename doesn't
include a .jpg or .jpeg extension, it will be added automatically.
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@v2to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
email_provider |
str |
Choose email delivery method: use Roboflow's managed service or configure your own SMTP server.. | ❌ |
subject |
str |
Subject of 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.. | ❌ |
sender_email |
str |
E-mail to be used to send the message.. | ✅ |
smtp_server |
str |
Custom SMTP server to be used.. | ✅ |
sender_email_password |
str |
Sender e-mail password be used when authenticating to SMTP server.. | ✅ |
cc_receiver_email |
Optional[List[str], str] |
CC e-mail address.. | ✅ |
bcc_receiver_email |
Optional[List[str], str] |
BCC e-mail address.. | ✅ |
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 v2.
- inputs:
Label Visualization,Blur Visualization,Background Color Visualization,Contrast Equalization,Detections Filter,Reference Path Visualization,Stability AI Outpainting,Image Slicer,Pixelate Visualization,Single-Label Classification Model,Clip Comparison,CSV Formatter,Perception Encoder Embedding Model,Seg Preview,Overlap Filter,Image Preprocessing,Rate Limiter,Color Visualization,SIFT Comparison,Email Notification,Cache Set,Dominant Color,Property Definition,Circle Visualization,Object Detection Model,QR Code Detection,Moondream2,VLM as Classifier,Model Monitoring Inference Aggregator,OCR Model,Absolute Static Crop,Path Deviation,LMM,Time in Zone,Morphological Transformation,Gaze Detection,Detections Consensus,Crop Visualization,OpenAI,Florence-2 Model,Barcode Detection,Classification Label Visualization,Byte Tracker,Segment Anything 2 Model,Cosine Similarity,SIFT Comparison,Time in Zone,YOLO-World Model,PTZ Tracking (ONVIF).md),Detection Offset,Icon Visualization,Detections Transformation,Distance Measurement,Data Aggregator,VLM as Detector,Line Counter Visualization,Grid Visualization,Halo Visualization,Size Measurement,Dynamic Zone,Twilio SMS Notification,Time in Zone,Detections Stitch,Llama 3.2 Vision,Image Blur,Slack Notification,Velocity,OpenAI,Byte Tracker,First Non Empty Or Default,Multi-Label Classification Model,Image Slicer,OpenAI,Environment Secrets Store,Dynamic Crop,Pixel Color Count,Detections Merge,Mask Visualization,Stitch Images,SIFT,Google Vision OCR,LMM For Classification,Keypoint Visualization,Bounding Box Visualization,SAM 3,Byte Tracker,SAM 3,Qwen2.5-VL,Object Detection Model,Path Deviation,Detections Combine,Anthropic Claude,Image Contours,Polygon Zone Visualization,Ellipse Visualization,Line Counter,Clip Comparison,Email Notification,Expression,Depth Estimation,Roboflow Dataset Upload,Image Convert Grayscale,CogVLM,Roboflow Custom Metadata,VLM as Detector,SAM 3,Multi-Label Classification Model,Buffer,Stitch OCR Detections,Keypoint Detection Model,Bounding Rectangle,Keypoint Detection Model,Line Counter,JSON Parser,Camera Calibration,CLIP Embedding Model,Polygon Visualization,Detections Classes Replacement,Cache Get,Identify Changes,Triangle Visualization,Template Matching,Roboflow Dataset Upload,Anthropic Claude,Model Comparison Visualization,Florence-2 Model,Corner Visualization,Google Gemini,Google Gemini,EasyOCR,Delta Filter,SmolVLM2,Stability AI Image Generation,Identify Outliers,QR Code Generator,Relative Static Crop,Dot Visualization,Dimension Collapse,Continue If,Local File Sink,Instance Segmentation Model,Stability AI Inpainting,Single-Label Classification Model,Camera Focus,Detections Stabilizer,Webhook Sink,Instance Segmentation Model,Image Threshold,OpenAI,Perspective Correction,VLM as Classifier,Trace Visualization - outputs:
Google Vision OCR,Label Visualization,LMM For Classification,Blur Visualization,Background Color Visualization,Keypoint Visualization,Bounding Box Visualization,Reference Path Visualization,Contrast Equalization,Stability AI Outpainting,Pixelate Visualization,Single-Label Classification Model,SAM 3,Perception Encoder Embedding Model,Seg Preview,Image Preprocessing,SAM 3,Color Visualization,SIFT Comparison,Object Detection Model,Path Deviation,Email Notification,Cache Set,Anthropic Claude,Circle Visualization,Object Detection Model,Polygon Zone Visualization,Ellipse Visualization,Line Counter,Email Notification,Clip Comparison,Moondream2,Model Monitoring Inference Aggregator,Path Deviation,LMM,Time in Zone,Roboflow Dataset Upload,Morphological Transformation,Gaze Detection,Detections Consensus,Crop Visualization,OpenAI,Florence-2 Model,SAM 3,Multi-Label Classification Model,Roboflow Custom Metadata,CogVLM,Classification Label Visualization,Keypoint Detection Model,Stitch OCR Detections,Segment Anything 2 Model,Keypoint Detection Model,Time in Zone,Line Counter,Polygon Visualization,YOLO-World Model,PTZ Tracking (ONVIF).md),CLIP Embedding Model,Detections Classes Replacement,Icon Visualization,Cache Get,Triangle Visualization,Template Matching,Roboflow Dataset Upload,Anthropic Claude,Model Comparison Visualization,Corner Visualization,Florence-2 Model,Distance Measurement,Google Gemini,Google Gemini,Line Counter Visualization,Halo Visualization,Size Measurement,Stability AI Image Generation,Dynamic Zone,QR Code Generator,Twilio SMS Notification,Time in Zone,Dot Visualization,Detections Stitch,Llama 3.2 Vision,Image Blur,Slack Notification,OpenAI,Local File Sink,Instance Segmentation Model,Multi-Label Classification Model,OpenAI,Stability AI Inpainting,Dynamic Crop,Single-Label Classification Model,Pixel Color Count,Webhook Sink,Instance Segmentation Model,Image Threshold,Perspective Correction,Mask Visualization,OpenAI,Trace Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Email Notification in version v2 has.
Bindings
-
input
receiver_email(Union[string,list_of_values]): Destination e-mail address..message_parameters(*): Data to be used inside the message..sender_email(string): E-mail to be used to send the message..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..cc_receiver_email(Union[string,list_of_values]): CC e-mail address..bcc_receiver_email(Union[string,list_of_values]): BCC e-mail address..attachments(Union[string,image,bytes]): Attachments.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 v2
{
"name": "<your_step_name_here>",
"type": "roboflow_core/email_notification@v2",
"email_provider": "Roboflow Managed API Key",
"subject": "Workflow alert",
"receiver_email": "receiver@gmail.com",
"message": "During last 5 minutes detected {{ $parameters.num_instances }} instances",
"message_parameters": {
"predictions": "$steps.model.predictions",
"reference": "$inputs.reference_class_names"
},
"message_parameters_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"sender_email": "sender@gmail.com",
"smtp_server": "$inputs.smtp_server",
"sender_email_password": "$inputs.email_password",
"cc_receiver_email": "cc-receiver@gmail.com",
"bcc_receiver_email": "bcc-receiver@gmail.com",
"smtp_port": 465,
"attachments": {
"report.cvs": "$steps.csv_formatter.csv_content"
},
"fire_and_forget": "$inputs.fire_and_forget",
"disable_sink": false,
"cooldown_seconds": "$inputs.cooldown_seconds"
}
v1¶
Class: EmailNotificationBlockV1 (there are multiple versions of this block)
Source: inference.core.workflows.core_steps.sinks.email_notification.v1.EmailNotificationBlockV1
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
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_emailproperties. 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@v1to 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:
Label Visualization,Blur Visualization,Background Color Visualization,Contrast Equalization,Detections Filter,Reference Path Visualization,Stability AI Outpainting,Image Slicer,Pixelate Visualization,Single-Label Classification Model,Clip Comparison,CSV Formatter,Perception Encoder Embedding Model,Seg Preview,Overlap Filter,Image Preprocessing,Rate Limiter,Color Visualization,SIFT Comparison,Email Notification,Cache Set,Dominant Color,Property Definition,Circle Visualization,Object Detection Model,QR Code Detection,Moondream2,VLM as Classifier,Model Monitoring Inference Aggregator,OCR Model,Absolute Static Crop,Path Deviation,LMM,Time in Zone,Morphological Transformation,Gaze Detection,Detections Consensus,Crop Visualization,OpenAI,Florence-2 Model,Barcode Detection,Classification Label Visualization,Byte Tracker,Segment Anything 2 Model,Cosine Similarity,SIFT Comparison,Time in Zone,YOLO-World Model,PTZ Tracking (ONVIF).md),Detection Offset,Icon Visualization,Detections Transformation,Distance Measurement,Data Aggregator,VLM as Detector,Line Counter Visualization,Grid Visualization,Halo Visualization,Size Measurement,Dynamic Zone,Twilio SMS Notification,Time in Zone,Detections Stitch,Llama 3.2 Vision,Image Blur,Slack Notification,Velocity,OpenAI,Byte Tracker,First Non Empty Or Default,Multi-Label Classification Model,Image Slicer,OpenAI,Environment Secrets Store,Dynamic Crop,Pixel Color Count,Detections Merge,Mask Visualization,Stitch Images,SIFT,Google Vision OCR,LMM For Classification,Keypoint Visualization,Bounding Box Visualization,SAM 3,Byte Tracker,SAM 3,Qwen2.5-VL,Object Detection Model,Path Deviation,Detections Combine,Anthropic Claude,Image Contours,Polygon Zone Visualization,Ellipse Visualization,Line Counter,Clip Comparison,Email Notification,Expression,Depth Estimation,Roboflow Dataset Upload,Image Convert Grayscale,CogVLM,Roboflow Custom Metadata,VLM as Detector,SAM 3,Multi-Label Classification Model,Buffer,Stitch OCR Detections,Keypoint Detection Model,Bounding Rectangle,Keypoint Detection Model,Line Counter,JSON Parser,Camera Calibration,CLIP Embedding Model,Polygon Visualization,Detections Classes Replacement,Cache Get,Identify Changes,Triangle Visualization,Template Matching,Roboflow Dataset Upload,Anthropic Claude,Model Comparison Visualization,Florence-2 Model,Corner Visualization,Google Gemini,Google Gemini,EasyOCR,Delta Filter,SmolVLM2,Stability AI Image Generation,Identify Outliers,QR Code Generator,Relative Static Crop,Dot Visualization,Dimension Collapse,Continue If,Local File Sink,Instance Segmentation Model,Stability AI Inpainting,Single-Label Classification Model,Camera Focus,Detections Stabilizer,Webhook Sink,Instance Segmentation Model,Image Threshold,OpenAI,Perspective Correction,VLM as Classifier,Trace Visualization - outputs:
Google Vision OCR,Label Visualization,LMM For Classification,Blur Visualization,Background Color Visualization,Keypoint Visualization,Bounding Box Visualization,Reference Path Visualization,Contrast Equalization,Stability AI Outpainting,Pixelate Visualization,Single-Label Classification Model,SAM 3,Perception Encoder Embedding Model,Seg Preview,Image Preprocessing,SAM 3,Color Visualization,SIFT Comparison,Object Detection Model,Path Deviation,Email Notification,Cache Set,Anthropic Claude,Circle Visualization,Object Detection Model,Polygon Zone Visualization,Ellipse Visualization,Line Counter,Email Notification,Clip Comparison,Moondream2,Model Monitoring Inference Aggregator,Path Deviation,LMM,Time in Zone,Roboflow Dataset Upload,Morphological Transformation,Gaze Detection,Detections Consensus,Crop Visualization,OpenAI,Florence-2 Model,SAM 3,Multi-Label Classification Model,Roboflow Custom Metadata,CogVLM,Classification Label Visualization,Keypoint Detection Model,Stitch OCR Detections,Segment Anything 2 Model,Keypoint Detection Model,Time in Zone,Line Counter,Polygon Visualization,YOLO-World Model,PTZ Tracking (ONVIF).md),CLIP Embedding Model,Detections Classes Replacement,Icon Visualization,Cache Get,Triangle Visualization,Template Matching,Roboflow Dataset Upload,Anthropic Claude,Model Comparison Visualization,Corner Visualization,Florence-2 Model,Distance Measurement,Google Gemini,Google Gemini,Line Counter Visualization,Halo Visualization,Size Measurement,Stability AI Image Generation,Dynamic Zone,QR Code Generator,Twilio SMS Notification,Time in Zone,Dot Visualization,Detections Stitch,Llama 3.2 Vision,Image Blur,Slack Notification,OpenAI,Local File Sink,Instance Segmentation Model,Multi-Label Classification Model,OpenAI,Stability AI Inpainting,Dynamic Crop,Single-Label Classification Model,Pixel Color Count,Webhook Sink,Instance Segmentation Model,Image Threshold,Perspective Correction,Mask Visualization,OpenAI,Trace Visualization
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": "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"
}