2026/05/20 - Amazon Connect Customer Profiles - 4 updated api methods
Changes Amazon Connect Customer Profiles adds support for item catalog columns in RecommenderSchema, ExcludedColumns in Create and Update Recommender to specify columns to exclude from training, and the ability to disable automatic retraining by setting TrainingFrequency to 0.
{'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}}
Creates a recommender
See also: AWS API Documentation
Request Syntax
client.create_recommender(
DomainName='string',
RecommenderName='string',
RecommenderRecipeName='recommended-for-you'|'similar-items'|'frequently-paired-items'|'popular-items'|'trending-now'|'personalized-ranking',
RecommenderConfig={
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
},
Description='string',
RecommenderSchemaName='string',
Tags={
'string': 'string'
}
)
string
[REQUIRED]
The unique name of the domain.
string
[REQUIRED]
The name of the recommender.
string
[REQUIRED]
The name of the recommeder recipe.
dict
The recommender configuration.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) -- [REQUIRED]
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) -- [REQUIRED]
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
string
The description of the domain object type.
string
The name of the recommender schema to use for this recommender. If not specified, the default schema is used.
dict
The tags used to organize, track, or control access for this resource.
(string) --
(string) --
dict
Response Syntax
{
'RecommenderArn': 'string',
'Tags': {
'string': 'string'
}
}
Response Structure
(dict) --
RecommenderArn (string) --
The ARN of the recommender
Tags (dict) --
The tags used to organize, track, or control access for this resource.
(string) --
(string) --
{'LatestRecommenderUpdate': {'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}},
'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}}
Retrieves a recommender.
See also: AWS API Documentation
Request Syntax
client.get_recommender(
DomainName='string',
RecommenderName='string',
TrainingMetricsCount=123
)
string
[REQUIRED]
The unique name of the domain.
string
[REQUIRED]
The name of the recommender.
integer
The number of training metrics to retrieve for the recommender.
dict
Response Syntax
{
'RecommenderName': 'string',
'RecommenderRecipeName': 'recommended-for-you'|'similar-items'|'frequently-paired-items'|'popular-items'|'trending-now'|'personalized-ranking',
'RecommenderSchemaName': 'string',
'RecommenderConfig': {
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
},
'Description': 'string',
'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
'LastUpdatedAt': datetime(2015, 1, 1),
'CreatedAt': datetime(2015, 1, 1),
'FailureReason': 'string',
'LatestRecommenderUpdate': {
'RecommenderConfig': {
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
},
'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
'CreatedAt': datetime(2015, 1, 1),
'LastUpdatedAt': datetime(2015, 1, 1),
'FailureReason': 'string'
},
'TrainingMetrics': [
{
'Time': datetime(2015, 1, 1),
'Metrics': {
'string': 123.0
}
},
],
'Tags': {
'string': 'string'
}
}
Response Structure
(dict) --
RecommenderName (string) --
The name of the recommender.
RecommenderRecipeName (string) --
The name of the recipe used by the recommender to generate recommendations.
RecommenderSchemaName (string) --
The name of the recommender schema associated with this recommender.
RecommenderConfig (dict) --
The configuration settings for the recommender, including parameters and settings that define its behavior.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) --
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) --
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
Description (string) --
A detailed description of the recommender providing information about its purpose and functionality.
Status (string) --
The current status of the recommender, indicating whether it is active, creating, updating, or in another state.
LastUpdatedAt (datetime) --
The timestamp of when the recommender was edited.
CreatedAt (datetime) --
The timestamp of when the recommender was created.
FailureReason (string) --
If the recommender fails, provides the reason for the failure.
LatestRecommenderUpdate (dict) --
Information about the most recent update performed on the recommender, including status and timestamp.
RecommenderConfig (dict) --
The updated configuration settings applied to the recommender during this update.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) --
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) --
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
Status (string) --
The current status of the recommender update operation.
CreatedAt (datetime) --
The timestamp when this recommender update was initiated.
LastUpdatedAt (datetime) --
The timestamp of when the recommender was edited.
FailureReason (string) --
If the update operation failed, provides the reason for the failure.
TrainingMetrics (list) --
A set of metrics that provide information about the recommender's training performance and accuracy.
(dict) --
Contains metrics and performance indicators from the training of a recommender model.
Time (datetime) --
The timestamp when these training metrics were recorded.
Metrics (dict) --
A collection of performance metrics and statistics from the training process.
(string) --
(float) --
Tags (dict) --
The tags used to organize, track, or control access for this resource.
(string) --
(string) --
{'Recommenders': {'LatestRecommenderUpdate': {'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}},
'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}}}
Returns a list of recommenders in the specified domain.
See also: AWS API Documentation
Request Syntax
client.list_recommenders(
DomainName='string',
MaxResults=123,
NextToken='string'
)
string
[REQUIRED]
The unique name of the domain.
integer
The maximum number of recommenders to return in the response. The default value is 100.
string
A token received from a previous ListRecommenders call to retrieve the next page of results.
dict
Response Syntax
{
'NextToken': 'string',
'Recommenders': [
{
'RecommenderName': 'string',
'RecipeName': 'recommended-for-you'|'similar-items'|'frequently-paired-items'|'popular-items'|'trending-now'|'personalized-ranking',
'RecommenderSchemaName': 'string',
'RecommenderConfig': {
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
},
'CreatedAt': datetime(2015, 1, 1),
'Description': 'string',
'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
'LastUpdatedAt': datetime(2015, 1, 1),
'Tags': {
'string': 'string'
},
'FailureReason': 'string',
'LatestRecommenderUpdate': {
'RecommenderConfig': {
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
},
'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
'CreatedAt': datetime(2015, 1, 1),
'LastUpdatedAt': datetime(2015, 1, 1),
'FailureReason': 'string'
}
},
]
}
Response Structure
(dict) --
NextToken (string) --
A token to retrieve the next page of results. Null if there are no more results to retrieve.
Recommenders (list) --
A list of recommenders and their properties in the specified domain.
(dict) --
Provides a summary of a recommender's configuration and current state.
RecommenderName (string) --
The name of the recommender.
RecipeName (string) --
The name of the recipe used by this recommender.
RecommenderSchemaName (string) --
The name of the recommender schema associated with this recommender.
RecommenderConfig (dict) --
The configuration settings applied to this recommender.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) --
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) --
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
CreatedAt (datetime) --
The timestamp when the recommender was created.
Description (string) --
A description of the recommender's purpose and characteristics.
Status (string) --
The current operational status of the recommender.
LastUpdatedAt (datetime) --
The timestamp of when the recommender was edited.
Tags (dict) --
The tags used to organize, track, or control access for this resource.
(string) --
(string) --
FailureReason (string) --
If the recommender is in a failed state, provides the reason for the failure.
LatestRecommenderUpdate (dict) --
Information about the most recent update performed on the recommender, including its status and timing.
RecommenderConfig (dict) --
The updated configuration settings applied to the recommender during this update.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) --
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) --
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
Status (string) --
The current status of the recommender update operation.
CreatedAt (datetime) --
The timestamp when this recommender update was initiated.
LastUpdatedAt (datetime) --
The timestamp of when the recommender was edited.
FailureReason (string) --
If the update operation failed, provides the reason for the failure.
{'RecommenderConfig': {'ExcludedColumns': {'string': ['string']}}}
Updates the properties of an existing recommender, allowing you to modify its configuration and description.
See also: AWS API Documentation
Request Syntax
client.update_recommender(
DomainName='string',
RecommenderName='string',
Description='string',
RecommenderConfig={
'EventsConfig': {
'EventParametersList': [
{
'EventType': 'string',
'EventValueThreshold': 123.0,
'EventWeight': 123.0
},
]
},
'TrainingFrequency': 123,
'InferenceConfig': {
'MinProvisionedTPS': 123
},
'IncludedColumns': {
'string': [
'string',
]
},
'ExcludedColumns': {
'string': [
'string',
]
}
}
)
string
[REQUIRED]
The unique name of the domain.
string
[REQUIRED]
The name of the recommender to update.
string
The new description to assign to the recommender.
dict
The new configuration settings to apply to the recommender, including updated parameters and settings that define its behavior.
EventsConfig (dict) --
Configuration settings for how the recommender processes and uses events.
EventParametersList (list) -- [REQUIRED]
A list of event parameters configurations that specify how different event types should be handled.
(dict) --
Configuration parameters for events in the personalization system.
EventType (string) -- [REQUIRED]
The type of event being tracked (e.g., 'click', 'purchase', 'view').
EventValueThreshold (float) --
The minimum value threshold that an event must meet to be considered valid.
EventWeight (float) --
The weight of the event type. A higher weight means higher importance of the event type for the created solution.
TrainingFrequency (integer) --
How often the recommender should retrain its model with new data. If set to 0, automatic retraining will not be enabled.
InferenceConfig (dict) --
Configuration settings for how the recommender handles inference requests.
MinProvisionedTPS (integer) --
The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
IncludedColumns (dict) --
A map of dataset type to a list of column names to train on. The _webAnalytics and _catalogItem keys are supported. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included in training and do not need to be specified: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with ExcludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
ExcludedColumns (dict) --
A map of dataset type to a list of column names to exclude from training. The _webAnalytics and _catalogItem keys are supported. The column names must be valid columns defined in the recommender schema. All columns in the schema except the listed columns will be used for training. The following columns are mandatory and cannot be excluded: Item.Id, EventTimestamp, and EventType for _webAnalytics; Id for _catalogItem. Mutually exclusive with IncludedColumns — both cannot be specified in the same request.
(string) --
(list) --
(string) --
dict
Response Syntax
{
'RecommenderName': 'string'
}
Response Structure
(dict) --
RecommenderName (string) --
The name of the recommender that was updated.