API Methods 3.x
Alerts
Alert Rule
Alert rule object contains the below fields.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the alert rule. |
name | str | - | Unique name of the alert rule. |
model | - | Details of the model. | |
project | - | Details of the project to which the dataset belongs. | |
baseline | Optional[Baseline] | None | Details of the baseline for the alert. |
segment | Optional[Segment] | None | Details of segment for the alert. |
priority | Union[str, Priority] | - | To set the priority for the alert rule. Select from: 1. Priority.LOW 2. Priority.MEDIUM 3. Priority.HIGH. |
compare_to | Union[str, CompareTo] | - | Select from the two: 1. CompareTo.RAW_VALUE 2. CompareTo.TIME_PERIOD |
metric_id | Union[str, UUID] | - | Type of alert metric UUID or string denoting metric name. |
critical_threshold | float | - | Threshold value to crossing which a critical level severity alert will be triggered. |
condition | Union[str, AlertCondition] | - | Select from: 1. AlertCondition.LESSER 2. AlertCondition.GREATER |
bin_size | Union[str, BinSize] | - | Size of the bin for alert rule. |
columns | Optional[List[str]] | None | List of column names on which alert rule is to be created. It can take ['ANY'] to check for all columns. |
baseline_id | Optional[UUID] | None | UUID of the baseline for the alert. |
segment_id | Optional[UUID] | None | UUID of segment for the alert |
compare_bin_delta | Optional[int] | None | Number of bin_size to compare the metric to a previous time period. |
warning_threshold | Optional[float] | None | Threshold value to crossing which a warning level severity alert will be triggered. |
created_at | datetime | - | Time at which alert rule was created. |
updated_at | datetime | - | Latest time at which alert rule was updated. |
evaluation_delay | int | 0 | To introduce a delay in the evaluation of the alert, specifying the duration in hours. The delay period must not exceed one year(8760 hours). |
constructor()
Initialise a new alert rule on Fiddler Platform.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Unique name of the model |
model_id | UUID | - | Details of the model. |
metric_id | Union[str, UUID] | - | Type of alert metric UUID or enum. |
columns | Optional[List[str]] | None | List of column names on which alert rule is to be created. It can take ['ANY'] to check for all columns. |
baseline_id | Optional[UUID] | None | UUID of the baseline for the alert. |
segment_id | Optional[UUID] | None | UUID of the segment for the alert. |
priority | Union[str, Priority] | - | To set the priority for the alert rule. Select from: 1. Priority.LOW 2. Priority.MEDIUM 3. Priority.HIGH. |
compare_to | Union[str, CompareTo] | - | Select from the two: 1. CompareTo.RAW_VALUE (absolute alert) 2. CompareTo.TIME_PERIOD (relative alert) |
compare_bin_delta | Optional[int] | None | Compare the metric to a previous time period in units of bin_size. |
warning_threshold | Optional[float] | None | Threshold value to crossing which a warning level severity alert will be triggered. |
critical_threshold | float | - | Threshold value to crossing which a critical level severity alert will be triggered. |
condition | Union[str, AlertCondition] | - | Select from: 1. AlertCondition.LESSER 2. AlertCondition.GREATER |
bin_size | Union[str, BinSize] | - | Size of the bin for alert rule. |
evaluation_delay | int | 0 | To introduce a delay in the evaluation of the alert, specifying the duration in hours. The delay period must not exceed one year(8760 hours). |
Usage
create()
Set a new alert rule.
Parameters
No
Usage
Returns
Return Type | Description |
---|---|
Alert rule instance. |
get()
Get a single alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique identifier for the alert rule. |
Usage
Returns
Return Type | Description |
---|---|
Alert rule instance. |
Raises
Error code | Issue |
---|---|
NotFound | Alert rule with given identifier not found. |
Forbidden | Current user may not have permission to view details of alert rule. |
list()
Get a list of all alert rules in the organization.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
model_id | Optional[UUID] | None | Unique identifier for the model to which alert rule belongs. |
project_id | Optional[UUID] | None | Unique identifier for the project to which alert rule belongs |
metric_id | Union[str, UUID] | - | Type of alert metric UUID or enum. |
columns | Optional[List[str]] | None | List of column names on which alert rule is to be created. It can take ['ANY'] to check for all columns. |
baseline_id | Optional[UUID] | None | UUID of the baseline for the alert. |
ordering | Optional[List[str]] | None | List of Alert Rule fields to order by. Eg. [‘alert_time_bucket’] or [‘- alert_time_bucket’] for descending order. |
Usage
Returns
Return Type | Description |
---|---|
Iterator[AlertRule] | Iterable of alert rule instances. |
delete()
Delete an existing alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the alert rule . |
Usage
Returns
No
Raises
Error code | Issue |
---|---|
NotFound | Alert rule with given identifier not found. |
Forbidden | Current user may not have permission to view details of alert rule. |
enable_notifications()
Enable notification for an alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the alert rule . |
Usage
Returns
None
Raises
Error code | Issue |
---|---|
NotFound | Alert rule with given identifier not found. |
Forbidden | Current user may not have permission to view details of alert rule. |
disable_notification()
Disable notification for an alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the alert rule . |
Usage
Returns
None
Raises
Error code | Issue |
---|---|
NotFound | Alert rule with given identifier not found. |
Forbidden | Current user may not have permission to view details of alert rule. |
AlertNotifications
Alert notifications for an alert rule.
Parameter | Type | Default | Description |
---|---|---|---|
emails | Optional[List[str]] | None | List of emails to send notification to. |
pagerduty_services | Optional[List[str]] | None | List of pagerduty services to trigger the alert to. |
pagerduty_severity | Optional[str] | None | Severity of pagerduty. |
webhooks | Optional[List[UUID]] | None | List of webhook UUIDs. |
set_notification_config()
Set notifications for an alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
emails | Optional[List[str]] | None | List of emails to send notification to. |
pagerduty_services | Optional[List[str]] | None | List of pagerduty services to trigger the alert to. |
pagerduty_severity | Optional[str] | None | Severity of pagerduty. |
webhooks | Optional[List[UUID]] | None | List of webhook UUIDs. |
Usage
Returns
Return Type | Description |
---|---|
Alert notifications for an alert rule. |
If we
pagerduty_severity
is passed withoutpagerduty_services
then thepagerduty_severity
is ignored.
Raises
Error code | Issue |
---|---|
BadRequest | All 4 input parameters are empty. |
ValueError | Webhook ID is incorrect. |
get_notification_config()
Get notification configuration for an alert rule.
Parameters
None
Usage
Returns
Return Type | Description |
---|---|
Notification Config | Alert notifications for an alert rule. |
Raises
Error code | Issue |
---|---|
BadRequest | All 4 input parameters are empty. |
ValueError | Webhook ID is incorrect. |
TriggeredAlert
Alert records triggered for an alert rule.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the triggered alert rule. |
alert_rule_id | UUID | - | Unique identifier for the alert rule which needs to be triggered. |
alert_run_start_time | int | - | Timestamp of alert rule evaluation in epoch. |
alert_time_bucket | int | - | Timestamp pointing to the start of the time bucket in epoch. |
alert_value | float | - | Value of the metric for alert_time_bucket. |
baseline_time_bucket | Optional[int] | None | Timestamp pointing to the start of the baseline time bucket in epoch, only if alert rule is of 'time period' based comparison. |
baseline_value | Optional[float] | None | Value of the metric for baseline_time_bucket. |
is_alert | bool | - | Boolean to indicate if alert was supposed to be triggered. |
severity | str | - | Severity of alert represented by SeverityEnum, calculated based on value of metric and alert rule thresholds. |
failure_reason | str | - | String message if there was a failure sending notification. |
message | str | - | String message sent as a part of email notification. |
feature_name | Optional[str] | None | Name of feature for which alert was triggered. |
alert_record_main_version | int | - | Main version of triggered alert record in int, incremented when the value of severity changes. |
alert_record_sub_version | int | - | Sub version of triggered alert record in int, incremented when another alert with same severity as before is triggered. |
created_at | datetime | - | Time at which trigger alert rule was created. |
updated_at | datetime | - | Latest time at which trigger alert rule was updated. |
list()
List alert records triggered for an alert rule.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
alert_rule_id | UUID | - | Unique identifier for the alert rule which needs to be triggered. |
start_time | Optional[datetime] | None | Start time to filter trigger alerts in yyyy-MM-dd format, inclusive. |
end_time | Optional[datetime] | None | End time to filter trigger alerts in yyyy-MM-dd format, inclusive. |
ordering | Optional[List[str]] | None | List of Alert Rule fields to order by. Eg. [‘alert_time_bucket’] or [‘- alert_time_bucket’] for descending order. |
Usage
Returns
Return Type | Description |
---|---|
Iterator[AlertRecord] | Iterable of triggered alert rule instances for an alert rule. |
Baselines
Baseline datasets are used for making comparisons with production data.
A baseline dataset should be sampled from your model's training set, so it can serve as a representation of what the model expects to see in production.
Baseline
Baseline object contains the below fields.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the baseline. |
name | str | - | Baseline name. |
type_ | str | - | Type of baseline. Type can be static(Pre-production or production) or rolling(production). |
start_time | Optional[int] | None | Epoch to be used as start time for STATIC baseline. |
end_time | Optional[int] | None | Epoch to be used as end time for STATIC baseline. |
offset | Optional[int] | None | Offset in seconds relative to current time to be used for ROLLING baseline. |
window_size | Optional[int] | None | Span of window in seconds to be used for ROLLING baseline. |
row_count | Optional[int] | None | Number of rows in baseline. |
model | - | Details of the model. | |
project | - | Details of the project to which the baseline belongs. | |
dataset | - | Details of the dataset from which baseline is derived. | |
created_at | datetime | - | Time at which baseline was created. |
updated_at | datetime | - | Latest time at which baseline was updated. |
constructor()
Initialize a new baseline instance.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Unique name of the baseline. |
model_id | UUID | - | Unique identifier for the model to add baseline to. |
environment | - | Type of environment. Can either be PRE_PRODUCTION or PRODUCTION. | |
type_ | str | - | Type of Baseline. Type can be static(Pre-production or production) or rolling(production). |
dataset_id | Optional[UUID] | None | Unique identifier for the dataset on which the baseline is created. |
start_time | Optional[int] | None | Epoch to be used as start time for STATIC baseline. |
end_time | Optional[int] | None | Epoch to be used as end time for STATIC baseline. |
offset_delta | Optional[int] | None | Number of times of WindowBinSize to be used for ROLLING baseline. offset = offset_delta * window_bin_size |
window_bin_size | Optional[str] | None | Span of window in seconds to be used for ROLLING baseline using WindowBinSize |
Usage
create()
Adds a baseline to Fiddler.
Parameters
No
Usage
Returns
Return Type | Description |
---|---|
Baseline instance. |
Raises
Error code | Issue |
---|---|
Conflict | Baseline with same name may exist in project . |
NotFound | Given dataset may not exist in for the input model. |
ValueError | Validation failures like wrong window size, start_time, end_time etc |
get()
Get baseline from Fiddler Platform based on UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique identifier for the baseline. |
Usage
Returns
Return Type | Description |
---|---|
Baseline instance. |
Raises
Error code | Issue |
---|---|
NotFound | Baseline with given identifier not found. |
Forbidden | Current user may not have permission to view details of baseline. |
from_name()
Get baseline from Fiddler Platform based on name.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Name of the baseline. |
model_id | UUID | str | - | Unique identifier for the model. |
Usage
Returns
Return Type | Description |
---|---|
Baseline instance. |
Raises
Error code | Issue |
---|---|
NotFound | Baseline with given identifier not found. |
Forbidden | Current user may not have permission to view details of baseline. |
list()
List all baselines accessible to user.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
model_id | UUID | - | UUID of the model associated with baseline. |
Usage
Returns
Return Type | Description |
---|---|
Iterable[Baseline] | Iterable of all baseline objects. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of baseline. |
delete()
Deletes a baseline.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the baseline . |
Usage
Returns
None
Raises
Error code | Issue |
---|---|
NotFound | Baseline with given identifier not found. |
Forbidden | Current user may not have permission to delete baseline. |
CustomMetrics
Customized metrics for your specific use case.
CustomMetric
CustomMetric object contains the below parameters.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the custom metric. |
name | str | - | Custom metric name. |
model_id | UUID | - | UUID of the model in which the custom metric is being added. |
definition | str | - | Definition of the custom metric. |
description | Optional[str] | None | Description of the custom metric. |
created_at | datetime | - | Time of creation of custom metric. |
constructor()
Initialise a new custom metric.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Custom metric name. |
model_id | UUID | - | UUID of the model in which the custom metric is being added. |
definition | str | - | Definition of the custom metric. |
description | Optional[str] | None | Description of the custom metric. |
Usage
get()
Get CustomMetric from Fiddler Platform based on model UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
model_id | UUID | - | UUID of the model associated with the custom metrics. |
Usage
Returns
Return Type | Description |
---|---|
Iterable[CustomMetric] | Iterable of all custom metric objects. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of custom metric. |
from_name()
Get CustomMetric from Fiddler Platform based on name and model UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Name of the custom metric. |
model_id | UUID | str | - | Unique identifier for the model. |
Usage
Returns
Return Type | Description |
---|---|
Custom Metric instance. |
Raises
Error code | Issue |
---|---|
NotFound | Custom metric with given identifier not found. |
Forbidden | Current user may not have permission to view details of custom metric. |
create()
Creates a custom metric for a model on Fiddler Platform.
Parameters
None
Usage
Returns
Return Type | Description |
---|---|
Custom Metric instance. |
Raises
Error code | Issue |
---|---|
Conflict | Custom metric with same name may exist in project . |
BadRequest | Invalid definition. |
NotFound | Given model may not exist. |
delete()
Delete a custom metric.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the custom metric. |
Usage
Returns
No
Raises
Error code | Issue |
---|---|
NotFound | Custom metric with given identifier not found. |
Forbidden | Current user may not have permission to delete custom metric. |
Datasets
Datasets (or baseline datasets) are used for making comparisons with production data.
A baseline dataset should be sampled from your model's training set, so it can serve as a representation of what the model expects to see in production.
For more information, see Uploading a Baseline Dataset.
For guidance on how to design a baseline dataset, see Designing a Baseline Dataset.
Dataset
Dataset object contains the below parameters.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the dataset. |
name | str | - | Dataset name. |
row_count | Optional[int] | None | Number of rows in dataset. |
model | - | Details of the model. | |
project | - | Details of the project to which the dataset belongs. | |
organization | - | Details of the organization to which the dataset belongs. |
get()
Get dataset from Fiddler Platform based on UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique identifier for the dataset. |
Usage
Returns
Return Type | Description |
---|---|
Dataset instance. |
Raises
Error code | Issue |
---|---|
NotFound | Dataset with given identifier not found. |
Forbidden | Current user may not have permission to view details of dataset. |
from_name()
Get dataset from Fiddler Platform based on name and model UUID.
Usage params
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Name of the dataset. |
model_id | UUID | str | - | Unique identifier for the model. |
Usage
Returns
Return Type | Description |
---|---|
Dataset instance. |
Raises
Error code | Issue |
---|---|
NotFound | Dataset not found in the given project name. |
Forbidden | Current user may not have permission to view details of dataset. |
list()
Get a list of all datasets associated to a model.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
model_id | UUID | - | UUID of the model associated with baseline. |
Usage
Returns
Return Type | Description |
---|---|
Iterable[Dataset] | Iterable of all dataset objects. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of dataset. |
Jobs
Get job details.
Job
Job object contains the below fields.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the job. |
name | str | - | Name of the job. |
status | str | - | Current status of job. |
progress | float | - | Progress of job completion. |
info | dict | - | Dictionary containing resource_type, resource_name, project_name. |
error_message | Optional[str] | None | Message for job failure, if any. |
error_reason | Optional[str] | None | Reason for job failure, if any. |
extras | Optional[dict] | None | Metadata regarding the job. |
get()
Get the job instance using job UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | - | Unique UUID of the project to which model is associated. |
verbose | bool | False | Flag to get |
Usage
Returns
Return Type | Description |
---|---|
Single job object for the input params. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of job. |
wait()
Wait for job to complete either with success or failure status.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
interval | Optional[int] | 3 | Interval in seconds between polling for job status. |
timeout | Optional[int] | 1800 | Timeout in seconds for iterator to stop. |
Usage
Returns
Return Type | Description |
---|---|
Single job object for the input params. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of job. |
TimeoutError | When the default time out of 1800 secs. |
watch()
Watch job status at given interval and yield job object.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
interval | Optional[int] | 3 | Interval in seconds between polling for job status. |
timeout | Optional[int] | 1800 | Timeout in seconds for iterator to stop. |
Usage
Returns
Return Type | Description |
---|---|
Iterator[Job] | Iterator of job objects. |
Raises
Error code | Issue |
---|---|
Forbidden | Current user may not have permission to view details of job. |
TimeoutError | When the default time out of 1800 secs. |
Models
A model is a representation of your machine learning model. Each model can be used for monitoring, explainability, and fairness capabilities.
You do not need to upload your model artifact in order to onboard your model, but doing so will significantly improve the quality of explanations generated by Fiddler.
Model
Model object contains the below parameters.
Parameter | Type | Default | Description |
---|---|---|---|
id | UUID | - | Unique identifier for the model. |
name | str | - | Unique name of the model (only alphanumeric and underscores are allowed). |
input_type | ModelInputType.TABULAR | Input data type used by the model. | |
task | ModelTask.NOT_SET | Task the model is designed to address. | |
task_params | - | Task parameters given to a particular model. | |
schema | - | Model schema defines the details of each column. | |
version | Optional[str] | - | Unique version name within a model |
spec | - | Model spec defines how model columns are used along with model task. | |
description | str | - | Description of the model. |
event_id_col | str | - | Column containing event id. |
event_ts_col | str | - | Column containing event timestamp. |
xai_params | - | Explainability parameters of the model. | |
artifact_status | str | - | Artifact Status of the model. |
artifact_files | list[dict] | - | Dictionary containing file details of model artifact. |
is_binary_ranking_model | bool | - | True if model is ModelTask.RANKING and has only 2 target classes. |
created_at | datetime | - | Time at which model was created. |
updated_at | datetime | - | Latest time at which model was updated. |
created_by | - | Details of the who created the model. | |
updated_by | - | Details of the who last updated the model. | |
project | - | Details of the project to which the model belongs. | |
organization | - | Details of the organization to which the model belongs. |
constructor()
Initialize a new model instance.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Unique name of the model |
project_id | UUID | - | Unique identifier for the project to which model belongs. |
input_type | ModelInputType.TABULAR | Input data type used by the model. | |
task | ModelTask.NOT_SET | Task the model is designed to address. | |
schema | - | Model schema defines the details of each column. | |
spec | - | Model spec defines how model columns are used along with model task. | |
version | Optional[str] | - | Unique version name within a model |
task_params | - | Task parameters given to a particular model. | |
description | str | - | Description of the model. |
event_id_col | str | - | Column containing event id. |
event_ts_col | str | - | Column containing event timestamp. |
xai_params | - | Explainability parameters of the model. |
from_data()
Build model instance from the given dataframe or file(csv/parquet).
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
source | pd.DataFrame | Path | str | - | Pandas dataframe or path to csv/parquet file |
name | str | - | Unique name of the model |
project_id | UUID | str | - | Unique identifier for the project to which model belongs. |
input_type | ModelInputType.TABULAR | Input data type used by the model. | |
task | ModelTask.NOT_SET | Task the model is designed to address. | |
spec | - | Model spec defines how model columns are used along with model task. | |
version | Optional[str] | - | Unique version name within a model |
task_params | - | Task parameters given to a particular model. | |
description | Optional[str] | - | Description of the model. |
event_id_col | Optional[str] | - | Column containing event id. |
event_ts_col | Optional[str] | - | Column containing event timestamp. |
xai_params | - | Explainability parameters of the model. | |
max_cardinality | Optional[int] | None | Max cardinality to detect categorical columns. |
sample_size | Optional[int] | - | No. of samples to use for generating schema. |
Usage
Returns
Return Type | Description |
---|---|
Model instance. |
Notes
from_data
will not create a model entry on Fiddler Platform. Instead this method only returns a model instance which can be edited, call.create()
to onboard the model to Fiddler Platform.spec
is optional tofrom_data
method. However, aspec
with at leastinputs
is required for model onboarding.Make sure
spec
is passed tofrom_data
method if model requires custom features. This method generates centroids which are needed for custom feature drift computationIf
version
is not explicitly passed, Fiddler Platform will treat it asv1
version of the model.
create()
Onboard a new model to Fiddler Platform
Parameters
No
Usage
Returns
Return Type | Description |
---|---|
Model instance. |
Raises
Error code | Issue |
---|---|
Conflict | Model with same name may exist in project . |
get()
Get model from Fiddler Platform based on UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
id_ | UUID | str | - | Unique identifier for the model. |
Returns
Return Type | Description |
---|---|
Model instance. |
Raises
Error code | Issue |
---|---|
NotFound | Model with given identifier not found. |
Forbidden | Current user may not have permission to view details of model. |
Usage
from_name()
Get model from Fiddler Platform based on name and project UUID.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
name | str | - | Name of the model. |
project_id | UUID | str | - | Unique identifier for the project. |
version | Optiona[str] | - | Unique version name within a model |
version
parameter is available fromfiddler-client==3.1
onwards
\
Usage
Returns
Return Type | Description |
---|---|
Model instance. |
Notes
When the version is not passed, then the model created without any version will be fetched. Fiddler internally assigns version=v1 when not passed.
When the version is passed, method will fetch the model corresponding to that specific version.
\
Raises
Error code | Issue |
---|---|
NotFound | Model not found in the given project name. |
Forbidden | Current user may not have permission to view details of model. |
list()
Gets all models of a project.
Parameters
Parameter | Type | Default | Description |
---|---|---|---|
project_id | Optional[UUID] | - | Unique UUID of the project to which model is associated. |
name | < |