From bf6639758223afbd5734ff81f749b4497df07cdb Mon Sep 17 00:00:00 2001 From: Austin Zielman Date: Thu, 29 Feb 2024 23:51:53 +0000 Subject: [PATCH] Version 1.1.6 --- abacusai/__init__.py | 2 +- abacusai/api_class/batch_prediction.py | 26 +- abacusai/api_class/document_retriever.py | 2 + abacusai/api_class/enums.py | 20 ++ abacusai/api_class/model.py | 2 + abacusai/batch_prediction.py | 25 +- abacusai/batch_prediction_version.py | 22 +- abacusai/client.py | 52 ++- abacusai/dataset.py | 6 +- abacusai/deployment.py | 7 +- abacusai/document_retriever_config.py | 12 +- abacusai/external_application.py | 18 +- abacusai/feature_group.py | 17 +- abacusai/feature_group_export.py | 4 - abacusai/pipeline.py | 15 +- abacusai/pipeline_version.py | 13 +- abacusai/project.py | 22 -- abacusai/public.pem | 6 +- .../api_class/batch_prediction/index.rst.txt | 55 ++- .../document_retriever/index.rst.txt | 7 + .../abacusai/api_class/enums/index.rst.txt | 65 ++++ .../autoapi/abacusai/api_class/index.rst.txt | 134 +++++++- .../abacusai/api_class/model/index.rst.txt | 7 + .../abacusai/batch_prediction/index.rst.txt | 14 +- .../batch_prediction_version/index.rst.txt | 10 +- .../autoapi/abacusai/client/index.rst.txt | 43 +-- .../autoapi/abacusai/dataset/index.rst.txt | 2 +- .../autoapi/abacusai/deployment/index.rst.txt | 8 +- .../document_retriever_config/index.rst.txt | 4 +- .../external_application/index.rst.txt | 10 +- .../abacusai/feature_group/index.rst.txt | 15 +- .../feature_group_export/index.rst.txt | 3 - docs/_sources/autoapi/abacusai/index.rst.txt | 177 ++++++++-- .../autoapi/abacusai/pipeline/index.rst.txt | 4 +- .../abacusai/pipeline_version/index.rst.txt | 4 +- .../autoapi/abacusai/project/index.rst.txt | 21 -- .../api_class/batch_prediction/index.html | 58 +++- .../api_class/document_retriever/index.html | 6 + .../abacusai/api_class/enums/index.html | 66 ++++ docs/autoapi/abacusai/api_class/index.html | 280 +++++++++++----- .../abacusai/api_class/model/index.html | 6 + .../abacusai/batch_prediction/index.html | 13 +- .../batch_prediction_version/index.html | 10 +- docs/autoapi/abacusai/client/index.html | 45 +-- docs/autoapi/abacusai/dataset/index.html | 2 +- docs/autoapi/abacusai/deployment/index.html | 7 +- .../document_retriever_config/index.html | 3 +- .../abacusai/external_application/index.html | 7 +- .../autoapi/abacusai/feature_group/index.html | 22 +- .../abacusai/feature_group_export/index.html | 5 - docs/autoapi/abacusai/index.html | 313 ++++++++++++------ docs/autoapi/abacusai/pipeline/index.html | 3 +- .../abacusai/pipeline_version/index.html | 3 +- docs/autoapi/abacusai/project/index.html | 31 -- docs/genindex.html | 208 +++++++++--- docs/objects.inv | Bin 47609 -> 48060 bytes docs/searchindex.js | 2 +- setup.py | 2 +- 58 files changed, 1364 insertions(+), 582 deletions(-) diff --git a/abacusai/__init__.py b/abacusai/__init__.py index 45423432c..b7389d2ff 100644 --- a/abacusai/__init__.py +++ b/abacusai/__init__.py @@ -4,4 +4,4 @@ from .streaming_client import StreamingClient -__version__ = "1.1.5" +__version__ = "1.1.6" diff --git a/abacusai/api_class/batch_prediction.py b/abacusai/api_class/batch_prediction.py index dc3de2a57..7e228132b 100644 --- a/abacusai/api_class/batch_prediction.py +++ b/abacusai/api_class/batch_prediction.py @@ -24,9 +24,11 @@ class AnomalyOutliersBatchPredictionArgs(BatchPredictionArgs): Args: for_eval (bool): If True, the test fold which was created during training and used for metrics calculation will be used as input data. These predictions are hence, used for model evaluation. threshold (float): The threshold for detecting an anomaly. Range: [0.8, 0.99] + explain_predictions (bool): If True, calculates explanations for the predicted values along with predictions. """ for_eval: bool = dataclasses.field(default=None) threshold: float = dataclasses.field(default=None) + explain_predictions: bool = dataclasses.field(default=None) def __post_init__(self): self.problem_type = enums.ProblemType.ANOMALY_OUTLIERS @@ -44,7 +46,8 @@ class ForecastingBatchPredictionArgs(BatchPredictionArgs): start_date_offset (int): Sets prediction start date as this offset relative to the prediction start date. forecasting_horizon (int): The number of timestamps to predict in the future. Range: [1, 1000]. item_attributes_to_include_in_the_result (list): List of columns to include in the prediction output. - explain_predictions (bool): If True, explain predictions for the forecast. + explain_predictions (bool): If True, calculates explanations for the forecasted values along with predictions. + automate_monitoring (bool): If True, creates a monitor to calculate the drift for the batch prediction. """ for_eval: bool = dataclasses.field(default=None) predictions_start_date: str = dataclasses.field(default=None) @@ -53,6 +56,7 @@ class ForecastingBatchPredictionArgs(BatchPredictionArgs): forecasting_horizon: int = dataclasses.field(default=None) item_attributes_to_include_in_the_result: list = dataclasses.field(default=None) explain_predictions: bool = dataclasses.field(default=None) + automate_monitoring: bool = dataclasses.field(default=None) def __post_init__(self): self.problem_type = enums.ProblemType.FORECASTING @@ -110,6 +114,8 @@ class PredictiveModelingBatchPredictionArgs(BatchPredictionArgs): explanation_filter_upper_bound (float): If set explanations will be limited to predictions below this value, Range: [0, 1]. bound_label (str): For classification problems specifies the label to which the explanation bounds are applied. output_columns (list): A list of column names to include in the prediction result. + explain_predictions (bool): If True, calculates explanations for the predicted values along with predictions. + automate_monitoring (bool): If True, creates a monitor to calculate the drift for the batch prediction. """ for_eval: bool = dataclasses.field(default=None) explainer_type: enums.ExplainerType = dataclasses.field(default=None) @@ -121,6 +127,8 @@ class PredictiveModelingBatchPredictionArgs(BatchPredictionArgs): explanation_filter_upper_bound: float = dataclasses.field(default=None) explanation_filter_label: str = dataclasses.field(default=None) output_columns: list = dataclasses.field(default=None) + explain_predictions: bool = dataclasses.field(default=None) + automate_monitoring: bool = dataclasses.field(default=None) def __post_init__(self): self.problem_type = enums.ProblemType.PREDICTIVE_MODELING @@ -194,6 +202,21 @@ def __post_init__(self): self.problem_type = enums.ProblemType.CHAT_LLM +@dataclasses.dataclass +class TrainablePlugAndPlayBatchPredictionArgs(BatchPredictionArgs): + """ + Batch Prediction Config for the TrainablePlugAndPlay problem type + + Args: + automate_monitoring (bool): If True, creates a monitor to calculate the drift for the batch prediction. + """ + for_eval: bool = dataclasses.field(default=None) + automate_monitoring: bool = dataclasses.field(default=None) + + def __post_init__(self): + self.problem_type = enums.ProblemType.CUSTOM_ALGORITHM + + @dataclasses.dataclass class _BatchPredictionArgsFactory(_ApiClassFactory): config_abstract_class = BatchPredictionArgs @@ -208,4 +231,5 @@ class _BatchPredictionArgsFactory(_ApiClassFactory): enums.ProblemType.SENTENCE_BOUNDARY_DETECTION: SentenceBoundaryDetectionBatchPredictionArgs, enums.ProblemType.THEME_ANALYSIS: ThemeAnalysisBatchPredictionArgs, enums.ProblemType.CHAT_LLM: ChatLLMBatchPredictionArgs, + enums.ProblemType.CUSTOM_ALGORITHM: TrainablePlugAndPlayBatchPredictionArgs, } diff --git a/abacusai/api_class/document_retriever.py b/abacusai/api_class/document_retriever.py index 2efc7b430..4d8e8681d 100644 --- a/abacusai/api_class/document_retriever.py +++ b/abacusai/api_class/document_retriever.py @@ -14,11 +14,13 @@ class VectorStoreConfig(ApiClass): chunk_overlap_fraction (float): The fraction of overlap between chunks. text_encoder (VectorStoreTextEncoder): Encoder used to index texts from the documents. chunk_size_factors (list): Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to `chunk_size`. + score_multiplier_column (str): If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries. """ chunk_size: int = dataclasses.field(default=None) chunk_overlap_fraction: float = dataclasses.field(default=None) text_encoder: VectorStoreTextEncoder = dataclasses.field(default=None) chunk_size_factors: list = dataclasses.field(default=None) + score_multiplier_column: str = dataclasses.field(default=None) @dataclasses.dataclass diff --git a/abacusai/api_class/enums.py b/abacusai/api_class/enums.py index 944370e76..a034f629f 100644 --- a/abacusai/api_class/enums.py +++ b/abacusai/api_class/enums.py @@ -350,6 +350,7 @@ class ApplicationConnectorType(ApiEnum): SHAREPOINT = 'SHAREPOINT' TEAMS = 'TEAMS' ABACUSUSAGEMETRICS = 'ABACUSUSAGEMETRICS' + MICROSOFTAUTH = 'MICROSOFTAUTH' class PythonFunctionArgumentType(ApiEnum): @@ -476,3 +477,22 @@ class OcrMode(ApiEnum): COMPREHENSIVE = 'COMPREHENSIVE' COMPREHENSIVE_V2 = 'COMPREHENSIVE_V2' COMPREHENSIVE_TABLE_MD = 'COMPREHENSIVE_TABLE_MD' + + +class DataType(ApiEnum): + INTEGER = 'integer' + FLOAT = 'float' + STRING = 'string' + DATE = 'date' + DATETIME = 'datetime' + BOOLEAN = 'boolean' + LIST = 'list' + STRUCT = 'struct' + NULL = 'null' + + @classmethod + def from_str(cls, value): + if not value: + return None + default_map = {val.value: val for val in DataType} + return default_map[value.lower()] diff --git a/abacusai/api_class/model.py b/abacusai/api_class/model.py index f6505f84d..3f3448835 100644 --- a/abacusai/api_class/model.py +++ b/abacusai/api_class/model.py @@ -453,6 +453,7 @@ class ChatLLMTrainingConfig(TrainingConfig): hide_generated_sql (bool): When running data queries, hides the generated SQL in the response and will just return the table. disable_data_summarization (bool): After executing a query summarize the reponse and reply back with only the table and query run. search_score_cutoff (float): Minimum search score to consider a document as a valid search result. + database_connector_id (str): Database connector id to use for the chatllm. """ document_retrievers: List[str] = None num_completion_tokens: int = None @@ -468,6 +469,7 @@ class ChatLLMTrainingConfig(TrainingConfig): hide_generated_sql: bool = None disable_data_summarization: bool = None search_score_cutoff: float = None + database_connector_id: str = None def __post_init__(self): self.problem_type = enums.ProblemType.CHAT_LLM diff --git a/abacusai/batch_prediction.py b/abacusai/batch_prediction.py index 0fb2a8a13..5241ed4b2 100644 --- a/abacusai/batch_prediction.py +++ b/abacusai/batch_prediction.py @@ -21,11 +21,11 @@ class BatchPrediction(AbstractApiClass): fileConnectorOutputLocation (str): Contains information about where the batch predictions are written to. databaseConnectorId (str): The database connector to write the results to. databaseOutputConfiguration (dict): Contains information about where the batch predictions are written to. - explanations (bool): If true, explanations for each prediction will be created. + explanations (bool): fileOutputFormat (str): The format of the batch prediction output (CSV or JSON). connectorType (str): Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR. legacyInputLocation (str): The location of the input data. - outputFeatureGroupId (str): The BP output feature group id if applicable + outputFeatureGroupId (str): The Batch Prediction output feature group ID if applicable featureGroupTableName (str): The table name of the Batch Prediction output feature group. outputFeatureGroupTableName (str): The table name of the Batch Prediction output feature group. summaryFeatureGroupTableName (str): The table name of the metrics summary feature group output by Batch Prediction. @@ -43,7 +43,7 @@ class BatchPrediction(AbstractApiClass): inputFeatureGroups (PredictionFeatureGroup): List of prediction feature groups. """ - def __init__(self, client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={}): + def __init__(self, client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={}): super().__init__(client, batchPredictionId) self.batch_prediction_id = batchPredictionId self.created_at = createdAt @@ -77,11 +77,13 @@ def __init__(self, client, batchPredictionId=None, createdAt=None, name=None, de PredictionFeatureGroup, inputFeatureGroups) self.global_prediction_args = client._build_class( BatchPredictionArgs, globalPredictionArgs) - self.deprecated_keys = {} + self.batch_prediction_args = client._build_class( + BatchPredictionArgs, batchPredictionArgs) + self.deprecated_keys = {'global_prediction_args', 'explanations'} def __repr__(self): - repr_dict = {f'batch_prediction_id': repr(self.batch_prediction_id), f'created_at': repr(self.created_at), f'name': repr(self.name), f'deployment_id': repr(self.deployment_id), f'file_connector_output_location': repr(self.file_connector_output_location), f'database_connector_id': repr(self.database_connector_id), f'database_output_configuration': repr(self.database_output_configuration), f'explanations': repr(self.explanations), f'file_output_format': repr(self.file_output_format), f'connector_type': repr(self.connector_type), f'legacy_input_location': repr(self.legacy_input_location), f'output_feature_group_id': repr(self.output_feature_group_id), f'feature_group_table_name': repr(self.feature_group_table_name), f'output_feature_group_table_name': repr( - self.output_feature_group_table_name), f'summary_feature_group_table_name': repr(self.summary_feature_group_table_name), f'csv_input_prefix': repr(self.csv_input_prefix), f'csv_prediction_prefix': repr(self.csv_prediction_prefix), f'csv_explanations_prefix': repr(self.csv_explanations_prefix), f'output_includes_metadata': repr(self.output_includes_metadata), f'result_input_columns': repr(self.result_input_columns), f'model_monitor_id': repr(self.model_monitor_id), f'model_version': repr(self.model_version), f'algorithm': repr(self.algorithm), f'batch_inputs': repr(self.batch_inputs), f'latest_batch_prediction_version': repr(self.latest_batch_prediction_version), f'refresh_schedules': repr(self.refresh_schedules), f'input_feature_groups': repr(self.input_feature_groups), f'global_prediction_args': repr(self.global_prediction_args)} + repr_dict = {f'batch_prediction_id': repr(self.batch_prediction_id), f'created_at': repr(self.created_at), f'name': repr(self.name), f'deployment_id': repr(self.deployment_id), f'file_connector_output_location': repr(self.file_connector_output_location), f'database_connector_id': repr(self.database_connector_id), f'database_output_configuration': repr(self.database_output_configuration), f'explanations': repr(self.explanations), f'file_output_format': repr(self.file_output_format), f'connector_type': repr(self.connector_type), f'legacy_input_location': repr(self.legacy_input_location), f'output_feature_group_id': repr(self.output_feature_group_id), f'feature_group_table_name': repr(self.feature_group_table_name), f'output_feature_group_table_name': repr(self.output_feature_group_table_name), f'summary_feature_group_table_name': repr( + self.summary_feature_group_table_name), f'csv_input_prefix': repr(self.csv_input_prefix), f'csv_prediction_prefix': repr(self.csv_prediction_prefix), f'csv_explanations_prefix': repr(self.csv_explanations_prefix), f'output_includes_metadata': repr(self.output_includes_metadata), f'result_input_columns': repr(self.result_input_columns), f'model_monitor_id': repr(self.model_monitor_id), f'model_version': repr(self.model_version), f'algorithm': repr(self.algorithm), f'batch_inputs': repr(self.batch_inputs), f'latest_batch_prediction_version': repr(self.latest_batch_prediction_version), f'refresh_schedules': repr(self.refresh_schedules), f'input_feature_groups': repr(self.input_feature_groups), f'global_prediction_args': repr(self.global_prediction_args), f'batch_prediction_args': repr(self.batch_prediction_args)} class_name = "BatchPrediction" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -94,8 +96,8 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'batch_prediction_id': self.batch_prediction_id, 'created_at': self.created_at, 'name': self.name, 'deployment_id': self.deployment_id, 'file_connector_output_location': self.file_connector_output_location, 'database_connector_id': self.database_connector_id, 'database_output_configuration': self.database_output_configuration, 'explanations': self.explanations, 'file_output_format': self.file_output_format, 'connector_type': self.connector_type, 'legacy_input_location': self.legacy_input_location, 'output_feature_group_id': self.output_feature_group_id, 'feature_group_table_name': self.feature_group_table_name, 'output_feature_group_table_name': self.output_feature_group_table_name, 'summary_feature_group_table_name': self.summary_feature_group_table_name, - 'csv_input_prefix': self.csv_input_prefix, 'csv_prediction_prefix': self.csv_prediction_prefix, 'csv_explanations_prefix': self.csv_explanations_prefix, 'output_includes_metadata': self.output_includes_metadata, 'result_input_columns': self.result_input_columns, 'model_monitor_id': self.model_monitor_id, 'model_version': self.model_version, 'algorithm': self.algorithm, 'batch_inputs': self._get_attribute_as_dict(self.batch_inputs), 'latest_batch_prediction_version': self._get_attribute_as_dict(self.latest_batch_prediction_version), 'refresh_schedules': self._get_attribute_as_dict(self.refresh_schedules), 'input_feature_groups': self._get_attribute_as_dict(self.input_feature_groups), 'global_prediction_args': self._get_attribute_as_dict(self.global_prediction_args)} + resp = {'batch_prediction_id': self.batch_prediction_id, 'created_at': self.created_at, 'name': self.name, 'deployment_id': self.deployment_id, 'file_connector_output_location': self.file_connector_output_location, 'database_connector_id': self.database_connector_id, 'database_output_configuration': self.database_output_configuration, 'explanations': self.explanations, 'file_output_format': self.file_output_format, 'connector_type': self.connector_type, 'legacy_input_location': self.legacy_input_location, 'output_feature_group_id': self.output_feature_group_id, 'feature_group_table_name': self.feature_group_table_name, 'output_feature_group_table_name': self.output_feature_group_table_name, 'summary_feature_group_table_name': self.summary_feature_group_table_name, 'csv_input_prefix': self.csv_input_prefix, + 'csv_prediction_prefix': self.csv_prediction_prefix, 'csv_explanations_prefix': self.csv_explanations_prefix, 'output_includes_metadata': self.output_includes_metadata, 'result_input_columns': self.result_input_columns, 'model_monitor_id': self.model_monitor_id, 'model_version': self.model_version, 'algorithm': self.algorithm, 'batch_inputs': self._get_attribute_as_dict(self.batch_inputs), 'latest_batch_prediction_version': self._get_attribute_as_dict(self.latest_batch_prediction_version), 'refresh_schedules': self._get_attribute_as_dict(self.refresh_schedules), 'input_feature_groups': self._get_attribute_as_dict(self.input_feature_groups), 'global_prediction_args': self._get_attribute_as_dict(self.global_prediction_args), 'batch_prediction_args': self._get_attribute_as_dict(self.batch_prediction_args)} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} def start(self): @@ -145,14 +147,13 @@ def list_versions(self, limit: int = 100, start_after_version: str = None): """ return self.client.list_batch_prediction_versions(self.batch_prediction_id, limit, start_after_version) - def update(self, deployment_id: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = None, output_format: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, name: str = None): + def update(self, deployment_id: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, batch_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = None, output_format: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, name: str = None): """ Update a batch prediction job description. Args: deployment_id (str): Unique identifier of the deployment. - global_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. - explanations (bool): If True, SHAP explanations for each prediction will be provided, if supported by the use case. + batch_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. output_format (str): If specified, sets the format of the batch prediction output (CSV or JSON). csv_input_prefix (str): Prefix to prepend to the input columns, only applies when output format is CSV. csv_prediction_prefix (str): Prefix to prepend to the prediction columns, only applies when output format is CSV. @@ -164,7 +165,7 @@ def update(self, deployment_id: str = None, global_prediction_args: Union[dict, Returns: BatchPrediction: The batch prediction. """ - return self.client.update_batch_prediction(self.batch_prediction_id, deployment_id, global_prediction_args, explanations, output_format, csv_input_prefix, csv_prediction_prefix, csv_explanations_prefix, output_includes_metadata, result_input_columns, name) + return self.client.update_batch_prediction(self.batch_prediction_id, deployment_id, global_prediction_args, batch_prediction_args, explanations, output_format, csv_input_prefix, csv_prediction_prefix, csv_explanations_prefix, output_includes_metadata, result_input_columns, name) def set_file_connector_output(self, output_format: str = None, output_location: str = None): """ diff --git a/abacusai/batch_prediction_version.py b/abacusai/batch_prediction_version.py index 10482e140..bc3d1c7b3 100644 --- a/abacusai/batch_prediction_version.py +++ b/abacusai/batch_prediction_version.py @@ -24,7 +24,7 @@ class BatchPredictionVersion(AbstractApiClass): failedPredictions (int): Number of predictions that failed databaseConnectorId (str): The database connector to write the results to databaseOutputConfiguration (dict): Contains information about where the batch predictions are written to - explanations (bool): If true, explanations for each prediction were created + explanations (bool): fileConnectorOutputLocation (str): Contains information about where the batch predictions are written to fileOutputFormat (str): The format of the batch prediction output (CSV or JSON) connectorType (str): Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR @@ -42,15 +42,15 @@ class BatchPredictionVersion(AbstractApiClass): modelMonitorVersion (str): The version of the model monitor algoName (str): The name of the algorithm used to train the model algorithm (str): The algorithm that is currently deployed. - outputFeatureGroupId (str): The BP output feature group id if applicable - outputFeatureGroupVersion (str): The BP output feature group version if applicable - outputFeatureGroupTableName (str): The BP output feature group name if applicable + outputFeatureGroupId (str): The Batch Prediction output feature group ID if applicable + outputFeatureGroupVersion (str): The Batch Prediction output feature group version if applicable + outputFeatureGroupTableName (str): The Batch Prediction output feature group name if applicable batchPredictionWarnings (str): Relevant warnings if any issues are found batchInputs (PredictionInput): Inputs to the batch prediction inputFeatureGroups (PredictionFeatureGroup): List of prediction feature groups """ - def __init__(self, client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}): + def __init__(self, client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={}): super().__init__(client, batchPredictionVersion) self.batch_prediction_version = batchPredictionVersion self.batch_prediction_id = batchPredictionId @@ -93,11 +93,13 @@ def __init__(self, client, batchPredictionVersion=None, batchPredictionId=None, PredictionFeatureGroup, inputFeatureGroups) self.global_prediction_args = client._build_class( BatchPredictionArgs, globalPredictionArgs) - self.deprecated_keys = {} + self.batch_prediction_args = client._build_class( + BatchPredictionArgs, batchPredictionArgs) + self.deprecated_keys = {'global_prediction_args', 'explanations'} def __repr__(self): - repr_dict = {f'batch_prediction_version': repr(self.batch_prediction_version), f'batch_prediction_id': repr(self.batch_prediction_id), f'status': repr(self.status), f'drift_monitor_status': repr(self.drift_monitor_status), f'deployment_id': repr(self.deployment_id), f'model_id': repr(self.model_id), f'model_version': repr(self.model_version), f'predictions_started_at': repr(self.predictions_started_at), f'predictions_completed_at': repr(self.predictions_completed_at), f'database_output_error': repr(self.database_output_error), f'total_predictions': repr(self.total_predictions), f'failed_predictions': repr(self.failed_predictions), f'database_connector_id': repr(self.database_connector_id), f'database_output_configuration': repr(self.database_output_configuration), f'explanations': repr(self.explanations), f'file_connector_output_location': repr(self.file_connector_output_location), f'file_output_format': repr(self.file_output_format), f'connector_type': repr(self.connector_type), f'legacy_input_location': repr(self.legacy_input_location), f'error': repr(self.error), f'drift_monitor_error': repr( - self.drift_monitor_error), f'monitor_warnings': repr(self.monitor_warnings), f'csv_input_prefix': repr(self.csv_input_prefix), f'csv_prediction_prefix': repr(self.csv_prediction_prefix), f'csv_explanations_prefix': repr(self.csv_explanations_prefix), f'database_output_total_writes': repr(self.database_output_total_writes), f'database_output_failed_writes': repr(self.database_output_failed_writes), f'output_includes_metadata': repr(self.output_includes_metadata), f'result_input_columns': repr(self.result_input_columns), f'model_monitor_version': repr(self.model_monitor_version), f'algo_name': repr(self.algo_name), f'algorithm': repr(self.algorithm), f'output_feature_group_id': repr(self.output_feature_group_id), f'output_feature_group_version': repr(self.output_feature_group_version), f'output_feature_group_table_name': repr(self.output_feature_group_table_name), f'batch_prediction_warnings': repr(self.batch_prediction_warnings), f'batch_inputs': repr(self.batch_inputs), f'input_feature_groups': repr(self.input_feature_groups), f'global_prediction_args': repr(self.global_prediction_args)} + repr_dict = {f'batch_prediction_version': repr(self.batch_prediction_version), f'batch_prediction_id': repr(self.batch_prediction_id), f'status': repr(self.status), f'drift_monitor_status': repr(self.drift_monitor_status), f'deployment_id': repr(self.deployment_id), f'model_id': repr(self.model_id), f'model_version': repr(self.model_version), f'predictions_started_at': repr(self.predictions_started_at), f'predictions_completed_at': repr(self.predictions_completed_at), f'database_output_error': repr(self.database_output_error), f'total_predictions': repr(self.total_predictions), f'failed_predictions': repr(self.failed_predictions), f'database_connector_id': repr(self.database_connector_id), f'database_output_configuration': repr(self.database_output_configuration), f'explanations': repr(self.explanations), f'file_connector_output_location': repr(self.file_connector_output_location), f'file_output_format': repr(self.file_output_format), f'connector_type': repr(self.connector_type), f'legacy_input_location': repr(self.legacy_input_location), f'error': repr(self.error), f'drift_monitor_error': repr(self.drift_monitor_error), f'monitor_warnings': repr( + self.monitor_warnings), f'csv_input_prefix': repr(self.csv_input_prefix), f'csv_prediction_prefix': repr(self.csv_prediction_prefix), f'csv_explanations_prefix': repr(self.csv_explanations_prefix), f'database_output_total_writes': repr(self.database_output_total_writes), f'database_output_failed_writes': repr(self.database_output_failed_writes), f'output_includes_metadata': repr(self.output_includes_metadata), f'result_input_columns': repr(self.result_input_columns), f'model_monitor_version': repr(self.model_monitor_version), f'algo_name': repr(self.algo_name), f'algorithm': repr(self.algorithm), f'output_feature_group_id': repr(self.output_feature_group_id), f'output_feature_group_version': repr(self.output_feature_group_version), f'output_feature_group_table_name': repr(self.output_feature_group_table_name), f'batch_prediction_warnings': repr(self.batch_prediction_warnings), f'batch_inputs': repr(self.batch_inputs), f'input_feature_groups': repr(self.input_feature_groups), f'global_prediction_args': repr(self.global_prediction_args), f'batch_prediction_args': repr(self.batch_prediction_args)} class_name = "BatchPredictionVersion" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -110,8 +112,8 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'batch_prediction_version': self.batch_prediction_version, 'batch_prediction_id': self.batch_prediction_id, 'status': self.status, 'drift_monitor_status': self.drift_monitor_status, 'deployment_id': self.deployment_id, 'model_id': self.model_id, 'model_version': self.model_version, 'predictions_started_at': self.predictions_started_at, 'predictions_completed_at': self.predictions_completed_at, 'database_output_error': self.database_output_error, 'total_predictions': self.total_predictions, 'failed_predictions': self.failed_predictions, 'database_connector_id': self.database_connector_id, 'database_output_configuration': self.database_output_configuration, 'explanations': self.explanations, 'file_connector_output_location': self.file_connector_output_location, 'file_output_format': self.file_output_format, 'connector_type': self.connector_type, 'legacy_input_location': self.legacy_input_location, 'error': self.error, 'drift_monitor_error': self.drift_monitor_error, 'monitor_warnings': self.monitor_warnings, - 'csv_input_prefix': self.csv_input_prefix, 'csv_prediction_prefix': self.csv_prediction_prefix, 'csv_explanations_prefix': self.csv_explanations_prefix, 'database_output_total_writes': self.database_output_total_writes, 'database_output_failed_writes': self.database_output_failed_writes, 'output_includes_metadata': self.output_includes_metadata, 'result_input_columns': self.result_input_columns, 'model_monitor_version': self.model_monitor_version, 'algo_name': self.algo_name, 'algorithm': self.algorithm, 'output_feature_group_id': self.output_feature_group_id, 'output_feature_group_version': self.output_feature_group_version, 'output_feature_group_table_name': self.output_feature_group_table_name, 'batch_prediction_warnings': self.batch_prediction_warnings, 'batch_inputs': self._get_attribute_as_dict(self.batch_inputs), 'input_feature_groups': self._get_attribute_as_dict(self.input_feature_groups), 'global_prediction_args': self._get_attribute_as_dict(self.global_prediction_args)} + resp = {'batch_prediction_version': self.batch_prediction_version, 'batch_prediction_id': self.batch_prediction_id, 'status': self.status, 'drift_monitor_status': self.drift_monitor_status, 'deployment_id': self.deployment_id, 'model_id': self.model_id, 'model_version': self.model_version, 'predictions_started_at': self.predictions_started_at, 'predictions_completed_at': self.predictions_completed_at, 'database_output_error': self.database_output_error, 'total_predictions': self.total_predictions, 'failed_predictions': self.failed_predictions, 'database_connector_id': self.database_connector_id, 'database_output_configuration': self.database_output_configuration, 'explanations': self.explanations, 'file_connector_output_location': self.file_connector_output_location, 'file_output_format': self.file_output_format, 'connector_type': self.connector_type, 'legacy_input_location': self.legacy_input_location, 'error': self.error, 'drift_monitor_error': self.drift_monitor_error, 'monitor_warnings': self.monitor_warnings, 'csv_input_prefix': self.csv_input_prefix, + 'csv_prediction_prefix': self.csv_prediction_prefix, 'csv_explanations_prefix': self.csv_explanations_prefix, 'database_output_total_writes': self.database_output_total_writes, 'database_output_failed_writes': self.database_output_failed_writes, 'output_includes_metadata': self.output_includes_metadata, 'result_input_columns': self.result_input_columns, 'model_monitor_version': self.model_monitor_version, 'algo_name': self.algo_name, 'algorithm': self.algorithm, 'output_feature_group_id': self.output_feature_group_id, 'output_feature_group_version': self.output_feature_group_version, 'output_feature_group_table_name': self.output_feature_group_table_name, 'batch_prediction_warnings': self.batch_prediction_warnings, 'batch_inputs': self._get_attribute_as_dict(self.batch_inputs), 'input_feature_groups': self._get_attribute_as_dict(self.input_feature_groups), 'global_prediction_args': self._get_attribute_as_dict(self.global_prediction_args), 'batch_prediction_args': self._get_attribute_as_dict(self.batch_prediction_args)} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} def download_batch_prediction_result_chunk(self, offset: int = 0, chunk_size: int = 10485760): diff --git a/abacusai/client.py b/abacusai/client.py index 2c50afe2a..057318c78 100644 --- a/abacusai/client.py +++ b/abacusai/client.py @@ -33,11 +33,11 @@ from .annotations_status import AnnotationsStatus from .api_class import ( AlertActionConfig, AlertConditionConfig, ApiClass, ApiEnum, - BatchPredictionArgs, BlobInput, DatasetConfig, DocumentProcessingConfig, - DocumentRetrieverConfig, EvalArtifactType, FeatureGroupExportConfig, - ForecastingMonitorConfig, IncrementalDatabaseConnectorConfig, LLMName, - MergeConfig, ParsingConfig, ProblemType, PythonFunctionType, - SamplingConfig, TrainingConfig + BatchPredictionArgs, BlobInput, DatasetConfig, DataType, + DocumentProcessingConfig, DocumentRetrieverConfig, EvalArtifactType, + FeatureGroupExportConfig, ForecastingMonitorConfig, + IncrementalDatabaseConnectorConfig, LLMName, MergeConfig, ParsingConfig, + ProblemType, PythonFunctionType, SamplingConfig, TrainingConfig ) from .api_client_utils import ( INVALID_PANDAS_COLUMN_NAME_CHARACTERS, StreamingHandler, clean_column_name, @@ -575,7 +575,7 @@ class BaseApiClient: client_options (ClientOptions): Optional API client configurations skip_version_check (bool): If true, will skip checking the server's current API version on initializing the client """ - client_version = '1.1.5' + client_version = '1.1.6' def __init__(self, api_key: str = None, server: str = None, client_options: ClientOptions = None, skip_version_check: bool = False): self.api_key = api_key @@ -5026,13 +5026,13 @@ def snapshot_streaming_data(self, dataset_id: str) -> DatasetVersion: DatasetVersion: The new Dataset Version created by taking a snapshot of the current data in the streaming dataset.""" return self._call_api('snapshotStreamingData', 'POST', query_params={'datasetId': dataset_id}, body={}, parse_type=DatasetVersion) - def set_dataset_column_data_type(self, dataset_id: str, column: str, data_type: str) -> Dataset: + def set_dataset_column_data_type(self, dataset_id: str, column: str, data_type: Union[DataType, str]) -> Dataset: """Set a Dataset's column type. Args: dataset_id (str): The unique ID associated with the dataset. column (str): The name of the column. - data_type (str): The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. + data_type (DataType): The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. Returns: Dataset: The dataset and schema after the data type has been set.""" @@ -6717,15 +6717,14 @@ def execute_agent_with_binary_data(self, deployment_token: str, deployment_id: s deployment_id, deployment_token) if deployment_token else None return self._call_api('executeAgentWithBinaryData', 'POST', query_params={'deploymentToken': deployment_token, 'deploymentId': deployment_id}, data={'arguments': json.dumps(arguments) if (arguments is not None and not isinstance(arguments, str)) else arguments, 'keywordArguments': json.dumps(keyword_arguments) if (keyword_arguments is not None and not isinstance(keyword_arguments, str)) else keyword_arguments, 'deploymentConversationId': json.dumps(deployment_conversation_id) if (deployment_conversation_id is not None and not isinstance(deployment_conversation_id, str)) else deployment_conversation_id, 'externalSessionId': json.dumps(external_session_id) if (external_session_id is not None and not isinstance(external_session_id, str)) else external_session_id}, parse_type=AgentDataExecutionResult, files=blobs, server_override=prediction_url, timeout=1500) - def create_batch_prediction(self, deployment_id: str, table_name: str = None, name: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = False, output_format: str = None, output_location: str = None, database_connector_id: str = None, database_output_config: dict = None, refresh_schedule: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, input_feature_groups: dict = None) -> BatchPrediction: + def create_batch_prediction(self, deployment_id: str, table_name: str = None, name: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, batch_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = False, output_format: str = None, output_location: str = None, database_connector_id: str = None, database_output_config: dict = None, refresh_schedule: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, input_feature_groups: dict = None) -> BatchPrediction: """Creates a batch prediction job description for the given deployment. Args: deployment_id (str): Unique string identifier for the deployment. table_name (str): Name of the feature group table to write the results of the batch prediction. Can only be specified if outputLocation and databaseConnectorId are not specified. If tableName is specified, the outputType will be enforced as CSV. name (str): Name of the batch prediction job. - global_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. - explanations (bool): If true, SHAP explanations will be provided for each prediction, if supported by the use case. + batch_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. output_format (str): Format of the batch prediction output (CSV or JSON). output_location (str): Location to write the prediction results. Otherwise, results will be stored in Abacus.AI. database_connector_id (str): Unique identifier of a Database Connection to write predictions to. Cannot be specified in conjunction with outputLocation. @@ -6740,7 +6739,7 @@ def create_batch_prediction(self, deployment_id: str, table_name: str = None, na Returns: BatchPrediction: The batch prediction description.""" - return self._call_api('createBatchPrediction', 'POST', query_params={'deploymentId': deployment_id}, body={'tableName': table_name, 'name': name, 'globalPredictionArgs': global_prediction_args, 'explanations': explanations, 'outputFormat': output_format, 'outputLocation': output_location, 'databaseConnectorId': database_connector_id, 'databaseOutputConfig': database_output_config, 'refreshSchedule': refresh_schedule, 'csvInputPrefix': csv_input_prefix, 'csvPredictionPrefix': csv_prediction_prefix, 'csvExplanationsPrefix': csv_explanations_prefix, 'outputIncludesMetadata': output_includes_metadata, 'resultInputColumns': result_input_columns, 'inputFeatureGroups': input_feature_groups}, parse_type=BatchPrediction) + return self._call_api('createBatchPrediction', 'POST', query_params={'deploymentId': deployment_id}, body={'tableName': table_name, 'name': name, 'globalPredictionArgs': global_prediction_args, 'batchPredictionArgs': batch_prediction_args, 'explanations': explanations, 'outputFormat': output_format, 'outputLocation': output_location, 'databaseConnectorId': database_connector_id, 'databaseOutputConfig': database_output_config, 'refreshSchedule': refresh_schedule, 'csvInputPrefix': csv_input_prefix, 'csvPredictionPrefix': csv_prediction_prefix, 'csvExplanationsPrefix': csv_explanations_prefix, 'outputIncludesMetadata': output_includes_metadata, 'resultInputColumns': result_input_columns, 'inputFeatureGroups': input_feature_groups}, parse_type=BatchPrediction) def start_batch_prediction(self, batch_prediction_id: str) -> BatchPredictionVersion: """Creates a new batch prediction version job for a given batch prediction job description. @@ -6752,14 +6751,13 @@ def start_batch_prediction(self, batch_prediction_id: str) -> BatchPredictionVer BatchPredictionVersion: The batch prediction version started by this method call.""" return self._call_api('startBatchPrediction', 'POST', query_params={}, body={'batchPredictionId': batch_prediction_id}, parse_type=BatchPredictionVersion) - def update_batch_prediction(self, batch_prediction_id: str, deployment_id: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = None, output_format: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, name: str = None) -> BatchPrediction: + def update_batch_prediction(self, batch_prediction_id: str, deployment_id: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, batch_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = None, output_format: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, name: str = None) -> BatchPrediction: """Update a batch prediction job description. Args: batch_prediction_id (str): Unique identifier of the batch prediction. deployment_id (str): Unique identifier of the deployment. - global_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. - explanations (bool): If True, SHAP explanations for each prediction will be provided, if supported by the use case. + batch_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. output_format (str): If specified, sets the format of the batch prediction output (CSV or JSON). csv_input_prefix (str): Prefix to prepend to the input columns, only applies when output format is CSV. csv_prediction_prefix (str): Prefix to prepend to the prediction columns, only applies when output format is CSV. @@ -6770,7 +6768,7 @@ def update_batch_prediction(self, batch_prediction_id: str, deployment_id: str = Returns: BatchPrediction: The batch prediction.""" - return self._call_api('updateBatchPrediction', 'POST', query_params={'deploymentId': deployment_id}, body={'batchPredictionId': batch_prediction_id, 'globalPredictionArgs': global_prediction_args, 'explanations': explanations, 'outputFormat': output_format, 'csvInputPrefix': csv_input_prefix, 'csvPredictionPrefix': csv_prediction_prefix, 'csvExplanationsPrefix': csv_explanations_prefix, 'outputIncludesMetadata': output_includes_metadata, 'resultInputColumns': result_input_columns, 'name': name}, parse_type=BatchPrediction) + return self._call_api('updateBatchPrediction', 'POST', query_params={'deploymentId': deployment_id}, body={'batchPredictionId': batch_prediction_id, 'globalPredictionArgs': global_prediction_args, 'batchPredictionArgs': batch_prediction_args, 'explanations': explanations, 'outputFormat': output_format, 'csvInputPrefix': csv_input_prefix, 'csvPredictionPrefix': csv_prediction_prefix, 'csvExplanationsPrefix': csv_explanations_prefix, 'outputIncludesMetadata': output_includes_metadata, 'resultInputColumns': result_input_columns, 'name': name}, parse_type=BatchPrediction) def set_batch_prediction_file_connector_output(self, batch_prediction_id: str, output_format: str = None, output_location: str = None) -> BatchPrediction: """Updates the file connector output configuration of the batch prediction @@ -6983,19 +6981,7 @@ def append_multiple_data(self, feature_group_id: str, streaming_token: str, data streaming_token, feature_group_id=feature_group_id) return self._call_api('appendMultipleData', 'POST', query_params={'streamingToken': streaming_token}, body={'featureGroupId': feature_group_id, 'data': data}, server_override=prediction_url) - def upsert_data(self, feature_group_id: str, streaming_token: str = None, data: dict = None) -> FeatureGroupRow: - """Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. - - Args: - feature_group_id (str): A unique string identifier of the streaming feature group to record data to. - streaming_token (str): Optional streaming token for authenticating requests if upserting to streaming FG. - data (dict): The data to record, in JSON format. - - Returns: - FeatureGroupRow: The feature group row that was upserted.""" - return self._proxy_request('upsertData', 'POST', query_params={'streamingToken': streaming_token}, body={'featureGroupId': feature_group_id, 'data': data}, parse_type=FeatureGroupRow, is_sync=True) - - def upsert_online_data(self, feature_group_id: str, data: dict, streaming_token: str = None) -> FeatureGroupRow: + def upsert_data(self, feature_group_id: str, data: dict, streaming_token: str = None) -> FeatureGroupRow: """Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. Args: @@ -7005,7 +6991,7 @@ def upsert_online_data(self, feature_group_id: str, data: dict, streaming_token: Returns: FeatureGroupRow: The feature group row that was upserted.""" - return self._proxy_request('upsertOnlineData', 'POST', query_params={'streamingToken': streaming_token}, body={'featureGroupId': feature_group_id, 'data': data}, parse_type=FeatureGroupRow, is_sync=True) + return self._proxy_request('upsertData', 'POST', query_params={'streamingToken': streaming_token}, body={'featureGroupId': feature_group_id, 'data': data}, parse_type=FeatureGroupRow, is_sync=True) def delete_data(self, feature_group_id: str, primary_key: str): """Deletes a row from the feature group given the primary key @@ -7764,7 +7750,7 @@ def create_external_application(self, deployment_id: str, name: str = None, logo ExternalApplication: The newly created External Application.""" return self._call_api('createExternalApplication', 'POST', query_params={'deploymentId': deployment_id}, body={'name': name, 'logo': logo, 'theme': theme}, parse_type=ExternalApplication) - def update_external_application(self, external_application_id: str, name: str = None, theme: dict = None, deployment_id: str = None) -> ExternalApplication: + def update_external_application(self, external_application_id: str, name: str = None, theme: dict = None, deployment_id: str = None, deployment_conversation_retention_hours: int = None, reset_retention_policy: bool = False) -> ExternalApplication: """Updates an External Application. Args: @@ -7772,10 +7758,12 @@ def update_external_application(self, external_application_id: str, name: str = name (str): The name of the External Application. theme (dict): The visual theme of the External Application. deployment_id (str): The ID of the deployment to use. + deployment_conversation_retention_hours (int): The number of hours to retain the conversations for. + reset_retention_policy (bool): If true, the retention policy will be removed. Returns: ExternalApplication: The updated External Application.""" - return self._call_api('updateExternalApplication', 'POST', query_params={'deploymentId': deployment_id}, body={'externalApplicationId': external_application_id, 'name': name, 'theme': theme}, parse_type=ExternalApplication) + return self._call_api('updateExternalApplication', 'POST', query_params={'deploymentId': deployment_id}, body={'externalApplicationId': external_application_id, 'name': name, 'theme': theme, 'deploymentConversationRetentionHours': deployment_conversation_retention_hours, 'resetRetentionPolicy': reset_retention_policy}, parse_type=ExternalApplication) def delete_external_application(self, external_application_id: str): """Deletes an External Application. diff --git a/abacusai/dataset.py b/abacusai/dataset.py index 66352ca39..2c4d107ca 100644 --- a/abacusai/dataset.py +++ b/abacusai/dataset.py @@ -1,6 +1,6 @@ from typing import Union -from .api_class import DatasetConfig, DocumentProcessingConfig, ParsingConfig +from .api_class import DatasetConfig, DataType, DocumentProcessingConfig, ParsingConfig from .dataset_column import DatasetColumn from .dataset_version import DatasetVersion from .refresh_schedule import RefreshSchedule @@ -152,13 +152,13 @@ def snapshot_streaming_data(self): """ return self.client.snapshot_streaming_data(self.dataset_id) - def set_column_data_type(self, column: str, data_type: str): + def set_column_data_type(self, column: str, data_type: Union[dict, DataType]): """ Set a Dataset's column type. Args: column (str): The name of the column. - data_type (str): The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. + data_type (DataType): The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. Returns: Dataset: The dataset and schema after the data type has been set. diff --git a/abacusai/deployment.py b/abacusai/deployment.py index 96186fb2a..290b18207 100644 --- a/abacusai/deployment.py +++ b/abacusai/deployment.py @@ -334,15 +334,14 @@ def get_conversation_response_with_binary_data(self, deployment_token: str, mess """ return self.client.get_conversation_response_with_binary_data(self.deployment_id, deployment_token, message, deployment_conversation_id, external_session_id, llm_name, num_completion_tokens, system_message, temperature, filter_key_values, search_score_cutoff, chat_config, ignore_documents, attachments) - def create_batch_prediction(self, table_name: str = None, name: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = False, output_format: str = None, output_location: str = None, database_connector_id: str = None, database_output_config: dict = None, refresh_schedule: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, input_feature_groups: dict = None): + def create_batch_prediction(self, table_name: str = None, name: str = None, global_prediction_args: Union[dict, BatchPredictionArgs] = None, batch_prediction_args: Union[dict, BatchPredictionArgs] = None, explanations: bool = False, output_format: str = None, output_location: str = None, database_connector_id: str = None, database_output_config: dict = None, refresh_schedule: str = None, csv_input_prefix: str = None, csv_prediction_prefix: str = None, csv_explanations_prefix: str = None, output_includes_metadata: bool = None, result_input_columns: list = None, input_feature_groups: dict = None): """ Creates a batch prediction job description for the given deployment. Args: table_name (str): Name of the feature group table to write the results of the batch prediction. Can only be specified if outputLocation and databaseConnectorId are not specified. If tableName is specified, the outputType will be enforced as CSV. name (str): Name of the batch prediction job. - global_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. - explanations (bool): If true, SHAP explanations will be provided for each prediction, if supported by the use case. + batch_prediction_args (BatchPredictionArgs): Batch Prediction args specific to problem type. output_format (str): Format of the batch prediction output (CSV or JSON). output_location (str): Location to write the prediction results. Otherwise, results will be stored in Abacus.AI. database_connector_id (str): Unique identifier of a Database Connection to write predictions to. Cannot be specified in conjunction with outputLocation. @@ -358,7 +357,7 @@ def create_batch_prediction(self, table_name: str = None, name: str = None, glob Returns: BatchPrediction: The batch prediction description. """ - return self.client.create_batch_prediction(self.deployment_id, table_name, name, global_prediction_args, explanations, output_format, output_location, database_connector_id, database_output_config, refresh_schedule, csv_input_prefix, csv_prediction_prefix, csv_explanations_prefix, output_includes_metadata, result_input_columns, input_feature_groups) + return self.client.create_batch_prediction(self.deployment_id, table_name, name, global_prediction_args, batch_prediction_args, explanations, output_format, output_location, database_connector_id, database_output_config, refresh_schedule, csv_input_prefix, csv_prediction_prefix, csv_explanations_prefix, output_includes_metadata, result_input_columns, input_feature_groups) def describe_feature_group_row_process_by_key(self, primary_key_value: str): """ diff --git a/abacusai/document_retriever_config.py b/abacusai/document_retriever_config.py index 4a58867be..c4b695d60 100644 --- a/abacusai/document_retriever_config.py +++ b/abacusai/document_retriever_config.py @@ -11,18 +11,20 @@ class DocumentRetrieverConfig(AbstractApiClass): chunkSize (int): The size of chunks for vector store, i.e., maximum number of words in the chunk. chunkOverlapFraction (float): The fraction of overlap between two consecutive chunks. textEncoder (str): The text encoder used to encode texts in the vector store. + scoreMultiplierColumn (str): The values in this metadata column are used to modify the relevance scores of returned chunks. """ - def __init__(self, client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None): + def __init__(self, client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None, scoreMultiplierColumn=None): super().__init__(client, None) self.chunk_size = chunkSize self.chunk_overlap_fraction = chunkOverlapFraction self.text_encoder = textEncoder + self.score_multiplier_column = scoreMultiplierColumn self.deprecated_keys = {} def __repr__(self): - repr_dict = {f'chunk_size': repr(self.chunk_size), f'chunk_overlap_fraction': repr( - self.chunk_overlap_fraction), f'text_encoder': repr(self.text_encoder)} + repr_dict = {f'chunk_size': repr(self.chunk_size), f'chunk_overlap_fraction': repr(self.chunk_overlap_fraction), f'text_encoder': repr( + self.text_encoder), f'score_multiplier_column': repr(self.score_multiplier_column)} class_name = "DocumentRetrieverConfig" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -35,6 +37,6 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'chunk_size': self.chunk_size, 'chunk_overlap_fraction': - self.chunk_overlap_fraction, 'text_encoder': self.text_encoder} + resp = {'chunk_size': self.chunk_size, 'chunk_overlap_fraction': self.chunk_overlap_fraction, + 'text_encoder': self.text_encoder, 'score_multiplier_column': self.score_multiplier_column} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} diff --git a/abacusai/external_application.py b/abacusai/external_application.py index e292e5d5e..069ab4644 100644 --- a/abacusai/external_application.py +++ b/abacusai/external_application.py @@ -15,9 +15,10 @@ class ExternalApplication(AbstractApiClass): userGroupIds (list): A list of App User Groups with access to this external application useCase (str): Use Case of the project of this deployment status (str): The status of the deployment. + deploymentConversationRetentionHours (int): The retention policy for the external application. """ - def __init__(self, client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None): + def __init__(self, client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None, deploymentConversationRetentionHours=None): super().__init__(client, externalApplicationId) self.name = name self.external_application_id = externalApplicationId @@ -27,11 +28,12 @@ def __init__(self, client, name=None, externalApplicationId=None, deploymentId=N self.user_group_ids = userGroupIds self.use_case = useCase self.status = status + self.deployment_conversation_retention_hours = deploymentConversationRetentionHours self.deprecated_keys = {} def __repr__(self): - repr_dict = {f'name': repr(self.name), f'external_application_id': repr(self.external_application_id), f'deployment_id': repr(self.deployment_id), f'logo': repr( - self.logo), f'theme': repr(self.theme), f'user_group_ids': repr(self.user_group_ids), f'use_case': repr(self.use_case), f'status': repr(self.status)} + repr_dict = {f'name': repr(self.name), f'external_application_id': repr(self.external_application_id), f'deployment_id': repr(self.deployment_id), f'logo': repr(self.logo), f'theme': repr( + self.theme), f'user_group_ids': repr(self.user_group_ids), f'use_case': repr(self.use_case), f'status': repr(self.status), f'deployment_conversation_retention_hours': repr(self.deployment_conversation_retention_hours)} class_name = "ExternalApplication" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -44,11 +46,11 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'name': self.name, 'external_application_id': self.external_application_id, 'deployment_id': self.deployment_id, - 'logo': self.logo, 'theme': self.theme, 'user_group_ids': self.user_group_ids, 'use_case': self.use_case, 'status': self.status} + resp = {'name': self.name, 'external_application_id': self.external_application_id, 'deployment_id': self.deployment_id, 'logo': self.logo, 'theme': self.theme, + 'user_group_ids': self.user_group_ids, 'use_case': self.use_case, 'status': self.status, 'deployment_conversation_retention_hours': self.deployment_conversation_retention_hours} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} - def update(self, name: str = None, theme: dict = None, deployment_id: str = None): + def update(self, name: str = None, theme: dict = None, deployment_id: str = None, deployment_conversation_retention_hours: int = None, reset_retention_policy: bool = False): """ Updates an External Application. @@ -56,11 +58,13 @@ def update(self, name: str = None, theme: dict = None, deployment_id: str = None name (str): The name of the External Application. theme (dict): The visual theme of the External Application. deployment_id (str): The ID of the deployment to use. + deployment_conversation_retention_hours (int): The number of hours to retain the conversations for. + reset_retention_policy (bool): If true, the retention policy will be removed. Returns: ExternalApplication: The updated External Application. """ - return self.client.update_external_application(self.external_application_id, name, theme, deployment_id) + return self.client.update_external_application(self.external_application_id, name, theme, deployment_id, deployment_conversation_retention_hours, reset_retention_policy) def refresh(self): """ diff --git a/abacusai/feature_group.py b/abacusai/feature_group.py index fe36b166e..21c19ac27 100644 --- a/abacusai/feature_group.py +++ b/abacusai/feature_group.py @@ -1049,20 +1049,7 @@ def append_multiple_data(self, streaming_token: str, data: list): """ return self.client.append_multiple_data(self.feature_group_id, streaming_token, data) - def upsert_data(self, streaming_token: str = None, data: dict = None): - """ - Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. - - Args: - streaming_token (str): Optional streaming token for authenticating requests if upserting to streaming FG. - data (dict): The data to record, in JSON format. - - Returns: - FeatureGroupRow: The feature group row that was upserted. - """ - return self.client.upsert_data(self.feature_group_id, streaming_token, data) - - def upsert_online_data(self, data: dict, streaming_token: str = None): + def upsert_data(self, data: dict, streaming_token: str = None): """ Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. @@ -1073,7 +1060,7 @@ def upsert_online_data(self, data: dict, streaming_token: str = None): Returns: FeatureGroupRow: The feature group row that was upserted. """ - return self.client.upsert_online_data(self.feature_group_id, data, streaming_token) + return self.client.upsert_data(self.feature_group_id, data, streaming_token) def delete_data(self, primary_key: str): """ diff --git a/abacusai/feature_group_export.py b/abacusai/feature_group_export.py index d2769efef..47780ea53 100644 --- a/abacusai/feature_group_export.py +++ b/abacusai/feature_group_export.py @@ -140,7 +140,3 @@ def get_status(self): str: A string describing the status of a feature group export (pending, complete, etc.). """ return self.describe().status - - # to be deleted - def get_results(self): - return self.client.get_export_result(self.feature_group_export_id) diff --git a/abacusai/pipeline.py b/abacusai/pipeline.py index be5b16e73..6bb5f7b9d 100644 --- a/abacusai/pipeline.py +++ b/abacusai/pipeline.py @@ -1,3 +1,4 @@ +from .api_class import PythonFunctionArgument from .code_source import CodeSource from .pipeline_reference import PipelineReference from .pipeline_step import PipelineStep @@ -14,7 +15,6 @@ class Pipeline(AbstractApiClass): pipelineName (str): The name of the pipeline this step is a part of. pipelineId (str): The reference to the pipeline this step belongs to. createdAt (str): The date and time which the pipeline was created. - pipelineVariableMappings (dict): A description of the function variables into the pipeline. notebookId (str): The reference to the notebook this pipeline belongs to. cron (str): A cron-style string that describes when this refresh policy is to be executed in UTC nextRunTime (str): The next time this pipeline will be run. @@ -27,12 +27,11 @@ class Pipeline(AbstractApiClass): codeSource (CodeSource): information on the source code """ - def __init__(self, client, pipelineName=None, pipelineId=None, createdAt=None, pipelineVariableMappings=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={}): + def __init__(self, client, pipelineName=None, pipelineId=None, createdAt=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={}, pipelineVariableMappings={}): super().__init__(client, pipelineId) self.pipeline_name = pipelineName self.pipeline_id = pipelineId self.created_at = createdAt - self.pipeline_variable_mappings = pipelineVariableMappings self.notebook_id = notebookId self.cron = cron self.next_run_time = nextRunTime @@ -45,11 +44,13 @@ def __init__(self, client, pipelineName=None, pipelineId=None, createdAt=None, p self.latest_pipeline_version = client._build_class( PipelineVersion, latestPipelineVersion) self.code_source = client._build_class(CodeSource, codeSource) + self.pipeline_variable_mappings = client._build_class( + PythonFunctionArgument, pipelineVariableMappings) self.deprecated_keys = {} def __repr__(self): - repr_dict = {f'pipeline_name': repr(self.pipeline_name), f'pipeline_id': repr(self.pipeline_id), f'created_at': repr(self.created_at), f'pipeline_variable_mappings': repr(self.pipeline_variable_mappings), f'notebook_id': repr(self.notebook_id), f'cron': repr(self.cron), f'next_run_time': repr( - self.next_run_time), f'is_prod': repr(self.is_prod), f'warning': repr(self.warning), f'created_by': repr(self.created_by), f'steps': repr(self.steps), f'pipeline_references': repr(self.pipeline_references), f'latest_pipeline_version': repr(self.latest_pipeline_version), f'code_source': repr(self.code_source)} + repr_dict = {f'pipeline_name': repr(self.pipeline_name), f'pipeline_id': repr(self.pipeline_id), f'created_at': repr(self.created_at), f'notebook_id': repr(self.notebook_id), f'cron': repr(self.cron), f'next_run_time': repr(self.next_run_time), f'is_prod': repr(self.is_prod), f'warning': repr( + self.warning), f'created_by': repr(self.created_by), f'steps': repr(self.steps), f'pipeline_references': repr(self.pipeline_references), f'latest_pipeline_version': repr(self.latest_pipeline_version), f'code_source': repr(self.code_source), f'pipeline_variable_mappings': repr(self.pipeline_variable_mappings)} class_name = "Pipeline" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -62,8 +63,8 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'pipeline_name': self.pipeline_name, 'pipeline_id': self.pipeline_id, 'created_at': self.created_at, 'pipeline_variable_mappings': self.pipeline_variable_mappings, 'notebook_id': self.notebook_id, 'cron': self.cron, 'next_run_time': self.next_run_time, 'is_prod': self.is_prod, 'warning': self.warning, - 'created_by': self.created_by, 'steps': self._get_attribute_as_dict(self.steps), 'pipeline_references': self._get_attribute_as_dict(self.pipeline_references), 'latest_pipeline_version': self._get_attribute_as_dict(self.latest_pipeline_version), 'code_source': self._get_attribute_as_dict(self.code_source)} + resp = {'pipeline_name': self.pipeline_name, 'pipeline_id': self.pipeline_id, 'created_at': self.created_at, 'notebook_id': self.notebook_id, 'cron': self.cron, 'next_run_time': self.next_run_time, 'is_prod': self.is_prod, 'warning': self.warning, 'created_by': self.created_by, 'steps': self._get_attribute_as_dict( + self.steps), 'pipeline_references': self._get_attribute_as_dict(self.pipeline_references), 'latest_pipeline_version': self._get_attribute_as_dict(self.latest_pipeline_version), 'code_source': self._get_attribute_as_dict(self.code_source), 'pipeline_variable_mappings': self._get_attribute_as_dict(self.pipeline_variable_mappings)} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} def refresh(self): diff --git a/abacusai/pipeline_version.py b/abacusai/pipeline_version.py index 29e40f6ba..d4ca29268 100644 --- a/abacusai/pipeline_version.py +++ b/abacusai/pipeline_version.py @@ -1,3 +1,4 @@ +from .api_class import PythonFunctionArgument from .code_source import CodeSource from .pipeline_step_version import PipelineStepVersion from .return_class import AbstractApiClass @@ -17,12 +18,11 @@ class PipelineVersion(AbstractApiClass): completedAt (str): The date and time which this pipeline version was updated. status (str): The status of the pipeline version. error (str): The relevant error, if the status is FAILED. - pipelineVariableMappings (dict): A description of the function variables into the pipeline. stepVersions (PipelineStepVersion): A list of the pipeline step versions. codeSource (CodeSource): information on the source code """ - def __init__(self, client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, pipelineVariableMappings=None, stepVersions={}, codeSource={}): + def __init__(self, client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, stepVersions={}, codeSource={}, pipelineVariableMappings={}): super().__init__(client, pipelineVersion) self.pipeline_name = pipelineName self.pipeline_id = pipelineId @@ -32,15 +32,16 @@ def __init__(self, client, pipelineName=None, pipelineId=None, pipelineVersion=N self.completed_at = completedAt self.status = status self.error = error - self.pipeline_variable_mappings = pipelineVariableMappings self.step_versions = client._build_class( PipelineStepVersion, stepVersions) self.code_source = client._build_class(CodeSource, codeSource) + self.pipeline_variable_mappings = client._build_class( + PythonFunctionArgument, pipelineVariableMappings) self.deprecated_keys = {} def __repr__(self): repr_dict = {f'pipeline_name': repr(self.pipeline_name), f'pipeline_id': repr(self.pipeline_id), f'pipeline_version': repr(self.pipeline_version), f'created_at': repr(self.created_at), f'updated_at': repr(self.updated_at), f'completed_at': repr( - self.completed_at), f'status': repr(self.status), f'error': repr(self.error), f'pipeline_variable_mappings': repr(self.pipeline_variable_mappings), f'step_versions': repr(self.step_versions), f'code_source': repr(self.code_source)} + self.completed_at), f'status': repr(self.status), f'error': repr(self.error), f'step_versions': repr(self.step_versions), f'code_source': repr(self.code_source), f'pipeline_variable_mappings': repr(self.pipeline_variable_mappings)} class_name = "PipelineVersion" repr_str = ',\n '.join([f'{key}={value}' for key, value in repr_dict.items( ) if getattr(self, key, None) is not None and key not in self.deprecated_keys]) @@ -53,8 +54,8 @@ def to_dict(self): Returns: dict: The dict value representation of the class parameters """ - resp = {'pipeline_name': self.pipeline_name, 'pipeline_id': self.pipeline_id, 'pipeline_version': self.pipeline_version, 'created_at': self.created_at, 'updated_at': self.updated_at, 'completed_at': self.completed_at, - 'status': self.status, 'error': self.error, 'pipeline_variable_mappings': self.pipeline_variable_mappings, 'step_versions': self._get_attribute_as_dict(self.step_versions), 'code_source': self._get_attribute_as_dict(self.code_source)} + resp = {'pipeline_name': self.pipeline_name, 'pipeline_id': self.pipeline_id, 'pipeline_version': self.pipeline_version, 'created_at': self.created_at, 'updated_at': self.updated_at, 'completed_at': self.completed_at, 'status': self.status, + 'error': self.error, 'step_versions': self._get_attribute_as_dict(self.step_versions), 'code_source': self._get_attribute_as_dict(self.code_source), 'pipeline_variable_mappings': self._get_attribute_as_dict(self.pipeline_variable_mappings)} return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys} def refresh(self): diff --git a/abacusai/project.py b/abacusai/project.py index 732934b8f..749040bc6 100644 --- a/abacusai/project.py +++ b/abacusai/project.py @@ -643,28 +643,6 @@ def list_document_retrievers(self, limit: int = 100, start_after_id: str = None) """ return self.client.list_document_retrievers(self.project_id, limit, start_after_id) - def attach_dataset(self, dataset_id, project_dataset_type): - """ - Attaches dataset to the project. - - Args: - dataset_id (unique string identifier): A unique identifier for the dataset. - project_dataset_type (enum of type string): The unique use case specific dataset type that might be required or recommended for the specific use case. - - Returns: - Schema: The schema of the attached dataset. - """ - return self.client.attach_dataset_to_project(dataset_id, self.project_id, project_dataset_type) - - def remove_dataset(self, dataset_id): - """ - Removes dataset from the project. - - Args: - dataset_id (unique string identifier): A unique identifier for the dataset. - """ - return self.client.remove_dataset_from_project(dataset_id, self.project_id) - def create_model_from_functions(self, train_function: callable, predict_function: callable = None, training_input_tables: list = None, predict_many_function: callable = None, initialize_function: callable = None, cpu_size: str = None, memory: int = None, training_config: dict = None, exclusive_run: bool = False): """ Creates a model using python. diff --git a/abacusai/public.pem b/abacusai/public.pem index 21352214d..2c1ac3929 100644 --- a/abacusai/public.pem +++ b/abacusai/public.pem @@ -1,5 +1,5 @@ -----BEGIN RSA PUBLIC KEY----- -MIGJAoGBAMIl9DR1FJ2VDzIn4ywL93//RDkAQD+ll92RSmqJ7FpwJP0Uzd+a5wvC -4n9Y7xRvDuLF88qVDwZx4/SCdn8E8QKg1Avn5j8WF3SDjYH/3oLOHHyUDX3zYYsN -5RCfwHb2ErmvtFvZf+6i/diSTUxypy7+szQnDB2y2FbbSMMGnHwbAgMBAAE= +MIGJAoGBAJDNVZuidY2kTpX1JCqE/T4cVZ3NVjm29QMrkPqsvgNS1joltn0wCGi/ +cw/TLAgvbSIf3YiYRPKGTHhVxhIS6lWFc9O8WaD+8eWW/Mv/m0QWUr6RW3bCYArd +gyyRURjK4cFGkHzpnFkwc7424MVj8FliJVbDg7W6PuBJAuduC7FtAgMBAAE= -----END RSA PUBLIC KEY----- diff --git a/docs/_sources/autoapi/abacusai/api_class/batch_prediction/index.rst.txt b/docs/_sources/autoapi/abacusai/api_class/batch_prediction/index.rst.txt index 52d494a37..96c9ad382 100644 --- a/docs/_sources/autoapi/abacusai/api_class/batch_prediction/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/api_class/batch_prediction/index.rst.txt @@ -22,6 +22,7 @@ Classes abacusai.api_class.batch_prediction.SentenceBoundaryDetectionBatchPredictionArgs abacusai.api_class.batch_prediction.ThemeAnalysisBatchPredictionArgs abacusai.api_class.batch_prediction.ChatLLMBatchPredictionArgs + abacusai.api_class.batch_prediction.TrainablePlugAndPlayBatchPredictionArgs abacusai.api_class.batch_prediction._BatchPredictionArgsFactory @@ -66,6 +67,8 @@ Classes :type for_eval: bool :param threshold: The threshold for detecting an anomaly. Range: [0.8, 0.99] :type threshold: float + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool .. py:attribute:: for_eval :type: bool @@ -77,6 +80,11 @@ Classes + .. py:attribute:: explain_predictions + :type: bool + + + .. py:method:: __post_init__() @@ -100,8 +108,10 @@ Classes :type forecasting_horizon: int :param item_attributes_to_include_in_the_result: List of columns to include in the prediction output. :type item_attributes_to_include_in_the_result: list - :param explain_predictions: If True, explain predictions for the forecast. + :param explain_predictions: If True, calculates explanations for the forecasted values along with predictions. :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -138,6 +148,11 @@ Classes + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -235,6 +250,10 @@ Classes :type bound_label: str :param output_columns: A list of column names to include in the prediction result. :type output_columns: list + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -286,6 +305,16 @@ Classes + .. py:attribute:: explain_predictions + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -408,6 +437,30 @@ Classes +.. py:class:: TrainablePlugAndPlayBatchPredictionArgs + + + Bases: :py:obj:`BatchPredictionArgs` + + Batch Prediction Config for the TrainablePlugAndPlay problem type + + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool + + .. py:attribute:: for_eval + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + + .. py:method:: __post_init__() + + + .. py:class:: _BatchPredictionArgsFactory diff --git a/docs/_sources/autoapi/abacusai/api_class/document_retriever/index.rst.txt b/docs/_sources/autoapi/abacusai/api_class/document_retriever/index.rst.txt index 280083e90..9391e963f 100644 --- a/docs/_sources/autoapi/abacusai/api_class/document_retriever/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/api_class/document_retriever/index.rst.txt @@ -33,6 +33,8 @@ Classes :type text_encoder: VectorStoreTextEncoder :param chunk_size_factors: Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to `chunk_size`. :type chunk_size_factors: list + :param score_multiplier_column: If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries. + :type score_multiplier_column: str .. py:attribute:: chunk_size :type: int @@ -54,6 +56,11 @@ Classes + .. py:attribute:: score_multiplier_column + :type: str + + + .. py:class:: DocumentRetrieverConfig diff --git a/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt b/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt index f4d27dceb..017f1788e 100644 --- a/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt @@ -61,6 +61,7 @@ Classes abacusai.api_class.enums.EvalArtifactType abacusai.api_class.enums.FieldDescriptorType abacusai.api_class.enums.OcrMode + abacusai.api_class.enums.DataType @@ -1544,6 +1545,11 @@ Classes + .. py:attribute:: MICROSOFTAUTH + :value: 'MICROSOFTAUTH' + + + .. py:class:: PythonFunctionArgumentType @@ -2110,3 +2116,62 @@ Classes +.. py:class:: DataType + + + Bases: :py:obj:`ApiEnum` + + Generic enumeration. + + Derive from this class to define new enumerations. + + .. py:attribute:: INTEGER + :value: 'integer' + + + + .. py:attribute:: FLOAT + :value: 'float' + + + + .. py:attribute:: STRING + :value: 'string' + + + + .. py:attribute:: DATE + :value: 'date' + + + + .. py:attribute:: DATETIME + :value: 'datetime' + + + + .. py:attribute:: BOOLEAN + :value: 'boolean' + + + + .. py:attribute:: LIST + :value: 'list' + + + + .. py:attribute:: STRUCT + :value: 'struct' + + + + .. py:attribute:: NULL + :value: 'null' + + + + .. py:method:: from_str(value) + :classmethod: + + + diff --git a/docs/_sources/autoapi/abacusai/api_class/index.rst.txt b/docs/_sources/autoapi/abacusai/api_class/index.rst.txt index 88cd4130e..e42d4c41b 100644 --- a/docs/_sources/autoapi/abacusai/api_class/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/api_class/index.rst.txt @@ -52,6 +52,7 @@ Classes abacusai.api_class.SentenceBoundaryDetectionBatchPredictionArgs abacusai.api_class.ThemeAnalysisBatchPredictionArgs abacusai.api_class.ChatLLMBatchPredictionArgs + abacusai.api_class.TrainablePlugAndPlayBatchPredictionArgs abacusai.api_class._BatchPredictionArgsFactory abacusai.api_class.ApiClass abacusai.api_class.BlobInput @@ -125,6 +126,7 @@ Classes abacusai.api_class.EvalArtifactType abacusai.api_class.FieldDescriptorType abacusai.api_class.OcrMode + abacusai.api_class.DataType abacusai.api_class.ApiClass abacusai.api_class._ApiClassFactory abacusai.api_class.SamplingConfig @@ -498,6 +500,8 @@ Classes :type for_eval: bool :param threshold: The threshold for detecting an anomaly. Range: [0.8, 0.99] :type threshold: float + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool .. py:attribute:: for_eval :type: bool @@ -509,6 +513,11 @@ Classes + .. py:attribute:: explain_predictions + :type: bool + + + .. py:method:: __post_init__() @@ -532,8 +541,10 @@ Classes :type forecasting_horizon: int :param item_attributes_to_include_in_the_result: List of columns to include in the prediction output. :type item_attributes_to_include_in_the_result: list - :param explain_predictions: If True, explain predictions for the forecast. + :param explain_predictions: If True, calculates explanations for the forecasted values along with predictions. :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -570,6 +581,11 @@ Classes + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -667,6 +683,10 @@ Classes :type bound_label: str :param output_columns: A list of column names to include in the prediction result. :type output_columns: list + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -718,6 +738,16 @@ Classes + .. py:attribute:: explain_predictions + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -840,6 +870,30 @@ Classes +.. py:class:: TrainablePlugAndPlayBatchPredictionArgs + + + Bases: :py:obj:`BatchPredictionArgs` + + Batch Prediction Config for the TrainablePlugAndPlay problem type + + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool + + .. py:attribute:: for_eval + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + + .. py:method:: __post_init__() + + + .. py:class:: _BatchPredictionArgsFactory @@ -1661,6 +1715,8 @@ Classes :type text_encoder: VectorStoreTextEncoder :param chunk_size_factors: Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to `chunk_size`. :type chunk_size_factors: list + :param score_multiplier_column: If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries. + :type score_multiplier_column: str .. py:attribute:: chunk_size :type: int @@ -1682,6 +1738,11 @@ Classes + .. py:attribute:: score_multiplier_column + :type: str + + + .. py:class:: DocumentRetrieverConfig @@ -3170,6 +3231,11 @@ Classes + .. py:attribute:: MICROSOFTAUTH + :value: 'MICROSOFTAUTH' + + + .. py:class:: PythonFunctionArgumentType @@ -3736,6 +3802,65 @@ Classes +.. py:class:: DataType + + + Bases: :py:obj:`ApiEnum` + + Generic enumeration. + + Derive from this class to define new enumerations. + + .. py:attribute:: INTEGER + :value: 'integer' + + + + .. py:attribute:: FLOAT + :value: 'float' + + + + .. py:attribute:: STRING + :value: 'string' + + + + .. py:attribute:: DATE + :value: 'date' + + + + .. py:attribute:: DATETIME + :value: 'datetime' + + + + .. py:attribute:: BOOLEAN + :value: 'boolean' + + + + .. py:attribute:: LIST + :value: 'list' + + + + .. py:attribute:: STRUCT + :value: 'struct' + + + + .. py:attribute:: NULL + :value: 'null' + + + + .. py:method:: from_str(value) + :classmethod: + + + .. py:class:: ApiClass @@ -5337,6 +5462,8 @@ Classes :type disable_data_summarization: bool :param search_score_cutoff: Minimum search score to consider a document as a valid search result. :type search_score_cutoff: float + :param database_connector_id: Database connector id to use for the chatllm. + :type database_connector_id: str .. py:attribute:: document_retrievers :type: List[str] @@ -5408,6 +5535,11 @@ Classes + .. py:attribute:: database_connector_id + :type: str + + + .. py:method:: __post_init__() diff --git a/docs/_sources/autoapi/abacusai/api_class/model/index.rst.txt b/docs/_sources/autoapi/abacusai/api_class/model/index.rst.txt index e51c62319..ef9f548d0 100644 --- a/docs/_sources/autoapi/abacusai/api_class/model/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/api_class/model/index.rst.txt @@ -1268,6 +1268,8 @@ Classes :type disable_data_summarization: bool :param search_score_cutoff: Minimum search score to consider a document as a valid search result. :type search_score_cutoff: float + :param database_connector_id: Database connector id to use for the chatllm. + :type database_connector_id: str .. py:attribute:: document_retrievers :type: List[str] @@ -1339,6 +1341,11 @@ Classes + .. py:attribute:: database_connector_id + :type: str + + + .. py:method:: __post_init__() diff --git a/docs/_sources/autoapi/abacusai/batch_prediction/index.rst.txt b/docs/_sources/autoapi/abacusai/batch_prediction/index.rst.txt index c4a3e771a..a76d45c57 100644 --- a/docs/_sources/autoapi/abacusai/batch_prediction/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/batch_prediction/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: BatchPrediction(client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={}) +.. py:class:: BatchPrediction(client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={}) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -40,7 +40,7 @@ Classes :type databaseConnectorId: str :param databaseOutputConfiguration: Contains information about where the batch predictions are written to. :type databaseOutputConfiguration: dict - :param explanations: If true, explanations for each prediction will be created. + :param explanations: :type explanations: bool :param fileOutputFormat: The format of the batch prediction output (CSV or JSON). :type fileOutputFormat: str @@ -48,7 +48,7 @@ Classes :type connectorType: str :param legacyInputLocation: The location of the input data. :type legacyInputLocation: str - :param outputFeatureGroupId: The BP output feature group id if applicable + :param outputFeatureGroupId: The Batch Prediction output feature group ID if applicable :type outputFeatureGroupId: str :param featureGroupTableName: The table name of the Batch Prediction output feature group. :type featureGroupTableName: str @@ -137,16 +137,14 @@ Classes :rtype: list[BatchPredictionVersion] - .. py:method:: update(deployment_id = None, global_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) + .. py:method:: update(deployment_id = None, global_prediction_args = None, batch_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) Update a batch prediction job description. :param deployment_id: Unique identifier of the deployment. :type deployment_id: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If True, SHAP explanations for each prediction will be provided, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: If specified, sets the format of the batch prediction output (CSV or JSON). :type output_format: str :param csv_input_prefix: Prefix to prepend to the input columns, only applies when output format is CSV. diff --git a/docs/_sources/autoapi/abacusai/batch_prediction_version/index.rst.txt b/docs/_sources/autoapi/abacusai/batch_prediction_version/index.rst.txt index e7d900498..b76d072ad 100644 --- a/docs/_sources/autoapi/abacusai/batch_prediction_version/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/batch_prediction_version/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: BatchPredictionVersion(client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}) +.. py:class:: BatchPredictionVersion(client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={}) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -54,7 +54,7 @@ Classes :type databaseConnectorId: str :param databaseOutputConfiguration: Contains information about where the batch predictions are written to :type databaseOutputConfiguration: dict - :param explanations: If true, explanations for each prediction were created + :param explanations: :type explanations: bool :param fileConnectorOutputLocation: Contains information about where the batch predictions are written to :type fileConnectorOutputLocation: str @@ -90,11 +90,11 @@ Classes :type algoName: str :param algorithm: The algorithm that is currently deployed. :type algorithm: str - :param outputFeatureGroupId: The BP output feature group id if applicable + :param outputFeatureGroupId: The Batch Prediction output feature group ID if applicable :type outputFeatureGroupId: str - :param outputFeatureGroupVersion: The BP output feature group version if applicable + :param outputFeatureGroupVersion: The Batch Prediction output feature group version if applicable :type outputFeatureGroupVersion: str - :param outputFeatureGroupTableName: The BP output feature group name if applicable + :param outputFeatureGroupTableName: The Batch Prediction output feature group name if applicable :type outputFeatureGroupTableName: str :param batchPredictionWarnings: Relevant warnings if any issues are found :type batchPredictionWarnings: str diff --git a/docs/_sources/autoapi/abacusai/client/index.rst.txt b/docs/_sources/autoapi/abacusai/client/index.rst.txt index 80cc570e0..7e25cc3bd 100644 --- a/docs/_sources/autoapi/abacusai/client/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/client/index.rst.txt @@ -487,7 +487,7 @@ Attributes :type skip_version_check: bool .. py:attribute:: client_version - :value: '1.1.5' + :value: '1.1.6' @@ -5084,7 +5084,7 @@ Attributes :param column: The name of the column. :type column: str :param data_type: The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. - :type data_type: str + :type data_type: DataType :returns: The dataset and schema after the data type has been set. :rtype: Dataset @@ -7267,7 +7267,7 @@ Attributes :rtype: AgentDataExecutionResult - .. py:method:: create_batch_prediction(deployment_id, table_name = None, name = None, global_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) + .. py:method:: create_batch_prediction(deployment_id, table_name = None, name = None, global_prediction_args = None, batch_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) Creates a batch prediction job description for the given deployment. @@ -7277,10 +7277,8 @@ Attributes :type table_name: str :param name: Name of the batch prediction job. :type name: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If true, SHAP explanations will be provided for each prediction, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: Format of the batch prediction output (CSV or JSON). :type output_format: str :param output_location: Location to write the prediction results. Otherwise, results will be stored in Abacus.AI. @@ -7319,7 +7317,7 @@ Attributes :rtype: BatchPredictionVersion - .. py:method:: update_batch_prediction(batch_prediction_id, deployment_id = None, global_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) + .. py:method:: update_batch_prediction(batch_prediction_id, deployment_id = None, global_prediction_args = None, batch_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) Update a batch prediction job description. @@ -7327,10 +7325,8 @@ Attributes :type batch_prediction_id: str :param deployment_id: Unique identifier of the deployment. :type deployment_id: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If True, SHAP explanations for each prediction will be provided, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: If specified, sets the format of the batch prediction output (CSV or JSON). :type output_format: str :param csv_input_prefix: Prefix to prepend to the input columns, only applies when output format is CSV. @@ -7610,22 +7606,7 @@ Attributes :type data: list - .. py:method:: upsert_data(feature_group_id, streaming_token = None, data = None) - - Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. - - :param feature_group_id: A unique string identifier of the streaming feature group to record data to. - :type feature_group_id: str - :param streaming_token: Optional streaming token for authenticating requests if upserting to streaming FG. - :type streaming_token: str - :param data: The data to record, in JSON format. - :type data: dict - - :returns: The feature group row that was upserted. - :rtype: FeatureGroupRow - - - .. py:method:: upsert_online_data(feature_group_id, data, streaming_token = None) + .. py:method:: upsert_data(feature_group_id, data, streaming_token = None) Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. @@ -8599,7 +8580,7 @@ Attributes :rtype: ExternalApplication - .. py:method:: update_external_application(external_application_id, name = None, theme = None, deployment_id = None) + .. py:method:: update_external_application(external_application_id, name = None, theme = None, deployment_id = None, deployment_conversation_retention_hours = None, reset_retention_policy = False) Updates an External Application. @@ -8611,6 +8592,10 @@ Attributes :type theme: dict :param deployment_id: The ID of the deployment to use. :type deployment_id: str + :param deployment_conversation_retention_hours: The number of hours to retain the conversations for. + :type deployment_conversation_retention_hours: int + :param reset_retention_policy: If true, the retention policy will be removed. + :type reset_retention_policy: bool :returns: The updated External Application. :rtype: ExternalApplication diff --git a/docs/_sources/autoapi/abacusai/dataset/index.rst.txt b/docs/_sources/autoapi/abacusai/dataset/index.rst.txt index feb858401..f39a3add0 100644 --- a/docs/_sources/autoapi/abacusai/dataset/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/dataset/index.rst.txt @@ -158,7 +158,7 @@ Classes :param column: The name of the column. :type column: str :param data_type: The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. - :type data_type: str + :type data_type: DataType :returns: The dataset and schema after the data type has been set. :rtype: Dataset diff --git a/docs/_sources/autoapi/abacusai/deployment/index.rst.txt b/docs/_sources/autoapi/abacusai/deployment/index.rst.txt index 84ab328ee..470ef6d7e 100644 --- a/docs/_sources/autoapi/abacusai/deployment/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/deployment/index.rst.txt @@ -351,7 +351,7 @@ Classes :type attachments: None - .. py:method:: create_batch_prediction(table_name = None, name = None, global_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) + .. py:method:: create_batch_prediction(table_name = None, name = None, global_prediction_args = None, batch_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) Creates a batch prediction job description for the given deployment. @@ -359,10 +359,8 @@ Classes :type table_name: str :param name: Name of the batch prediction job. :type name: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If true, SHAP explanations will be provided for each prediction, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: Format of the batch prediction output (CSV or JSON). :type output_format: str :param output_location: Location to write the prediction results. Otherwise, results will be stored in Abacus.AI. diff --git a/docs/_sources/autoapi/abacusai/document_retriever_config/index.rst.txt b/docs/_sources/autoapi/abacusai/document_retriever_config/index.rst.txt index 90b3ab5e2..b15d03f73 100644 --- a/docs/_sources/autoapi/abacusai/document_retriever_config/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/document_retriever_config/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: DocumentRetrieverConfig(client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None) +.. py:class:: DocumentRetrieverConfig(client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None, scoreMultiplierColumn=None) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -32,6 +32,8 @@ Classes :type chunkOverlapFraction: float :param textEncoder: The text encoder used to encode texts in the vector store. :type textEncoder: str + :param scoreMultiplierColumn: The values in this metadata column are used to modify the relevance scores of returned chunks. + :type scoreMultiplierColumn: str .. py:method:: __repr__() diff --git a/docs/_sources/autoapi/abacusai/external_application/index.rst.txt b/docs/_sources/autoapi/abacusai/external_application/index.rst.txt index 146bdc5d3..8fb43d43a 100644 --- a/docs/_sources/autoapi/abacusai/external_application/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/external_application/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: ExternalApplication(client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None) +.. py:class:: ExternalApplication(client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None, deploymentConversationRetentionHours=None) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -42,6 +42,8 @@ Classes :type useCase: str :param status: The status of the deployment. :type status: str + :param deploymentConversationRetentionHours: The retention policy for the external application. + :type deploymentConversationRetentionHours: int .. py:method:: __repr__() @@ -56,7 +58,7 @@ Classes :rtype: dict - .. py:method:: update(name = None, theme = None, deployment_id = None) + .. py:method:: update(name = None, theme = None, deployment_id = None, deployment_conversation_retention_hours = None, reset_retention_policy = False) Updates an External Application. @@ -66,6 +68,10 @@ Classes :type theme: dict :param deployment_id: The ID of the deployment to use. :type deployment_id: str + :param deployment_conversation_retention_hours: The number of hours to retain the conversations for. + :type deployment_conversation_retention_hours: int + :param reset_retention_policy: If true, the retention policy will be removed. + :type reset_retention_policy: bool :returns: The updated External Application. :rtype: ExternalApplication diff --git a/docs/_sources/autoapi/abacusai/feature_group/index.rst.txt b/docs/_sources/autoapi/abacusai/feature_group/index.rst.txt index df82c993b..4de91922f 100644 --- a/docs/_sources/autoapi/abacusai/feature_group/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/feature_group/index.rst.txt @@ -1067,20 +1067,7 @@ Classes :type data: list - .. py:method:: upsert_data(streaming_token = None, data = None) - - Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. - - :param streaming_token: Optional streaming token for authenticating requests if upserting to streaming FG. - :type streaming_token: str - :param data: The data to record, in JSON format. - :type data: dict - - :returns: The feature group row that was upserted. - :rtype: FeatureGroupRow - - - .. py:method:: upsert_online_data(data, streaming_token = None) + .. py:method:: upsert_data(data, streaming_token = None) Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. diff --git a/docs/_sources/autoapi/abacusai/feature_group_export/index.rst.txt b/docs/_sources/autoapi/abacusai/feature_group_export/index.rst.txt index 3506de56f..e6b247b3a 100644 --- a/docs/_sources/autoapi/abacusai/feature_group_export/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/feature_group_export/index.rst.txt @@ -140,7 +140,4 @@ Classes :rtype: str - .. py:method:: get_results() - - diff --git a/docs/_sources/autoapi/abacusai/index.rst.txt b/docs/_sources/autoapi/abacusai/index.rst.txt index 97e24f022..3dd258d96 100644 --- a/docs/_sources/autoapi/abacusai/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/index.rst.txt @@ -244,6 +244,7 @@ Classes abacusai.SentenceBoundaryDetectionBatchPredictionArgs abacusai.ThemeAnalysisBatchPredictionArgs abacusai.ChatLLMBatchPredictionArgs + abacusai.TrainablePlugAndPlayBatchPredictionArgs abacusai._BatchPredictionArgsFactory abacusai.BlobInput abacusai.OcrMode @@ -310,6 +311,7 @@ Classes abacusai.PythonFunctionType abacusai.EvalArtifactType abacusai.FieldDescriptorType + abacusai.DataType abacusai.SamplingConfig abacusai.NSamplingConfig abacusai.PercentSamplingConfig @@ -567,6 +569,8 @@ Attributes :type for_eval: bool :param threshold: The threshold for detecting an anomaly. Range: [0.8, 0.99] :type threshold: float + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool .. py:attribute:: for_eval :type: bool @@ -578,6 +582,11 @@ Attributes + .. py:attribute:: explain_predictions + :type: bool + + + .. py:method:: __post_init__() @@ -601,8 +610,10 @@ Attributes :type forecasting_horizon: int :param item_attributes_to_include_in_the_result: List of columns to include in the prediction output. :type item_attributes_to_include_in_the_result: list - :param explain_predictions: If True, explain predictions for the forecast. + :param explain_predictions: If True, calculates explanations for the forecasted values along with predictions. :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -639,6 +650,11 @@ Attributes + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -736,6 +752,10 @@ Attributes :type bound_label: str :param output_columns: A list of column names to include in the prediction result. :type output_columns: list + :param explain_predictions: If True, calculates explanations for the predicted values along with predictions. + :type explain_predictions: bool + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool .. py:attribute:: for_eval :type: bool @@ -787,6 +807,16 @@ Attributes + .. py:attribute:: explain_predictions + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + .. py:method:: __post_init__() @@ -909,6 +939,30 @@ Attributes +.. py:class:: TrainablePlugAndPlayBatchPredictionArgs + + + Bases: :py:obj:`BatchPredictionArgs` + + Batch Prediction Config for the TrainablePlugAndPlay problem type + + :param automate_monitoring: If True, creates a monitor to calculate the drift for the batch prediction. + :type automate_monitoring: bool + + .. py:attribute:: for_eval + :type: bool + + + + .. py:attribute:: automate_monitoring + :type: bool + + + + .. py:method:: __post_init__() + + + .. py:class:: _BatchPredictionArgsFactory @@ -1465,6 +1519,8 @@ Attributes :type text_encoder: VectorStoreTextEncoder :param chunk_size_factors: Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to `chunk_size`. :type chunk_size_factors: list + :param score_multiplier_column: If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries. + :type score_multiplier_column: str .. py:attribute:: chunk_size :type: int @@ -1486,6 +1542,11 @@ Attributes + .. py:attribute:: score_multiplier_column + :type: str + + + .. py:class:: DocumentRetrieverConfig @@ -2974,6 +3035,11 @@ Attributes + .. py:attribute:: MICROSOFTAUTH + :value: 'MICROSOFTAUTH' + + + .. py:class:: PythonFunctionArgumentType @@ -3470,6 +3536,65 @@ Attributes +.. py:class:: DataType + + + Bases: :py:obj:`ApiEnum` + + Generic enumeration. + + Derive from this class to define new enumerations. + + .. py:attribute:: INTEGER + :value: 'integer' + + + + .. py:attribute:: FLOAT + :value: 'float' + + + + .. py:attribute:: STRING + :value: 'string' + + + + .. py:attribute:: DATE + :value: 'date' + + + + .. py:attribute:: DATETIME + :value: 'datetime' + + + + .. py:attribute:: BOOLEAN + :value: 'boolean' + + + + .. py:attribute:: LIST + :value: 'list' + + + + .. py:attribute:: STRUCT + :value: 'struct' + + + + .. py:attribute:: NULL + :value: 'null' + + + + .. py:method:: from_str(value) + :classmethod: + + + .. py:class:: SamplingConfig @@ -4901,6 +5026,8 @@ Attributes :type disable_data_summarization: bool :param search_score_cutoff: Minimum search score to consider a document as a valid search result. :type search_score_cutoff: float + :param database_connector_id: Database connector id to use for the chatllm. + :type database_connector_id: str .. py:attribute:: document_retrievers :type: List[str] @@ -4972,6 +5099,11 @@ Attributes + .. py:attribute:: database_connector_id + :type: str + + + .. py:method:: __post_init__() @@ -8703,7 +8835,7 @@ Attributes :param column: The name of the column. :type column: str :param data_type: The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType. - :type data_type: str + :type data_type: DataType :returns: The dataset and schema after the data type has been set. :rtype: Dataset @@ -10886,7 +11018,7 @@ Attributes :rtype: AgentDataExecutionResult - .. py:method:: create_batch_prediction(deployment_id, table_name = None, name = None, global_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) + .. py:method:: create_batch_prediction(deployment_id, table_name = None, name = None, global_prediction_args = None, batch_prediction_args = None, explanations = False, output_format = None, output_location = None, database_connector_id = None, database_output_config = None, refresh_schedule = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, input_feature_groups = None) Creates a batch prediction job description for the given deployment. @@ -10896,10 +11028,8 @@ Attributes :type table_name: str :param name: Name of the batch prediction job. :type name: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If true, SHAP explanations will be provided for each prediction, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: Format of the batch prediction output (CSV or JSON). :type output_format: str :param output_location: Location to write the prediction results. Otherwise, results will be stored in Abacus.AI. @@ -10938,7 +11068,7 @@ Attributes :rtype: BatchPredictionVersion - .. py:method:: update_batch_prediction(batch_prediction_id, deployment_id = None, global_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) + .. py:method:: update_batch_prediction(batch_prediction_id, deployment_id = None, global_prediction_args = None, batch_prediction_args = None, explanations = None, output_format = None, csv_input_prefix = None, csv_prediction_prefix = None, csv_explanations_prefix = None, output_includes_metadata = None, result_input_columns = None, name = None) Update a batch prediction job description. @@ -10946,10 +11076,8 @@ Attributes :type batch_prediction_id: str :param deployment_id: Unique identifier of the deployment. :type deployment_id: str - :param global_prediction_args: Batch Prediction args specific to problem type. - :type global_prediction_args: BatchPredictionArgs - :param explanations: If True, SHAP explanations for each prediction will be provided, if supported by the use case. - :type explanations: bool + :param batch_prediction_args: Batch Prediction args specific to problem type. + :type batch_prediction_args: BatchPredictionArgs :param output_format: If specified, sets the format of the batch prediction output (CSV or JSON). :type output_format: str :param csv_input_prefix: Prefix to prepend to the input columns, only applies when output format is CSV. @@ -11229,22 +11357,7 @@ Attributes :type data: list - .. py:method:: upsert_data(feature_group_id, streaming_token = None, data = None) - - Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. - - :param feature_group_id: A unique string identifier of the streaming feature group to record data to. - :type feature_group_id: str - :param streaming_token: Optional streaming token for authenticating requests if upserting to streaming FG. - :type streaming_token: str - :param data: The data to record, in JSON format. - :type data: dict - - :returns: The feature group row that was upserted. - :rtype: FeatureGroupRow - - - .. py:method:: upsert_online_data(feature_group_id, data, streaming_token = None) + .. py:method:: upsert_data(feature_group_id, data, streaming_token = None) Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group. @@ -12218,7 +12331,7 @@ Attributes :rtype: ExternalApplication - .. py:method:: update_external_application(external_application_id, name = None, theme = None, deployment_id = None) + .. py:method:: update_external_application(external_application_id, name = None, theme = None, deployment_id = None, deployment_conversation_retention_hours = None, reset_retention_policy = False) Updates an External Application. @@ -12230,6 +12343,10 @@ Attributes :type theme: dict :param deployment_id: The ID of the deployment to use. :type deployment_id: str + :param deployment_conversation_retention_hours: The number of hours to retain the conversations for. + :type deployment_conversation_retention_hours: int + :param reset_retention_policy: If true, the retention policy will be removed. + :type reset_retention_policy: bool :returns: The updated External Application. :rtype: ExternalApplication @@ -15611,7 +15728,7 @@ Attributes .. py:data:: __version__ - :value: '1.1.5' + :value: '1.1.6' diff --git a/docs/_sources/autoapi/abacusai/pipeline/index.rst.txt b/docs/_sources/autoapi/abacusai/pipeline/index.rst.txt index f6643b0fc..f01680264 100644 --- a/docs/_sources/autoapi/abacusai/pipeline/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/pipeline/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: Pipeline(client, pipelineName=None, pipelineId=None, createdAt=None, pipelineVariableMappings=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={}) +.. py:class:: Pipeline(client, pipelineName=None, pipelineId=None, createdAt=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={}, pipelineVariableMappings={}) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -32,8 +32,6 @@ Classes :type pipelineId: str :param createdAt: The date and time which the pipeline was created. :type createdAt: str - :param pipelineVariableMappings: A description of the function variables into the pipeline. - :type pipelineVariableMappings: dict :param notebookId: The reference to the notebook this pipeline belongs to. :type notebookId: str :param cron: A cron-style string that describes when this refresh policy is to be executed in UTC diff --git a/docs/_sources/autoapi/abacusai/pipeline_version/index.rst.txt b/docs/_sources/autoapi/abacusai/pipeline_version/index.rst.txt index 1418cdd63..059de0709 100644 --- a/docs/_sources/autoapi/abacusai/pipeline_version/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/pipeline_version/index.rst.txt @@ -17,7 +17,7 @@ Classes -.. py:class:: PipelineVersion(client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, pipelineVariableMappings=None, stepVersions={}, codeSource={}) +.. py:class:: PipelineVersion(client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, stepVersions={}, codeSource={}, pipelineVariableMappings={}) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` @@ -42,8 +42,6 @@ Classes :type status: str :param error: The relevant error, if the status is FAILED. :type error: str - :param pipelineVariableMappings: A description of the function variables into the pipeline. - :type pipelineVariableMappings: dict :param stepVersions: A list of the pipeline step versions. :type stepVersions: PipelineStepVersion :param codeSource: information on the source code diff --git a/docs/_sources/autoapi/abacusai/project/index.rst.txt b/docs/_sources/autoapi/abacusai/project/index.rst.txt index c46dd17f4..256582061 100644 --- a/docs/_sources/autoapi/abacusai/project/index.rst.txt +++ b/docs/_sources/autoapi/abacusai/project/index.rst.txt @@ -702,27 +702,6 @@ Classes :rtype: list[DocumentRetriever] - .. py:method:: attach_dataset(dataset_id, project_dataset_type) - - Attaches dataset to the project. - - :param dataset_id: A unique identifier for the dataset. - :type dataset_id: unique string identifier - :param project_dataset_type: The unique use case specific dataset type that might be required or recommended for the specific use case. - :type project_dataset_type: enum of type string - - :returns: The schema of the attached dataset. - :rtype: Schema - - - .. py:method:: remove_dataset(dataset_id) - - Removes dataset from the project. - - :param dataset_id: A unique identifier for the dataset. - :type dataset_id: unique string identifier - - .. py:method:: create_model_from_functions(train_function, predict_function = None, training_input_tables = None, predict_many_function = None, initialize_function = None, cpu_size = None, memory = None, training_config = None, exclusive_run = False) Creates a model using python. diff --git a/docs/autoapi/abacusai/api_class/batch_prediction/index.html b/docs/autoapi/abacusai/api_class/batch_prediction/index.html index bb35297ba..ddde95f8f 100644 --- a/docs/autoapi/abacusai/api_class/batch_prediction/index.html +++ b/docs/autoapi/abacusai/api_class/batch_prediction/index.html @@ -123,7 +123,10 @@

Classes

ChatLLMBatchPredictionArgs

Batch Prediction Config for the ChatLLM problem type

-

_BatchPredictionArgsFactory

+

TrainablePlugAndPlayBatchPredictionArgs

+

Batch Prediction Config for the TrainablePlugAndPlay problem type

+ +

_BatchPredictionArgsFactory

Helper class that provides a standard way to create an ABC using

@@ -166,6 +169,7 @@

Classes @@ -179,6 +183,11 @@

Classesthreshold: float
+
+
+explain_predictions: bool
+
+
__post_init__()
@@ -200,7 +209,8 @@

Classesint) – Sets prediction start date as this offset relative to the prediction start date.

  • forecasting_horizon (int) – The number of timestamps to predict in the future. Range: [1, 1000].

  • item_attributes_to_include_in_the_result (list) – List of columns to include in the prediction output.

    • -

  • explain_predictions (bool) – If True, explain predictions for the forecast.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the forecasted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -239,6 +249,11 @@

    Classesexplain_predictions: bool
    +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -336,6 +351,8 @@

    Classesfloat) – If set explanations will be limited to predictions below this value, Range: [0, 1].

  • bound_label (str) – For classification problems specifies the label to which the explanation bounds are applied.

  • output_columns (list) – A list of column names to include in the prediction result.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the predicted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -389,6 +406,16 @@

    Classesoutput_columns: list
    +
    +
    +explain_predictions: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -526,6 +553,33 @@

    Classes +
    +class abacusai.api_class.batch_prediction.TrainablePlugAndPlayBatchPredictionArgs
    +

    Bases: BatchPredictionArgs

    +

    Batch Prediction Config for the TrainablePlugAndPlay problem type

    +
    +
    Parameters:
    +

    automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    +
    +
    +
    +
    +for_eval: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    + +
    +
    +__post_init__()
    +
    + +

    +
    class abacusai.api_class.batch_prediction._BatchPredictionArgsFactory
    diff --git a/docs/autoapi/abacusai/api_class/document_retriever/index.html b/docs/autoapi/abacusai/api_class/document_retriever/index.html index 78d7fb51d..afd77d055 100644 --- a/docs/autoapi/abacusai/api_class/document_retriever/index.html +++ b/docs/autoapi/abacusai/api_class/document_retriever/index.html @@ -113,6 +113,7 @@

    Classesfloat) – The fraction of overlap between chunks.

  • text_encoder (VectorStoreTextEncoder) – Encoder used to index texts from the documents.

  • chunk_size_factors (list) – Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to chunk_size.

    • +

  • score_multiplier_column (str) – If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries.

    • @@ -136,6 +137,11 @@

    Classeschunk_size_factors: list
    +
    +
    +score_multiplier_column: str
    +
    +
    diff --git a/docs/autoapi/abacusai/api_class/enums/index.html b/docs/autoapi/abacusai/api_class/enums/index.html index 382b3e741..5531e4b09 100644 --- a/docs/autoapi/abacusai/api_class/enums/index.html +++ b/docs/autoapi/abacusai/api_class/enums/index.html @@ -240,6 +240,9 @@

    Classes

    OcrMode

    Generic enumeration.

    +

    DataType

    +

    Generic enumeration.

    +
    @@ -1650,6 +1653,11 @@

    ClassesABACUSUSAGEMETRICS = 'ABACUSUSAGEMETRICS'

    +
    +
    +MICROSOFTAUTH = 'MICROSOFTAUTH'
    +
    +

    @@ -2191,6 +2199,64 @@

    Classes +
    +class abacusai.api_class.enums.DataType
    +

    Bases: ApiEnum

    +

    Generic enumeration.

    +

    Derive from this class to define new enumerations.

    +
    +
    +INTEGER = 'integer'
    +
    + +
    +
    +FLOAT = 'float'
    +
    + +
    +
    +STRING = 'string'
    +
    + +
    +
    +DATE = 'date'
    +
    + +
    +
    +DATETIME = 'datetime'
    +
    + +
    +
    +BOOLEAN = 'boolean'
    +
    + +
    +
    +LIST = 'list'
    +
    + +
    +
    +STRUCT = 'struct'
    +
    + +
    +
    +NULL = 'null'
    +
    + +
    +
    +classmethod from_str(value)
    +
    + +

    + diff --git a/docs/autoapi/abacusai/api_class/index.html b/docs/autoapi/abacusai/api_class/index.html index ed0bd4d8e..c8e00fbde 100644 --- a/docs/autoapi/abacusai/api_class/index.html +++ b/docs/autoapi/abacusai/api_class/index.html @@ -163,223 +163,229 @@

    Classes

    ChatLLMBatchPredictionArgs

    Batch Prediction Config for the ChatLLM problem type

    -

    _BatchPredictionArgsFactory

    +

    TrainablePlugAndPlayBatchPredictionArgs

    +

    Batch Prediction Config for the TrainablePlugAndPlay problem type

    + +

    _BatchPredictionArgsFactory

    Helper class that provides a standard way to create an ABC using

    -

    ApiClass

    +

    ApiClass

    Helper class that provides a standard way to create an ABC using

    -

    BlobInput

    +

    BlobInput

    Binary large object input data.

    -

    ApiClass

    +

    ApiClass

    Helper class that provides a standard way to create an ABC using

    -

    OcrMode

    +

    OcrMode

    Generic enumeration.

    -

    ParsingConfig

    +

    ParsingConfig

    Helper class that provides a standard way to create an ABC using

    -

    DocumentProcessingConfig

    +

    DocumentProcessingConfig

    Document processing configuration.

    -

    IncrementalDatabaseConnectorConfig

    +

    IncrementalDatabaseConnectorConfig

    Config information for incremental datasets from database connectors

    -

    ApiClass

    +

    ApiClass

    Helper class that provides a standard way to create an ABC using

    -

    _ApiClassFactory

    +

    _ApiClassFactory

    Helper class that provides a standard way to create an ABC using

    -

    DatasetConfig

    +

    DatasetConfig

    Helper class that provides a standard way to create an ABC using

    -

    ConfluenceDatasetConfig

    +

    ConfluenceDatasetConfig

    Dataset config for Confluence Application Connector

    -

    GoogleAnalyticsDatasetConfig

    +

    GoogleAnalyticsDatasetConfig

    Dataset config for Google Analytics Application Connector

    -

    GoogleDriveDatasetConfig

    +

    GoogleDriveDatasetConfig

    Dataset config for Google Drive Application Connector

    -

    JiraDatasetConfig

    +

    JiraDatasetConfig

    Dataset config for Jira Application Connector

    -

    OneDriveDatasetConfig

    +

    OneDriveDatasetConfig

    Dataset config for OneDrive Application Connector

    -

    SharepointDatasetConfig

    +

    SharepointDatasetConfig

    Dataset config for Sharepoint Application Connector

    -

    ZendeskDatasetConfig

    +

    ZendeskDatasetConfig

    Dataset config for Zendesk Application Connector

    -

    AbacusUsageMetricsDatasetConfig

    +

    AbacusUsageMetricsDatasetConfig

    Dataset config for Abacus Usage Metrics Application Connector

    -

    _DatasetConfigFactory

    +

    _DatasetConfigFactory

    Helper class that provides a standard way to create an ABC using

    -

    ApiClass

    +

    ApiClass

    Helper class that provides a standard way to create an ABC using

    -

    VectorStoreTextEncoder

    +

    VectorStoreTextEncoder

    Generic enumeration.

    -

    VectorStoreConfig

    +

    VectorStoreConfig

    Configs for vector store indexing.

    -

    DocumentRetrieverConfig

    +

    DocumentRetrieverConfig

    Configs for document retriever.

    -

    ApiEnum

    +

    ApiEnum

    Generic enumeration.

    -

    ProblemType

    +

    ProblemType

    Generic enumeration.

    -

    RegressionObjective

    +

    RegressionObjective

    Generic enumeration.

    -

    RegressionTreeHPOMode

    +

    RegressionTreeHPOMode

    Generic enumeration.

    -

    PartialDependenceAnalysis

    +

    PartialDependenceAnalysis

    Generic enumeration.

    -

    RegressionAugmentationStrategy

    +

    RegressionAugmentationStrategy

    Generic enumeration.

    -

    RegressionTargetTransform

    +

    RegressionTargetTransform

    Generic enumeration.

    -

    RegressionTypeOfSplit

    +

    RegressionTypeOfSplit

    Generic enumeration.

    -

    RegressionTimeSplitMethod

    +

    RegressionTimeSplitMethod

    Generic enumeration.

    -

    RegressionLossFunction

    +

    RegressionLossFunction

    Generic enumeration.

    -

    ExplainerType

    +

    ExplainerType

    Generic enumeration.

    -

    SamplingMethodType

    +

    SamplingMethodType

    Generic enumeration.

    -

    MergeMode

    +

    MergeMode

    Generic enumeration.

    -

    FillLogic

    +

    FillLogic

    Generic enumeration.

    -

    BatchSize

    +

    BatchSize

    Generic enumeration.

    -

    HolidayCalendars

    +

    HolidayCalendars

    Generic enumeration.

    -

    FileFormat

    +

    FileFormat

    Generic enumeration.

    -

    ExperimentationMode

    +

    ExperimentationMode

    Generic enumeration.

    -

    PersonalizationTrainingMode

    +

    PersonalizationTrainingMode

    Generic enumeration.

    -

    PersonalizationObjective

    +

    PersonalizationObjective

    Generic enumeration.

    -

    ForecastingObjective

    +

    ForecastingObjective

    Generic enumeration.

    -

    ForecastingFrequency

    +

    ForecastingFrequency

    Generic enumeration.

    -

    ForecastingDataSplitType

    +

    ForecastingDataSplitType

    Generic enumeration.

    -

    ForecastingLossFunction

    +

    ForecastingLossFunction

    Generic enumeration.

    -

    ForecastingLocalScaling

    +

    ForecastingLocalScaling

    Generic enumeration.

    -

    ForecastingFillMethod

    +

    ForecastingFillMethod

    Generic enumeration.

    -

    ForecastingQuanitlesExtensionMethod

    +

    ForecastingQuanitlesExtensionMethod

    Generic enumeration.

    -

    TimeseriesAnomalyDataSplitType

    +

    TimeseriesAnomalyDataSplitType

    Generic enumeration.

    -

    TimeseriesAnomalyTypeOfAnomaly

    +

    TimeseriesAnomalyTypeOfAnomaly

    Generic enumeration.

    -

    NERObjective

    +

    NERObjective

    Generic enumeration.

    -

    NERModelType

    +

    NERModelType

    Generic enumeration.

    -

    NLPDocumentFormat

    +

    NLPDocumentFormat

    Generic enumeration.

    -

    SentimentType

    +

    SentimentType

    Generic enumeration.

    -

    ClusteringImputationMethod

    +

    ClusteringImputationMethod

    Generic enumeration.

    -

    ConnectorType

    +

    ConnectorType

    Generic enumeration.

    -

    ApplicationConnectorType

    +

    ApplicationConnectorType

    Generic enumeration.

    -

    PythonFunctionArgumentType

    +

    PythonFunctionArgumentType

    Generic enumeration.

    -

    PythonFunctionOutputArgumentType

    +

    PythonFunctionOutputArgumentType

    Generic enumeration.

    -

    VectorStoreTextEncoder

    +

    VectorStoreTextEncoder

    Generic enumeration.

    -

    LLMName

    +

    LLMName

    Generic enumeration.

    -

    MonitorAlertType

    +

    MonitorAlertType

    Generic enumeration.

    -

    FeatureDriftType

    +

    FeatureDriftType

    Generic enumeration.

    -

    DataIntegrityViolationType

    +

    DataIntegrityViolationType

    Generic enumeration.

    -

    BiasType

    +

    BiasType

    Generic enumeration.

    -

    AlertActionType

    +

    AlertActionType

    Generic enumeration.

    -

    PythonFunctionType

    +

    PythonFunctionType

    Generic enumeration.

    -

    EvalArtifactType

    +

    EvalArtifactType

    Generic enumeration.

    -

    FieldDescriptorType

    +

    FieldDescriptorType

    Generic enumeration.

    -

    OcrMode

    +

    OcrMode

    +

    Generic enumeration.

    + +

    DataType

    Generic enumeration.

    ApiClass

    @@ -1063,6 +1069,7 @@

    Classes @@ -1076,6 +1083,11 @@

    Classesthreshold: float
    +
    +
    +explain_predictions: bool
    +
    +
    __post_init__()
    @@ -1097,7 +1109,8 @@

    Classesint) – Sets prediction start date as this offset relative to the prediction start date.

  • forecasting_horizon (int) – The number of timestamps to predict in the future. Range: [1, 1000].

  • item_attributes_to_include_in_the_result (list) – List of columns to include in the prediction output.

    • -

  • explain_predictions (bool) – If True, explain predictions for the forecast.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the forecasted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -1136,6 +1149,11 @@

    Classesexplain_predictions: bool
    +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -1233,6 +1251,8 @@

    Classesfloat) – If set explanations will be limited to predictions below this value, Range: [0, 1].

  • bound_label (str) – For classification problems specifies the label to which the explanation bounds are applied.

  • output_columns (list) – A list of column names to include in the prediction result.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the predicted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -1286,6 +1306,16 @@

    Classesoutput_columns: list
    +
    +
    +explain_predictions: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -1423,6 +1453,33 @@

    Classes +
    +class abacusai.api_class.TrainablePlugAndPlayBatchPredictionArgs
    +

    Bases: BatchPredictionArgs

    +

    Batch Prediction Config for the TrainablePlugAndPlay problem type

    +
    +
    Parameters:
    +

    automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    +
    +
    +
    +
    +for_eval: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    + +
    +
    +__post_init__()
    +
    + +

    +
    class abacusai.api_class._BatchPredictionArgsFactory
    @@ -2503,6 +2560,7 @@

    Classesfloat) – The fraction of overlap between chunks.

  • text_encoder (VectorStoreTextEncoder) – Encoder used to index texts from the documents.

  • chunk_size_factors (list) – Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to chunk_size.

    • +

  • score_multiplier_column (str) – If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries.

    • @@ -2526,6 +2584,11 @@

    Classeschunk_size_factors: list
    +
    +
    +score_multiplier_column: str
    +
    +
    @@ -3943,6 +4006,11 @@

    ClassesABACUSUSAGEMETRICS = 'ABACUSUSAGEMETRICS'

    +
    +
    +MICROSOFTAUTH = 'MICROSOFTAUTH'
    +
    +
    @@ -4484,6 +4552,64 @@

    Classes +
    +class abacusai.api_class.DataType
    +

    Bases: ApiEnum

    +

    Generic enumeration.

    +

    Derive from this class to define new enumerations.

    +
    +
    +INTEGER = 'integer'
    +
    + +
    +
    +FLOAT = 'float'
    +
    + +
    +
    +STRING = 'string'
    +
    + +
    +
    +DATE = 'date'
    +
    + +
    +
    +DATETIME = 'datetime'
    +
    + +
    +
    +BOOLEAN = 'boolean'
    +
    + +
    +
    +LIST = 'list'
    +
    + +
    +
    +STRUCT = 'struct'
    +
    + +
    +
    +NULL = 'null'
    +
    + +
    +
    +classmethod from_str(value)
    +
    + +

    +
    class abacusai.api_class.ApiClass
    @@ -6099,6 +6225,7 @@

    Classesbool) – When running data queries, hides the generated SQL in the response and will just return the table.

  • disable_data_summarization (bool) – After executing a query summarize the reponse and reply back with only the table and query run.

  • search_score_cutoff (float) – Minimum search score to consider a document as a valid search result.

    • +

  • database_connector_id (str) – Database connector id to use for the chatllm.

    • @@ -6172,6 +6299,11 @@

    Classessearch_score_cutoff: float
    +
    +
    +database_connector_id: str
    +
    +
    __post_init__()
    diff --git a/docs/autoapi/abacusai/api_class/model/index.html b/docs/autoapi/abacusai/api_class/model/index.html index 81f22caa1..13c9979fa 100644 --- a/docs/autoapi/abacusai/api_class/model/index.html +++ b/docs/autoapi/abacusai/api_class/model/index.html @@ -1258,6 +1258,7 @@

    Classesbool) – When running data queries, hides the generated SQL in the response and will just return the table.

  • disable_data_summarization (bool) – After executing a query summarize the reponse and reply back with only the table and query run.

  • search_score_cutoff (float) – Minimum search score to consider a document as a valid search result.

    • +

  • database_connector_id (str) – Database connector id to use for the chatllm.

    • @@ -1331,6 +1332,11 @@

    Classessearch_score_cutoff: float
    +
    +
    +database_connector_id: str
    +
    +
    __post_init__()
    diff --git a/docs/autoapi/abacusai/batch_prediction/index.html b/docs/autoapi/abacusai/batch_prediction/index.html index ac195e6d8..8babd4e7b 100644 --- a/docs/autoapi/abacusai/batch_prediction/index.html +++ b/docs/autoapi/abacusai/batch_prediction/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.batch_prediction.BatchPrediction(client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={})
    +class abacusai.batch_prediction.BatchPrediction(client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, outputFeatureGroupId=None, featureGroupTableName=None, outputFeatureGroupTableName=None, summaryFeatureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorId=None, modelVersion=None, algorithm=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={})

    Bases: abacusai.return_class.AbstractApiClass

    Make batch predictions.

    @@ -312,11 +312,11 @@

    Classesstr) – Contains information about where the batch predictions are written to.

  • databaseConnectorId (str) – The database connector to write the results to.

  • databaseOutputConfiguration (dict) – Contains information about where the batch predictions are written to.

    • -

  • explanations (bool) – If true, explanations for each prediction will be created.

    • +

  • explanations (bool) –

  • fileOutputFormat (str) – The format of the batch prediction output (CSV or JSON).

  • connectorType (str) – Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR.

  • legacyInputLocation (str) – The location of the input data.

    • -

  • outputFeatureGroupId (str) – The BP output feature group id if applicable

    • +

  • outputFeatureGroupId (str) – The Batch Prediction output feature group ID if applicable

  • featureGroupTableName (str) – The table name of the Batch Prediction output feature group.

  • outputFeatureGroupTableName (str) – The table name of the Batch Prediction output feature group.

  • summaryFeatureGroupTableName (str) – The table name of the metrics summary feature group output by Batch Prediction.

    • @@ -425,14 +425,13 @@

    Classes
    -update(deployment_id=None, global_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)
    +update(deployment_id=None, global_prediction_args=None, batch_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)

    Update a batch prediction job description.

    Parameters:

    • deployment_id (str) – Unique identifier of the deployment.

      • -

    • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

      • -

    • explanations (bool) – If True, SHAP explanations for each prediction will be provided, if supported by the use case.

      • +

    • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • output_format (str) – If specified, sets the format of the batch prediction output (CSV or JSON).

    • csv_input_prefix (str) – Prefix to prepend to the input columns, only applies when output format is CSV.

    • csv_prediction_prefix (str) – Prefix to prepend to the prediction columns, only applies when output format is CSV.

      • @@ -440,6 +439,8 @@

      Classesbool) – If True, output will contain columns including prediction start time, batch prediction version, and model version.

    • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

    • name (str) – If present, will rename the batch prediction.

      • +

    • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

      • +

    • explanations (bool) –

    Returns:
    diff --git a/docs/autoapi/abacusai/batch_prediction_version/index.html b/docs/autoapi/abacusai/batch_prediction_version/index.html index 70345f813..f3a7a8ea6 100644 --- a/docs/autoapi/abacusai/batch_prediction_version/index.html +++ b/docs/autoapi/abacusai/batch_prediction_version/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.batch_prediction_version.BatchPredictionVersion(client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={})
    +class abacusai.batch_prediction_version.BatchPredictionVersion(client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={})

    Bases: abacusai.return_class.AbstractApiClass

    Batch Prediction Version

    @@ -319,7 +319,7 @@

    Classesint) – Number of predictions that failed

  • databaseConnectorId (str) – The database connector to write the results to

  • databaseOutputConfiguration (dict) – Contains information about where the batch predictions are written to

    • -

  • explanations (bool) – If true, explanations for each prediction were created

    • +

  • explanations (bool) –

  • fileConnectorOutputLocation (str) – Contains information about where the batch predictions are written to

  • fileOutputFormat (str) – The format of the batch prediction output (CSV or JSON)

  • connectorType (str) – Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR

    • @@ -337,9 +337,9 @@

    Classesstr) – The version of the model monitor

  • algoName (str) – The name of the algorithm used to train the model

  • algorithm (str) – The algorithm that is currently deployed.

    • -

  • outputFeatureGroupId (str) – The BP output feature group id if applicable

    • -

  • outputFeatureGroupVersion (str) – The BP output feature group version if applicable

    • -

  • outputFeatureGroupTableName (str) – The BP output feature group name if applicable

    • +

  • outputFeatureGroupId (str) – The Batch Prediction output feature group ID if applicable

    • +

  • outputFeatureGroupVersion (str) – The Batch Prediction output feature group version if applicable

    • +

  • outputFeatureGroupTableName (str) – The Batch Prediction output feature group name if applicable

  • batchPredictionWarnings (str) – Relevant warnings if any issues are found

  • batchInputs (PredictionInput) – Inputs to the batch prediction

  • inputFeatureGroups (PredictionFeatureGroup) – List of prediction feature groups

    • diff --git a/docs/autoapi/abacusai/client/index.html b/docs/autoapi/abacusai/client/index.html index dda40f80d..b9c890949 100644 --- a/docs/autoapi/abacusai/client/index.html +++ b/docs/autoapi/abacusai/client/index.html @@ -838,7 +838,7 @@

    Attributes
    -client_version = '1.1.5'
    +client_version = '1.1.6'

    @@ -7153,7 +7153,7 @@

    Attributes

    • dataset_id (str) – The unique ID associated with the dataset.

    • column (str) – The name of the column.

      • -

    • data_type (str) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

      • +

    • data_type (DataType) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

    Returns:
    @@ -9746,7 +9746,7 @@

    Attributes
    -create_batch_prediction(deployment_id, table_name=None, name=None, global_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)
    +create_batch_prediction(deployment_id, table_name=None, name=None, global_prediction_args=None, batch_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)

    Creates a batch prediction job description for the given deployment.

    Parameters:
    @@ -9754,8 +9754,7 @@

    Attributesstr) – Unique string identifier for the deployment.

  • table_name (str) – Name of the feature group table to write the results of the batch prediction. Can only be specified if outputLocation and databaseConnectorId are not specified. If tableName is specified, the outputType will be enforced as CSV.

  • name (str) – Name of the batch prediction job.

    • -

  • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • -

  • explanations (bool) – If true, SHAP explanations will be provided for each prediction, if supported by the use case.

    • +

  • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

  • output_format (str) – Format of the batch prediction output (CSV or JSON).

  • output_location (str) – Location to write the prediction results. Otherwise, results will be stored in Abacus.AI.

  • database_connector_id (str) – Unique identifier of a Database Connection to write predictions to. Cannot be specified in conjunction with outputLocation.

    • @@ -9767,6 +9766,8 @@

    Attributesbool) – If true, output will contain columns including prediction start time, batch prediction version, and model version.

  • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

  • input_feature_groups (dict) – A dict of {‘<feature_group_type>’: ‘<feature_group_id>’} which overrides the default input data of that type for the Batch Prediction. Default input data is the training data that was used for training the deployed model.

    • +

  • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

    • +

  • explanations (bool) –

    • Returns:
    @@ -9797,15 +9798,14 @@

    Attributes
    -update_batch_prediction(batch_prediction_id, deployment_id=None, global_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)
    +update_batch_prediction(batch_prediction_id, deployment_id=None, global_prediction_args=None, batch_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)

    Update a batch prediction job description.

    Parameters:

    • batch_prediction_id (str) – Unique identifier of the batch prediction.

    • deployment_id (str) – Unique identifier of the deployment.

      • -

    • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

      • -

    • explanations (bool) – If True, SHAP explanations for each prediction will be provided, if supported by the use case.

      • +

    • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • output_format (str) – If specified, sets the format of the batch prediction output (CSV or JSON).

    • csv_input_prefix (str) – Prefix to prepend to the input columns, only applies when output format is CSV.

    • csv_prediction_prefix (str) – Prefix to prepend to the prediction columns, only applies when output format is CSV.

      • @@ -9813,6 +9813,8 @@

      Attributesbool) – If True, output will contain columns including prediction start time, batch prediction version, and model version.

    • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

    • name (str) – If present, will rename the batch prediction.

      • +

    • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

      • +

    • explanations (bool) –

    Returns:
    @@ -10149,28 +10151,7 @@

    Attributes
    -upsert_data(feature_group_id, streaming_token=None, data=None)
    -

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    -
    -
    Parameters:
    -
      -

    • feature_group_id (str) – A unique string identifier of the streaming feature group to record data to.

      • -

    • streaming_token (str) – Optional streaming token for authenticating requests if upserting to streaming FG.

      • -

    • data (dict) – The data to record, in JSON format.

      • -
    -
    -
    Returns:
    -

    The feature group row that was upserted.

    -
    -
    Return type:
    -

    FeatureGroupRow

    -
    -
    -

    - -
    -
    -upsert_online_data(feature_group_id, data, streaming_token=None)
    +upsert_data(feature_group_id, data, streaming_token=None)

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    Parameters:
    @@ -11454,7 +11435,7 @@

    Attributes
    -update_external_application(external_application_id, name=None, theme=None, deployment_id=None)
    +update_external_application(external_application_id, name=None, theme=None, deployment_id=None, deployment_conversation_retention_hours=None, reset_retention_policy=False)

    Updates an External Application.

    Parameters:
    @@ -11463,6 +11444,8 @@

    Attributesstr) – The name of the External Application.

  • theme (dict) – The visual theme of the External Application.

  • deployment_id (str) – The ID of the deployment to use.

    • +

  • deployment_conversation_retention_hours (int) – The number of hours to retain the conversations for.

    • +

  • reset_retention_policy (bool) – If true, the retention policy will be removed.

    • Returns:
    diff --git a/docs/autoapi/abacusai/dataset/index.html b/docs/autoapi/abacusai/dataset/index.html index a387fdee0..737fa6fce 100644 --- a/docs/autoapi/abacusai/dataset/index.html +++ b/docs/autoapi/abacusai/dataset/index.html @@ -453,7 +453,7 @@

    ClassesParameters:

    • column (str) – The name of the column.

      • -

    • data_type (str) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

      • +

    • data_type (DataType) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

    Returns:
    diff --git a/docs/autoapi/abacusai/deployment/index.html b/docs/autoapi/abacusai/deployment/index.html index 2ea7c8fd9..3e84af7f1 100644 --- a/docs/autoapi/abacusai/deployment/index.html +++ b/docs/autoapi/abacusai/deployment/index.html @@ -666,15 +666,14 @@

    Classes
    -create_batch_prediction(table_name=None, name=None, global_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)
    +create_batch_prediction(table_name=None, name=None, global_prediction_args=None, batch_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)

    Creates a batch prediction job description for the given deployment.

    Parameters:

    • table_name (str) – Name of the feature group table to write the results of the batch prediction. Can only be specified if outputLocation and databaseConnectorId are not specified. If tableName is specified, the outputType will be enforced as CSV.

    • name (str) – Name of the batch prediction job.

      • -

    • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

      • -

    • explanations (bool) – If true, SHAP explanations will be provided for each prediction, if supported by the use case.

      • +

    • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • output_format (str) – Format of the batch prediction output (CSV or JSON).

    • output_location (str) – Location to write the prediction results. Otherwise, results will be stored in Abacus.AI.

    • database_connector_id (str) – Unique identifier of a Database Connection to write predictions to. Cannot be specified in conjunction with outputLocation.

      • @@ -686,6 +685,8 @@

      Classesbool) – If true, output will contain columns including prediction start time, batch prediction version, and model version.

    • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

    • input_feature_groups (dict) – A dict of {‘<feature_group_type>’: ‘<feature_group_id>’} which overrides the default input data of that type for the Batch Prediction. Default input data is the training data that was used for training the deployed model.

      • +

    • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

      • +

    • explanations (bool) –

    Returns:
    diff --git a/docs/autoapi/abacusai/document_retriever_config/index.html b/docs/autoapi/abacusai/document_retriever_config/index.html index 9ca8a5e8d..912543559 100644 --- a/docs/autoapi/abacusai/document_retriever_config/index.html +++ b/docs/autoapi/abacusai/document_retriever_config/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.document_retriever_config.DocumentRetrieverConfig(client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None)
    +class abacusai.document_retriever_config.DocumentRetrieverConfig(client, chunkSize=None, chunkOverlapFraction=None, textEncoder=None, scoreMultiplierColumn=None)

    Bases: abacusai.return_class.AbstractApiClass

    A config for document retriever creation.

    @@ -308,6 +308,7 @@

    Classesint) – The size of chunks for vector store, i.e., maximum number of words in the chunk.

  • chunkOverlapFraction (float) – The fraction of overlap between two consecutive chunks.

  • textEncoder (str) – The text encoder used to encode texts in the vector store.

    • +

  • scoreMultiplierColumn (str) – The values in this metadata column are used to modify the relevance scores of returned chunks.

    • diff --git a/docs/autoapi/abacusai/external_application/index.html b/docs/autoapi/abacusai/external_application/index.html index 0babf197d..0f0619167 100644 --- a/docs/autoapi/abacusai/external_application/index.html +++ b/docs/autoapi/abacusai/external_application/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.external_application.ExternalApplication(client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None)
    +class abacusai.external_application.ExternalApplication(client, name=None, externalApplicationId=None, deploymentId=None, logo=None, theme=None, userGroupIds=None, useCase=None, status=None, deploymentConversationRetentionHours=None)

    Bases: abacusai.return_class.AbstractApiClass

    An external application.

    @@ -313,6 +313,7 @@

    Classeslist) – A list of App User Groups with access to this external application

  • useCase (str) – Use Case of the project of this deployment

  • status (str) – The status of the deployment.

    • +

  • deploymentConversationRetentionHours (int) – The retention policy for the external application.

    • @@ -338,7 +339,7 @@

    Classes
    -update(name=None, theme=None, deployment_id=None)
    +update(name=None, theme=None, deployment_id=None, deployment_conversation_retention_hours=None, reset_retention_policy=False)

    Updates an External Application.

    Parameters:
    @@ -346,6 +347,8 @@

    Classesstr) – The name of the External Application.

  • theme (dict) – The visual theme of the External Application.

  • deployment_id (str) – The ID of the deployment to use.

    • +

  • deployment_conversation_retention_hours (int) – The number of hours to retain the conversations for.

    • +

  • reset_retention_policy (bool) – If true, the retention policy will be removed.

    • Returns:
    diff --git a/docs/autoapi/abacusai/feature_group/index.html b/docs/autoapi/abacusai/feature_group/index.html index c1677713c..2d33fc855 100644 --- a/docs/autoapi/abacusai/feature_group/index.html +++ b/docs/autoapi/abacusai/feature_group/index.html @@ -1624,27 +1624,7 @@

    Classes
    -upsert_data(streaming_token=None, data=None)
    -

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    -
    -
    Parameters:
    -
      -

    • streaming_token (str) – Optional streaming token for authenticating requests if upserting to streaming FG.

      • -

    • data (dict) – The data to record, in JSON format.

      • -
    -
    -
    Returns:
    -

    The feature group row that was upserted.

    -
    -
    Return type:
    -

    FeatureGroupRow

    -
    -
    -

    - -
    -
    -upsert_online_data(data, streaming_token=None)
    +upsert_data(data, streaming_token=None)

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    Parameters:
    diff --git a/docs/autoapi/abacusai/feature_group_export/index.html b/docs/autoapi/abacusai/feature_group_export/index.html index 98d7e0be4..ffa6457de 100644 --- a/docs/autoapi/abacusai/feature_group_export/index.html +++ b/docs/autoapi/abacusai/feature_group_export/index.html @@ -442,11 +442,6 @@

    Classes -
    -get_results()
    -

    -
    diff --git a/docs/autoapi/abacusai/index.html b/docs/autoapi/abacusai/index.html index 3b213b29c..75b71f59b 100644 --- a/docs/autoapi/abacusai/index.html +++ b/docs/autoapi/abacusai/index.html @@ -270,6 +270,7 @@
  • SentenceBoundaryDetectionBatchPredictionArgs
  • ThemeAnalysisBatchPredictionArgs
  • ChatLLMBatchPredictionArgs
    • +
  • TrainablePlugAndPlayBatchPredictionArgs
  • _BatchPredictionArgsFactory
  • BlobInput
  • OcrMode
    • @@ -336,6 +337,7 @@
  • PythonFunctionType
  • EvalArtifactType
  • FieldDescriptorType
    • +
  • DataType
  • SamplingConfig
  • NSamplingConfig
  • PercentSamplingConfig
    • @@ -715,202 +717,208 @@

    Classes

    ChatLLMBatchPredictionArgs

    Batch Prediction Config for the ChatLLM problem type

    -

    _BatchPredictionArgsFactory

    +

    TrainablePlugAndPlayBatchPredictionArgs

    +

    Batch Prediction Config for the TrainablePlugAndPlay problem type

    + +

    _BatchPredictionArgsFactory

    Helper class that provides a standard way to create an ABC using

    -

    BlobInput

    +

    BlobInput

    Binary large object input data.

    -

    OcrMode

    +

    OcrMode

    Generic enumeration.

    -

    ParsingConfig

    +

    ParsingConfig

    Helper class that provides a standard way to create an ABC using

    -

    DocumentProcessingConfig

    +

    DocumentProcessingConfig

    Document processing configuration.

    -

    IncrementalDatabaseConnectorConfig

    +

    IncrementalDatabaseConnectorConfig

    Config information for incremental datasets from database connectors

    -

    DatasetConfig

    +

    DatasetConfig

    Helper class that provides a standard way to create an ABC using

    -

    ConfluenceDatasetConfig

    +

    ConfluenceDatasetConfig

    Dataset config for Confluence Application Connector

    -

    GoogleAnalyticsDatasetConfig

    +

    GoogleAnalyticsDatasetConfig

    Dataset config for Google Analytics Application Connector

    -

    GoogleDriveDatasetConfig

    +

    GoogleDriveDatasetConfig

    Dataset config for Google Drive Application Connector

    -

    JiraDatasetConfig

    +

    JiraDatasetConfig

    Dataset config for Jira Application Connector

    -

    OneDriveDatasetConfig

    +

    OneDriveDatasetConfig

    Dataset config for OneDrive Application Connector

    -

    SharepointDatasetConfig

    +

    SharepointDatasetConfig

    Dataset config for Sharepoint Application Connector

    -

    ZendeskDatasetConfig

    +

    ZendeskDatasetConfig

    Dataset config for Zendesk Application Connector

    -

    AbacusUsageMetricsDatasetConfig

    +

    AbacusUsageMetricsDatasetConfig

    Dataset config for Abacus Usage Metrics Application Connector

    -

    _DatasetConfigFactory

    +

    _DatasetConfigFactory

    Helper class that provides a standard way to create an ABC using

    -

    VectorStoreTextEncoder

    +

    VectorStoreTextEncoder

    Generic enumeration.

    -

    VectorStoreConfig

    +

    VectorStoreConfig

    Configs for vector store indexing.

    -

    DocumentRetrieverConfig

    +

    DocumentRetrieverConfig

    Configs for document retriever.

    -

    ApiEnum

    +

    ApiEnum

    +

    Generic enumeration.

    + +

    ProblemType

    Generic enumeration.

    -

    ProblemType

    +

    RegressionObjective

    Generic enumeration.

    -

    RegressionObjective

    +

    RegressionTreeHPOMode

    Generic enumeration.

    -

    RegressionTreeHPOMode

    +

    PartialDependenceAnalysis

    Generic enumeration.

    -

    PartialDependenceAnalysis

    +

    RegressionAugmentationStrategy

    Generic enumeration.

    -

    RegressionAugmentationStrategy

    +

    RegressionTargetTransform

    Generic enumeration.

    -

    RegressionTargetTransform

    +

    RegressionTypeOfSplit

    Generic enumeration.

    -

    RegressionTypeOfSplit

    +

    RegressionTimeSplitMethod

    Generic enumeration.

    -

    RegressionTimeSplitMethod

    +

    RegressionLossFunction

    Generic enumeration.

    -

    RegressionLossFunction

    +

    ExplainerType

    Generic enumeration.

    -

    ExplainerType

    +

    SamplingMethodType

    Generic enumeration.

    -

    SamplingMethodType

    +

    MergeMode

    Generic enumeration.

    -

    MergeMode

    +

    FillLogic

    Generic enumeration.

    -

    FillLogic

    +

    BatchSize

    Generic enumeration.

    -

    BatchSize

    +

    HolidayCalendars

    Generic enumeration.

    -

    HolidayCalendars

    +

    FileFormat

    Generic enumeration.

    -

    FileFormat

    +

    ExperimentationMode

    Generic enumeration.

    -

    ExperimentationMode

    +

    PersonalizationTrainingMode

    Generic enumeration.

    -

    PersonalizationTrainingMode

    +

    PersonalizationObjective

    Generic enumeration.

    -

    PersonalizationObjective

    +

    ForecastingObjective

    Generic enumeration.

    -

    ForecastingObjective

    +

    ForecastingFrequency

    Generic enumeration.

    -

    ForecastingFrequency

    +

    ForecastingDataSplitType

    Generic enumeration.

    -

    ForecastingDataSplitType

    +

    ForecastingLossFunction

    Generic enumeration.

    -

    ForecastingLossFunction

    +

    ForecastingLocalScaling

    Generic enumeration.

    -

    ForecastingLocalScaling

    +

    ForecastingFillMethod

    Generic enumeration.

    -

    ForecastingFillMethod

    +

    ForecastingQuanitlesExtensionMethod

    Generic enumeration.

    -

    ForecastingQuanitlesExtensionMethod

    +

    TimeseriesAnomalyDataSplitType

    Generic enumeration.

    -

    TimeseriesAnomalyDataSplitType

    +

    TimeseriesAnomalyTypeOfAnomaly

    Generic enumeration.

    -

    TimeseriesAnomalyTypeOfAnomaly

    +

    NERObjective

    Generic enumeration.

    -

    NERObjective

    +

    NERModelType

    Generic enumeration.

    -

    NERModelType

    +

    NLPDocumentFormat

    Generic enumeration.

    -

    NLPDocumentFormat

    +

    SentimentType

    Generic enumeration.

    -

    SentimentType

    +

    ClusteringImputationMethod

    Generic enumeration.

    -

    ClusteringImputationMethod

    +

    ConnectorType

    Generic enumeration.

    -

    ConnectorType

    +

    ApplicationConnectorType

    Generic enumeration.

    -

    ApplicationConnectorType

    +

    PythonFunctionArgumentType

    Generic enumeration.

    -

    PythonFunctionArgumentType

    +

    PythonFunctionOutputArgumentType

    Generic enumeration.

    -

    PythonFunctionOutputArgumentType

    +

    LLMName

    Generic enumeration.

    -

    LLMName

    +

    MonitorAlertType

    Generic enumeration.

    -

    MonitorAlertType

    +

    FeatureDriftType

    Generic enumeration.

    -

    FeatureDriftType

    +

    DataIntegrityViolationType

    Generic enumeration.

    -

    DataIntegrityViolationType

    +

    BiasType

    Generic enumeration.

    -

    BiasType

    +

    AlertActionType

    Generic enumeration.

    -

    AlertActionType

    +

    PythonFunctionType

    Generic enumeration.

    -

    PythonFunctionType

    +

    EvalArtifactType

    Generic enumeration.

    -

    EvalArtifactType

    +

    FieldDescriptorType

    Generic enumeration.

    -

    FieldDescriptorType

    +

    DataType

    Generic enumeration.

    SamplingConfig

    @@ -1360,6 +1368,7 @@

    Attributes

    • for_eval (bool) – If True, the test fold which was created during training and used for metrics calculation will be used as input data. These predictions are hence, used for model evaluation.

    • threshold (float) – The threshold for detecting an anomaly. Range: [0.8, 0.99]

      • +

    • explain_predictions (bool) – If True, calculates explanations for the predicted values along with predictions.

    @@ -1373,6 +1382,11 @@

    Attributesthreshold: float

    +
    +
    +explain_predictions: bool
    +
    +
    __post_init__()
    @@ -1394,7 +1408,8 @@

    Attributesint) – Sets prediction start date as this offset relative to the prediction start date.

  • forecasting_horizon (int) – The number of timestamps to predict in the future. Range: [1, 1000].

  • item_attributes_to_include_in_the_result (list) – List of columns to include in the prediction output.

    • -

  • explain_predictions (bool) – If True, explain predictions for the forecast.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the forecasted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -1433,6 +1448,11 @@

    Attributesexplain_predictions: bool
    +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -1530,6 +1550,8 @@

    Attributesfloat) – If set explanations will be limited to predictions below this value, Range: [0, 1].

  • bound_label (str) – For classification problems specifies the label to which the explanation bounds are applied.

  • output_columns (list) – A list of column names to include in the prediction result.

    • +

  • explain_predictions (bool) – If True, calculates explanations for the predicted values along with predictions.

    • +

  • automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    • @@ -1583,6 +1605,16 @@

    Attributesoutput_columns: list
    +
    +
    +explain_predictions: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    +
    __post_init__()
    @@ -1720,6 +1752,33 @@

    Attributes +
    +class abacusai.TrainablePlugAndPlayBatchPredictionArgs
    +

    Bases: BatchPredictionArgs

    +

    Batch Prediction Config for the TrainablePlugAndPlay problem type

    +
    +
    Parameters:
    +

    automate_monitoring (bool) – If True, creates a monitor to calculate the drift for the batch prediction.

    +
    +
    +
    +
    +for_eval: bool
    +
    + +
    +
    +automate_monitoring: bool
    +
    + +
    +
    +__post_init__()
    +
    + +

    +
    class abacusai._BatchPredictionArgsFactory
    @@ -2300,6 +2359,7 @@

    Attributesfloat) – The fraction of overlap between chunks.

  • text_encoder (VectorStoreTextEncoder) – Encoder used to index texts from the documents.

  • chunk_size_factors (list) – Chunking data with multiple sizes. The specified list of factors are used to calculate more sizes, in addition to chunk_size.

    • +

  • score_multiplier_column (str) – If provided, will use the values in this metadata column to modify the relevance score of returned chunks for all queries.

    • @@ -2323,6 +2383,11 @@

    Attributeschunk_size_factors: list
    +
    +
    +score_multiplier_column: str
    +
    +
    @@ -3740,6 +3805,11 @@

    AttributesABACUSUSAGEMETRICS = 'ABACUSUSAGEMETRICS'

    +
    +
    +MICROSOFTAUTH = 'MICROSOFTAUTH'
    +
    +
    @@ -4215,6 +4285,64 @@

    Attributes +
    +class abacusai.DataType
    +

    Bases: ApiEnum

    +

    Generic enumeration.

    +

    Derive from this class to define new enumerations.

    +
    +
    +INTEGER = 'integer'
    +
    + +
    +
    +FLOAT = 'float'
    +
    + +
    +
    +STRING = 'string'
    +
    + +
    +
    +DATE = 'date'
    +
    + +
    +
    +DATETIME = 'datetime'
    +
    + +
    +
    +BOOLEAN = 'boolean'
    +
    + +
    +
    +LIST = 'list'
    +
    + +
    +
    +STRUCT = 'struct'
    +
    + +
    +
    +NULL = 'null'
    +
    + +
    +
    +classmethod from_str(value)
    +
    + +

    +
    class abacusai.SamplingConfig
    @@ -5526,6 +5654,7 @@

    Attributesbool) – When running data queries, hides the generated SQL in the response and will just return the table.

  • disable_data_summarization (bool) – After executing a query summarize the reponse and reply back with only the table and query run.

  • search_score_cutoff (float) – Minimum search score to consider a document as a valid search result.

    • +

  • database_connector_id (str) – Database connector id to use for the chatllm.

    • @@ -5599,6 +5728,11 @@

    Attributessearch_score_cutoff: float
    +
    +
    +database_connector_id: str
    +
    +
    __post_init__()
    @@ -10003,7 +10137,7 @@

    Attributes

    • dataset_id (str) – The unique ID associated with the dataset.

    • column (str) – The name of the column.

      • -

    • data_type (str) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

      • +

    • data_type (DataType) – The type of the data in the column. Note: Some ColumnMappings may restrict the options or explicitly set the DataType.

    Returns:
    @@ -12596,7 +12730,7 @@

    Attributes
    -create_batch_prediction(deployment_id, table_name=None, name=None, global_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)
    +create_batch_prediction(deployment_id, table_name=None, name=None, global_prediction_args=None, batch_prediction_args=None, explanations=False, output_format=None, output_location=None, database_connector_id=None, database_output_config=None, refresh_schedule=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, input_feature_groups=None)

    Creates a batch prediction job description for the given deployment.

    Parameters:
    @@ -12604,8 +12738,7 @@

    Attributesstr) – Unique string identifier for the deployment.

  • table_name (str) – Name of the feature group table to write the results of the batch prediction. Can only be specified if outputLocation and databaseConnectorId are not specified. If tableName is specified, the outputType will be enforced as CSV.

  • name (str) – Name of the batch prediction job.

    • -

  • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • -

  • explanations (bool) – If true, SHAP explanations will be provided for each prediction, if supported by the use case.

    • +

  • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

  • output_format (str) – Format of the batch prediction output (CSV or JSON).

  • output_location (str) – Location to write the prediction results. Otherwise, results will be stored in Abacus.AI.

  • database_connector_id (str) – Unique identifier of a Database Connection to write predictions to. Cannot be specified in conjunction with outputLocation.

    • @@ -12617,6 +12750,8 @@

    Attributesbool) – If true, output will contain columns including prediction start time, batch prediction version, and model version.

  • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

  • input_feature_groups (dict) – A dict of {‘<feature_group_type>’: ‘<feature_group_id>’} which overrides the default input data of that type for the Batch Prediction. Default input data is the training data that was used for training the deployed model.

    • +

  • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

    • +

  • explanations (bool) –

    • Returns:
    @@ -12647,15 +12782,14 @@

    Attributes
    -update_batch_prediction(batch_prediction_id, deployment_id=None, global_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)
    +update_batch_prediction(batch_prediction_id, deployment_id=None, global_prediction_args=None, batch_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None, name=None)

    Update a batch prediction job description.

    Parameters:

    • batch_prediction_id (str) – Unique identifier of the batch prediction.

    • deployment_id (str) – Unique identifier of the deployment.

      • -

    • global_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

      • -

    • explanations (bool) – If True, SHAP explanations for each prediction will be provided, if supported by the use case.

      • +

    • batch_prediction_args (BatchPredictionArgs) – Batch Prediction args specific to problem type.

    • output_format (str) – If specified, sets the format of the batch prediction output (CSV or JSON).

    • csv_input_prefix (str) – Prefix to prepend to the input columns, only applies when output format is CSV.

    • csv_prediction_prefix (str) – Prefix to prepend to the prediction columns, only applies when output format is CSV.

      • @@ -12663,6 +12797,8 @@

      Attributesbool) – If True, output will contain columns including prediction start time, batch prediction version, and model version.

    • result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list.

    • name (str) – If present, will rename the batch prediction.

      • +

    • global_prediction_args (Union[dict, abacusai.api_class.BatchPredictionArgs]) –

      • +

    • explanations (bool) –

    Returns:
    @@ -12999,28 +13135,7 @@

    Attributes
    -upsert_data(feature_group_id, streaming_token=None, data=None)
    -

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    -
    -
    Parameters:
    -
      -

    • feature_group_id (str) – A unique string identifier of the streaming feature group to record data to.

      • -

    • streaming_token (str) – Optional streaming token for authenticating requests if upserting to streaming FG.

      • -

    • data (dict) – The data to record, in JSON format.

      • -
    -
    -
    Returns:
    -

    The feature group row that was upserted.

    -
    -
    Return type:
    -

    FeatureGroupRow

    -
    -
    -

    - -
    -
    -upsert_online_data(feature_group_id, data, streaming_token=None)
    +upsert_data(feature_group_id, data, streaming_token=None)

    Update new data into the feature group for a given lookup key record ID if the record ID is found; otherwise, insert new data into the feature group.

    Parameters:
    @@ -14304,7 +14419,7 @@

    Attributes
    -update_external_application(external_application_id, name=None, theme=None, deployment_id=None)
    +update_external_application(external_application_id, name=None, theme=None, deployment_id=None, deployment_conversation_retention_hours=None, reset_retention_policy=False)

    Updates an External Application.

    Parameters:
    @@ -14313,6 +14428,8 @@

    Attributesstr) – The name of the External Application.

  • theme (dict) – The visual theme of the External Application.

  • deployment_id (str) – The ID of the deployment to use.

    • +

  • deployment_conversation_retention_hours (int) – The number of hours to retain the conversations for.

    • +

  • reset_retention_policy (bool) – If true, the retention policy will be removed.

    • Returns:
    @@ -18957,7 +19074,7 @@

    Attributes
    -abacusai.__version__ = '1.1.5'
    +abacusai.__version__ = '1.1.6'

    diff --git a/docs/autoapi/abacusai/pipeline/index.html b/docs/autoapi/abacusai/pipeline/index.html index 490110d41..563921799 100644 --- a/docs/autoapi/abacusai/pipeline/index.html +++ b/docs/autoapi/abacusai/pipeline/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.pipeline.Pipeline(client, pipelineName=None, pipelineId=None, createdAt=None, pipelineVariableMappings=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={})
    +class abacusai.pipeline.Pipeline(client, pipelineName=None, pipelineId=None, createdAt=None, notebookId=None, cron=None, nextRunTime=None, isProd=None, warning=None, createdBy=None, steps={}, pipelineReferences={}, latestPipelineVersion={}, codeSource={}, pipelineVariableMappings={})

    Bases: abacusai.return_class.AbstractApiClass

    A Pipeline For Steps.

    @@ -308,7 +308,6 @@

    Classesstr) – The name of the pipeline this step is a part of.

  • pipelineId (str) – The reference to the pipeline this step belongs to.

  • createdAt (str) – The date and time which the pipeline was created.

    • -

  • pipelineVariableMappings (dict) – A description of the function variables into the pipeline.

  • notebookId (str) – The reference to the notebook this pipeline belongs to.

  • cron (str) – A cron-style string that describes when this refresh policy is to be executed in UTC

  • nextRunTime (str) – The next time this pipeline will be run.

    • diff --git a/docs/autoapi/abacusai/pipeline_version/index.html b/docs/autoapi/abacusai/pipeline_version/index.html index 2d55f1927..63a2b4aaa 100644 --- a/docs/autoapi/abacusai/pipeline_version/index.html +++ b/docs/autoapi/abacusai/pipeline_version/index.html @@ -298,7 +298,7 @@

    Classes
    -class abacusai.pipeline_version.PipelineVersion(client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, pipelineVariableMappings=None, stepVersions={}, codeSource={})
    +class abacusai.pipeline_version.PipelineVersion(client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, stepVersions={}, codeSource={}, pipelineVariableMappings={})

    Bases: abacusai.return_class.AbstractApiClass

    A version of a pipeline.

    @@ -313,7 +313,6 @@

    Classesstr) – The date and time which this pipeline version was updated.

  • status (str) – The status of the pipeline version.

  • error (str) – The relevant error, if the status is FAILED.

    • -

  • pipelineVariableMappings (dict) – A description of the function variables into the pipeline.

  • stepVersions (PipelineStepVersion) – A list of the pipeline step versions.

  • codeSource (CodeSource) – information on the source code

    • diff --git a/docs/autoapi/abacusai/project/index.html b/docs/autoapi/abacusai/project/index.html index 8e32d4672..6fbc3272b 100644 --- a/docs/autoapi/abacusai/project/index.html +++ b/docs/autoapi/abacusai/project/index.html @@ -1149,37 +1149,6 @@

    Classes -
    -attach_dataset(dataset_id, project_dataset_type)
    -

    Attaches dataset to the project.

    -
    -
    Parameters:
    -
      -

    • dataset_id (unique string identifier) – A unique identifier for the dataset.

      • -

    • project_dataset_type (enum of type string) – The unique use case specific dataset type that might be required or recommended for the specific use case.

      • -
    -
    -
    Returns:
    -

    The schema of the attached dataset.

    -
    -
    Return type:
    -

    Schema

    -
    -
    -

    - -
    -
    -remove_dataset(dataset_id)
    -

    Removes dataset from the project.

    -
    -
    Parameters:
    -

    dataset_id (unique string identifier) – A unique identifier for the dataset.

    -
    -
    -
    -
    create_model_from_functions(train_function, predict_function=None, training_input_tables=None, predict_many_function=None, initialize_function=None, cpu_size=None, memory=None, training_config=None, exclusive_run=False)
    diff --git a/docs/genindex.html b/docs/genindex.html index 0b57f4d35..d2ed09ed3 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -167,6 +167,8 @@

    _

  • (abacusai.api_class.batch_prediction.SentenceBoundaryDetectionBatchPredictionArgs method)
  • (abacusai.api_class.batch_prediction.ThemeAnalysisBatchPredictionArgs method) +
    • +
  • (abacusai.api_class.batch_prediction.TrainablePlugAndPlayBatchPredictionArgs method)
  • (abacusai.api_class.BiasViolationConditionConfig method)
    • @@ -355,6 +357,8 @@

    _

  • (abacusai.api_class.TimeseriesAnomalyTrainingConfig method)
  • (abacusai.api_class.TimeWindowMergeConfig method) +
    • +
  • (abacusai.api_class.TrainablePlugAndPlayBatchPredictionArgs method)
  • (abacusai.api_class.ZendeskDatasetConfig method)
    • @@ -457,6 +461,8 @@

    _

  • (abacusai.TimeseriesAnomalyTrainingConfig method)
  • (abacusai.TimeWindowMergeConfig method) +
    • +
  • (abacusai.TrainablePlugAndPlayBatchPredictionArgs method)
  • (abacusai.ZendeskDatasetConfig method)
    • @@ -2359,8 +2365,6 @@

    A

  • module
    • - -
    • abacusai.pipeline_reference @@ -2375,6 +2379,8 @@

      A

    • module
    + + -
  • attach_dataset() (abacusai.project.Project method) -
  • AU (abacusai.api_class.enums.HolidayCalendars attribute)
    • +
  • automate_monitoring (abacusai.api_class.batch_prediction.ForecastingBatchPredictionArgs attribute) + +
  • AUTOMATIC (abacusai.api_class.ClusteringImputationMethod attribute) @@ -3614,9 +3638,13 @@

    B

  • (class in abacusai.api_class.blob_input)
    • -
  • BOOLEAN (abacusai.api_class.enums.FieldDescriptorType attribute) +
  • BOOLEAN (abacusai.api_class.DataType attribute)
    • -
  • database_connector_id (abacusai.api_class.DatabaseConnectorExportConfig attribute) +
  • database_connector_id (abacusai.api_class.ChatLLMTrainingConfig attribute) - +
    • - - +
  • from_response() (abacusai.client._ApiExceptionFactory class method)
    • +
  • from_str() (abacusai.api_class.DataType class method) + +
  • full_data_retraining (abacusai.api_class.ForecastingTrainingConfig attribute)
    • -
  • get_results() (abacusai.feature_group_export.FeatureGroupExport method) -
  • get_schema() (abacusai.dataset.Dataset method)
      @@ -8616,14 +8702,20 @@

      I

  • InstanceNotModifiedError
    • -
  • INTEGER (abacusai.api_class.enums.FieldDescriptorType attribute) +
  • INTEGER (abacusai.api_class.DataType attribute)
    • -
  • LIST (abacusai.api_class.enums.PythonFunctionArgumentType attribute) +
  • LIST (abacusai.api_class.DataType attribute)
    • + + - + -
  • remove_dataset() (abacusai.project.Project method) -
  • remove_deployment_feature_group_export_output() (abacusai.ApiClient method)
    • +
  • score_multiplier_column (abacusai.api_class.document_retriever.VectorStoreConfig attribute) + +
  • search_chunk_size (abacusai.api_class.model.NaturalLanguageSearchTrainingConfig attribute) @@ -12983,8 +13103,6 @@

    S

  • (abacusai.client.ApiClient method)
    • - - + + + + -
    • update_point_in_time_group() (abacusai.ApiClient method)
        @@ -14991,14 +15133,6 @@

        U

        -
      • upsert_online_data() (abacusai.ApiClient method) - -
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173, 179, 180, 181, 183, 184, 185, 186, 188, 190, 192, 194, 196, 198, 199, 200, 201, 205, 206, 212, 213, 218], "date": [1, 5, 16, 21, 23, 24, 36, 41, 47, 61, 62, 77, 84, 120, 124, 137, 143, 147, 151, 154, 155, 156, 165, 167, 169, 170, 173, 179, 183, 184, 185, 186, 188, 196, 203, 216, 218], "time": [1, 5, 11, 12, 21, 22, 23, 24, 26, 35, 36, 41, 47, 57, 58, 59, 61, 62, 69, 72, 77, 83, 84, 86, 90, 94, 96, 102, 107, 111, 116, 117, 118, 120, 122, 124, 137, 138, 143, 144, 147, 151, 154, 155, 156, 160, 165, 167, 169, 170, 173, 175, 176, 177, 178, 179, 183, 184, 185, 186, 188, 190, 196, 198, 199, 200, 203, 207, 212, 216, 218], "which": [1, 11, 16, 18, 23, 24, 31, 33, 35, 39, 40, 41, 43, 57, 61, 63, 64, 66, 67, 69, 72, 74, 77, 84, 94, 96, 97, 98, 105, 107, 120, 121, 122, 124, 134, 137, 138, 143, 150, 151, 155, 156, 163, 164, 167, 169, 170, 173, 175, 176, 177, 178, 179, 185, 186, 187, 188, 190, 199, 205, 212], "wa": [1, 7, 11, 12, 16, 23, 24, 30, 32, 34, 35, 39, 40, 41, 46, 47, 48, 54, 57, 59, 61, 62, 63, 64, 66, 67, 69, 71, 72, 73, 74, 77, 94, 96, 101, 102, 103, 105, 107, 114, 120, 122, 123, 124, 126, 137, 138, 142, 143, 150, 154, 155, 156, 163, 165, 167, 169, 170, 173, 183, 184, 185, 186, 188, 190, 194, 196, 198, 199, 204, 206, 212, 218], "creat": [1, 5, 7, 13, 16, 18, 19, 22, 23, 24, 25, 26, 27, 29, 30, 32, 34, 35, 36, 40, 41, 46, 47, 48, 54, 57, 59, 61, 62, 63, 66, 69, 72, 73, 74, 77, 79, 81, 90, 94, 96, 101, 102, 105, 107, 114, 120, 121, 122, 123, 124, 137, 138, 141, 143, 147, 150, 151, 154, 155, 156, 159, 163, 165, 167, 169, 170, 173, 179, 183, 184, 185, 186, 188, 190, 194, 196, 198, 199, 200, 204, 206, 212, 218], "project": [1, 23, 40, 41, 61, 77, 87, 94, 96, 99, 109, 120, 124, 137, 143, 147, 155, 179, 183, 185, 189, 190, 191, 193, 199, 203, 210, 214, 215], "belong": [1, 5, 11, 23, 24, 41, 59, 61, 63, 77, 84, 95, 101, 102, 103, 107, 120, 124, 137, 143, 147, 150, 151, 155, 167, 169, 170, 173, 175, 176, 183, 185, 216], "notebook": [1, 41, 42, 46, 47, 74, 124, 137, 154, 167, 168, 172, 185, 188, 194, 196, 199], "associ": [1, 35, 40, 41, 57, 59, 61, 62, 63, 64, 69, 72, 77, 81, 84, 87, 94, 105, 107, 121, 122, 124, 137, 143, 147, 155, 156, 179, 188, 198, 199, 212], "function": [1, 7, 23, 24, 28, 42, 46, 48, 49, 69, 94, 107, 118, 119, 120, 124, 137, 151, 154, 167, 169, 170, 173, 179, 185, 188, 190, 194, 196], "found": [1, 7, 23, 24, 36, 41, 69, 94, 124, 137, 179, 185, 188, 205], "sourc": [1, 5, 7, 22, 23, 41, 42, 43, 46, 48, 57, 59, 90, 94, 107, 124, 128, 137, 151, 154, 159, 160, 167, 169, 170, 173, 177, 179, 185, 186, 188, 190, 194, 196], "code": [1, 5, 7, 41, 42, 46, 48, 94, 107, 124, 128, 131, 134, 137, 151, 154, 167, 169, 170, 173, 185, 186, 188, 190, 194, 196, 208], "execut": [1, 3, 5, 7, 23, 24, 41, 86, 94, 118, 124, 129, 130, 135, 137, 167, 179, 185, 188, 190, 194, 195, 199, 200], "run": [1, 7, 23, 24, 35, 41, 42, 54, 61, 64, 84, 86, 124, 137, 143, 147, 155, 156, 167, 168, 173, 183, 184, 185, 188, 194, 195, 198, 199, 200], "predict": [1, 7, 16, 21, 23, 24, 26, 30, 31, 35, 36, 37, 38, 41, 61, 62, 75, 76, 91, 93, 116, 117, 124, 137, 142, 143, 144, 145, 147, 148, 151, 161, 168, 172, 179, 180, 181, 182, 183, 184, 185, 186, 188, 197, 198, 199, 209, 211, 212], "through": [1, 7, 23, 24, 41, 124, 137, 164, 188], "It": [1, 7, 23, 24, 41, 57, 94, 124, 137, 139, 179, 188, 212], "i": [1, 5, 7, 8, 10, 11, 14, 16, 18, 19, 23, 24, 26, 28, 30, 33, 35, 36, 40, 41, 42, 45, 47, 57, 59, 61, 62, 63, 69, 70, 72, 74, 77, 81, 84, 86, 94, 96, 97, 98, 100, 102, 105, 107, 114, 118, 122, 123, 124, 128, 136, 137, 138, 139, 143, 147, 151, 153, 155, 156, 158, 167, 168, 169, 172, 173, 175, 177, 179, 180, 181, 184, 185, 186, 187, 188, 190, 193, 194, 195, 198, 199, 200, 204, 205, 210, 212, 215, 218], "when": [1, 7, 18, 22, 23, 24, 26, 32, 34, 35, 36, 41, 45, 46, 47, 48, 54, 57, 59, 61, 62, 69, 72, 73, 77, 94, 98, 101, 102, 105, 107, 111, 114, 123, 124, 136, 137, 142, 143, 150, 154, 163, 165, 167, 169, 170, 179, 183, 184, 185, 188, 190, 194, 196, 198, 199, 200, 204, 206, 210, 212, 216], "python": [1, 5, 23, 28, 41, 42, 94, 107, 120, 124, 128, 137, 151, 154, 167, 169, 170, 185, 186, 188, 190, 194, 195, 196, 208], "us": [1, 5, 7, 12, 13, 14, 16, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, 39, 41, 45, 46, 47, 57, 61, 62, 63, 64, 65, 67, 69, 70, 74, 87, 90, 94, 96, 97, 98, 100, 105, 107, 109, 120, 121, 122, 123, 124, 125, 126, 129, 130, 134, 136, 137, 139, 141, 142, 144, 148, 149, 150, 151, 152, 154, 159, 162, 164, 175, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 190, 194, 196, 203, 204, 210, 212, 214, 215], "make": [1, 7, 23, 24, 31, 35, 36, 41, 124, 137, 179, 185, 186, 188], "config": [1, 5, 7, 9, 12, 13, 14, 15, 16, 18, 19, 20, 22, 23, 24, 26, 28, 41, 43, 49, 57, 61, 69, 70, 94, 96, 100, 105, 107, 114, 124, 125, 137, 139, 143, 147, 151, 179, 188, 189, 190, 191, 201, 210], "option": [1, 5, 9, 18, 19, 23, 24, 26, 35, 36, 41, 57, 58, 59, 61, 63, 69, 72, 84, 86, 94, 96, 102, 106, 107, 112, 119, 121, 122, 124, 135, 137, 138, 147, 148, 151, 156, 167, 173, 175, 177, 179, 184, 185, 187, 188, 198, 205, 210, 212], "int": [1, 2, 5, 10, 12, 14, 16, 17, 19, 20, 22, 23, 24, 26, 30, 35, 36, 40, 41, 43, 44, 50, 51, 57, 59, 61, 63, 64, 66, 67, 68, 69, 70, 72, 73, 74, 77, 84, 86, 94, 96, 102, 104, 107, 122, 124, 127, 128, 134, 137, 138, 143, 144, 147, 151, 156, 166, 167, 169, 170, 173, 175, 177, 179, 184, 185, 186, 188, 190, 198, 207, 209, 210, 212], "gb": [1, 41, 94, 107, 124, 137, 151, 167, 169, 170, 185, 186, 188, 190], "specifi": [1, 5, 16, 20, 22, 23, 24, 26, 30, 32, 35, 36, 38, 41, 43, 54, 57, 59, 61, 69, 76, 77, 84, 85, 91, 92, 93, 94, 105, 107, 108, 121, 124, 137, 143, 147, 151, 163, 167, 169, 170, 173, 175, 177, 179, 185, 186, 188, 190, 197, 205, 207, 210, 212], "deploy": [1, 3, 5, 19, 23, 26, 31, 35, 36, 41, 62, 63, 64, 65, 87, 94, 102, 103, 104, 107, 124, 137, 142, 147, 149, 151, 155, 168, 172, 179, 185, 188, 198, 199, 218], "resourc": [1, 41, 150, 198], "bool": [1, 7, 10, 12, 13, 14, 16, 18, 19, 22, 23, 24, 28, 33, 35, 36, 39, 40, 41, 43, 54, 57, 59, 61, 63, 64, 69, 74, 81, 94, 96, 105, 107, 111, 112, 113, 119, 122, 124, 128, 136, 137, 143, 151, 153, 158, 163, 167, 173, 179, 180, 181, 185, 186, 188, 190, 193, 199, 210, 215], "whether": [1, 7, 10, 12, 18, 19, 23, 24, 26, 28, 33, 39, 40, 41, 57, 59, 64, 69, 94, 107, 122, 124, 128, 137, 143, 151, 153, 158, 167, 173, 179, 185, 186, 188, 190], "train": [1, 5, 7, 16, 23, 24, 35, 36, 38, 41, 49, 52, 57, 61, 75, 76, 77, 85, 91, 92, 93, 116, 122, 124, 137, 139, 142, 143, 147, 149, 151, 161, 179, 187, 188, 193, 197, 198, 210, 211, 215], "requir": [1, 18, 23, 28, 41, 42, 61, 63, 69, 94, 107, 124, 137, 150, 151, 167, 169, 179, 180, 181, 185, 187, 188, 194, 210, 215], "deploi": [1, 7, 23, 24, 35, 36, 41, 61, 69, 124, 137, 179, 185, 188], "latest": [1, 12, 23, 24, 35, 41, 47, 57, 61, 69, 77, 79, 82, 83, 94, 116, 117, 124, 137, 143, 155, 167, 183, 185, 190], "argument": [1, 5, 23, 28, 41, 57, 64, 94, 124, 137, 167, 169, 179, 188, 194, 195], "agentvers": [1, 5, 41, 124], "version": [1, 5, 22, 23, 24, 35, 36, 37, 41, 47, 48, 51, 57, 59, 60, 61, 69, 72, 74, 77, 79, 80, 82, 83, 84, 94, 96, 98, 102, 107, 114, 116, 117, 121, 122, 124, 137, 138, 139, 142, 143, 144, 145, 146, 147, 148, 150, 151, 152, 155, 156, 164, 167, 170, 171, 172, 173, 174, 180, 181, 183, 184, 185, 186, 188, 190, 192, 198, 200, 212, 215], "If": [1, 5, 14, 15, 16, 18, 19, 22, 23, 24, 30, 35, 36, 41, 42, 43, 54, 57, 59, 61, 63, 69, 74, 94, 96, 105, 107, 124, 137, 151, 163, 175, 177, 179, 180, 181, 185, 186, 188, 190, 194, 195, 200, 210, 215, 218], "model": [1, 5, 7, 16, 23, 35, 36, 38, 41, 42, 52, 61, 64, 77, 84, 93, 94, 102, 108, 114, 121, 122, 123, 124, 132, 134, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 156, 157, 161, 168, 172, 179, 180, 181, 183, 185, 186, 188, 197, 198, 199, 205, 210, 211, 212], "inform": [1, 2, 3, 4, 5, 18, 23, 34, 35, 36, 41, 46, 48, 49, 54, 61, 64, 90, 94, 97, 106, 107, 120, 124, 130, 135, 137, 141, 144, 145, 146, 151, 153, 154, 155, 160, 163, 167, 169, 170, 173, 179, 185, 186, 188, 190, 194, 203, 206, 217], "refresh": [1, 5, 23, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 100, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 185, 188, 198, 199, 200, 212, 218], "call": [1, 5, 23, 24, 31, 35, 36, 41, 48, 49, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 102, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 149, 151, 155, 156, 163, 167, 169, 170, 173, 184, 185, 188, 198, 199, 212, 218], "describ": [1, 5, 35, 36, 41, 42, 48, 57, 59, 61, 69, 72, 76, 77, 79, 80, 82, 84, 86, 87, 91, 94, 96, 102, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 179, 185, 188, 194, 198, 199, 200, 212, 218], "current": [1, 5, 12, 35, 36, 40, 41, 48, 57, 59, 61, 69, 72, 74, 77, 84, 86, 87, 94, 96, 104, 105, 107, 110, 114, 115, 120, 121, 122, 124, 137, 138, 139, 143, 147, 150, 151, 155, 156, 163, 167, 169, 170, 173, 175, 177, 179, 184, 185, 186, 188, 198, 199, 212, 218], "object": [1, 5, 17, 23, 24, 30, 34, 35, 36, 41, 48, 54, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 97, 100, 105, 107, 112, 120, 121, 122, 124, 132, 137, 138, 143, 145, 146, 147, 151, 153, 155, 156, 158, 163, 164, 167, 168, 169, 170, 172, 173, 179, 185, 188, 194, 195, 198, 199, 200, 205, 212, 218], "": [1, 5, 22, 23, 26, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 84, 86, 87, 90, 94, 96, 105, 107, 109, 110, 111, 120, 121, 122, 124, 137, 138, 143, 144, 147, 151, 153, 155, 156, 159, 163, 167, 169, 170, 173, 177, 179, 185, 188, 198, 199, 203, 212, 216, 218], "field": [1, 5, 13, 14, 16, 19, 23, 24, 25, 26, 29, 35, 36, 41, 48, 57, 59, 61, 69, 72, 74, 77, 84, 86, 87, 89, 94, 96, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 179, 185, 188, 198, 199, 210, 212, 218], "retriev": [1, 5, 20, 23, 24, 35, 36, 41, 45, 57, 59, 61, 69, 70, 71, 72, 77, 84, 94, 124, 137, 143, 147, 151, 164, 179, 188, 198, 199, 212], "full": [1, 5, 18, 23, 41, 57, 59, 61, 77, 84, 112, 124, 134, 137, 143, 147, 151, 188, 212], "descript": [1, 5, 14, 15, 23, 24, 35, 41, 55, 56, 57, 58, 59, 61, 77, 78, 84, 93, 94, 105, 109, 112, 115, 119, 120, 124, 126, 137, 138, 139, 140, 143, 147, 148, 151, 155, 156, 160, 161, 167, 168, 173, 175, 183, 184, 187, 188, 190, 191, 194, 203, 209, 210, 214, 215], "agent_id": [1, 41, 124], "string": [1, 5, 11, 14, 16, 21, 23, 30, 34, 35, 36, 41, 47, 48, 54, 57, 59, 61, 65, 68, 69, 72, 73, 77, 84, 86, 94, 96, 97, 98, 102, 105, 107, 120, 122, 124, 128, 137, 138, 143, 147, 151, 153, 154, 155, 156, 163, 166, 167, 169, 173, 179, 183, 185, 188, 194, 195, 196, 198, 199, 200, 203, 205, 206, 212, 213, 218], "wait_for_publish": [1, 5, 137], "timeout": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 169, 170, 173, 184, 198, 212], "A": [1, 3, 4, 5, 6, 8, 15, 16, 19, 23, 28, 30, 32, 34, 35, 36, 39, 40, 41, 48, 50, 51, 53, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 69, 70, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 86, 87, 90, 91, 93, 94, 95, 96, 98, 99, 100, 101, 102, 104, 105, 107, 108, 109, 110, 112, 114, 120, 121, 122, 123, 124, 125, 126, 134, 137, 138, 140, 143, 144, 145, 146, 147, 150, 151, 155, 156, 157, 159, 160, 164, 167, 168, 169, 170, 172, 173, 174, 175, 176, 177, 178, 179, 183, 184, 185, 186, 187, 188, 190, 191, 192, 193, 194, 195, 198, 199, 200, 203, 204, 205, 206, 209, 210, 212, 213, 214, 215, 218], "wait": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "until": [1, 5, 11, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "publish": [1, 5, 41, 124, 137], "given": [1, 5, 22, 23, 24, 30, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 82, 84, 86, 94, 96, 102, 107, 120, 122, 124, 133, 136, 137, 138, 143, 146, 147, 151, 155, 156, 167, 169, 170, 171, 173, 174, 179, 184, 188, 194, 195, 198, 199, 205, 212, 218], "finish": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "doesn": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 211, 212], "t": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 179, 184, 198, 211, 212], "alloc": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 188, 198, 212], "said": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "out": [1, 5, 19, 23, 24, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 108, 118, 122, 124, 137, 138, 147, 151, 156, 167, 173, 179, 184, 198, 212], "get_statu": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "statu": [1, 5, 9, 11, 12, 34, 35, 36, 40, 41, 42, 54, 57, 59, 61, 69, 72, 74, 84, 86, 87, 94, 95, 96, 102, 107, 114, 122, 124, 130, 137, 138, 147, 150, 151, 156, 167, 170, 172, 173, 184, 186, 198, 206, 212, 216], "pend": [1, 5, 35, 36, 41, 61, 69, 72, 84, 86, 94, 96, 104, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 198, 212], "complet": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 104, 107, 122, 124, 137, 138, 142, 147, 151, 156, 167, 173, 184, 198, 212], "etc": [1, 5, 8, 13, 23, 24, 25, 26, 29, 35, 36, 41, 46, 57, 59, 61, 69, 72, 84, 86, 94, 96, 107, 122, 124, 128, 137, 138, 147, 151, 156, 167, 173, 179, 198, 212], "agentdatadocumentinfo": [2, 3, 4], "docid": [2, 10, 11, 39, 41, 68, 95, 124, 166, 179], "filenam": [2, 17, 23, 41, 124], "mimetyp": [2, 68], "size": [2, 17, 20, 23, 24, 41, 44, 59, 66, 69, 70, 72, 94, 107, 124, 135, 137, 151, 167, 169, 170, 179, 185, 188, 190, 212], "pagecount": [2, 68, 166], "document": [2, 3, 4, 10, 11, 12, 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199], "predictfunctionnam": [1, 7, 41, 124, 137, 185, 188], "sourcecod": [1, 42, 137, 185, 186], "agentconfig": [1, 5], "memori": [1, 41, 44, 57, 94, 107, 124, 135, 137, 151, 167, 169, 170, 185, 186, 188, 190], "trainingrequir": [1, 137], "agentexecutionconfig": [1, 5], "codesourc": [1, 5, 7, 42, 46, 48, 94, 107, 137, 151, 154, 167, 169, 170, 173, 185, 186, 190, 194, 196], "latestagentvers": 1, "ai": [1, 5, 6, 23, 24, 32, 34, 35, 40, 41, 54, 61, 109, 111, 112, 113, 124, 136, 137, 179, 188, 195, 203, 205, 206, 212, 216, 218], "user": [1, 23, 24, 32, 33, 34, 41, 54, 61, 63, 64, 77, 87, 88, 94, 105, 106, 114, 120, 123, 124, 136, 137, 143, 149, 151, 153, 155, 156, 163, 167, 169, 179, 188, 199, 206, 214, 215], "friendli": [1, 32, 34, 41, 54, 61, 77, 94, 105, 114, 120, 123, 124, 137, 143, 155, 156, 199, 206, 214, 215], "uniqu": [1, 3, 5, 7, 32, 33, 34, 35, 36, 40, 41, 46, 47, 48, 54, 55, 56, 57, 58, 59, 61, 62, 63, 65, 68, 69, 72, 73, 74, 77, 84, 87, 90, 94, 95, 96, 97, 100, 105, 107, 109, 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176, 177, 178, 179, 183, 184, 185, 186, 188, 190, 196, 198, 199, 200, 203, 207, 212, 216, 218], "which": [1, 11, 16, 18, 23, 24, 31, 33, 35, 39, 40, 41, 43, 57, 61, 63, 64, 66, 67, 69, 72, 74, 77, 84, 94, 96, 97, 98, 105, 107, 120, 121, 122, 124, 134, 137, 138, 143, 150, 151, 155, 156, 163, 164, 167, 169, 170, 173, 175, 176, 177, 178, 179, 185, 186, 187, 188, 190, 199, 205, 212], "wa": [1, 7, 11, 12, 16, 23, 24, 30, 32, 34, 35, 39, 40, 41, 46, 47, 48, 54, 57, 59, 61, 62, 63, 64, 66, 67, 69, 71, 72, 73, 74, 77, 94, 96, 101, 102, 103, 105, 107, 114, 120, 122, 123, 124, 126, 137, 138, 142, 143, 150, 154, 155, 156, 163, 165, 167, 169, 170, 173, 183, 184, 185, 186, 188, 190, 194, 196, 198, 199, 204, 206, 212, 218], "creat": [1, 5, 7, 13, 16, 18, 19, 22, 23, 24, 25, 26, 27, 29, 30, 32, 34, 35, 40, 41, 46, 47, 48, 54, 57, 59, 61, 62, 63, 66, 69, 72, 73, 74, 77, 79, 81, 90, 94, 96, 101, 102, 105, 107, 114, 120, 121, 122, 123, 124, 137, 138, 141, 143, 147, 150, 151, 154, 155, 156, 159, 163, 165, 167, 169, 170, 173, 179, 183, 184, 185, 186, 188, 190, 194, 196, 198, 199, 200, 204, 206, 212, 218], "project": [1, 23, 40, 41, 61, 77, 87, 94, 96, 99, 109, 120, 124, 137, 143, 147, 155, 179, 183, 185, 189, 190, 191, 193, 199, 203, 210, 214, 215], "belong": [1, 5, 11, 23, 24, 41, 59, 61, 63, 77, 84, 95, 101, 102, 103, 107, 120, 124, 137, 143, 147, 150, 151, 155, 167, 169, 170, 173, 175, 176, 183, 185, 216], "notebook": [1, 41, 42, 46, 47, 74, 124, 137, 154, 167, 168, 172, 185, 188, 194, 196, 199], "associ": [1, 35, 40, 41, 57, 59, 61, 62, 63, 64, 69, 72, 77, 81, 84, 87, 94, 105, 107, 121, 122, 124, 137, 143, 147, 155, 156, 179, 188, 198, 199, 212], "function": [1, 7, 23, 24, 28, 42, 46, 48, 49, 69, 94, 107, 118, 119, 120, 124, 137, 151, 154, 167, 169, 170, 179, 185, 188, 190, 194, 196], "found": [1, 7, 23, 24, 36, 41, 69, 94, 124, 137, 179, 185, 188, 205], "sourc": [1, 5, 7, 22, 23, 41, 42, 43, 46, 48, 57, 59, 90, 94, 107, 124, 128, 137, 151, 154, 159, 160, 167, 169, 170, 173, 177, 179, 185, 186, 188, 190, 194, 196], "code": [1, 5, 7, 41, 42, 46, 48, 94, 107, 124, 128, 131, 134, 137, 151, 154, 167, 169, 170, 173, 185, 186, 188, 190, 194, 196, 208], "execut": [1, 3, 5, 7, 23, 24, 41, 86, 94, 118, 124, 129, 130, 135, 137, 167, 179, 185, 188, 190, 194, 195, 199, 200], "run": [1, 7, 23, 24, 35, 41, 42, 54, 61, 64, 84, 86, 124, 137, 143, 147, 155, 156, 167, 168, 173, 183, 184, 185, 188, 194, 195, 198, 199, 200], "predict": [1, 7, 16, 21, 23, 24, 26, 30, 31, 35, 36, 37, 38, 41, 61, 62, 75, 76, 91, 93, 116, 117, 124, 137, 142, 143, 144, 145, 147, 148, 151, 161, 168, 172, 179, 180, 181, 182, 183, 184, 185, 186, 188, 197, 198, 199, 209, 211, 212], "through": [1, 7, 23, 24, 41, 124, 137, 164, 188], "It": [1, 7, 23, 24, 41, 57, 94, 124, 137, 139, 179, 188, 212], "i": [1, 5, 7, 8, 10, 11, 14, 16, 18, 19, 23, 24, 26, 28, 30, 33, 35, 36, 40, 41, 42, 45, 47, 57, 59, 61, 62, 63, 69, 70, 72, 74, 77, 81, 84, 86, 94, 96, 97, 98, 100, 102, 105, 107, 114, 118, 122, 123, 124, 128, 136, 137, 138, 139, 143, 147, 151, 153, 155, 156, 158, 167, 168, 169, 172, 173, 175, 177, 179, 180, 181, 184, 185, 186, 187, 188, 190, 193, 194, 195, 198, 199, 200, 204, 205, 210, 212, 215, 218], "when": [1, 7, 18, 22, 23, 24, 26, 32, 34, 35, 36, 41, 45, 46, 47, 48, 54, 57, 59, 61, 62, 69, 72, 73, 77, 94, 98, 101, 102, 105, 107, 111, 114, 123, 124, 136, 137, 142, 143, 150, 154, 163, 165, 167, 169, 170, 179, 183, 184, 185, 188, 190, 194, 196, 198, 199, 200, 204, 206, 210, 212, 216], "python": [1, 5, 23, 28, 41, 42, 94, 107, 120, 124, 128, 137, 151, 154, 167, 169, 170, 185, 186, 188, 190, 194, 195, 196, 208], "us": [1, 5, 7, 12, 13, 14, 16, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, 39, 41, 45, 46, 47, 57, 61, 62, 63, 64, 65, 67, 69, 70, 74, 87, 90, 94, 96, 97, 98, 100, 105, 107, 109, 120, 121, 122, 123, 124, 125, 126, 129, 130, 134, 136, 137, 139, 141, 142, 144, 148, 149, 150, 151, 152, 154, 159, 162, 164, 175, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 190, 194, 196, 203, 204, 210, 212, 214, 215], "make": [1, 7, 23, 24, 31, 35, 36, 41, 124, 137, 179, 185, 186, 188], "config": [1, 5, 7, 9, 12, 13, 14, 15, 16, 18, 19, 20, 22, 23, 24, 26, 28, 41, 43, 49, 57, 61, 69, 70, 94, 96, 100, 105, 107, 114, 124, 125, 137, 139, 143, 147, 151, 179, 188, 189, 190, 191, 201, 210], "option": [1, 5, 9, 18, 19, 23, 24, 26, 35, 36, 41, 57, 58, 59, 61, 63, 69, 72, 84, 86, 94, 96, 102, 106, 107, 112, 119, 121, 122, 124, 135, 137, 138, 147, 148, 151, 156, 167, 173, 175, 177, 179, 184, 185, 187, 188, 198, 205, 210, 212], "int": [1, 2, 5, 10, 12, 14, 16, 17, 19, 20, 22, 23, 24, 26, 30, 35, 36, 40, 41, 43, 44, 50, 51, 57, 59, 61, 63, 64, 66, 67, 68, 69, 70, 72, 73, 74, 77, 84, 86, 87, 94, 96, 102, 104, 107, 122, 124, 127, 128, 134, 137, 138, 143, 144, 147, 151, 156, 166, 167, 169, 170, 173, 175, 177, 179, 184, 185, 186, 188, 190, 198, 207, 209, 210, 212], "gb": [1, 41, 94, 107, 124, 137, 151, 167, 169, 170, 185, 186, 188, 190], "specifi": [1, 5, 16, 20, 22, 23, 24, 26, 30, 32, 35, 36, 38, 41, 43, 54, 57, 59, 61, 69, 76, 77, 84, 85, 91, 92, 93, 94, 105, 107, 108, 121, 124, 137, 143, 147, 151, 163, 167, 169, 170, 173, 175, 177, 179, 185, 186, 188, 190, 197, 205, 207, 210, 212], "deploy": [1, 3, 5, 19, 23, 26, 31, 35, 36, 41, 62, 63, 64, 65, 87, 94, 102, 103, 104, 107, 124, 137, 142, 147, 149, 151, 155, 168, 172, 179, 185, 188, 198, 199, 218], "resourc": [1, 41, 150, 198], "bool": [1, 7, 10, 12, 13, 14, 16, 18, 19, 22, 23, 24, 28, 33, 35, 36, 39, 40, 41, 43, 54, 57, 59, 61, 63, 64, 69, 74, 81, 87, 94, 96, 105, 107, 111, 112, 113, 119, 122, 124, 128, 136, 137, 143, 151, 153, 158, 163, 167, 173, 179, 180, 181, 185, 186, 188, 190, 193, 199, 210, 215], "whether": [1, 7, 10, 12, 18, 19, 23, 24, 26, 28, 33, 39, 40, 41, 57, 59, 64, 69, 94, 107, 122, 124, 128, 137, 143, 151, 153, 158, 167, 173, 179, 185, 186, 188, 190], "train": [1, 5, 7, 16, 23, 24, 35, 36, 38, 41, 49, 52, 57, 61, 75, 76, 77, 85, 91, 92, 93, 116, 122, 124, 137, 139, 142, 143, 147, 149, 151, 161, 179, 187, 188, 193, 197, 198, 210, 211, 215], "requir": [1, 18, 23, 28, 41, 42, 61, 63, 69, 94, 107, 124, 137, 150, 151, 167, 169, 179, 180, 181, 185, 187, 188, 194, 210, 215], "deploi": [1, 7, 23, 24, 35, 36, 41, 61, 69, 124, 137, 179, 185, 188], "latest": [1, 12, 23, 24, 35, 41, 47, 57, 61, 69, 77, 79, 82, 83, 94, 116, 117, 124, 137, 143, 155, 167, 183, 185, 190], "argument": [1, 5, 23, 28, 41, 57, 64, 94, 124, 137, 167, 169, 179, 188, 194, 195], "agentvers": [1, 5, 41, 124], "version": [1, 5, 22, 23, 24, 35, 36, 37, 41, 47, 48, 51, 57, 59, 60, 61, 69, 72, 74, 77, 79, 80, 82, 83, 84, 94, 96, 98, 102, 107, 114, 116, 117, 121, 122, 124, 137, 138, 139, 142, 143, 144, 145, 146, 147, 148, 150, 151, 152, 155, 156, 164, 167, 170, 171, 172, 173, 174, 180, 181, 183, 184, 185, 186, 188, 190, 192, 198, 200, 212, 215], "If": [1, 5, 14, 15, 16, 18, 19, 20, 22, 23, 24, 30, 35, 36, 41, 42, 43, 54, 57, 59, 61, 63, 69, 74, 87, 94, 96, 105, 107, 124, 137, 151, 163, 175, 177, 179, 180, 181, 185, 186, 188, 190, 194, 195, 200, 210, 215, 218], "model": [1, 5, 7, 16, 23, 35, 36, 38, 41, 42, 52, 61, 64, 77, 84, 93, 94, 102, 108, 114, 121, 122, 123, 124, 132, 134, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 156, 157, 161, 168, 172, 179, 180, 181, 183, 185, 186, 188, 197, 198, 199, 205, 210, 211, 212], "inform": [1, 2, 3, 4, 5, 18, 23, 34, 35, 36, 41, 46, 48, 49, 54, 61, 64, 90, 94, 97, 106, 107, 120, 124, 130, 135, 137, 141, 144, 145, 146, 151, 153, 154, 155, 160, 163, 167, 169, 170, 173, 179, 185, 186, 188, 190, 194, 203, 206, 217], "refresh": [1, 5, 23, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 100, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 185, 188, 198, 199, 200, 212, 218], "call": [1, 5, 23, 24, 31, 35, 36, 41, 48, 49, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 102, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 149, 151, 155, 156, 163, 167, 169, 170, 173, 184, 185, 188, 198, 199, 212, 218], "describ": [1, 5, 35, 36, 41, 42, 48, 57, 59, 61, 69, 72, 76, 77, 79, 80, 82, 84, 86, 87, 91, 94, 96, 102, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 179, 185, 188, 194, 198, 199, 200, 212, 218], "current": [1, 5, 12, 35, 36, 40, 41, 48, 57, 59, 61, 69, 72, 74, 77, 84, 86, 87, 94, 96, 104, 105, 107, 110, 114, 115, 120, 121, 122, 124, 137, 138, 139, 143, 147, 150, 151, 155, 156, 163, 167, 169, 170, 173, 175, 177, 179, 184, 185, 186, 188, 198, 199, 212, 218], "object": [1, 5, 17, 23, 24, 30, 34, 35, 36, 41, 48, 54, 57, 59, 61, 69, 72, 77, 84, 86, 87, 94, 96, 97, 100, 105, 107, 112, 120, 121, 122, 124, 132, 137, 138, 143, 145, 146, 147, 151, 153, 155, 156, 158, 163, 164, 167, 168, 169, 170, 172, 173, 179, 185, 188, 194, 195, 198, 199, 200, 205, 212, 218], "": [1, 5, 22, 23, 26, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 84, 86, 87, 90, 94, 96, 105, 107, 109, 110, 111, 120, 121, 122, 124, 137, 138, 143, 144, 147, 151, 153, 155, 156, 159, 163, 167, 169, 170, 173, 177, 179, 185, 188, 198, 199, 203, 212, 216, 218], "field": [1, 5, 13, 14, 16, 19, 23, 24, 25, 26, 29, 35, 36, 41, 48, 57, 59, 61, 69, 72, 74, 77, 84, 86, 87, 89, 94, 96, 105, 107, 120, 121, 122, 124, 137, 138, 143, 147, 151, 155, 156, 163, 167, 169, 170, 173, 179, 185, 188, 198, 199, 210, 212, 218], "retriev": [1, 5, 20, 23, 24, 35, 36, 41, 45, 57, 59, 61, 69, 70, 71, 72, 77, 84, 94, 124, 137, 143, 147, 151, 164, 179, 188, 198, 199, 212], "full": [1, 5, 18, 23, 41, 57, 59, 61, 77, 84, 112, 124, 134, 137, 143, 147, 151, 188, 212], "descript": [1, 5, 14, 15, 23, 24, 35, 41, 55, 56, 57, 58, 59, 61, 77, 78, 84, 93, 94, 105, 109, 112, 115, 119, 120, 124, 126, 137, 138, 139, 140, 143, 147, 148, 151, 155, 156, 160, 161, 168, 175, 183, 184, 187, 188, 190, 191, 194, 203, 209, 210, 214, 215], "agent_id": [1, 41, 124], "string": [1, 5, 11, 14, 16, 21, 23, 30, 34, 35, 36, 41, 47, 48, 54, 57, 59, 61, 65, 68, 69, 72, 73, 77, 84, 86, 94, 96, 97, 98, 102, 105, 107, 120, 122, 124, 128, 137, 138, 143, 147, 151, 153, 154, 155, 156, 163, 166, 167, 169, 173, 179, 183, 185, 188, 194, 195, 196, 198, 199, 200, 203, 205, 206, 212, 213, 218], "wait_for_publish": [1, 5, 137], "timeout": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 169, 170, 173, 184, 198, 212], "A": [1, 3, 4, 5, 6, 8, 15, 16, 19, 23, 28, 30, 32, 34, 35, 36, 39, 40, 41, 48, 50, 51, 53, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 69, 70, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 86, 87, 90, 91, 93, 94, 95, 96, 98, 99, 100, 101, 102, 104, 105, 107, 108, 109, 110, 112, 114, 120, 121, 122, 123, 124, 125, 126, 134, 137, 138, 140, 143, 144, 145, 146, 147, 150, 151, 155, 156, 157, 159, 160, 164, 167, 168, 169, 170, 172, 173, 174, 175, 176, 177, 178, 179, 183, 184, 185, 186, 187, 188, 190, 191, 192, 193, 194, 195, 198, 199, 200, 203, 204, 205, 206, 209, 210, 212, 213, 214, 215, 218], "wait": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "until": [1, 5, 11, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "publish": [1, 5, 41, 124, 137], "given": [1, 5, 22, 23, 24, 30, 35, 36, 41, 48, 57, 59, 61, 69, 72, 77, 82, 84, 86, 94, 96, 102, 107, 120, 122, 124, 133, 136, 137, 138, 143, 146, 147, 151, 155, 156, 167, 169, 170, 171, 173, 174, 179, 184, 188, 194, 195, 198, 199, 205, 212, 218], "finish": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "doesn": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 211, 212], "t": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 179, 184, 198, 211, 212], "alloc": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 184, 188, 198, 212], "said": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "out": [1, 5, 19, 23, 24, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 108, 118, 122, 124, 137, 138, 147, 151, 156, 167, 173, 179, 184, 198, 212], "get_statu": [1, 5, 35, 36, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 107, 122, 137, 138, 147, 151, 156, 167, 173, 184, 198, 212], "statu": [1, 5, 9, 11, 12, 34, 35, 36, 40, 41, 42, 54, 57, 59, 61, 69, 72, 74, 84, 86, 87, 94, 95, 96, 102, 107, 114, 122, 124, 130, 137, 138, 147, 150, 151, 156, 167, 170, 172, 173, 184, 186, 198, 206, 212, 216], "pend": [1, 5, 35, 36, 41, 61, 69, 72, 84, 86, 94, 96, 104, 107, 122, 124, 137, 138, 147, 151, 156, 167, 173, 198, 212], "complet": [1, 5, 35, 36, 41, 57, 59, 61, 69, 72, 84, 86, 94, 96, 102, 104, 107, 122, 124, 137, 138, 142, 147, 151, 156, 167, 173, 184, 198, 212], "etc": [1, 5, 8, 13, 23, 24, 25, 26, 29, 35, 36, 41, 46, 57, 59, 61, 69, 72, 84, 86, 94, 96, 107, 122, 124, 128, 137, 138, 147, 151, 156, 167, 173, 179, 198, 212], "agentdatadocumentinfo": [2, 3, 4], "docid": [2, 10, 11, 39, 41, 68, 95, 124, 166, 179], "filenam": [2, 17, 23, 41, 124], "mimetyp": [2, 68], "size": [2, 17, 20, 23, 24, 41, 44, 59, 66, 69, 70, 72, 94, 107, 124, 135, 137, 151, 167, 169, 170, 179, 185, 188, 190, 212], "pagecount": [2, 68, 166], "document": [2, 3, 4, 10, 11, 12, 18, 19, 20, 23, 24, 39, 41, 57, 61, 64, 67, 68, 69, 70, 71, 72, 73, 74, 89, 94, 95, 107, 109, 124, 137, 151, 166, 167, 169, 179, 188, 203], "upload": [2, 3, 4, 23, 24, 39, 41, 57, 59, 74, 124, 137, 150, 179], "agent": [2, 3, 4, 5, 23, 24, 41, 61, 64, 124, 137, 179, 188], "docstor": [2, 10, 30, 41, 68, 124, 166, 179], "id": [2, 3, 5, 10, 11, 16, 19, 23, 24, 32, 33, 34, 35, 36, 39, 40, 41, 49, 57, 59, 61, 63, 64, 69, 72, 77, 84, 86, 87, 94, 95, 96, 97, 100, 101, 102, 103, 107, 114, 117, 120, 121, 122, 124, 137, 142, 143, 147, 148, 151, 152, 155, 156, 167, 168, 169, 170, 171, 172, 173, 179, 182, 185, 186, 188, 190, 192, 198, 199, 202, 205, 206, 212, 218], "file": [2, 16, 19, 21, 23, 24, 30, 35, 36, 40, 41, 57, 59, 61, 66, 72, 94, 96, 97, 100, 107, 111, 113, 124, 137, 138, 150, 151, 167, 169, 185, 188, 190, 212], "mime": [2, 17, 23, 68, 124], "total": [2, 10, 12, 21, 23, 24, 36, 41, 50, 68, 69, 96, 102, 104, 124, 144, 166, 179, 209], "number": [2, 10, 12, 16, 21, 22, 23, 24, 26, 35, 36, 41, 50, 51, 57, 59, 61, 63, 64, 67, 68, 69, 70, 72, 73, 74, 80, 83, 86, 87, 94, 96, 102, 104, 107, 124, 134, 144, 154, 166, 167, 175, 177, 179, 188, 194, 196, 207, 212], "page": [2, 18, 19, 23, 24, 30, 41, 68, 71, 94, 107, 124, 137, 166, 179, 188], "agentdataexecutionresult": [3, 41, 124, 179], "respons": [3, 13, 14, 23, 24, 25, 26, 29, 40, 41, 45, 59, 61, 63, 64, 88, 89, 107, 124, 128, 132, 134, 136, 179, 188], "deploymentconversationid": [3, 63, 65], "docinfo": [3, 4, 64], "result": [3, 4, 16, 23, 24, 30, 35, 36, 41, 53, 61, 64, 69, 71, 86, 94, 111, 124, 130, 132, 137, 151, 156, 164, 179, 188, 193, 194, 195, 201, 209], "data": [3, 4, 6, 7, 8, 15, 16, 17, 20, 23, 24, 26, 30, 35, 36, 40, 41, 43, 44, 49, 50, 52, 53, 55, 57, 58, 61, 68, 69, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 89, 90, 91, 93, 94, 107, 109, 110, 115, 116, 117, 124, 126, 127, 136, 137, 144, 145, 146, 147, 148, 151, 159, 160, 166, 179, 188, 190, 203, 204, 205, 209, 211, 212], "convers": [3, 19, 23, 24, 40, 41, 61, 63, 64, 65, 87, 124, 179], "list": [3, 4, 5, 9, 14, 16, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 33, 34, 35, 36, 37, 38, 39, 41, 42, 44, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 63, 64, 68, 69, 71, 72, 77, 79, 80, 81, 82, 83, 84, 85, 87, 88, 93, 94, 96, 99, 100, 105, 106, 107, 112, 115, 120, 121, 124, 125, 134, 135, 137, 140, 143, 145, 146, 147, 148, 151, 152, 153, 157, 163, 166, 167, 169, 170, 173, 174, 175, 177, 179, 182, 183, 185, 186, 187, 188, 190, 191, 193, 194, 195, 198, 199, 203, 205, 209, 210, 212, 215, 216], "contain": [3, 9, 18, 23, 35, 36, 41, 50, 61, 80, 94, 96, 99, 107, 115, 120, 124, 135, 137, 151, 155, 163, 164, 167, 169, 175, 177, 179, 185, 188, 205, 212], "agentdatauploadresult": 4, "publishingstartedat": 5, "publishingcompletedat": 5, "pendingdeploymentid": [5, 147, 151], "faileddeploymentid": [5, 147, 151], "error": [5, 21, 23, 30, 36, 41, 42, 59, 61, 64, 72, 74, 84, 86, 94, 96, 102, 107, 112, 114, 118, 122, 124, 126, 129, 130, 147, 151, 156, 167, 170, 172, 173, 184, 186, 190, 193, 194, 195, 200, 201, 209, 217], "refer": [5, 41, 57, 59, 77, 84, 120, 124, 147, 150, 151, 167, 168, 169, 170, 172, 173, 179, 188, 212], "start": [5, 16, 19, 21, 23, 24, 35, 36, 41, 57, 61, 69, 77, 84, 94, 102, 118, 124, 128, 137, 143, 147, 151, 156, 166, 175, 177, 179, 184, 188, 198, 207], "process": [5, 18, 23, 24, 41, 44, 51, 61, 84, 95, 102, 103, 104, 107, 124, 140, 147, 151, 156, 185, 212], "iso": [5, 11, 12, 35, 47, 48, 54, 61, 62, 73, 96, 98, 101, 102, 120, 138, 150, 151, 154, 165, 194, 196, 198], "8601": [5, 11, 12, 35, 47, 48, 54, 61, 62, 73, 96, 98, 101, 102, 120, 138, 150, 151, 154, 165, 194, 196, 198], "format": [5, 8, 11, 12, 19, 23, 24, 30, 35, 36, 41, 47, 57, 58, 61, 62, 73, 94, 96, 97, 100, 101, 102, 107, 120, 124, 138, 150, 151, 154, 158, 165, 179, 194, 196, 198, 215], "end": [5, 16, 19, 23, 41, 69, 84, 118, 124, 128, 147, 151, 156], "where": [5, 23, 24, 35, 36, 41, 61, 90, 94, 124, 147, 151, 179, 188], "fail": [5, 36, 41, 42, 59, 61, 72, 74, 84, 86, 96, 102, 104, 107, 114, 122, 124, 129, 130, 144, 147, 151, 156, 170, 173, 184, 186], "relev": [5, 20, 23, 24, 36, 41, 61, 69, 70, 84, 94, 107, 114, 124, 147, 151, 156, 164, 173, 179, 184], "locat": [5, 16, 19, 23, 24, 29, 35, 36, 41, 57, 61, 96, 97, 98, 100, 107, 124, 137, 138, 141, 151, 179, 195, 208], "under": [5, 10, 35, 41, 94, 121, 124, 147, 151, 179, 188], "aibuildingtask": [6, 40], "task": [6, 39, 40], "tasktyp": 6, "scienc": [6, 15, 23, 40, 41, 124, 188], "co": [6, 15, 23, 40, 41, 124, 188], "pilot": [6, 15, 23, 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170, 173, 185, 186, 194, 199, 205, 218], "default": [7, 13, 14, 18, 21, 23, 24, 26, 30, 35, 41, 44, 59, 61, 69, 72, 94, 107, 119, 124, 135, 136, 137, 142, 150, 151, 163, 167, 169, 179, 180, 181, 188, 210, 212], "map": [7, 16, 21, 23, 24, 41, 49, 61, 69, 90, 96, 97, 100, 105, 108, 109, 124, 126, 142, 148, 151, 159, 160, 170, 179, 188, 190, 194, 195, 196, 201, 203, 209, 215], "e": [7, 8, 11, 23, 24, 26, 35, 36, 41, 46, 47, 69, 70, 84, 94, 105, 124, 147, 179, 194], "g": [7, 8, 11, 23, 24, 26, 35, 36, 41, 46, 47, 84, 94, 105, 124, 147, 179], "batch": [7, 16, 23, 24, 35, 36, 37, 41, 61, 124, 137, 143, 147, 168, 172, 180, 181, 182, 188, 198, 212], "initi": [7, 23, 24, 41, 124, 137, 185, 186, 188, 212], "befor": [7, 12, 23, 24, 41, 57, 94, 124, 137, 140, 179, 188], "dataset": [7, 19, 22, 23, 24, 35, 41, 51, 58, 59, 60, 74, 94, 99, 107, 108, 114, 124, 137, 168, 172, 179, 180, 181, 182, 183, 188, 190, 193, 198, 199, 204, 212, 215], "gpu": [7, 23, 24, 41, 44, 94, 124, 135, 137, 151, 185, 186, 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-__version__ = '1.1.5' +__version__ = '1.1.6' setup(name='abacusai',