Version 1.4.78

Author: yogesh-abacusai

abacusai/__init__.py

@@ -292,4 +292,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.77"
+__version__ = "1.4.78"

abacusai/api_class/ai_agents.py

@@ -233,12 +233,12 @@ def from_tool_variable_mappings(cls, tool_variable_mappings: dict):
                 json_schema['properties'][mapping['name']]['format'] = 'data-url'
                 ui_schema[mapping['name']] = {'ui:widget': 'file'}
             if mapping['variable_type'] == enums.PythonFunctionArgumentType.LIST:
-                if mapping['item_type'] == enums.PythonFunctionArgumentType.ATTACHMENT:
+                if mapping.get('item_type') == enums.PythonFunctionArgumentType.ATTACHMENT:
                     json_schema['properties'][mapping['name']]['type'] = 'string'
                     json_schema['properties'][mapping['name']]['format'] = 'data-url'
                     ui_schema[mapping['name']] = {'ui:widget': 'file', 'ui:options': {'multiple': True}}
                 else:
-                    json_schema['properties'][mapping['name']]['items'] = {'type': enums.PythonFunctionArgumentType.to_json_type(mapping['item_type'])}
+                    json_schema['properties'][mapping['name']]['items'] = {'type': enums.PythonFunctionArgumentType.to_json_type(mapping.get('item_type', 'STRING'))}
             if mapping['is_required']:
                 json_schema['required'].append(mapping['name'])
         return cls(json_schema=json_schema, ui_schema=ui_schema)
@@ -738,6 +738,9 @@ def from_dict(cls, node: dict):
 class LLMAgentNode(WorkflowGraphNode):
     """
     Represents an LLM agent node in an Agent workflow graph. The LLM Agent Node can be initialized using either chatbot_deployment_id or creation_parameters.
+    The presence of chatbot_deployment_id indicates that the LLM agent node has already been trained and deployed. During creation of an LLM Node using AI Engineer or deepagent.
+    The chatbot_deployment_id is always passed as None pre-training.
+    chatbot_paramters may contain training_config such as builtin tools, document_retrievers, behaviour instructions etc.
 
     Args:
         name (str): A unique name for the LLM agent node.

abacusai/api_class/enums.py

@@ -427,6 +427,7 @@ class ApplicationConnectorType(ApiEnum):
     OUTLOOK = 'OUTLOOK'
     BIGQUERY = 'BIGQUERY'
     AZURESTORAGE = 'AZURESTORAGE'
+    SHOPIFY = 'SHOPIFY'
 
     @classmethod
     def user_connectors(cls):
@@ -448,7 +449,8 @@ def user_connectors(cls):
             cls.DBC,
             cls.GENERIC_OAUTH,
             cls.OUTLOOK,
-            cls.BIGQUERY
+            cls.BIGQUERY,
+            cls.SHOPIFY
         ]
 
     @classmethod

abacusai/client.py

@@ -667,7 +667,7 @@ 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 = '1.4.77'
+    client_version = '1.4.78'
 
     def __init__(self, api_key: str = None, server: str = None, client_options: ClientOptions = None, skip_version_check: bool = False, include_tb: bool = False):
         self.api_key = api_key

abacusai/dataset.py

@@ -36,6 +36,7 @@ class Dataset(AbstractApiClass):
             mergeFileSchemas (bool): If the merge file schemas policy is enabled.
             referenceOnlyDocumentset (bool): Signifies whether to save the data reference only. Only valid if is_documentset if True.
             versionLimit (int): Version limit for the dataset.
+            disableRealtimeContentProcessing (bool): Whether realtime content processing is disabled for this dataset (only applicable to REALTIME_CONTENT_STORE datasets).
             latestDatasetVersion (DatasetVersion): The latest version of this dataset.
             schema (DatasetColumn): List of resolved columns.
             refreshSchedules (RefreshSchedule): List of schedules that determines when the next version of the dataset will be created.
@@ -44,7 +45,7 @@ class Dataset(AbstractApiClass):
             attachmentParsingConfig (AttachmentParsingConfig): The attachment parsing config used for dataset (eg. for salesforce attachment parsing)
     """
 
-    def __init__(self, client, datasetId=None, sourceType=None, dataSource=None, createdAt=None, ignoreBefore=None, ephemeral=None, lookbackDays=None, databaseConnectorId=None, databaseConnectorConfig=None, connectorType=None, featureGroupTableName=None, applicationConnectorId=None, applicationConnectorConfig=None, incremental=None, isDocumentset=None, extractBoundingBoxes=None, mergeFileSchemas=None, referenceOnlyDocumentset=None, versionLimit=None, schema={}, refreshSchedules={}, latestDatasetVersion={}, parsingConfig={}, documentProcessingConfig={}, attachmentParsingConfig={}):
+    def __init__(self, client, datasetId=None, sourceType=None, dataSource=None, createdAt=None, ignoreBefore=None, ephemeral=None, lookbackDays=None, databaseConnectorId=None, databaseConnectorConfig=None, connectorType=None, featureGroupTableName=None, applicationConnectorId=None, applicationConnectorConfig=None, incremental=None, isDocumentset=None, extractBoundingBoxes=None, mergeFileSchemas=None, referenceOnlyDocumentset=None, versionLimit=None, disableRealtimeContentProcessing=None, schema={}, refreshSchedules={}, latestDatasetVersion={}, parsingConfig={}, documentProcessingConfig={}, attachmentParsingConfig={}):
         super().__init__(client, datasetId)
         self.dataset_id = datasetId
         self.source_type = sourceType
@@ -65,6 +66,7 @@ def __init__(self, client, datasetId=None, sourceType=None, dataSource=None, cre
         self.merge_file_schemas = mergeFileSchemas
         self.reference_only_documentset = referenceOnlyDocumentset
         self.version_limit = versionLimit
+        self.disable_realtime_content_processing = disableRealtimeContentProcessing
         self.schema = client._build_class(DatasetColumn, schema)
         self.refresh_schedules = client._build_class(
             RefreshSchedule, refreshSchedules)
@@ -78,8 +80,8 @@ def __init__(self, client, datasetId=None, sourceType=None, dataSource=None, cre
         self.deprecated_keys = {}
 
     def __repr__(self):
-        repr_dict = {f'dataset_id': repr(self.dataset_id), f'source_type': repr(self.source_type), f'data_source': repr(self.data_source), f'created_at': repr(self.created_at), f'ignore_before': repr(self.ignore_before), f'ephemeral': repr(self.ephemeral), f'lookback_days': repr(self.lookback_days), f'database_connector_id': repr(self.database_connector_id), f'database_connector_config': repr(self.database_connector_config), f'connector_type': repr(self.connector_type), f'feature_group_table_name': repr(self.feature_group_table_name), f'application_connector_id': repr(self.application_connector_id), f'application_connector_config': repr(
-            self.application_connector_config), f'incremental': repr(self.incremental), f'is_documentset': repr(self.is_documentset), f'extract_bounding_boxes': repr(self.extract_bounding_boxes), f'merge_file_schemas': repr(self.merge_file_schemas), f'reference_only_documentset': repr(self.reference_only_documentset), f'version_limit': repr(self.version_limit), f'schema': repr(self.schema), f'refresh_schedules': repr(self.refresh_schedules), f'latest_dataset_version': repr(self.latest_dataset_version), f'parsing_config': repr(self.parsing_config), f'document_processing_config': repr(self.document_processing_config), f'attachment_parsing_config': repr(self.attachment_parsing_config)}
+        repr_dict = {f'dataset_id': repr(self.dataset_id), f'source_type': repr(self.source_type), f'data_source': repr(self.data_source), f'created_at': repr(self.created_at), f'ignore_before': repr(self.ignore_before), f'ephemeral': repr(self.ephemeral), f'lookback_days': repr(self.lookback_days), f'database_connector_id': repr(self.database_connector_id), f'database_connector_config': repr(self.database_connector_config), f'connector_type': repr(self.connector_type), f'feature_group_table_name': repr(self.feature_group_table_name), f'application_connector_id': repr(self.application_connector_id), f'application_connector_config': repr(self.application_connector_config), f'incremental': repr(
+            self.incremental), f'is_documentset': repr(self.is_documentset), f'extract_bounding_boxes': repr(self.extract_bounding_boxes), f'merge_file_schemas': repr(self.merge_file_schemas), f'reference_only_documentset': repr(self.reference_only_documentset), f'version_limit': repr(self.version_limit), f'disable_realtime_content_processing': repr(self.disable_realtime_content_processing), f'schema': repr(self.schema), f'refresh_schedules': repr(self.refresh_schedules), f'latest_dataset_version': repr(self.latest_dataset_version), f'parsing_config': repr(self.parsing_config), f'document_processing_config': repr(self.document_processing_config), f'attachment_parsing_config': repr(self.attachment_parsing_config)}
         class_name = "Dataset"
         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])
@@ -92,8 +94,8 @@ def to_dict(self):
         Returns:
             dict: The dict value representation of the class parameters
         """
-        resp = {'dataset_id': self.dataset_id, 'source_type': self.source_type, 'data_source': self.data_source, 'created_at': self.created_at, 'ignore_before': self.ignore_before, 'ephemeral': self.ephemeral, 'lookback_days': self.lookback_days, 'database_connector_id': self.database_connector_id, 'database_connector_config': self.database_connector_config, 'connector_type': self.connector_type, 'feature_group_table_name': self.feature_group_table_name, 'application_connector_id': self.application_connector_id, 'application_connector_config': self.application_connector_config, 'incremental': self.incremental, 'is_documentset': self.is_documentset,
-                'extract_bounding_boxes': self.extract_bounding_boxes, 'merge_file_schemas': self.merge_file_schemas, 'reference_only_documentset': self.reference_only_documentset, 'version_limit': self.version_limit, 'schema': self._get_attribute_as_dict(self.schema), 'refresh_schedules': self._get_attribute_as_dict(self.refresh_schedules), 'latest_dataset_version': self._get_attribute_as_dict(self.latest_dataset_version), 'parsing_config': self._get_attribute_as_dict(self.parsing_config), 'document_processing_config': self._get_attribute_as_dict(self.document_processing_config), 'attachment_parsing_config': self._get_attribute_as_dict(self.attachment_parsing_config)}
+        resp = {'dataset_id': self.dataset_id, 'source_type': self.source_type, 'data_source': self.data_source, 'created_at': self.created_at, 'ignore_before': self.ignore_before, 'ephemeral': self.ephemeral, 'lookback_days': self.lookback_days, 'database_connector_id': self.database_connector_id, 'database_connector_config': self.database_connector_config, 'connector_type': self.connector_type, 'feature_group_table_name': self.feature_group_table_name, 'application_connector_id': self.application_connector_id, 'application_connector_config': self.application_connector_config, 'incremental': self.incremental, 'is_documentset': self.is_documentset, 'extract_bounding_boxes': self.extract_bounding_boxes,
+                'merge_file_schemas': self.merge_file_schemas, 'reference_only_documentset': self.reference_only_documentset, 'version_limit': self.version_limit, 'disable_realtime_content_processing': self.disable_realtime_content_processing, 'schema': self._get_attribute_as_dict(self.schema), 'refresh_schedules': self._get_attribute_as_dict(self.refresh_schedules), 'latest_dataset_version': self._get_attribute_as_dict(self.latest_dataset_version), 'parsing_config': self._get_attribute_as_dict(self.parsing_config), 'document_processing_config': self._get_attribute_as_dict(self.document_processing_config), 'attachment_parsing_config': self._get_attribute_as_dict(self.attachment_parsing_config)}
         return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}
 
     def get_raw_data_from_realtime(self, check_permissions: bool = False, start_time: str = None, end_time: str = None, column_filter: dict = None):

abacusai/video_gen_settings.py

@@ -10,19 +10,21 @@ class VideoGenSettings(AbstractApiClass):
             client (ApiClient): An authenticated API Client instance
             settings (dict): The settings for each model.
             warnings (dict): The warnings for each model.
+            descriptions (dict): The descriptions for each model.
             model (VideoGenModel): Dropdown for models available for video generation.
     """
 
-    def __init__(self, client, settings=None, warnings=None, model={}):
+    def __init__(self, client, settings=None, warnings=None, descriptions=None, model={}):
         super().__init__(client, None)
         self.settings = settings
         self.warnings = warnings
+        self.descriptions = descriptions
         self.model = client._build_class(VideoGenModel, model)
         self.deprecated_keys = {}
 
     def __repr__(self):
         repr_dict = {f'settings': repr(self.settings), f'warnings': repr(
-            self.warnings), f'model': repr(self.model)}
+            self.warnings), f'descriptions': repr(self.descriptions), f'model': repr(self.model)}
         class_name = "VideoGenSettings"
         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])
@@ -36,5 +38,5 @@ def to_dict(self):
             dict: The dict value representation of the class parameters
         """
         resp = {'settings': self.settings, 'warnings': self.warnings,
-                'model': self._get_attribute_as_dict(self.model)}
+                'descriptions': self.descriptions, 'model': self._get_attribute_as_dict(self.model)}
         return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

docs/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: df4b3fc78cc9b7bc30e9104def812ac3
+config: 83f5dc97472bfb08cd934f5b9735673a
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/.buildinfo.bak

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 1807596735468513042c35ba1a2f25ef
+config: df4b3fc78cc9b7bc30e9104def812ac3
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_sources/autoapi/abacusai/api_class/ai_agents/index.rst.txt

@@ -570,6 +570,9 @@ Module Contents
 
 
    Represents an LLM agent node in an Agent workflow graph. The LLM Agent Node can be initialized using either chatbot_deployment_id or creation_parameters.
+   The presence of chatbot_deployment_id indicates that the LLM agent node has already been trained and deployed. During creation of an LLM Node using AI Engineer or deepagent.
+   The chatbot_deployment_id is always passed as None pre-training.
+   chatbot_paramters may contain training_config such as builtin tools, document_retrievers, behaviour instructions etc.
 
    :param name: A unique name for the LLM agent node.
    :type name: str

docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt

@@ -1866,6 +1866,11 @@ Module Contents
 
 
 
+   .. py:attribute:: SHOPIFY
+      :value: 'SHOPIFY'
+
+
+
    .. py:method:: user_connectors()
       :classmethod: