Version 1.4.33

Author: arvindsun

abacusai/__init__.py

@@ -38,6 +38,7 @@
 from .code_edit_response import CodeEditResponse
 from .code_edits import CodeEdits
 from .code_source import CodeSource
+from .code_suggestion_validation_response import CodeSuggestionValidationResponse
 from .compute_point_info import ComputePointInfo
 from .concatenation_config import ConcatenationConfig
 from .constants_autocomplete_response import ConstantsAutocompleteResponse
@@ -237,4 +238,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.32"
+__version__ = "1.4.33"

abacusai/api_class/dataset_application_connector.py

@@ -222,6 +222,26 @@ def __post_init__(self):
         self.application_connector_type = enums.ApplicationConnectorType.FRESHSERVICE
 
 
+@dataclasses.dataclass
+class SftpDatasetConfig(ApplicationConnectorDatasetConfig):
+    """
+    Dataset config for SFTP Application Connector
+
+    Args:
+        location (str): The regex location of the files to fetch
+        csv_delimiter (str): If the file format is CSV, use a specific csv delimiter
+        extract_bounding_boxes (bool): Signifies whether to extract bounding boxes out of the documents. Only valid if is_documentset if True
+        merge_file_schemas (bool): Signifies if the merge file schema policy is enabled. Not applicable if is_documentset is True
+    """
+    location: str = dataclasses.field(default=None)
+    csv_delimiter: str = dataclasses.field(default=None)
+    extract_bounding_boxes: bool = dataclasses.field(default=False)  # TODO: Deprecate in favour of document_processing_config
+    merge_file_schemas: bool = dataclasses.field(default=False)
+
+    def __post_init__(self):
+        self.application_connector_type = enums.ApplicationConnectorType.SFTPAPPLICATION
+
+
 @dataclasses.dataclass
 class _ApplicationConnectorDatasetConfigFactory(_ApiClassFactory):
     config_abstract_class = ApplicationConnectorDatasetConfig
@@ -238,4 +258,5 @@ class _ApplicationConnectorDatasetConfigFactory(_ApiClassFactory):
         enums.ApplicationConnectorType.FRESHSERVICE: FreshserviceDatasetConfig,
         enums.ApplicationConnectorType.TEAMSSCRAPER: TeamsScraperDatasetConfig,
         enums.ApplicationConnectorType.BOX: BoxDatasetConfig,
+        enums.ApplicationConnectorType.SFTPAPPLICATION: SftpDatasetConfig,
     }

abacusai/api_class/enums.py

@@ -414,6 +414,7 @@ class ApplicationConnectorType(ApiEnum):
     GITHUBUSER = 'GITHUBUSER'
     OKTASAML = 'OKTASAML'
     BOX = 'BOX'
+    SFTPAPPLICATION = 'SFTPAPPLICATION'
 
 
 class StreamingConnectorType(ApiEnum):
@@ -482,6 +483,7 @@ class LLMName(ApiEnum):
     CLAUDE_V3_SONNET = 'CLAUDE_V3_SONNET'
     CLAUDE_V3_HAIKU = 'CLAUDE_V3_HAIKU'
     CLAUDE_V3_5_SONNET = 'CLAUDE_V3_5_SONNET'
+    CLAUDE_V3_7_SONNET = 'CLAUDE_V3_7_SONNET'
     CLAUDE_V3_5_HAIKU = 'CLAUDE_V3_5_HAIKU'
     GEMINI_1_5_PRO = 'GEMINI_1_5_PRO'
     GEMINI_2_FLASH = 'GEMINI_2_FLASH'
@@ -726,3 +728,4 @@ class DeploymentConversationType(ApiEnum):
     CHAT_LLM_TASK = 'CHAT_LLM_TASK'
     COMPUTER_AGENT = 'COMPUTER_AGENT'
     SEARCH_LLM = 'SEARCH_LLM'
+    APP_LLM = 'APP_LLM'

abacusai/api_client_utils.py

@@ -613,7 +613,7 @@ def tokens_to_text(tokens: List[dict]) -> str:
         def combine_doc_info(group):
             page_infos = group.to_dict(orient='records')
             document_data = {
-                cls.METADATA: [{cls.HEIGHT: page.get(cls.HEIGHT, None), cls.WIDTH: page.get(cls.WIDTH, None), cls.PAGE: page_no + 1, cls.MARKDOWN_FEATURES: page.get(cls.MARKDOWN_FEATURES)}
+                cls.METADATA: [{cls.HEIGHT: page.get(cls.HEIGHT, None), cls.WIDTH: page.get(cls.WIDTH, None), cls.PAGE: page_no, cls.MARKDOWN_FEATURES: page.get(cls.MARKDOWN_FEATURES)}
                                for page_no, page in enumerate(page_infos)],
                 cls.TOKENS: [token for page in page_infos for token in page.get(cls.TOKENS) or []],
                 # default to embedded text

abacusai/chatllm_task.py

@@ -16,11 +16,11 @@ class ChatllmTask(AbstractApiClass):
             deploymentConversationId (str): The deployment conversation id associated with the chatllm task.
             enableEmailAlerts (bool): Whether email alerts are enabled for the chatllm task.
             email (str): The email to send alerts to.
+            numUnreadTaskInstances (int): The number of unread task instances for the chatllm task.
             computePointsUsed (int): The compute points used for the chatllm task.
-            wasSeen (bool): Whether the chatllm task has been seen.
     """
 
-    def __init__(self, client, chatllmTaskId=None, name=None, instructions=None, lifecycle=None, scheduleInfo=None, externalApplicationId=None, deploymentConversationId=None, enableEmailAlerts=None, email=None, computePointsUsed=None, wasSeen=None):
+    def __init__(self, client, chatllmTaskId=None, name=None, instructions=None, lifecycle=None, scheduleInfo=None, externalApplicationId=None, deploymentConversationId=None, enableEmailAlerts=None, email=None, numUnreadTaskInstances=None, computePointsUsed=None):
         super().__init__(client, chatllmTaskId)
         self.chatllm_task_id = chatllmTaskId
         self.name = name
@@ -31,13 +31,13 @@ def __init__(self, client, chatllmTaskId=None, name=None, instructions=None, lif
         self.deployment_conversation_id = deploymentConversationId
         self.enable_email_alerts = enableEmailAlerts
         self.email = email
+        self.num_unread_task_instances = numUnreadTaskInstances
         self.compute_points_used = computePointsUsed
-        self.was_seen = wasSeen
         self.deprecated_keys = {}
 
     def __repr__(self):
-        repr_dict = {f'chatllm_task_id': repr(self.chatllm_task_id), f'name': repr(self.name), f'instructions': repr(self.instructions), f'lifecycle': repr(self.lifecycle), f'schedule_info': repr(self.schedule_info), f'external_application_id': repr(
-            self.external_application_id), f'deployment_conversation_id': repr(self.deployment_conversation_id), f'enable_email_alerts': repr(self.enable_email_alerts), f'email': repr(self.email), f'compute_points_used': repr(self.compute_points_used), f'was_seen': repr(self.was_seen)}
+        repr_dict = {f'chatllm_task_id': repr(self.chatllm_task_id), f'name': repr(self.name), f'instructions': repr(self.instructions), f'lifecycle': repr(self.lifecycle), f'schedule_info': repr(self.schedule_info), f'external_application_id': repr(self.external_application_id), f'deployment_conversation_id': repr(
+            self.deployment_conversation_id), f'enable_email_alerts': repr(self.enable_email_alerts), f'email': repr(self.email), f'num_unread_task_instances': repr(self.num_unread_task_instances), f'compute_points_used': repr(self.compute_points_used)}
         class_name = "ChatllmTask"
         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])
@@ -51,5 +51,5 @@ def to_dict(self):
             dict: The dict value representation of the class parameters
         """
         resp = {'chatllm_task_id': self.chatllm_task_id, 'name': self.name, 'instructions': self.instructions, 'lifecycle': self.lifecycle, 'schedule_info': self.schedule_info, 'external_application_id': self.external_application_id,
-                'deployment_conversation_id': self.deployment_conversation_id, 'enable_email_alerts': self.enable_email_alerts, 'email': self.email, 'compute_points_used': self.compute_points_used, 'was_seen': self.was_seen}
+                'deployment_conversation_id': self.deployment_conversation_id, 'enable_email_alerts': self.enable_email_alerts, 'email': self.email, 'num_unread_task_instances': self.num_unread_task_instances, 'compute_points_used': self.compute_points_used}
         return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

abacusai/client.py

@@ -652,7 +652,7 @@ 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 = '1.4.32'
+    client_version = '1.4.33'
 
     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
@@ -3983,7 +3983,7 @@ def execute_chatllm_computer_streaming(self, computer_id: str, prompt: str, is_t
             text (str): The text responses from the computer.
         """
         request_id = self._get_agent_app_request_id()
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         proxy_caller = self._is_proxy_app_caller()
 
         if not request_id or not caller:
@@ -4049,7 +4049,7 @@ def streaming_evaluate_prompt(self, prompt: str = None, system_message: str = No
         Returns:
             text (str): The response from the model.
         """
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         request_id = self._get_agent_app_request_id()
         if prompt and not isinstance(prompt, str):
             raise ValueError('prompt must be a string')
@@ -4113,9 +4113,9 @@ def _get_agent_app_request_id(self):
         """
         return get_object_from_context(self, _request_context, 'request_id', str)
 
-    def _get_agent_async_app_caller(self):
+    def _get_agent_caller(self):
         """
-        Gets the caller for the current request context of async app. Applicable within a AIAgent execute function.
+        Gets the caller for the current request context. Applicable within a AIAgent execute function.
 
         Returns:
             str: The caller for the current request being processed by the Agent.
@@ -4124,13 +4124,22 @@ def _get_agent_async_app_caller(self):
 
     def _is_proxy_app_caller(self):
         """
-        Gets the caller for the current request context of async app. Applicable within a AIAgent execute function.
+        Checks if the caller is cluster-proxy app.
 
         Returns:
-            bool: True if the caller is proxy app.
+            bool: True if the caller is cluster-proxy app.
         """
         return get_object_from_context(self, _request_context, 'proxy_app_caller', str) is not None
 
+    def _is_async_app_caller(self):
+        """
+        Checks if the caller is async app.
+
+        Returns:
+            bool: True if the caller is async app.
+        """
+        return get_object_from_context(self, _request_context, 'async_app_caller', str) is not None
+
     def stream_message(self, message: str, is_transient: bool = False) -> None:
         """
         Streams a message to the current request context. Applicable within a AIAgent execute function.
@@ -4141,7 +4150,7 @@ def stream_message(self, message: str, is_transient: bool = False) -> None:
             is_transient (bool): If True, the message will be marked as transient and will not be persisted on reload in external chatllm UI. Transient messages are useful for streaming interim updates or results.
         """
         request_id = self._get_agent_app_request_id()
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         proxy_caller = self._is_proxy_app_caller()
         if request_id and caller:
             extra_args = {'stream_type': StreamType.MESSAGE.value,
@@ -4163,7 +4172,7 @@ def stream_section_output(self, section_key: str, value: str) -> None:
             value (Any): The output contents.
         """
         request_id = self._get_agent_app_request_id()
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         proxy_caller = self._is_proxy_app_caller()
         if _is_json_serializable(value):
             message_args = {'id': section_key,
@@ -4189,7 +4198,7 @@ def stream_response_section(self, response_section: ResponseSection):
             response_section (ResponseSection): The response section to be streamed.
         """
         request_id = self._get_agent_app_request_id()
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         proxy_caller = self._is_proxy_app_caller()
         if request_id and caller:
             segment = response_section.to_dict()
@@ -4203,7 +4212,7 @@ def stream_response_section(self, response_section: ResponseSection):
 
     def _stream_llm_call(self, section_key=None, **kwargs):
         request_id = self._get_agent_app_request_id()
-        caller = self._get_agent_async_app_caller()
+        caller = self._get_agent_caller()
         proxy_caller = self._is_proxy_app_caller()
         if not request_id or not caller:
             logging.info('Please use evaluate_prompt for local testing.')
@@ -8010,7 +8019,7 @@ def get_feature_group_row_process_logs_by_key(self, deployment_id: str, primary_
             FeatureGroupRowProcessLogs: An object representing the logs for the feature group row process"""
         return self._call_api('getFeatureGroupRowProcessLogsByKey', 'POST', query_params={'deploymentId': deployment_id}, body={'primaryKeyValue': primary_key_value}, parse_type=FeatureGroupRowProcessLogs)
 
-    def create_python_function(self, name: str, source_code: str = None, function_name: str = None, function_variable_mappings: List = None, package_requirements: list = None, function_type: str = 'FEATURE_GROUP', description: str = None, examples: dict = None) -> PythonFunction:
+    def create_python_function(self, name: str, source_code: str = None, function_name: str = None, function_variable_mappings: List = None, package_requirements: list = None, function_type: str = 'FEATURE_GROUP', description: str = None, examples: dict = None, user_level_connectors: Dict = None, org_level_connectors: list = None, output_variable_mappings: List = None) -> PythonFunction:
         """Creates a custom Python function that is reusable.
 
         Args:
@@ -8021,13 +8030,16 @@ def create_python_function(self, name: str, source_code: str = None, function_na
             package_requirements (list): List of package requirement strings. For example: ['numpy==1.2.3', 'pandas>=1.4.0'].
             function_type (str): Type of Python function to create. Default is FEATURE_GROUP, but can also be PLOTLY_FIG.
             description (str): Description of the Python function. This should include details about the function's purpose, expected inputs and outputs, and any important usage considerations or limitations.
-            examples (dict): Dictionary containing example use cases and anti-patterns. Should include 'positive_examples' showing recommended usage and 'negative_examples' showing cases to avoid.
+            examples (dict): Dictionary containing example use cases and anti-patterns. Should include 'positive_examples' showing recommended usage and 'negative_examples' showing cases to avoid.])
+            user_level_connectors (Dict): Dictionary containing user level connectors.
+            org_level_connectors (list): List containing organization level connectors.
+            output_variable_mappings (List): List of output variable mappings that defines the elements of the function's return value.
 
         Returns:
             PythonFunction: The Python function that can be used (e.g. for feature group transform)."""
-        return self._call_api('createPythonFunction', 'POST', query_params={}, body={'name': name, 'sourceCode': source_code, 'functionName': function_name, 'functionVariableMappings': function_variable_mappings, 'packageRequirements': package_requirements, 'functionType': function_type, 'description': description, 'examples': examples}, parse_type=PythonFunction)
+        return self._call_api('createPythonFunction', 'POST', query_params={}, body={'name': name, 'sourceCode': source_code, 'functionName': function_name, 'functionVariableMappings': function_variable_mappings, 'packageRequirements': package_requirements, 'functionType': function_type, 'description': description, 'examples': examples, 'userLevelConnectors': user_level_connectors, 'orgLevelConnectors': org_level_connectors, 'outputVariableMappings': output_variable_mappings}, parse_type=PythonFunction)
 
-    def update_python_function(self, name: str, source_code: str = None, function_name: str = None, function_variable_mappings: List = None, package_requirements: list = None, description: str = None, examples: dict = None) -> PythonFunction:
+    def update_python_function(self, name: str, source_code: str = None, function_name: str = None, function_variable_mappings: List = None, package_requirements: list = None, description: str = None, examples: dict = None, user_level_connectors: Dict = None, org_level_connectors: List = None, output_variable_mappings: List = None) -> PythonFunction:
         """Update custom python function with user inputs for the given python function.
 
         Args:
@@ -8038,10 +8050,13 @@ def update_python_function(self, name: str, source_code: str = None, function_na
             package_requirements (list): List of package requirement strings. For example: ['numpy==1.2.3', 'pandas>=1.4.0'].
             description (str): Description of the Python function. This should include details about the function's purpose, expected inputs and outputs, and any important usage considerations or limitations.
             examples (dict): Dictionary containing example use cases and anti-patterns. Should include 'positive_examples' showing recommended usage and 'negative_examples' showing cases to avoid.
+            user_level_connectors (Dict): Dictionary containing user level connectors.
+            org_level_connectors (List): List of organization level connectors.
+            output_variable_mappings (List): List of output variable mappings that defines the elements of the function's return value.
 
         Returns:
             PythonFunction: The Python function object."""
-        return self._call_api('updatePythonFunction', 'PATCH', query_params={}, body={'name': name, 'sourceCode': source_code, 'functionName': function_name, 'functionVariableMappings': function_variable_mappings, 'packageRequirements': package_requirements, 'description': description, 'examples': examples}, parse_type=PythonFunction)
+        return self._call_api('updatePythonFunction', 'PATCH', query_params={}, body={'name': name, 'sourceCode': source_code, 'functionName': function_name, 'functionVariableMappings': function_variable_mappings, 'packageRequirements': package_requirements, 'description': description, 'examples': examples, 'userLevelConnectors': user_level_connectors, 'orgLevelConnectors': org_level_connectors, 'outputVariableMappings': output_variable_mappings}, parse_type=PythonFunction)
 
     def delete_python_function(self, name: str):
         """Removes an existing Python function.