Version 1.4.69

Author: gyanendra8

abacusai/__init__.py

@@ -224,6 +224,7 @@
 from .prediction_operator import PredictionOperator
 from .prediction_operator_version import PredictionOperatorVersion
 from .presentation_export_result import PresentationExportResult
+from .private_web_app_deployment import PrivateWebAppDeployment
 from .problem_type import ProblemType
 from .project import Project
 from .project_config import ProjectConfig
@@ -276,6 +277,7 @@
 from .video_search_result import VideoSearchResult
 from .voice_gen_details import VoiceGenDetails
 from .web_app_conversation import WebAppConversation
+from .web_app_deployment_permission_dict import WebAppDeploymentPermissionDict
 from .web_app_domain import WebAppDomain
 from .web_page_response import WebPageResponse
 from .web_search_response import WebSearchResponse
@@ -285,4 +287,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.68"
+__version__ = "1.4.69"

abacusai/api_class/model.py

@@ -503,6 +503,7 @@ class ChatLLMTrainingConfig(TrainingConfig):
         json_response_schema (str): Specifies the JSON schema that the model should adhere to if `response_format` is set to "JSON". This should be a json-formatted string where each field of the expected schema is mapped to a dictionary containing the fields 'type', 'required' and 'description'. For example - '{"sample_field": {"type": "integer", "required": true, "description": "Sample Field"}}'
         mask_pii (bool): Mask PII in the prompts and uploaded documents before sending it to the LLM. Only available for Enterprise users and will cause validation errors if set to True for ChatLLM Teams users.
         builtin_tools (List[SystemConnectorTool]): List of builtin system connector tools to use in the ChatLLM. Using builtin tools does not require enabling tool bar (enable_tool_bar flag).
+        config_connectors (List[str]): List of names of config connectors to use in the ChatLLM. This should not be used with document_retrievers.
         mcp_servers (List[str]): List of names of MCP servers to use in the ChatLLM. This should not be used with document_retrievers.
         agentic_loop_mode (bool): Enables use of agentic loop that uses a series of tool calls when needed to respond. If set to False, the agentic loop will not be used. If not set or set to Auto, the agentic loop will be automatically used based on certain conditions like presence of tools in the model.
     """
@@ -545,6 +546,7 @@ class ChatLLMTrainingConfig(TrainingConfig):
     json_response_schema: str = dataclasses.field(default=None)
     mask_pii: bool = dataclasses.field(default=None)
     builtin_tools: List[SystemConnectorTool] = dataclasses.field(default=None)
+    config_connectors: List[str] = dataclasses.field(default=None)
     mcp_servers: List[str] = dataclasses.field(default=None)
     agentic_loop_mode: bool = dataclasses.field(default=None)
 

abacusai/batch_prediction.py

@@ -84,7 +84,7 @@ def __init__(self, client, batchPredictionId=None, createdAt=None, name=None, de
             BatchPredictionArgs, globalPredictionArgs)
         self.batch_prediction_args = client._build_class(getattr(
             api_class, batchPredictionArgsType, BatchPredictionArgs) if batchPredictionArgsType else BatchPredictionArgs, batchPredictionArgs)
-        self.deprecated_keys = {'explanations', 'global_prediction_args'}
+        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'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(

abacusai/batch_prediction_version.py

@@ -100,7 +100,7 @@ def __init__(self, client, batchPredictionVersion=None, batchPredictionId=None,
             BatchPredictionArgs, globalPredictionArgs)
         self.batch_prediction_args = client._build_class(getattr(
             api_class, batchPredictionArgsType, BatchPredictionArgs) if batchPredictionArgsType else BatchPredictionArgs, batchPredictionArgs)
-        self.deprecated_keys = {'explanations', 'global_prediction_args'}
+        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'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(

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 = '1.4.68'
+    client_version = '1.4.69'
 
     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
@@ -857,7 +857,7 @@ def _call_api(
                 error_message, response.status_code, error_type, request_id)
         return result
 
-    def _proxy_request(self, name: str, method: str = 'POST', query_params: dict = None, body: dict = None, data: dict = None, files=None, parse_type=None, is_sync: bool = False, streamable_response: bool = False):
+    def _proxy_request(self, name: str, method: str = 'POST', query_params: dict = None, body: dict = None, data: dict = None, files=None, parse_type=None, is_sync: bool = False, streamable_response: bool = False, timeout=None):
         headers = {'APIKEY': self.api_key}
         deployment_id = os.getenv('ABACUS_EXEC_SERVICE_DEPLOYMENT_ID')
         if deployment_id:
@@ -908,7 +908,7 @@ def _proxy_request(self, name: str, method: str = 'POST', query_params: dict = N
             if is_sync:
                 sync_api_endpoint = f'{endpoint}/api/{name}'
                 response = self._request(url=sync_api_endpoint, method=method, query_params=query_params,
-                                         headers=headers, body=body, data=data, files=files, stream=streamable_response)
+                                         headers=headers, body=body, data=data, files=files, stream=streamable_response, timeout=timeout)
                 status_code = response.status_code
                 if streamable_response and status_code == 200:
                     return response.raw
@@ -7719,7 +7719,7 @@ def get_deep_agent_response(self, message: str, deployment_conversation_id: str
         Args:
             message (str): The user's message/task for DeepAgent to complete
             deployment_conversation_id (str): The unique identifier of a deployment conversation to continue. If not specified, a new one will be created."""
-        return self._proxy_request('getDeepAgentResponse', 'POST', query_params={}, body={'message': message, 'deploymentConversationId': deployment_conversation_id}, is_sync=True)
+        return self._proxy_request('getDeepAgentResponse', 'POST', query_params={}, body={'message': message, 'deploymentConversationId': deployment_conversation_id}, is_sync=True, timeout=3600)
 
     def get_search_results(self, deployment_token: str, deployment_id: str, query_data: dict, num: int = 15) -> Dict:
         """Return the most relevant search results to the search query from the uploaded documents.

abacusai/hosted_app_container.py

@@ -12,6 +12,8 @@ class HostedAppContainer(AbstractApiClass):
             deploymentConversationId (id): The deployment conversation ID
             hostedAppVersion (id): The instance of the hosted app
             name (str): The name of the hosted app
+            userId (id): The ID of the creation user
+            email (str): The email of the creation user
             createdAt (str): Creation timestamp
             updatedAt (str): Last update timestamp
             containerImage (str): Container image name
@@ -34,13 +36,15 @@ class HostedAppContainer(AbstractApiClass):
             parentConversationId (id): The ID of the parent conversation
     """
 
-    def __init__(self, client, hostedAppContainerId=None, hostedAppId=None, deploymentConversationId=None, hostedAppVersion=None, name=None, createdAt=None, updatedAt=None, containerImage=None, route=None, appConfig=None, isDev=None, isDeployable=None, isPreviewAvailable=None, lifecycle=None, status=None, deployedStatus=None, accessLevel=None, hostname=None, llmArtifactId=None, artifactType=None, deployedLlmArtifactId=None, hasDatabase=None, hasStorage=None, webAppProjectId=None, parentConversationId=None):
+    def __init__(self, client, hostedAppContainerId=None, hostedAppId=None, deploymentConversationId=None, hostedAppVersion=None, name=None, userId=None, email=None, createdAt=None, updatedAt=None, containerImage=None, route=None, appConfig=None, isDev=None, isDeployable=None, isPreviewAvailable=None, lifecycle=None, status=None, deployedStatus=None, accessLevel=None, hostname=None, llmArtifactId=None, artifactType=None, deployedLlmArtifactId=None, hasDatabase=None, hasStorage=None, webAppProjectId=None, parentConversationId=None):
         super().__init__(client, hostedAppContainerId)
         self.hosted_app_container_id = hostedAppContainerId
         self.hosted_app_id = hostedAppId
         self.deployment_conversation_id = deploymentConversationId
         self.hosted_app_version = hostedAppVersion
         self.name = name
+        self.user_id = userId
+        self.email = email
         self.created_at = createdAt
         self.updated_at = updatedAt
         self.container_image = containerImage
@@ -64,7 +68,7 @@ def __init__(self, client, hostedAppContainerId=None, hostedAppId=None, deployme
         self.deprecated_keys = {}
 
     def __repr__(self):
-        repr_dict = {f'hosted_app_container_id': repr(self.hosted_app_container_id), f'hosted_app_id': repr(self.hosted_app_id), f'deployment_conversation_id': repr(self.deployment_conversation_id), f'hosted_app_version': repr(self.hosted_app_version), f'name': repr(self.name), f'created_at': repr(self.created_at), f'updated_at': repr(self.updated_at), f'container_image': repr(self.container_image), f'route': repr(self.route), f'app_config': repr(self.app_config), f'is_dev': repr(self.is_dev), f'is_deployable': repr(self.is_deployable), f'is_preview_available': repr(
+        repr_dict = {f'hosted_app_container_id': repr(self.hosted_app_container_id), f'hosted_app_id': repr(self.hosted_app_id), f'deployment_conversation_id': repr(self.deployment_conversation_id), f'hosted_app_version': repr(self.hosted_app_version), f'name': repr(self.name), f'user_id': repr(self.user_id), f'email': repr(self.email), f'created_at': repr(self.created_at), f'updated_at': repr(self.updated_at), f'container_image': repr(self.container_image), f'route': repr(self.route), f'app_config': repr(self.app_config), f'is_dev': repr(self.is_dev), f'is_deployable': repr(self.is_deployable), f'is_preview_available': repr(
             self.is_preview_available), f'lifecycle': repr(self.lifecycle), f'status': repr(self.status), f'deployed_status': repr(self.deployed_status), f'access_level': repr(self.access_level), f'hostname': repr(self.hostname), f'llm_artifact_id': repr(self.llm_artifact_id), f'artifact_type': repr(self.artifact_type), f'deployed_llm_artifact_id': repr(self.deployed_llm_artifact_id), f'has_database': repr(self.has_database), f'has_storage': repr(self.has_storage), f'web_app_project_id': repr(self.web_app_project_id), f'parent_conversation_id': repr(self.parent_conversation_id)}
         class_name = "HostedAppContainer"
         repr_str = ',\n  '.join([f'{key}={value}' for key, value in repr_dict.items(
@@ -78,6 +82,6 @@ def to_dict(self):
         Returns:
             dict: The dict value representation of the class parameters
         """
-        resp = {'hosted_app_container_id': self.hosted_app_container_id, 'hosted_app_id': self.hosted_app_id, 'deployment_conversation_id': self.deployment_conversation_id, 'hosted_app_version': self.hosted_app_version, 'name': self.name, 'created_at': self.created_at, 'updated_at': self.updated_at, 'container_image': self.container_image, 'route': self.route, 'app_config': self.app_config, 'is_dev': self.is_dev, 'is_deployable': self.is_deployable, 'is_preview_available': self.is_preview_available,
-                'lifecycle': self.lifecycle, 'status': self.status, 'deployed_status': self.deployed_status, 'access_level': self.access_level, 'hostname': self.hostname, 'llm_artifact_id': self.llm_artifact_id, 'artifact_type': self.artifact_type, 'deployed_llm_artifact_id': self.deployed_llm_artifact_id, 'has_database': self.has_database, 'has_storage': self.has_storage, 'web_app_project_id': self.web_app_project_id, 'parent_conversation_id': self.parent_conversation_id}
+        resp = {'hosted_app_container_id': self.hosted_app_container_id, 'hosted_app_id': self.hosted_app_id, 'deployment_conversation_id': self.deployment_conversation_id, 'hosted_app_version': self.hosted_app_version, 'name': self.name, 'user_id': self.user_id, 'email': self.email, 'created_at': self.created_at, 'updated_at': self.updated_at, 'container_image': self.container_image, 'route': self.route, 'app_config': self.app_config, 'is_dev': self.is_dev, 'is_deployable': self.is_deployable,
+                'is_preview_available': self.is_preview_available, 'lifecycle': self.lifecycle, 'status': self.status, 'deployed_status': self.deployed_status, 'access_level': self.access_level, 'hostname': self.hostname, 'llm_artifact_id': self.llm_artifact_id, 'artifact_type': self.artifact_type, 'deployed_llm_artifact_id': self.deployed_llm_artifact_id, 'has_database': self.has_database, 'has_storage': self.has_storage, 'web_app_project_id': self.web_app_project_id, 'parent_conversation_id': self.parent_conversation_id}
         return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

abacusai/prediction_client.py

@@ -431,7 +431,7 @@ def get_deep_agent_response(self, message: str, deployment_conversation_id: str
         Args:
             message (str): The user's message/task for DeepAgent to complete
             deployment_conversation_id (str): The unique identifier of a deployment conversation to continue. If not specified, a new one will be created."""
-        return self._proxy_request('getDeepAgentResponse', 'POST', query_params={}, body={'message': message, 'deploymentConversationId': deployment_conversation_id}, is_sync=True)
+        return self._proxy_request('getDeepAgentResponse', 'POST', query_params={}, body={'message': message, 'deploymentConversationId': deployment_conversation_id}, is_sync=True, timeout=3600)
 
     def get_search_results(self, deployment_token: str, deployment_id: str, query_data: dict, num: int = 15) -> Dict:
         """Return the most relevant search results to the search query from the uploaded documents.

abacusai/private_web_app_deployment.py

@@ -0,0 +1,57 @@
+from .return_class import AbstractApiClass
+
+
+class PrivateWebAppDeployment(AbstractApiClass):
+    """
+        Private web app deployment list.
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            hostname (str): The hostname of the web app deployment.
+            llmArtifactId (id): The ID of the LLM artifact.
+            hostedAppVersion (id): The version of the hosted app.
+            applicationType (str): The type of application.
+            lifecycle (str): The lifecycle of the web app deployment.
+            deploymentConversationId (id): The ID of the deployment conversation.
+            conversationName (str): The name of the conversation.
+            userId (id): The ID of the user who created the deployment.
+            email (str): The email of the user who created the deployment.
+            conversationType (str): The type of conversation.
+            source (str): The source of the conversation.
+            conversationCreatedAt (str): The timestamp when the conversation was created.
+    """
+
+    def __init__(self, client, hostname=None, llmArtifactId=None, hostedAppVersion=None, applicationType=None, lifecycle=None, deploymentConversationId=None, conversationName=None, userId=None, email=None, conversationType=None, source=None, conversationCreatedAt=None):
+        super().__init__(client, None)
+        self.hostname = hostname
+        self.llm_artifact_id = llmArtifactId
+        self.hosted_app_version = hostedAppVersion
+        self.application_type = applicationType
+        self.lifecycle = lifecycle
+        self.deployment_conversation_id = deploymentConversationId
+        self.conversation_name = conversationName
+        self.user_id = userId
+        self.email = email
+        self.conversation_type = conversationType
+        self.source = source
+        self.conversation_created_at = conversationCreatedAt
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'hostname': repr(self.hostname), f'llm_artifact_id': repr(self.llm_artifact_id), f'hosted_app_version': repr(self.hosted_app_version), f'application_type': repr(self.application_type), f'lifecycle': repr(self.lifecycle), f'deployment_conversation_id': repr(
+            self.deployment_conversation_id), f'conversation_name': repr(self.conversation_name), f'user_id': repr(self.user_id), f'email': repr(self.email), f'conversation_type': repr(self.conversation_type), f'source': repr(self.source), f'conversation_created_at': repr(self.conversation_created_at)}
+        class_name = "PrivateWebAppDeployment"
+        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])
+        return f"{class_name}({repr_str})"
+
+    def to_dict(self):
+        """
+        Get a dict representation of the parameters in this class
+
+        Returns:
+            dict: The dict value representation of the class parameters
+        """
+        resp = {'hostname': self.hostname, 'llm_artifact_id': self.llm_artifact_id, 'hosted_app_version': self.hosted_app_version, 'application_type': self.application_type, 'lifecycle': self.lifecycle, 'deployment_conversation_id': self.deployment_conversation_id,
+                'conversation_name': self.conversation_name, 'user_id': self.user_id, 'email': self.email, 'conversation_type': self.conversation_type, 'source': self.source, 'conversation_created_at': self.conversation_created_at}
+        return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}