Version 1.4.56

Author: gyanendra8

abacusai/__init__.py

@@ -140,6 +140,7 @@
 from .hosted_database import HostedDatabase
 from .hosted_database_snapshot import HostedDatabaseSnapshot
 from .hosted_model_token import HostedModelToken
+from .hostname_info import HostnameInfo
 from .hume_voice import HumeVoice
 from .image_gen_model import ImageGenModel
 from .image_gen_model_options import ImageGenModelOptions
@@ -151,6 +152,7 @@
 from .lip_sync_gen_settings import LipSyncGenSettings
 from .llm_app import LlmApp
 from .llm_artifact import LlmArtifact
+from .llm_artifact_conversation import LlmArtifactConversation
 from .llm_code_block import LlmCodeBlock
 from .llm_execution_preview import LlmExecutionPreview
 from .llm_execution_result import LlmExecutionResult
@@ -160,6 +162,8 @@
 from .llm_response import LlmResponse
 from .mcp_config import McpConfig
 from .mcp_server import McpServer
+from .mcp_server_connection import McpServerConnection
+from .mcp_server_query_result import McpServerQueryResult
 from .memory_options import MemoryOptions
 from .messaging_connector_response import MessagingConnectorResponse
 from .model import Model
@@ -273,4 +277,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.55"
+__version__ = "1.4.56"

abacusai/api_class/dataset.py

@@ -64,7 +64,7 @@ def __post_init__(self):
         if self.document_type is not None:
             if DocumentType.is_ocr_forced(self.document_type):
                 self.highlight_relevant_text = True
-            else:
+            elif self.highlight_relevant_text is None:
                 self.highlight_relevant_text = False
         if self.highlight_relevant_text is not None:
             self.extract_bounding_boxes = self.highlight_relevant_text  # Highlight_relevant text acts as a wrapper over extract_bounding_boxes

abacusai/api_class/enums.py

@@ -418,6 +418,7 @@ class ApplicationConnectorType(ApiEnum):
     OAUTH = 'OAUTH'
     SALESFORCE = 'SALESFORCE'
     TWITTER = 'TWITTER'
+    MCP = 'MCP'
 
     @classmethod
     def user_connectors(cls):
@@ -430,7 +431,8 @@ def user_connectors(cls):
             cls.ONEDRIVE,
             cls.SALESFORCE,
             cls.TWITTER,
-            cls.SHAREPOINT
+            cls.SHAREPOINT,
+            cls.CONFLUENCE
         ]
 
     @classmethod

abacusai/api_class/model.py

@@ -501,7 +501,7 @@ 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.
         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).
-        mcp_server_configs (str): JSON string of MCP servers configs to use in the ChatLLM model. 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.
     """
     document_retrievers: List[str] = dataclasses.field(default=None)
     num_completion_tokens: int = dataclasses.field(default=None)
@@ -540,7 +540,7 @@ 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)
-    mcp_server_configs: str = dataclasses.field(default=None)
+    mcp_servers: List[str] = dataclasses.field(default=None)
 
     def __post_init__(self):
         self.problem_type = enums.ProblemType.CHAT_LLM

abacusai/client.py

@@ -126,6 +126,7 @@
 from .llm_generated_code import LlmGeneratedCode
 from .llm_input import LlmInput
 from .llm_response import LlmResponse
+from .mcp_server_query_result import McpServerQueryResult
 from .model import Model
 from .model_artifacts_export import ModelArtifactsExport
 from .model_metrics import ModelMetrics
@@ -662,7 +663,7 @@ 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 = '1.4.55'
+    client_version = '1.4.56'
 
     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
@@ -1611,6 +1612,16 @@ def get_user_connector_auth(self, service: Union[ApplicationConnectorType, str],
             UnifiedConnector: The application connector with the authentication details."""
         return self._call_api('getUserConnectorAuth', 'GET', query_params={'service': service, 'scopes': scopes}, parse_type=UnifiedConnector)
 
+    def get_user_mcp_connector_auth(self, mcp_server_name: str = None) -> ApplicationConnector:
+        """Get the auth for a MCP connector
+
+        Args:
+            mcp_server_name (str): The name of the MCP server
+
+        Returns:
+            ApplicationConnector: The MCP connector"""
+        return self._call_api('getUserMcpConnectorAuth', 'GET', query_params={'mcpServerName': mcp_server_name}, parse_type=ApplicationConnector)
+
     def list_streaming_connectors(self) -> List[StreamingConnector]:
         """Retrieves a list of all streaming connectors along with their corresponding attributes.
 
@@ -8970,7 +8981,7 @@ def delete_external_application(self, external_application_id: str):
             external_application_id (str): The ID of the External Application."""
         return self._call_api('deleteExternalApplication', 'DELETE', query_params={'externalApplicationId': external_application_id})
 
-    def create_agent(self, project_id: str, function_source_code: str = None, agent_function_name: str = None, name: str = None, memory: int = None, package_requirements: list = [], description: str = None, enable_binary_input: bool = False, evaluation_feature_group_id: str = None, agent_input_schema: dict = None, agent_output_schema: dict = None, workflow_graph: Union[dict, WorkflowGraph] = None, agent_interface: Union[AgentInterface, str] = AgentInterface.DEFAULT, included_modules: List = None, org_level_connectors: List = None, user_level_connectors: Dict = None, initialize_function_name: str = None, initialize_function_code: str = None, agent_mcp_config: dict = None) -> Agent:
+    def create_agent(self, project_id: str, function_source_code: str = None, agent_function_name: str = None, name: str = None, memory: int = None, package_requirements: list = [], description: str = None, enable_binary_input: bool = False, evaluation_feature_group_id: str = None, agent_input_schema: dict = None, agent_output_schema: dict = None, workflow_graph: Union[dict, WorkflowGraph] = None, agent_interface: Union[AgentInterface, str] = AgentInterface.DEFAULT, included_modules: List = None, org_level_connectors: List = None, user_level_connectors: Dict = None, initialize_function_name: str = None, initialize_function_code: str = None) -> Agent:
         """Creates a new AI agent using the given agent workflow graph definition.
 
         Args:
@@ -8987,13 +8998,12 @@ def create_agent(self, project_id: str, function_source_code: str = None, agent_
             user_level_connectors (Dict): A dictionary mapping ApplicationConnectorType keys to lists of OAuth scopes. Each key represents a specific user level application connector, while the value is a list of scopes that define the permissions granted to the application.
             initialize_function_name (str): The name of the function to be used for initialization.
             initialize_function_code (str): The function code to be used for initialization.
-            agent_mcp_config (dict): The MCP config for the agent.
 
         Returns:
             Agent: The new agent."""
-        return self._call_api('createAgent', 'POST', query_params={}, body={'projectId': project_id, 'functionSourceCode': function_source_code, 'agentFunctionName': agent_function_name, 'name': name, 'memory': memory, 'packageRequirements': package_requirements, 'description': description, 'enableBinaryInput': enable_binary_input, 'evaluationFeatureGroupId': evaluation_feature_group_id, 'agentInputSchema': agent_input_schema, 'agentOutputSchema': agent_output_schema, 'workflowGraph': workflow_graph, 'agentInterface': agent_interface, 'includedModules': included_modules, 'orgLevelConnectors': org_level_connectors, 'userLevelConnectors': user_level_connectors, 'initializeFunctionName': initialize_function_name, 'initializeFunctionCode': initialize_function_code, 'agentMcpConfig': agent_mcp_config}, parse_type=Agent)
+        return self._call_api('createAgent', 'POST', query_params={}, body={'projectId': project_id, 'functionSourceCode': function_source_code, 'agentFunctionName': agent_function_name, 'name': name, 'memory': memory, 'packageRequirements': package_requirements, 'description': description, 'enableBinaryInput': enable_binary_input, 'evaluationFeatureGroupId': evaluation_feature_group_id, 'agentInputSchema': agent_input_schema, 'agentOutputSchema': agent_output_schema, 'workflowGraph': workflow_graph, 'agentInterface': agent_interface, 'includedModules': included_modules, 'orgLevelConnectors': org_level_connectors, 'userLevelConnectors': user_level_connectors, 'initializeFunctionName': initialize_function_name, 'initializeFunctionCode': initialize_function_code}, parse_type=Agent)
 
-    def update_agent(self, model_id: str, function_source_code: str = None, agent_function_name: str = None, memory: int = None, package_requirements: list = None, description: str = None, enable_binary_input: bool = None, agent_input_schema: dict = None, agent_output_schema: dict = None, workflow_graph: Union[dict, WorkflowGraph] = None, agent_interface: Union[AgentInterface, str] = None, included_modules: List = None, org_level_connectors: List = None, user_level_connectors: Dict = None, initialize_function_name: str = None, initialize_function_code: str = None, agent_mcp_config: dict = None) -> Agent:
+    def update_agent(self, model_id: str, function_source_code: str = None, agent_function_name: str = None, memory: int = None, package_requirements: list = None, description: str = None, enable_binary_input: bool = None, agent_input_schema: dict = None, agent_output_schema: dict = None, workflow_graph: Union[dict, WorkflowGraph] = None, agent_interface: Union[AgentInterface, str] = None, included_modules: List = None, org_level_connectors: List = None, user_level_connectors: Dict = None, initialize_function_name: str = None, initialize_function_code: str = None) -> Agent:
         """Updates an existing AI Agent. A new version of the agent will be created and published.
 
         Args:
@@ -9008,11 +9018,10 @@ def update_agent(self, model_id: str, function_source_code: str = None, agent_fu
             user_level_connectors (Dict): A dictionary mapping ApplicationConnectorType keys to lists of OAuth scopes. Each key represents a specific user level application connector, while the value is a list of scopes that define the permissions granted to the application.
             initialize_function_name (str): The name of the function to be used for initialization.
             initialize_function_code (str): The function code to be used for initialization.
-            agent_mcp_config (dict): The MCP config for the agent.
 
         Returns:
             Agent: The updated agent."""
-        return self._call_api('updateAgent', 'POST', query_params={}, body={'modelId': model_id, 'functionSourceCode': function_source_code, 'agentFunctionName': agent_function_name, 'memory': memory, 'packageRequirements': package_requirements, 'description': description, 'enableBinaryInput': enable_binary_input, 'agentInputSchema': agent_input_schema, 'agentOutputSchema': agent_output_schema, 'workflowGraph': workflow_graph, 'agentInterface': agent_interface, 'includedModules': included_modules, 'orgLevelConnectors': org_level_connectors, 'userLevelConnectors': user_level_connectors, 'initializeFunctionName': initialize_function_name, 'initializeFunctionCode': initialize_function_code, 'agentMcpConfig': agent_mcp_config}, parse_type=Agent)
+        return self._call_api('updateAgent', 'POST', query_params={}, body={'modelId': model_id, 'functionSourceCode': function_source_code, 'agentFunctionName': agent_function_name, 'memory': memory, 'packageRequirements': package_requirements, 'description': description, 'enableBinaryInput': enable_binary_input, 'agentInputSchema': agent_input_schema, 'agentOutputSchema': agent_output_schema, 'workflowGraph': workflow_graph, 'agentInterface': agent_interface, 'includedModules': included_modules, 'orgLevelConnectors': org_level_connectors, 'userLevelConnectors': user_level_connectors, 'initializeFunctionName': initialize_function_name, 'initializeFunctionCode': initialize_function_code}, parse_type=Agent)
 
     def generate_agent_code(self, project_id: str, prompt: str, fast_mode: bool = None) -> list:
         """Generates the code for defining an AI Agent
@@ -9257,3 +9266,17 @@ def get_relevant_snippets(self, doc_ids: List = None, blobs: io.TextIOBase = Non
         Returns:
             list[DocumentRetrieverLookupResult]: The snippets found from the documents."""
         return self._proxy_request('GetRelevantSnippets', 'POST', query_params={}, data={'docIds': doc_ids, 'query': query, 'documentRetrieverConfig': json.dumps(document_retriever_config.to_dict()) if hasattr(document_retriever_config, 'to_dict') else json.dumps(document_retriever_config), 'honorSentenceBoundary': honor_sentence_boundary, 'numRetrievalMarginWords': num_retrieval_margin_words, 'maxWordsPerSnippet': max_words_per_snippet, 'maxSnippetsPerDocument': max_snippets_per_document, 'startWordIndex': start_word_index, 'endWordIndex': end_word_index, 'includingBoundingBoxes': including_bounding_boxes, 'text': text, 'documentProcessingConfig': json.dumps(document_processing_config.to_dict()) if hasattr(document_processing_config, 'to_dict') else json.dumps(document_processing_config)}, files=blobs, parse_type=DocumentRetrieverLookupResult)
+
+    def query_mcp_server(self, task: str, server_name: str) -> McpServerQueryResult:
+        """Query a Remote MCP server. For a given task, it runs the required tools of the MCP
+
+        server with appropriate arguments and returns the output.
+
+
+        Args:
+            task (str): a comprehensive description of the task to perform using the MCP server tools.
+            server_name (str): The name of the MCP server.
+
+        Returns:
+            McpServerQueryResult: The execution logs as well as the final output of the task execution."""
+        return self._proxy_request('QueryMcpServer', 'POST', query_params={}, body={'task': task, 'serverName': server_name}, parse_type=McpServerQueryResult)