Version 1.4.18

Author: quantumfusion

abacusai/__init__.py

@@ -150,6 +150,7 @@
 from .nested_feature import NestedFeature
 from .nested_feature_schema import NestedFeatureSchema
 from .news_search_result import NewsSearchResult
+from .nlp_chat_response import NlpChatResponse
 from .notebook_completion import NotebookCompletion
 from .notebook_template import NotebookTemplate
 from .null_violation import NullViolation
@@ -166,6 +167,7 @@
 from .pipeline_step_version_reference import PipelineStepVersionReference
 from .pipeline_version import PipelineVersion
 from .pipeline_version_logs import PipelineVersionLogs
+from .playground_text import PlaygroundText
 from .point_in_time_feature import PointInTimeFeature
 from .point_in_time_feature_info import PointInTimeFeatureInfo
 from .point_in_time_group import PointInTimeGroup
@@ -219,4 +221,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.17"
+__version__ = "1.4.18"

abacusai/agent.py

@@ -23,10 +23,11 @@ class Agent(AbstractApiClass):
             agentExecutionConfig (dict): The config for arguments used to execute the agent.
             latestAgentVersion (AgentVersion): The latest agent version.
             codeSource (CodeSource): If a python model, information on the source code
+            draftWorkflowGraph (WorkflowGraph): The last saved draft of workflow graph for the agent.
             workflowGraph (WorkflowGraph): The workflow graph for the agent.
     """
 
-    def __init__(self, client, name=None, agentId=None, createdAt=None, projectId=None, notebookId=None, predictFunctionName=None, sourceCode=None, agentConfig=None, memory=None, trainingRequired=None, agentExecutionConfig=None, codeSource={}, latestAgentVersion={}, workflowGraph={}):
+    def __init__(self, client, name=None, agentId=None, createdAt=None, projectId=None, notebookId=None, predictFunctionName=None, sourceCode=None, agentConfig=None, memory=None, trainingRequired=None, agentExecutionConfig=None, codeSource={}, latestAgentVersion={}, draftWorkflowGraph={}, workflowGraph={}):
         super().__init__(client, agentId)
         self.name = name
         self.agent_id = agentId
@@ -42,12 +43,14 @@ def __init__(self, client, name=None, agentId=None, createdAt=None, projectId=No
         self.code_source = client._build_class(CodeSource, codeSource)
         self.latest_agent_version = client._build_class(
             AgentVersion, latestAgentVersion)
+        self.draft_workflow_graph = client._build_class(
+            WorkflowGraph, draftWorkflowGraph)
         self.workflow_graph = client._build_class(WorkflowGraph, workflowGraph)
         self.deprecated_keys = {}
 
     def __repr__(self):
-        repr_dict = {f'name': repr(self.name), f'agent_id': repr(self.agent_id), f'created_at': repr(self.created_at), f'project_id': repr(self.project_id), f'notebook_id': repr(self.notebook_id), f'predict_function_name': repr(self.predict_function_name), f'source_code': repr(self.source_code), f'agent_config': repr(
-            self.agent_config), f'memory': repr(self.memory), f'training_required': repr(self.training_required), f'agent_execution_config': repr(self.agent_execution_config), f'code_source': repr(self.code_source), f'latest_agent_version': repr(self.latest_agent_version), f'workflow_graph': repr(self.workflow_graph)}
+        repr_dict = {f'name': repr(self.name), f'agent_id': repr(self.agent_id), f'created_at': repr(self.created_at), f'project_id': repr(self.project_id), f'notebook_id': repr(self.notebook_id), f'predict_function_name': repr(self.predict_function_name), f'source_code': repr(self.source_code), f'agent_config': repr(self.agent_config), f'memory': repr(
+            self.memory), f'training_required': repr(self.training_required), f'agent_execution_config': repr(self.agent_execution_config), f'code_source': repr(self.code_source), f'latest_agent_version': repr(self.latest_agent_version), f'draft_workflow_graph': repr(self.draft_workflow_graph), f'workflow_graph': repr(self.workflow_graph)}
         class_name = "Agent"
         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])
@@ -60,8 +63,8 @@ def to_dict(self):
         Returns:
             dict: The dict value representation of the class parameters
         """
-        resp = {'name': self.name, 'agent_id': self.agent_id, 'created_at': self.created_at, 'project_id': self.project_id, 'notebook_id': self.notebook_id, 'predict_function_name': self.predict_function_name, 'source_code': self.source_code, 'agent_config': self.agent_config, 'memory': self.memory,
-                'training_required': self.training_required, 'agent_execution_config': self.agent_execution_config, 'code_source': self._get_attribute_as_dict(self.code_source), 'latest_agent_version': self._get_attribute_as_dict(self.latest_agent_version), 'workflow_graph': self._get_attribute_as_dict(self.workflow_graph)}
+        resp = {'name': self.name, 'agent_id': self.agent_id, 'created_at': self.created_at, 'project_id': self.project_id, 'notebook_id': self.notebook_id, 'predict_function_name': self.predict_function_name, 'source_code': self.source_code, 'agent_config': self.agent_config, 'memory': self.memory, 'training_required': self.training_required,
+                'agent_execution_config': self.agent_execution_config, 'code_source': self._get_attribute_as_dict(self.code_source), 'latest_agent_version': self._get_attribute_as_dict(self.latest_agent_version), 'draft_workflow_graph': self._get_attribute_as_dict(self.draft_workflow_graph), 'workflow_graph': self._get_attribute_as_dict(self.workflow_graph)}
         return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}
 
     def refresh(self):

abacusai/api_class/abstract.py

@@ -25,6 +25,8 @@
 def _validate_instance(value, expected_type):
     if expected_type == callable:
         return callable(value)
+    if expected_type is Any:
+        return True
     elif isinstance(expected_type, _GenericAlias):
         if expected_type.__origin__ == list:
             if not isinstance(value, list):

abacusai/api_class/ai_agents.py

@@ -1,6 +1,6 @@
 import ast
 import dataclasses
-from typing import Dict, List, Union
+from typing import Any, Dict, List, Union
 
 from . import enums
 from .abstract import ApiClass, get_clean_function_source_code_for_agent, validate_constructor_arg_types
@@ -67,14 +67,16 @@ class WorkflowNodeInputMapping(ApiClass):
     variable_source: str = dataclasses.field(default=None)
     source_prop: str = dataclasses.field(default=None)
     is_required: bool = dataclasses.field(default=True)
+    default_value: Any = dataclasses.field(default=None)
 
     def to_dict(self):
         return {
             'name': self.name,
             'variable_type': self.variable_type.value,
             'variable_source': self.variable_source,
             'source_prop': self.source_prop or self.name,
-            'is_required': self.is_required
+            'is_required': self.is_required,
+            'default_value': self.default_value
         }
 
     @classmethod
@@ -87,7 +89,8 @@ def from_dict(cls, mapping: dict):
             variable_type=enums.WorkflowNodeInputType(mapping['variable_type']),
             variable_source=mapping.get('variable_source'),
             source_prop=mapping.get('source_prop') or mapping['name'] if mapping.get('variable_source') else None,
-            is_required=mapping.get('is_required', True)
+            is_required=mapping.get('is_required', True),
+            default_value=mapping.get('default_value')
         )
 
 
@@ -283,14 +286,14 @@ def __init__(self, name: str, input_mappings: Union[Dict[str, WorkflowNodeInputM
                         raise ValueError('workflow_graph_node', f'Invalid input mapping. Argument "{input_name}" not found in function "{self.function_name}".')
                 for arg, default in arg_defaults.items():
                     if arg not in input_mapping_args:
-                        self.input_mappings.append(WorkflowNodeInputMapping(name=arg, variable_type=enums.WorkflowNodeInputType.USER_INPUT, is_required=default is None))
+                        self.input_mappings.append(WorkflowNodeInputMapping(name=arg, variable_type=enums.WorkflowNodeInputType.USER_INPUT, is_required=default is None, default_value=default.value if default else None))
             elif isinstance(input_mappings, Dict) and all(isinstance(key, str) and isinstance(value, WorkflowNodeInputMapping) for key, value in input_mappings.items()):
                 is_shortform_input_mappings = True
-                self.input_mappings = [WorkflowNodeInputMapping(name=arg, variable_type=enums.WorkflowNodeInputType.USER_INPUT, is_required=default is None) for arg, default in arg_defaults.items() if arg not in input_mappings]
+                self.input_mappings = [WorkflowNodeInputMapping(name=arg, variable_type=enums.WorkflowNodeInputType.USER_INPUT, is_required=default is None, default_value=default.value if default else None) for arg, default in arg_defaults.items() if arg not in input_mappings]
                 for key, value in input_mappings.items():
                     if key not in arg_defaults:
                         raise ValueError('workflow_graph_node', f'Invalid input mapping. Argument "{key}" not found in function "{self.function_name}".')
-                    self.input_mappings.append(WorkflowNodeInputMapping(name=key, variable_type=value.variable_type, variable_source=value.variable_source, source_prop=value.source_prop, is_required=arg_defaults.get(key) is None))
+                    self.input_mappings.append(WorkflowNodeInputMapping(name=key, variable_type=value.variable_type, variable_source=value.variable_source, source_prop=value.source_prop, is_required=arg_defaults.get(key) is None, default_value=value.default_value))
             else:
                 raise ValueError('workflow_graph_node', 'Invalid input mappings. Must be a list of WorkflowNodeInputMapping or a dictionary of input mappings in the form {arg_name: node_name.outputs.prop_name}.')
 
@@ -359,7 +362,7 @@ def from_template(cls, template_name: str, name: str, configs: dict = None, inpu
         if isinstance(input_mappings, List) and all(isinstance(input, WorkflowNodeInputMapping) for input in input_mappings):
             instance_input_mappings = input_mappings
         elif isinstance(input_mappings, Dict) and all(isinstance(key, str) and isinstance(value, WorkflowNodeInputMapping) for key, value in input_mappings.items()):
-            instance_input_mappings = [WorkflowNodeInputMapping(name=arg, variable_type=mapping.variable_type, variable_source=mapping.variable_source, source_prop=mapping.source_prop) for arg, mapping in input_mappings]
+            instance_input_mappings = [WorkflowNodeInputMapping(name=arg, variable_type=mapping.variable_type, variable_source=mapping.variable_source, source_prop=mapping.source_prop, is_required=mapping.is_required, default_value=mapping.default_value) for arg, mapping in input_mappings]
         elif input_mappings is None:
             instance_input_mappings = []
         else:

abacusai/api_class/dataset.py

@@ -71,7 +71,7 @@ def _detect_ocr_mode(self):
             elif self.document_type == DocumentType.EMBEDDED_IMAGES:
                 return OcrMode.SCANNED
             elif self.document_type == DocumentType.SCANNED_TEXT:
-                return OcrMode.DEFAULT
+                return OcrMode.SCANNED
         if self.ocr_mode is not None:
             return self.ocr_mode
         return OcrMode.AUTO

abacusai/api_class/enums.py

@@ -478,8 +478,10 @@ 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_5_HAIKU = 'CLAUDE_V3_5_HAIKU'
     GEMINI_1_5_PRO = 'GEMINI_1_5_PRO'
     ABACUS_SMAUG3 = 'ABACUS_SMAUG3'
+    ABACUS_DRACARYS = 'ABACUS_DRACARYS'
     GEMINI_1_5_FLASH = 'GEMINI_1_5_FLASH'
 
 
@@ -594,14 +596,15 @@ class OcrMode(ApiEnum):
     COMPREHENSIVE = 'COMPREHENSIVE'
     COMPREHENSIVE_V2 = 'COMPREHENSIVE_V2'
     COMPREHENSIVE_TABLE_MD = 'COMPREHENSIVE_TABLE_MD'
+    COMPREHENSIVE_FORM_MD = 'COMPREHENSIVE_FORM_MD'
     COMPREHENSIVE_FORM_AND_TABLE_MD = 'COMPREHENSIVE_FORM_AND_TABLE_MD'
     TESSERACT_FAST = 'TESSERACT_FAST'
     LLM = 'LLM'
     AUGMENTED_LLM = 'AUGMENTED_LLM'
 
     @classmethod
     def aws_ocr_modes(cls):
-        return [cls.COMPREHENSIVE_V2, cls.COMPREHENSIVE_TABLE_MD, cls.COMPREHENSIVE_FORM_AND_TABLE_MD]
+        return [cls.COMPREHENSIVE_V2, cls.COMPREHENSIVE_TABLE_MD, cls.COMPREHENSIVE_FORM_MD, cls.COMPREHENSIVE_FORM_AND_TABLE_MD]
 
 
 class DocumentType(ApiEnum):

abacusai/client.py

@@ -285,6 +285,9 @@ def __init__(self, *args, **kwargs):
             self.section_data_list.append({key: value})
 
     def to_dict(self):
+        """
+        Get a dict representation of the response object
+        """
         result = {}
         if self.data_list:
             result['data_list'] = self.data_list
@@ -589,6 +592,9 @@ class _ApiExceptionFactory:
     """
     @classmethod
     def from_response(cls, message: str, http_status: int, exception: str = None, request_id: str = None):
+        """
+        Creates an appropriate exception instance based on HTTP response data.
+        """
         if http_status == 504:
             message = 'Gateway timeout, please try again later'
             return GatewayTimeoutError(message, http_status, exception, request_id)
@@ -618,7 +624,7 @@ 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 = '1.4.17'
+    client_version = '1.4.18'
 
     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
@@ -3612,6 +3618,9 @@ def run_workflow_graph(self, workflow_graph: WorkflowGraph, sample_user_inputs:
         return workflow_info['run_info']
 
     def execute_workflow_node(self, node: WorkflowGraphNode, inputs: dict):
+        """
+        Executes a workflow node.
+        """
         source_code = None
         function_name = None
         if node.template_metadata:

abacusai/nlp_chat_response.py

@@ -0,0 +1,37 @@
+from .return_class import AbstractApiClass
+
+
+class NlpChatResponse(AbstractApiClass):
+    """
+        A chat response from an LLM
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            deploymentConversationId (str): The unique identifier of the deployment conversation.
+            messages (list): The conversation messages in the chat.
+    """
+
+    def __init__(self, client, deploymentConversationId=None, messages=None):
+        super().__init__(client, None)
+        self.deployment_conversation_id = deploymentConversationId
+        self.messages = messages
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'deployment_conversation_id': repr(
+            self.deployment_conversation_id), f'messages': repr(self.messages)}
+        class_name = "NlpChatResponse"
+        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 = {'deployment_conversation_id': self.deployment_conversation_id,
+                'messages': self.messages}
+        return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

abacusai/playground_text.py

@@ -0,0 +1,37 @@
+from .return_class import AbstractApiClass
+
+
+class PlaygroundText(AbstractApiClass):
+    """
+        The text content inside of a playground segment.
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            playgroundText (str): The text of the playground segment.
+            renderingCode (str): The rendering code of the playground segment.
+    """
+
+    def __init__(self, client, playgroundText=None, renderingCode=None):
+        super().__init__(client, None)
+        self.playground_text = playgroundText
+        self.rendering_code = renderingCode
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'playground_text': repr(
+            self.playground_text), f'rendering_code': repr(self.rendering_code)}
+        class_name = "PlaygroundText"
+        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 = {'playground_text': self.playground_text,
+                'rendering_code': self.rendering_code}
+        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: 787e52a6c82af449544cb6a1253baab3
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 12535596649b36dd1c7e0cddf2d1e3b2
 tags: 645f666f9bcd5a90fca523b33c5a78b7