Version 1.4.43

Author: arvindsun

abacusai/__init__.py

@@ -34,12 +34,14 @@
 from .chatllm_task import ChatllmTask
 from .client import AgentResponse, ApiClient, ApiException, ClientOptions, ReadOnlyClient, ToolResponse, _request_context
 from .code_agent_response import CodeAgentResponse
+from .code_autocomplete_edit_prediction_response import CodeAutocompleteEditPredictionResponse
 from .code_autocomplete_response import CodeAutocompleteResponse
 from .code_bot import CodeBot
 from .code_edit import CodeEdit
 from .code_edit_response import CodeEditResponse
 from .code_edits import CodeEdits
 from .code_embeddings import CodeEmbeddings
+from .code_llm_changed_files import CodeLlmChangedFiles
 from .code_source import CodeSource
 from .code_suggestion_validation_response import CodeSuggestionValidationResponse
 from .code_summary_response import CodeSummaryResponse
@@ -67,6 +69,7 @@
 from .dataset_column import DatasetColumn
 from .dataset_version import DatasetVersion
 from .dataset_version_logs import DatasetVersionLogs
+from .default_llm import DefaultLlm
 from .deployment import Deployment
 from .deployment_auth_token import DeploymentAuthToken
 from .deployment_conversation import DeploymentConversation
@@ -153,6 +156,7 @@
 from .llm_input import LlmInput
 from .llm_parameters import LlmParameters
 from .llm_response import LlmResponse
+from .mcp_config import McpConfig
 from .memory_options import MemoryOptions
 from .messaging_connector_response import MessagingConnectorResponse
 from .model import Model
@@ -248,6 +252,7 @@
 from .video_gen_settings import VideoGenSettings
 from .video_search_result import VideoSearchResult
 from .voice_gen_details import VoiceGenDetails
+from .web_app_domain import WebAppDomain
 from .web_page_response import WebPageResponse
 from .web_search_response import WebSearchResponse
 from .web_search_result import WebSearchResult
@@ -256,4 +261,4 @@
 from .workflow_node_template import WorkflowNodeTemplate
 
 
-__version__ = "1.4.42"
+__version__ = "1.4.43"

abacusai/api_class/ai_agents.py

@@ -495,6 +495,12 @@ def from_template(cls, template_name: str, name: str, configs: dict = None, inpu
         else:
             raise ValueError('workflow_graph_node', 'Invalid output schema. Must be a WorkflowNodeOutputSchema or a list of output section names.')
 
+        if sleep_time is not None:
+            if isinstance(sleep_time, str) and sleep_time.isdigit():
+                sleep_time = int(sleep_time)
+            if not isinstance(sleep_time, int) or sleep_time < 0:
+                raise ValueError('workflow_graph_node', 'Invalid sleep time. Must be a non-negative integer.')
+
         return cls(
             name=name,
             input_mappings=instance_input_mappings,

abacusai/api_class/enums.py

@@ -481,7 +481,10 @@ class VectorStoreTextEncoder(ApiEnum):
     CODE_BERT = 'CODE_BERT'
 
 
-@deprecated_enums('OPENAI_GPT4_32K', 'OPENAI_GPT3_5', 'OPENAI_GPT3_5_TEXT', 'LLAMA3_LARGE_CHAT', 'CLAUDE_V3_OPUS', 'CLAUDE_V3_SONNET', 'OPENAI_GPT4', 'OPENAI_GPT4_128K', 'QWEN_2_5_32B_BASE')
+@deprecated_enums('OPENAI_GPT4_32K', 'OPENAI_GPT3_5', 'OPENAI_GPT3_5_TEXT',
+                  'OPENAI_GPT4', 'OPENAI_GPT4_128K', 'OPENAI_GPT4_128K_LATEST',
+                  'LLAMA3_LARGE_CHAT', 'CLAUDE_V3_OPUS', 'CLAUDE_V3_SONNET', 'CLAUDE_V3_HAIKU',
+                  'QWEN_2_5_32B_BASE')
 class LLMName(ApiEnum):
     OPENAI_GPT4 = 'OPENAI_GPT4'
     OPENAI_GPT4_32K = 'OPENAI_GPT4_32K'

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

@@ -213,7 +213,7 @@ async def sse_asynchronous_generator(endpoint: str, headers: dict, body: dict):
     except Exception:
         raise Exception('Please install aiohttp to use this functionality')
 
-    async with aiohttp.request('POST', endpoint, json=body, headers=headers) as response:
+    async with aiohttp.request('POST', endpoint, json=body, headers=headers, timeout=aiohttp.ClientTimeout(total=0)) as response:
         async for line in response.content:
             if line:
                 streamed_responses = line.decode('utf-8').split('\n\n')
@@ -661,7 +661,7 @@ 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 = '1.4.42'
+    client_version = '1.4.43'
 
     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
@@ -2838,6 +2838,13 @@ def copy_agent(self, agent_id: str, project_id: str = None) -> Agent:
             Agent: The newly generated agent."""
         return self._call_api('copyAgent', 'GET', query_params={'agentId': agent_id, 'projectId': project_id}, parse_type=Agent)
 
+    def sdk_link_hosted_app(self, app: str = None) -> io.BytesIO:
+        """Returns custom SDK JS for Widget JS
+
+        Args:
+            app (str): Application ID to be used as appId"""
+        return self._call_api('sdkLinkHostedApp', 'GET', query_params={'app': app}, streamable_response=True)
+
     def list_llm_apps(self) -> List[LlmApp]:
         """Lists all available LLM Apps, which are LLMs tailored to achieve a specific task like code generation for a specific service's API.
 
@@ -3035,6 +3042,47 @@ def _serialize_df_with_dtypes(df):
             deployment_token=deployment_token, deployment_id=deployment_id, query_data=query_data, solve_time_limit_seconds=solve_time_limit_seconds, optimality_gap_limit=optimality_gap_limit)
         return result
 
+    def get_optimisation_input_dataframes_with_new_inputs(deployment_token: str, deployment_id: str, query_data: dict):
+        """
+        Get assignments for given query, with new inputs
+
+        Args:
+            deployment_token (str): The deployment token used to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it can be safely embedded in an application or website.
+            deployment_id (str): The unique identifier of a deployment created under the project.
+            query_data (dict): a dictionary with various key: value pairs corresponding to various updated FGs in the FG tree, which we want to update to compute new top level FGs for online solve. values are dataframes and keys are their names. Names should be same as the ones used during training.
+
+        Returns:
+            OptimizationAssignment: The output dataframes for a given query.
+        """
+        def _serialize_df_with_dtypes(df):
+            # Get dtypes dictionary
+            dtypes_dict = df.dtypes.apply(lambda x: str(x)).to_dict()
+
+            # Handle special dtypes
+            for col, dtype in dtypes_dict.items():
+                if 'datetime' in dtype.lower():
+                    dtypes_dict[col] = 'datetime'
+                elif 'category' in dtype.lower():
+                    dtypes_dict[col] = 'category'
+
+            # Convert DataFrame to JSON
+            json_data = df.to_json(date_format='iso')
+
+            # Create final dictionary with both data and dtypes
+            serialized = {
+                'data': json_data,
+                'dtypes': dtypes_dict
+            }
+
+            return json.dumps(serialized)
+
+        query_data = {name: _serialize_df_with_dtypes(
+            df) for name, df in query_data.items()}
+
+        result = self.get_optimisation_input_dataframes_with_new_serialized_inputs(
+            deployment_token=deployment_token, deployment_id=deployment_id, query_data=query_data)
+        return result
+
     def create_dataset_version_from_pandas(self, table_name_or_id: str, df: pd.DataFrame, clean_column_names: bool = False) -> Dataset:
         """
         [Deprecated]
@@ -7593,6 +7641,17 @@ def get_alternative_assignments(self, deployment_token: str, deployment_id: str,
             deployment_id, deployment_token) if deployment_token else None
         return self._call_api('getAlternativeAssignments', 'POST', query_params={'deploymentToken': deployment_token, 'deploymentId': deployment_id}, body={'queryData': query_data, 'addConstraints': add_constraints, 'solveTimeLimitSeconds': solve_time_limit_seconds, 'bestAlternateOnly': best_alternate_only}, server_override=prediction_url)
 
+    def get_optimisation_inputs_from_serialized(self, deployment_token: str, deployment_id: str, query_data: dict = None) -> Dict:
+        """Get assignments for given query, with new inputs
+
+        Args:
+            deployment_token (str): The deployment token used to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it can be safely embedded in an application or website.
+            deployment_id (str): The unique identifier of a deployment created under the project.
+            query_data (dict): a dictionary with various key: value pairs corresponding to various updated FGs in the FG tree, which we want to update to compute new top level FGs for online solve. (query data will be dict of names: serialized dataframes)"""
+        prediction_url = self._get_prediction_endpoint(
+            deployment_id, deployment_token) if deployment_token else None
+        return self._call_api('getOptimisationInputsFromSerialized', 'POST', query_params={'deploymentToken': deployment_token, 'deploymentId': deployment_id}, body={'queryData': query_data}, server_override=prediction_url)
+
     def get_assignments_online_with_new_serialized_inputs(self, deployment_token: str, deployment_id: str, query_data: dict = None, solve_time_limit_seconds: float = None, optimality_gap_limit: float = None) -> Dict:
         """Get assignments for given query, with new inputs
 

abacusai/code_autocomplete_edit_prediction_response.py

@@ -0,0 +1,37 @@
+from .return_class import AbstractApiClass
+
+
+class CodeAutocompleteEditPredictionResponse(AbstractApiClass):
+    """
+        A autocomplete response from an LLM
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            autocompleteResponse (str): autocomplete code
+            showAutocomplete (bool): Whether to show autocomplete in the client
+    """
+
+    def __init__(self, client, autocompleteResponse=None, showAutocomplete=None):
+        super().__init__(client, None)
+        self.autocomplete_response = autocompleteResponse
+        self.show_autocomplete = showAutocomplete
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'autocomplete_response': repr(
+            self.autocomplete_response), f'show_autocomplete': repr(self.show_autocomplete)}
+        class_name = "CodeAutocompleteEditPredictionResponse"
+        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 = {'autocomplete_response': self.autocomplete_response,
+                'show_autocomplete': self.show_autocomplete}
+        return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

abacusai/code_llm_changed_files.py

@@ -0,0 +1,39 @@
+from .return_class import AbstractApiClass
+
+
+class CodeLlmChangedFiles(AbstractApiClass):
+    """
+        Code changed files
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            addedFiles (list): A list of added file paths.
+            updatedFiles (list): A list of updated file paths.
+            deletedFiles (list): A list of deleted file paths.
+    """
+
+    def __init__(self, client, addedFiles=None, updatedFiles=None, deletedFiles=None):
+        super().__init__(client, None)
+        self.added_files = addedFiles
+        self.updated_files = updatedFiles
+        self.deleted_files = deletedFiles
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'added_files': repr(self.added_files), f'updated_files': repr(
+            self.updated_files), f'deleted_files': repr(self.deleted_files)}
+        class_name = "CodeLlmChangedFiles"
+        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 = {'added_files': self.added_files,
+                'updated_files': self.updated_files, 'deleted_files': self.deleted_files}
+        return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}

abacusai/default_llm.py

@@ -0,0 +1,35 @@
+from .return_class import AbstractApiClass
+
+
+class DefaultLlm(AbstractApiClass):
+    """
+        A default LLM.
+
+        Args:
+            client (ApiClient): An authenticated API Client instance
+            name (str): The name of the LLM.
+            enum (str): The enum of the LLM.
+    """
+
+    def __init__(self, client, name=None, enum=None):
+        super().__init__(client, None)
+        self.name = name
+        self.enum = enum
+        self.deprecated_keys = {}
+
+    def __repr__(self):
+        repr_dict = {f'name': repr(self.name), f'enum': repr(self.enum)}
+        class_name = "DefaultLlm"
+        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 = {'name': self.name, 'enum': self.enum}
+        return {key: value for key, value in resp.items() if value is not None and key not in self.deprecated_keys}