Application API

This section documents the application layer components.

Application Executors

Application executors module

Contains service executors and application-level coordination.

class aiecs.application.executors.OperationExecutor

Bases: object

Core logic for handling operation execution

__init__(tool_executor, execution_utils, config)

Parameters:

• tool_executor (ToolExecutor)

• execution_utils (ExecutionUtils)

• config (Dict[str, Any])

async execute_operation(operation_spec, params)

Execute a single operation (tool_name.operation_name)

Parameters:

• operation_spec (str)

• params (Dict[str, Any])

Return type:

Any

async batch_execute_operations(operations)

Batch execute operations with rate limiting

Parameters:

operations (List[Dict[str, Any]])

Return type:

List[Any]

async execute_operations_sequence(operations, user_id, task_id, stop_on_failure=False, save_callback=None)

Execute operations sequence sequentially, with option to stop on failure

Parameters:

• operations (List[Dict[str, Any]])

• user_id (str)

• task_id (str)

• stop_on_failure (bool)

Return type:

List[TaskStepResult]

async batch_tool_calls(tool_calls, tool_executor_func=None)

Execute batch tool calls with rate limiting

Parameters:

tool_calls (List[Dict])

Return type:

List[Any]

extract_tool_calls(description, input_data, context)

Extract tool calls from description

Parameters:

• description (str)

• input_data (Dict)

• context (Dict)

Return type:

List[Dict]

async execute_parallel_operations(operations)

Execute multiple operations in parallel

Parameters:

operations (List[Dict[str, Any]])

Return type:

List[TaskStepResult]

get_tool_instance(tool_name)

Get tool instance

Parameters:

tool_name (str)

clear_tool_cache()

Clear tool instance cache

get_stats()

Get operation executor statistics

Return type:

Dict[str, Any]

Knowledge Graph

Note

The knowledge graph module contains multiple submodules. See individual submodule documentation for details.