Tian AI Architecture Deep Dive: Building a Multi-Engine AI System

The provided code outlines a basic task queue system designed for executing asynchronous or concurrent tasks in Python, particularly useful in scenarios where tasks have dependencies on each other. Here's an overview of the key components and functionalities:

Task Class

• Initialization (__init__): Each Task object is initialized with unique attributes such as task_id, func (the function to be executed), args (arguments for the function), kwargs (keyword arguments for the function), depends_on (a list of task IDs that this task depends on), priority (to determine execution order among ready tasks), and timeout (time limit in seconds before a task is considered failed).

• Status Management: The status of each task can be one of three states: 'pending', 'running', or 'done/failed'. This helps track the lifecycle of each task.

TaskQueue Class

• Initialization (__init__): Initializes two dictionaries, tasks and results, to store tasks and their results respectively. Also initializes a threading lock for thread-safe operations.

• Add Task (add_task): Adds a new task to the queue by storing it

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