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106 lines
2.9 KiB
106 lines
2.9 KiB
from concurrent.futures import ThreadPoolExecutor, as_completed
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from graphlib import TopologicalSorter
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from typing import Dict, List
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class Task:
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"""
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Task is a unit of work that can be executed by an agent
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"""
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def __init__(
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self, id: str, parents: List["Task"] = None, children: List["Task"] = None
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):
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self.id = id
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self.parents = parents
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self.children = children
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def can_execute(self):
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"""
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can_execute returns True if the task can be executed
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"""
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raise NotImplementedError
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def execute(self):
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"""
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Execute the task
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"""
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raise NotImplementedError
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class NonLinearWorkflow:
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"""
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NonLinearWorkflow constructs a non sequential DAG of tasks to be executed by agents
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Architecture:
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NonLinearWorkflow = Task + Agent + Executor
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ASCII Diagram:
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+-------------------+
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| NonLinearWorkflow |
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+-------------------+
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+-------------------+
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"""
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def __init__(self, agents, iters_per_task):
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"""A workflow is a collection of tasks that can be executed in parallel or sequentially."""
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super().__init__()
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self.executor = ThreadPoolExecutor()
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self.agents = agents
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self.tasks = []
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def add(self, task: Task):
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"""Add a task to the workflow"""
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assert isinstance(task, Task), "Input must be an nstance of Task"
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self.tasks.append(task)
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return task
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def run(self):
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"""Run the workflow"""
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ordered_tasks = self.ordered_tasks
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exit_loop = False
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while not self.is_finished() and not exit_loop:
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futures_list = {}
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for task in ordered_tasks:
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if task.can_execute:
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future = self.executor.submit(self.agents.run, task.task_string)
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futures_list[future] = task
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for future in as_completed(futures_list):
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if isinstance(future.result(), Exception):
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exit_loop = True
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break
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return self.output_tasks()
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def output_tasks(self) -> List[Task]:
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"""Output tasks from the workflow"""
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return [task for task in self.tasks if not task.children]
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def to_graph(self) -> Dict[str, set[str]]:
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"""Convert the workflow to a graph"""
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graph = {
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task.id: set(child.id for child in task.children) for task in self.tasks
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}
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return graph
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def order_tasks(self) -> List[Task]:
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"""Order the tasks USING TOPOLOGICAL SORTING"""
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task_order = TopologicalSorter(self.to_graph()).static_order()
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return [self.find_task(task_id) for task_id in task_order]
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