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84 lines
2.4 KiB
84 lines
2.4 KiB
from __future__ import annotations
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import uuid
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from concurrent.futures import ThreadPoolExecutor
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from typing import Any, Dict, List, Optional
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from swarms.structs.task import Task
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class Workflow:
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"""
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Workflows are ideal for prescriptive processes that need to be executed
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sequentially.
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They string together multiple tasks of varying types, and can use Short-Term Memory
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or pass specific arguments downstream.
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Usage
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llm = LLM()
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workflow = Workflow(llm)
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workflow.add("What's the weather in miami")
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workflow.add("Provide details for {{ parent_output }}")
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workflow.add("Summarize the above information: {{ parent_output}})
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workflow.run()
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"""
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def __init__(self, agent, parallel: bool = False):
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"""__init__"""
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self.agent = agent
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self.tasks: List[Task] = []
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self.parallel = parallel
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def add(self, task: str) -> Task:
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"""Add a task"""
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task = Task(task_id=uuid.uuid4().hex, input=task)
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if self.last_task():
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self.last_task().add_child(task)
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else:
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task.structure = self
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self.tasks.append(task)
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return task
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def first_task(self) -> Optional[Task]:
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"""Add first task"""
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return self.tasks[0] if self.tasks else None
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def last_task(self) -> Optional[Task]:
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"""Last task"""
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return self.tasks[-1] if self.tasks else None
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def run(self, task: str) -> Task:
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"""Run tasks"""
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self.add(task)
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if self.parallel:
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with ThreadPoolExecutor() as executor:
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list(executor.map(self.__run_from_task, [self.first_task]))
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else:
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self.__run_from_task(self.first_task())
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return self.last_task()
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def context(self, task: Task) -> Dict[str, Any]:
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"""Context in tasks"""
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return {
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"parent_output": task.parents[0].output
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if task.parents and task.parents[0].output
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else None,
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"parent": task.parents[0] if task.parents else None,
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"child": task.children[0] if task.children else None,
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}
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def __run_from_task(self, task: Optional[Task]) -> None:
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"""Run from task"""
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if task is None:
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return
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else:
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if isinstance(task.execute(), Exception):
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return
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else:
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self.__run_from_task(next(iter(task.children), None))
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