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* docs(cli): document device-code login and config reset guidance; renumber sections * docs(cli): fix duplicate numbering (renumber Login/API Keys/Configuration sections) * docs: Fix webhook documentation to include meta dict in all webhook payloads - Add note explaining that meta objects from kickoff requests are included in all webhook payloads - Update webhook examples to show proper payload structure including meta field - Fix webhook examples to match actual API implementation - Apply changes to English, Korean, and Portuguese documentation Resolves the documentation gap where meta dict passing to webhooks was not documented despite being implemented in the API. * WIP: CrewAI docs theme, changelog, GEO, localization * docs(cli): fix merge markers; ensure mode: "wide"; convert ASCII tables to Markdown (en/pt-BR/ko) * docs: add group icons across locales; split Automation/Integrations; update tools overviews and links
90 lines
2.7 KiB
Plaintext
90 lines
2.7 KiB
Plaintext
---
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title: Tarefas Condicionais
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description: Saiba como usar tarefas condicionais em um kickoff do crewAI
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icon: diagram-subtask
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mode: "wide"
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---
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## Introdução
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As Tarefas Condicionais no crewAI permitem a adaptação dinâmica do fluxo de trabalho com base nos resultados de tarefas anteriores.
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Esse recurso poderoso possibilita que crews tomem decisões e executem tarefas seletivamente, aumentando a flexibilidade e a eficiência dos seus processos orientados por IA.
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## Exemplo de Uso
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```python Code
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from typing import List
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from pydantic import BaseModel
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from crewai import Agent, Crew
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from crewai.tasks.conditional_task import ConditionalTask
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from crewai.tasks.task_output import TaskOutput
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from crewai.task import Task
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from crewai_tools import SerperDevTool
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# Define a condition function for the conditional task
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# If false, the task will be skipped, if true, then execute the task.
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def is_data_missing(output: TaskOutput) -> bool:
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return len(output.pydantic.events) < 10 # this will skip this task
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# Define the agents
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data_fetcher_agent = Agent(
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role="Data Fetcher",
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goal="Fetch data online using Serper tool",
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backstory="Backstory 1",
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verbose=True,
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tools=[SerperDevTool()]
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)
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data_processor_agent = Agent(
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role="Data Processor",
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goal="Process fetched data",
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backstory="Backstory 2",
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verbose=True
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)
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summary_generator_agent = Agent(
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role="Summary Generator",
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goal="Generate summary from fetched data",
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backstory="Backstory 3",
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verbose=True
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)
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class EventOutput(BaseModel):
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events: List[str]
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task1 = Task(
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description="Fetch data about events in San Francisco using Serper tool",
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expected_output="List of 10 things to do in SF this week",
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agent=data_fetcher_agent,
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output_pydantic=EventOutput,
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)
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conditional_task = ConditionalTask(
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description="""
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Check if data is missing. If we have less than 10 events,
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fetch more events using Serper tool so that
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we have a total of 10 events in SF this week..
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""",
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expected_output="List of 10 Things to do in SF this week",
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condition=is_data_missing,
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agent=data_processor_agent,
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)
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task3 = Task(
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description="Generate summary of events in San Francisco from fetched data",
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expected_output="A complete report on the customer and their customers and competitors, including their demographics, preferences, market positioning and audience engagement.",
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agent=summary_generator_agent,
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)
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# Create a crew with the tasks
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crew = Crew(
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agents=[data_fetcher_agent, data_processor_agent, summary_generator_agent],
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tasks=[task1, conditional_task, task3],
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verbose=True,
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planning=True
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)
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# Run the crew
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result = crew.kickoff()
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print("results", result)
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``` |