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fix: correct code example language inconsistency in pt-BR docs (#3088)

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* fix: correct code example language inconsistency in pt-BR docs

* fix: fix: fully standardize code example language and naming in pt-BR docs

* fix: fix: fully standardize code example language and naming in pt-BR docs fixed variables

* fix: fix: fully standardize code example language and naming in pt-BR docs fixed params

---------

Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
This commit is contained in:
Irineu Brito
2025-07-02 12:18:32 -04:00
committed by GitHub
parent ceb310bcde
commit 7f83947020
37 changed files with 545 additions and 634 deletions
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40
docs/pt-BR/concepts/reasoning.mdx
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@@ -15,12 +15,12 @@ Para habilitar o reasoning para um agente, basta definir `reasoning=True` ao cri
```python
from crewai import Agent
agent = Agent(
role="Data Analyst",
goal="Analyze complex datasets and provide insights",
backstory="You are an experienced data analyst with expertise in finding patterns in complex data.",
reasoning=True, # Enable reasoning
max_reasoning_attempts=3 # Optional: Set a maximum number of reasoning attempts
analista = Agent(
role="Analista de Dados",
goal="Analisar dados e fornecer insights",
backstory="Você é um analista de dados especialista.",
reasoning=True,
max_reasoning_attempts=3 # Opcional: Defina um limite de tentativas de reasoning
)
```
@@ -53,23 +53,23 @@ Aqui está um exemplo completo:
from crewai import Agent, Task, Crew
# Create an agent with reasoning enabled
analyst = Agent(
role="Data Analyst",
goal="Analyze data and provide insights",
backstory="You are an expert data analyst.",
analista = Agent(
role="Analista de Dados",
goal="Analisar dados e fornecer insights",
backstory="Você é um analista de dados especialista.",
reasoning=True,
max_reasoning_attempts=3 # Optional: Set a limit on reasoning attempts
max_reasoning_attempts=3 # Opcional: Defina um limite de tentativas de reasoning
)
# Create a task
analysis_task = Task(
description="Analyze the provided sales data and identify key trends.",
expected_output="A report highlighting the top 3 sales trends.",
agent=analyst
description="Analise os dados de vendas fornecidos e identifique as principais tendências.",
expected_output="Um relatório destacando as 3 principais tendências de vendas.",
agent=analista
)
# Create a crew and run the task
crew = Crew(agents=[analyst], tasks=[analysis_task])
crew = Crew(agents=[analista], tasks=[analysis_task])
result = crew.kickoff()
print(result)
@@ -90,16 +90,16 @@ logging.basicConfig(level=logging.INFO)
# Create an agent with reasoning enabled
agent = Agent(
role="Data Analyst",
goal="Analyze data and provide insights",
role="Analista de Dados",
goal="Analisar dados e fornecer insights",
reasoning=True,
max_reasoning_attempts=3
)
# Create a task
task = Task(
description="Analyze the provided sales data and identify key trends.",
expected_output="A report highlighting the top 3 sales trends.",
description="Analise os dados de vendas fornecidos e identifique as principais tendências.",
expected_output="Um relatório destacando as 3 principais tendências de vendas.",
agent=agent
)
@@ -113,7 +113,7 @@ result = agent.execute_task(task)
Veja um exemplo de como pode ser um plano de reasoning para uma tarefa de análise de dados:
```
Task: Analyze the provided sales data and identify key trends.
Task: Analise os dados de vendas fornecidos e identifique as principais tendências.
Reasoning Plan:
I'll analyze the sales data to identify the top 3 trends.