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Complete code review improvements

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- Fix type errors by converting deque to list when passing to handle_mid_execution_reasoning
- Add proper type annotation for tools_used
- Fix agent type error by casting BaseAgent to Agent
- Fix _should_trigger_reasoning logic to correctly handle reasoning_interval
- All type checking passes (mypy clean)

Addresses all code quality suggestions from PR review.

Co-Authored-By: Joe Moura <joao@crewai.com>
This commit is contained in:
Devin AI
2025-05-26 17:54:05 +00:00
committed by João Moura
parent 53fed872f2
commit fdba0c8a03
1 changed files with 8 additions and 5 deletions
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13
src/crewai/agents/crew_agent_executor.py
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@@ -1,5 +1,5 @@
from collections import deque
from typing import Any, Callable, Dict, List, Optional, Union
from typing import Any, Callable, Dict, List, Optional, Union, cast
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
@@ -84,7 +84,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
self.tool_name_to_tool_map: Dict[str, Union[CrewStructuredTool, BaseTool]] = {
tool.name: tool for tool in self.tools
}
self.tools_used: deque = deque(maxlen=100) # Limit history size
self.tools_used: deque[str] = deque(maxlen=100) # Limit history size
self.steps_since_reasoning = 0
existing_stop = self.llm.stop or []
self.llm.stop = list(
@@ -473,9 +473,10 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
self.steps_since_reasoning += 1
if hasattr(self.agent, "reasoning_interval") and self.agent.reasoning_interval:
if hasattr(self.agent, "reasoning_interval") and self.agent.reasoning_interval is not None:
if self.steps_since_reasoning >= self.agent.reasoning_interval:
return True
return False # If interval is set but not reached, don't check adaptive
if hasattr(self.agent, "adaptive_reasoning") and self.agent.adaptive_reasoning:
return self._should_adaptive_reason()
@@ -528,11 +529,13 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
current_progress = self._summarize_current_progress()
reasoning_handler = AgentReasoning(task=self.task, agent=self.agent)
from crewai.agent import Agent
reasoning_handler = AgentReasoning(task=self.task, agent=cast(Agent, self.agent))
reasoning_output = reasoning_handler.handle_mid_execution_reasoning(
current_steps=self.iterations,
tools_used=self.tools_used,
tools_used=list(self.tools_used),
current_progress=current_progress,
iteration_messages=self.messages
)