fix: Address CI failures and code review feedback for multi-round dialogue

Co-Authored-By: Joe Moura <joao@crewai.com>

src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -105,8 +105,9 @@ class CrewAgentExecutorMixin:
         Returns:
             str: The user's feedback
         """
+        round_info = f"\033[1m\033[93mRound {current_round}/{max_rounds}\033[00m"
         self._printer.print(
-            content=f"\033[1m\033[95m ## Result (Round {current_round}/{max_rounds}):\033[00m \033[92m{final_answer}\033[00m"
+            content=f"\033[1m\033[95m ## Result {round_info}:\033[00m \033[92m{final_answer}\033[00m"
         )
 
         # Training mode prompt (single iteration)

src/crewai/agents/crew_agent_executor.py

@@ -574,6 +574,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         Returns:
             AgentFinish: The final answer after processing feedback
         """
+        if max_rounds < 1:
+            raise ValueError("max_rounds must be positive")
+            
         feedback = initial_feedback
         answer = current_answer
         current_round = 1

src/crewai/task.py

@@ -128,6 +128,8 @@ class Task(BaseModel):
     max_dialogue_rounds: int = Field(
         default=10,
         description="Maximum number of dialogue rounds for human input",
+        ge=1,  # Ensures positive integer
+        examples=[5, 10, 15],
     )
     converter_cls: Optional[Type[Converter]] = Field(
         description="A converter class used to export structured output",

tests/agent_test.py

@@ -1206,6 +1206,7 @@ def test_agent_max_retry_limit():
                         "tool_names": "",
                         "tools": "",
                         "ask_for_human_input": True,
+                        "max_dialogue_rounds": 10,
                     }
                 ),
                 mock.call(
@@ -1214,6 +1215,7 @@ def test_agent_max_retry_limit():
                         "tool_names": "",
                         "tools": "",
                         "ask_for_human_input": True,
+                        "max_dialogue_rounds": 10,
                     }
                 ),
             ]

tests/agents/test_multi_round_dialogue.py

@@ -1,7 +1,8 @@
 import unittest
-from unittest.mock import patch
+from unittest.mock import patch, MagicMock
 
 from crewai.task import Task
+from langchain_core.agents import AgentFinish
 
 
 class TestMultiRoundDialogue(unittest.TestCase):
@@ -31,6 +32,44 @@ class TestMultiRoundDialogue(unittest.TestCase):
         
         # Verify the custom value
         self.assertEqual(task.max_dialogue_rounds, 5)
+        
+    def test_task_max_dialogue_rounds_validation(self):
+        """Test that Task validates max_dialogue_rounds as a positive integer."""
+        # Create a task with invalid max_dialogue_rounds
+        with self.assertRaises(ValueError):
+            task = Task(
+                description="Test task",
+                expected_output="Test output",
+                human_input=True,
+                max_dialogue_rounds=0
+            )
+            
+    def test_handle_regular_feedback_rounds(self):
+        """Test that _handle_regular_feedback correctly handles multiple rounds."""
+        from crewai.agents.crew_agent_executor import CrewAgentExecutor
+        
+        # Create a simple mock executor
+        executor = MagicMock()
+        executor.ask_for_human_input = True
+        executor._ask_human_input = MagicMock(side_effect=["Feedback", ""])
+        executor._process_feedback_iteration = MagicMock(return_value=MagicMock())
+        
+        # Create a sample initial answer
+        initial_answer = MagicMock()
+        
+        # Call the method directly
+        CrewAgentExecutor._handle_regular_feedback(
+            executor, 
+            initial_answer, 
+            "Initial feedback", 
+            max_rounds=3
+        )
+        
+        # Verify the correct number of iterations occurred
+        # First call for initial feedback, second call for empty feedback to end loop
+        self.assertEqual(executor._ask_human_input.call_count, 2)
+        # The _process_feedback_iteration is called for the initial feedback and the first round
+        self.assertEqual(executor._process_feedback_iteration.call_count, 2)
 
 
 if __name__ == "__main__":