fix: re-raise OutputParserError in format_answer for retry logic

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -157,7 +157,7 @@ def handle_max_iterations_exceeded(
 
     # Perform one more LLM call to get the final answer
     answer = llm.call(
-        messages,  # type: ignore[arg-type]
+        messages,
         callbacks=callbacks,
     )
 
@@ -197,9 +197,14 @@ def format_answer(answer: str) -> AgentAction | AgentFinish:
 
     Returns:
         Either an AgentAction or AgentFinish
+
+    Raises:
+        OutputParserError: When the LLM response format is invalid, allowing retry logic
     """
     try:
         return parse(answer)
+    except OutputParserError:
+        raise
     except Exception:
         return AgentFinish(
             thought="Failed to parse LLM response",
@@ -249,10 +254,10 @@ def get_llm_response(
     """
     try:
         answer = llm.call(
-            messages,  # type: ignore[arg-type]
+            messages,
             callbacks=callbacks,
             from_task=from_task,
-            from_agent=from_agent,
+            from_agent=from_agent,  # type: ignore[arg-type]
             response_model=response_model,
         )
     except Exception as e:
@@ -294,8 +299,8 @@ def handle_agent_action_core(
     formatted_answer: AgentAction,
     tool_result: ToolResult,
     messages: list[LLMMessage] | None = None,
-    step_callback: Callable | None = None,
+    step_callback: Callable[[Any], Any] | None = None,
-    show_logs: Callable | None = None,
+    show_logs: Callable[[Any], Any] | None = None,
 ) -> AgentAction | AgentFinish:
     """Core logic for handling agent actions and tool results.
 
@@ -481,7 +486,7 @@ def summarize_messages(
             ),
         ]
         summary = llm.call(
-            messages,  # type: ignore[arg-type]
+            messages,
             callbacks=callbacks,
         )
         summarized_contents.append({"content": str(summary)})

lib/crewai/tests/utilities/test_agent_utils.py

@@ -0,0 +1,69 @@
+"""Tests for agent_utils module."""
+
+import pytest
+
+from crewai.agents.parser import AgentFinish, OutputParserError
+from crewai.utilities.agent_utils import format_answer
+
+
+class TestFormatAnswer:
+    """Tests for the format_answer function."""
+
+    def test_format_answer_with_valid_final_answer(self) -> None:
+        """Test that format_answer correctly parses a valid final answer."""
+        answer = """Thought: I have completed the task.
+Final Answer: The result is 42."""
+
+        result = format_answer(answer)
+
+        assert isinstance(result, AgentFinish)
+        assert result.output == "The result is 42."
+
+    def test_format_answer_reraises_output_parser_error(self) -> None:
+        """Test that format_answer re-raises OutputParserError for retry logic."""
+        # Malformed output missing colons after "Thought", "Action", and "Action Input"
+        malformed_answer = """Thought
+The user wants to verify something.
+Action
+Video Analysis Tool
+Action Input:
+{"query": "Is there something?"}"""
+
+        with pytest.raises(OutputParserError) as exc_info:
+            format_answer(malformed_answer)
+
+        # Verify that the error message contains helpful information
+        assert exc_info.value.error is not None
+
+    def test_format_answer_with_missing_action_colon(self) -> None:
+        """Test that format_answer raises OutputParserError when Action colon is missing."""
+        malformed_answer = """Thought: I need to search for information.
+Action
+Search Tool
+Action Input: {"query": "test"}"""
+
+        with pytest.raises(OutputParserError):
+            format_answer(malformed_answer)
+
+    def test_format_answer_with_missing_action_input_colon(self) -> None:
+        """Test that format_answer raises OutputParserError when Action Input colon is missing."""
+        malformed_answer = """Thought: I need to search for information.
+Action: Search Tool
+Action Input
+{"query": "test"}"""
+
+        with pytest.raises(OutputParserError):
+            format_answer(malformed_answer)
+
+    def test_format_answer_with_valid_action(self) -> None:
+        """Test that format_answer correctly parses a valid action format."""
+        valid_action = """Thought: I need to search for information.
+Action: Search Tool
+Action Input: {"query": "test"}"""
+
+        # This should parse successfully without raising an exception
+        result = format_answer(valid_action)
+
+        # The result should be an AgentAction (not AgentFinish)
+        assert result is not None
+        assert not isinstance(result, AgentFinish)