Fix #2740: Prevent IndexError in ollama_pt() with empty messages

src/crewai/llm.py

@@ -322,6 +322,23 @@ def _is_anthropic_model(self, model: str) -> bool:
         ANTHROPIC_PREFIXES = ("anthropic/", "claude-", "claude/")
         return any(prefix in model.lower() for prefix in ANTHROPIC_PREFIXES)
 
+    def _validate_messages(
+        self,
+        messages: Union[str, List[Dict[str, str]], None]
+    ) -> None:
+        """Validate that messages list is not empty or None.
+
+        Args:
+            messages: Input messages for the LLM
+
+        Raises:
+            ValueError: If messages is None or an empty list
+        """
+        if messages is None:
+            raise ValueError("Messages list cannot be empty. At least one message is required.")
+        if isinstance(messages, list) and len(messages) == 0:
+            raise ValueError("Messages list cannot be empty. At least one message is required.")
+
     def _prepare_completion_params(
         self,
         messages: Union[str, List[Dict[str, str]]],
@@ -337,8 +354,14 @@ def _prepare_completion_params(
 
         Returns:
             Dict[str, Any]: Parameters for the completion call
+
+        Raises:
+            ValueError: If messages is None or an empty list
         """
-        # --- 1) Format messages according to provider requirements
+        # --- 1) Ensure messages list is not empty
+        self._validate_messages(messages)
+
+        # --- 2) Format messages according to provider requirements
         if isinstance(messages, str):
             messages = [{"role": "user", "content": messages}]
         formatted_messages = self._format_messages_for_provider(messages)
@@ -842,10 +865,13 @@ def call(
 
         Raises:
             TypeError: If messages format is invalid
-            ValueError: If response format is not supported
+            ValueError: If messages is None or an empty list, or if response format is not supported
             LLMContextLengthExceededException: If input exceeds model's context limit
         """
-        # --- 1) Emit call started event
+        # --- 1) Validate messages is not None or empty to prevent IndexError in LiteLLM's ollama_pt()
+        self._validate_messages(messages)
+
+        # --- 2) Emit call started event
         assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
@@ -857,10 +883,10 @@ def call(
             ),
         )
 
-        # --- 2) Validate parameters before proceeding with the call
+        # --- 3) Validate parameters before proceeding with the call
         self._validate_call_params()
 
-        # --- 3) Convert string messages to proper format if needed
+        # --- 4) Convert string messages to proper format if needed
         if isinstance(messages, str):
             messages = [{"role": "user", "content": messages}]
 

tests/test_empty_messages.py

@@ -0,0 +1,59 @@
+from unittest.mock import patch, MagicMock
+
+import pytest
+
+from crewai.llm import LLM
+
+
+@patch('crewai.llm.LLM._prepare_completion_params')
+def test_empty_messages_validation(mock_prepare):
+    """
+    Test that LLM.call() raises a ValueError when an empty messages list is passed.
+    This prevents the IndexError in LiteLLM's ollama_pt() function.
+    """
+    llm = LLM(model="gpt-3.5-turbo")  # Any model will do for this test
+
+    with pytest.raises(ValueError, match="Messages list cannot be empty"):
+        llm.call(messages=[])
+
+    with pytest.raises(ValueError, match="Messages list cannot be empty"):
+        llm.call(messages=None)
+
+    mock_prepare.assert_not_called()
+
+
+@patch('crewai.llm.LLM._prepare_completion_params')
+def test_empty_string_message(mock_prepare):
+    """
+    Test that LLM.call() raises a ValueError when an empty string message is passed.
+    """
+    llm = LLM(model="gpt-3.5-turbo")
+
+    with pytest.raises(ValueError, match="Messages list cannot be empty"):
+        llm.call(messages="")
+
+    mock_prepare.assert_not_called()
+
+
+@patch('crewai.llm.LLM._prepare_completion_params')
+def test_invalid_message_format(mock_prepare):
+    """
+    Test that LLM.call() raises a TypeError when a message with invalid format is passed.
+    """
+    mock_prepare.side_effect = TypeError("Invalid message format")
+    llm = LLM(model="gpt-3.5-turbo")
+
+    with pytest.raises(TypeError, match="Invalid message format"):
+        llm.call(messages=[{}])
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_ollama_model_empty_messages():
+    """
+    Test that LLM.call() with an Ollama model raises a ValueError 
+    when an empty messages list is passed.
+    """
+    llm = LLM(model="ollama/llama3")
+
+    with pytest.raises(ValueError, match="Messages list cannot be empty"):
+        llm.call(messages=[])