Enhance function_calling_llm handling with logging and type validation

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

src/crewai/project/crew_base.py

@@ -172,11 +172,15 @@ def CrewBase(cls: T) -> T:
                 ]
 
             if function_calling_llm := agent_info.get("function_calling_llm"):
+                if not isinstance(function_calling_llm, str):
+                    raise ValueError(f"function_calling_llm must be a string, got {type(function_calling_llm)}")
+                
                 try:
                     self.agents_config[agent_name]["function_calling_llm"] = agents[
                         function_calling_llm
                     ]()
                 except KeyError:
+                    logging.debug(f"No agent found for function_calling_llm '{function_calling_llm}', using it as direct model name")
                     self.agents_config[agent_name]["function_calling_llm"] = function_calling_llm
 
             if step_callback := agent_info.get("step_callback"):

tests/yaml_config_test.py

@@ -1,15 +1,24 @@
 import os
+import pytest
 import tempfile
 import yaml
-import pytest
-from crewai.project import CrewBase, agent, crew, task, tool
-from crewai import Agent, Crew, Task, Process
-from crewai.tools import BaseTool
-from pydantic import BaseModel, Field
 from typing import Type
 
+from pydantic import BaseModel, Field
+
+from crewai import Agent, Crew, Process, Task
+from crewai.project import CrewBase, agent, crew, task, tool
+from crewai.tools import BaseTool
+
 def test_function_calling_llm_in_yaml():
-    """Test that function_calling_llm can be specified in YAML."""
+    """
+    Test function_calling_llm YAML configuration.
+    
+    Tests:
+        - Direct model name specification
+        - Configuration persistence
+        - Integration with Agent initialization
+    """
     # Create temporary YAML files
     with tempfile.TemporaryDirectory() as temp_dir:
         # Create agents.yaml with function_calling_llm
@@ -77,3 +86,69 @@ def test_function_calling_llm_in_yaml():
         # Verify that function_calling_llm was properly set
         assert crew_instance.agents[0].function_calling_llm is not None
         assert crew_instance.agents[0].function_calling_llm.model == "gpt-4o-mini"
+
+def test_invalid_function_calling_llm_type():
+    """Test that function_calling_llm must be a string."""
+    # Create temporary YAML files
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Create agents.yaml with invalid function_calling_llm type
+        agents_yaml = os.path.join(temp_dir, "agents.yaml")
+        with open(agents_yaml, "w") as f:
+            yaml.dump(
+                {
+                    "test_agent": {
+                        "role": "Test Agent",
+                        "goal": "Test Goal",
+                        "backstory": "Test Backstory",
+                        "function_calling_llm": 123  # Invalid type
+                    }
+                },
+                f
+            )
+        
+        # Create tasks.yaml
+        tasks_yaml = os.path.join(temp_dir, "tasks.yaml")
+        with open(tasks_yaml, "w") as f:
+            yaml.dump(
+                {
+                    "test_task": {
+                        "description": "Test Task",
+                        "expected_output": "Test Output",
+                        "agent": "test_agent"
+                    }
+                },
+                f
+            )
+        
+        # Create a CrewBase class that uses the YAML files
+        @CrewBase
+        class TestCrew:
+            """Test crew with invalid function_calling_llm type."""
+            agents_config = agents_yaml
+            tasks_config = tasks_yaml
+            
+            @agent
+            def test_agent(self) -> Agent:
+                return Agent(
+                    config=self.agents_config["test_agent"],
+                    verbose=True
+                )
+            
+            @task
+            def test_task(self) -> Task:
+                return Task(
+                    config=self.tasks_config["test_task"]
+                )
+            
+            @crew
+            def crew(self) -> Crew:
+                return Crew(
+                    agents=self.agents,
+                    tasks=self.tasks,
+                    process=Process.sequential,
+                    verbose=True
+                )
+        
+        # Initialize the crew - this should raise a ValueError
+        with pytest.raises(ValueError, match="function_calling_llm must be a string"):
+            test_crew = TestCrew()