fix: update LLMCallStartedEvent message type to support multimodal content (#2475)

fix: sort imports in test file to fix linting

fix: properly sort imports with ruff

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

src/crewai/utilities/events/llm_events.py

@@ -15,7 +15,7 @@ class LLMCallStartedEvent(CrewEvent):
     """Event emitted when a LLM call starts"""
 
     type: str = "llm_call_started"
-    messages: Union[str, List[Dict[str, str]]]
+    messages: Union[str, List[Dict[str, Any]]]
     tools: Optional[List[dict]] = None
     callbacks: Optional[List[Any]] = None
     available_functions: Optional[Dict[str, Any]] = None

tests/test_multimodal_validation.py

@@ -0,0 +1,46 @@
+import os
+
+import pytest
+
+from crewai import LLM, Agent, Crew, Task
+
+
+@pytest.mark.skip(reason="Only run manually with valid API keys")
+def test_multimodal_agent_with_image_url():
+    """
+    Test that a multimodal agent can process images without validation errors.
+    This test reproduces the scenario from issue #2475.
+    """
+    OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+    if not OPENAI_API_KEY:
+        pytest.skip("OPENAI_API_KEY environment variable not set")
+
+    llm = LLM(
+        model="openai/gpt-4o",  # model with vision capabilities
+        api_key=OPENAI_API_KEY,
+        temperature=0.7
+    )
+
+    expert_analyst = Agent(
+        role="Visual Quality Inspector",
+        goal="Perform detailed quality analysis of product images",
+        backstory="Senior quality control expert with expertise in visual inspection",
+        llm=llm,
+        verbose=True,
+        allow_delegation=False,
+        multimodal=True
+    )
+
+    inspection_task = Task(
+        description="""
+        Analyze the product image at https://www.us.maguireshoes.com/collections/spring-25/products/lucena-black-boot with focus on:
+        1. Quality of materials
+        2. Manufacturing defects
+        3. Compliance with standards
+        Provide a detailed report highlighting any issues found.
+        """,
+        expected_output="A detailed report highlighting any issues found",
+        agent=expert_analyst
+    )
+
+    crew = Crew(agents=[expert_analyst], tasks=[inspection_task])