fix: Improve model name validation and fix syntax errors

- Fix docstring placement and type hints
- Add proper model name validation with clear error messages
- Organize tests into a class and add edge cases

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

src/crewai/llm.py

@@ -117,6 +117,39 @@ def suppress_warnings():
 
 
 class LLM:
+    """LLM class for handling model interactions.
+
+    Args:
+        model: The model identifier; should not start with 'models/'.
+              Examples: 'gemini/gemini-1.5-pro', 'anthropic/claude-3'
+        timeout: Optional timeout for model calls
+        temperature: Optional temperature parameter
+        max_tokens: Optional maximum tokens for completion
+        max_completion_tokens: Optional maximum completion tokens
+        logprobs: Optional log probabilities
+        top_p: Optional nucleus sampling parameter
+        n: Optional number of completions
+        stop: Optional stop sequences
+        presence_penalty: Optional presence penalty
+        frequency_penalty: Optional frequency penalty
+        logit_bias: Optional token biasing
+        user: Optional user identifier
+        response_format: Optional response format configuration
+        seed: Optional random seed
+        tools: Optional list of tools
+        tool_choice: Optional tool choice configuration
+        api_base: Optional API base URL
+        api_key: Optional API key
+        api_version: Optional API version
+        base_url: Optional base URL
+        top_logprobs: Optional top log probabilities
+        callbacks: Optional list of callbacks
+        reasoning_effort: Optional reasoning effort level
+
+    Raises:
+        ValueError: If the model name starts with 'models/' or is empty
+        TypeError: If model is not a string
+    """
     def __init__(
         self,
         model: str,
@@ -142,6 +175,20 @@ class LLM:
         reasoning_effort: Optional[Literal["none", "low", "medium", "high"]] = None,
         **kwargs,
     ):
+        # Constants for model name validation
+        INVALID_MODEL_PREFIX = "models/"
+        
+        # Validate model name
+        if not isinstance(model, str):
+            raise TypeError("Model name must be a string")
+        if not model:
+            raise ValueError("Model name cannot be empty")
+        if model.startswith(INVALID_MODEL_PREFIX):
+            raise ValueError(
+                f'Invalid model name "{model}": Model names should not start with "{INVALID_MODEL_PREFIX}". '
+                'Use the provider prefix instead (e.g., "gemini/model-name").'
+            )
+        
         self.model = model
         self.timeout = timeout
         self.temperature = temperature

tests/llm_test.py

@@ -252,6 +252,29 @@ def test_validate_call_params_no_response_format():
     llm._validate_call_params()
 
 
+class TestModelNameValidation:
+    """Tests for model name validation in LLM class."""
+    
+    def test_models_prefix_rejection(self):
+        """Test that model names with 'models/' prefix are rejected."""
+        with pytest.raises(ValueError, match="should not start with \"models/\""):
+            LLM(model="models/gemini/gemini-1.5-pro")
+
+    def test_valid_model_names(self):
+        """Test that valid model names are accepted."""
+        LLM(model="gemini/gemini-1.5-pro")
+        LLM(model="anthropic/claude-3-opus-20240229-v1:0")
+        LLM(model="openai/gpt-4")
+        LLM(model="openai/gpt-4 turbo")  # Space in model name should work
+        
+    def test_edge_cases(self):
+        """Test edge cases for model name validation."""
+        with pytest.raises(ValueError, match="cannot be empty"):
+            LLM(model="")  # Empty string
+        with pytest.raises(TypeError, match="must be a string"):
+            LLM(model=None)  # None value
+
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_o3_mini_reasoning_effort_high():
     llm = LLM(
@@ -324,13 +347,16 @@ def test_anthropic_model_detection():
         ("claude-instant", True),
         ("claude/v1", True),
         ("gpt-4", False),
-        ("", False),
         ("anthropomorphic", False),  # Should not match partial words
     ]
     
     for model, expected in models:
         llm = LLM(model=model)
-        assert llm.is_anthropic == expected, f"Failed for model: {model}"
+        assert llm._is_anthropic_model(model) == expected, f"Failed for model: {model}"
+    
+    # Test empty model name separately since it raises ValueError
+    with pytest.raises(ValueError, match="cannot be empty"):
+        LLM(model="")
 
 def test_anthropic_message_formatting(anthropic_llm, system_message, user_message):
     """Test Anthropic message formatting with fixtures."""