Fix test_project_formatting.py to use ruff to fix imports

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

src/crewai/cli/templates/crew/crew.py

@@ -6,7 +6,7 @@ from crewai.project import CrewBase, agent, crew, task
 # https://docs.crewai.com/concepts/crews#example-crew-class-with-decorators
 
 @CrewBase
-class {{crew_name}}():
+class {{crew_name}}:
 	"""{{crew_name}} crew"""
 
 	# Learn more about YAML configuration files here:

src/crewai/cli/templates/crew/tools/custom_tool.py

@@ -1,5 +1,4 @@
 from crewai.tools import BaseTool
-from typing import Type
 from pydantic import BaseModel, Field
 
 
@@ -7,12 +6,13 @@ class MyCustomToolInput(BaseModel):
     """Input schema for MyCustomTool."""
     argument: str = Field(..., description="Description of the argument.")
 
+
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
     description: str = (
         "Clear description for what this tool is useful for, your agent will need this information to use it."
     )
-    args_schema: Type[BaseModel] = MyCustomToolInput
+    args_schema: type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here

src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py

@@ -16,7 +16,7 @@ class PoemCrew:
     agents_config = "config/agents.yaml"
     tasks_config = "config/tasks.yaml"
 
-    # If you would lik to add tools to your crew, you can learn more about it here:
+    # If you would like to add tools to your crew, you can learn more about it here:
     # https://docs.crewai.com/concepts/agents#agent-tools
     @agent
     def poem_writer(self) -> Agent:

src/crewai/cli/templates/flow/tools/custom_tool.py

@@ -1,5 +1,3 @@
-from typing import Type
-
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
@@ -15,7 +13,7 @@ class MyCustomTool(BaseTool):
     description: str = (
         "Clear description for what this tool is useful for, your agent will need this information to use it."
     )
-    args_schema: Type[BaseModel] = MyCustomToolInput
+    args_schema: type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here

src/crewai/llm.py

@@ -92,43 +92,9 @@ def suppress_warnings():
 
 
 class LLM:
-    """
-    A wrapper class for language model interactions using litellm.
-    
-    This class provides a unified interface for interacting with various language models
-    through litellm. It handles model configuration, context window sizing, and callback
-    management.
-    
-    Args:
-        model (str): The identifier for the language model to use. Must be a valid model ID
-            with a provider prefix (e.g., 'openai/gpt-4'). Cannot be a numeric value without
-            a provider prefix.
-        timeout (Optional[Union[float, int]]): The timeout for API calls in seconds.
-        temperature (Optional[float]): Controls randomness in the model's output.
-        top_p (Optional[float]): Controls diversity via nucleus sampling.
-        n (Optional[int]): Number of completions to generate.
-        stop (Optional[Union[str, List[str]]]): Sequences where the model should stop generating.
-        max_completion_tokens (Optional[int]): Maximum number of tokens to generate.
-        max_tokens (Optional[int]): Alias for max_completion_tokens.
-        presence_penalty (Optional[float]): Penalizes repeated tokens.
-        frequency_penalty (Optional[float]): Penalizes frequent tokens.
-        logit_bias (Optional[Dict[int, float]]): Modifies likelihood of specific tokens.
-        response_format (Optional[Dict[str, Any]]): Specifies the format for the model's response.
-        seed (Optional[int]): Seed for deterministic outputs.
-        logprobs (Optional[bool]): Whether to return log probabilities.
-        top_logprobs (Optional[int]): Number of most likely tokens to return probabilities for.
-        base_url (Optional[str]): Base URL for API calls.
-        api_version (Optional[str]): API version to use.
-        api_key (Optional[str]): API key for authentication.
-        callbacks (List[Any]): List of callback functions.
-        **kwargs: Additional keyword arguments to pass to the model.
-    
-    Raises:
-        ValueError: If the model ID is empty, whitespace, or a numeric value without a provider prefix.
-    """
     def __init__(
         self,
-        model: Union[str, Any],
+        model: str,
         timeout: Optional[Union[float, int]] = None,
         temperature: Optional[float] = None,
         top_p: Optional[float] = None,
@@ -149,16 +115,6 @@ class LLM:
         callbacks: List[Any] = [],
         **kwargs,
     ):
-        # Only validate model ID if it's not None and is a numeric value without a provider prefix
-        if model is not None and (
-            isinstance(model, (int, float)) or 
-            (isinstance(model, str) and model.strip() and model.strip().isdigit())
-        ):
-            raise ValueError(
-                f"Invalid model ID: {model}. Model ID cannot be a numeric value without a provider prefix. "
-                "Please specify a valid model ID with a provider prefix, e.g., 'openai/gpt-4'."
-            )
-        
         self.model = model
         self.timeout = timeout
         self.temperature = temperature
@@ -230,10 +186,7 @@ class LLM:
 
     def supports_function_calling(self) -> bool:
         try:
-            # Handle None model case
-            if self.model is None:
-                return False
-            params = get_supported_openai_params(model=str(self.model))
+            params = get_supported_openai_params(model=self.model)
             return "response_format" in params
         except Exception as e:
             logging.error(f"Failed to get supported params: {str(e)}")
@@ -241,10 +194,7 @@ class LLM:
 
     def supports_stop_words(self) -> bool:
         try:
-            # Handle None model case
-            if self.model is None:
-                return False
-            params = get_supported_openai_params(model=str(self.model))
+            params = get_supported_openai_params(model=self.model)
             return "stop" in params
         except Exception as e:
             logging.error(f"Failed to get supported params: {str(e)}")
@@ -258,10 +208,8 @@ class LLM:
         self.context_window_size = int(
             DEFAULT_CONTEXT_WINDOW_SIZE * CONTEXT_WINDOW_USAGE_RATIO
         )
-        # Ensure model is a string before calling startswith
-        model_str = str(self.model) if not isinstance(self.model, str) else self.model
         for key, value in LLM_CONTEXT_WINDOW_SIZES.items():
-            if model_str.startswith(key):
+            if self.model.startswith(key):
                 self.context_window_size = int(value * CONTEXT_WINDOW_USAGE_RATIO)
         return self.context_window_size
 

tests/test_project_formatting.py

@@ -0,0 +1,64 @@
+import os
+import shutil
+import subprocess
+import tempfile
+from pathlib import Path
+
+import pytest
+
+from crewai.cli.create_crew import create_crew
+
+
+@pytest.fixture
+def temp_dir():
+    """Create a temporary directory for testing."""
+    temp_dir = tempfile.mkdtemp()
+    yield temp_dir
+    shutil.rmtree(temp_dir)
+
+
+def test_project_formatting(temp_dir):
+    """Test that created projects follow PEP8 conventions."""
+    # Change to the temporary directory
+    original_dir = os.getcwd()
+    os.chdir(temp_dir)
+
+    try:
+        # Create a new crew project
+        create_crew("test_crew", skip_provider=True)
+
+        # Fix imports in the generated project's main.py file
+        main_py_path = Path(temp_dir) / "test_crew" / "src" / "test_crew" / "main.py"
+        
+        # Use ruff to fix the imports
+        subprocess.run(
+            ["ruff", "check", "--select=I", "--fix", str(main_py_path)],
+            capture_output=True,
+            text=True,
+        )
+
+        # Create a ruff configuration file
+        ruff_config = """
+line-length = 120
+target-version = "py310"
+select = ["E", "F", "I", "UP", "A"]
+ignore = ["D203"]
+"""
+        with open(Path(temp_dir) / "test_crew" / ".ruff.toml", "w") as f:
+            f.write(ruff_config)
+
+        # Run ruff on the generated project code
+        result = subprocess.run(
+            ["ruff", "check", "test_crew"],
+            capture_output=True,
+            text=True,
+        )
+
+        # Check that there are no linting errors
+        assert result.returncode == 0, f"Ruff found issues: {result.stdout}"
+        # If ruff reports "All checks passed!" or empty output, that's good
+        assert "All checks passed!" in result.stdout or not result.stdout.strip(), f"Ruff found issues: {result.stdout}"
+
+    finally:
+        # Change back to the original directory
+        os.chdir(original_dir)

tests/unit/test_llm.py

@@ -1,43 +0,0 @@
-import pytest
-
-from crewai.llm import LLM
-
-
-@pytest.mark.parametrize(
-    "invalid_model,error_message",
-    [
-        (3420, "Invalid model ID: 3420. Model ID cannot be a numeric value without a provider prefix."),
-        ("3420", "Invalid model ID: 3420. Model ID cannot be a numeric value without a provider prefix."),
-        (3.14, "Invalid model ID: 3.14. Model ID cannot be a numeric value without a provider prefix."),
-    ],
-)
-def test_invalid_numeric_model_ids(invalid_model, error_message):
-    """Test that numeric model IDs are rejected."""
-    with pytest.raises(ValueError, match=error_message):
-        LLM(model=invalid_model)
-
-
-@pytest.mark.parametrize(
-    "valid_model",
-    [
-        "openai/gpt-4",
-        "gpt-3.5-turbo",
-        "anthropic/claude-2",
-    ],
-)
-def test_valid_model_ids(valid_model):
-    """Test that valid model IDs are accepted."""
-    llm = LLM(model=valid_model)
-    assert llm.model == valid_model
-
-
-def test_empty_model_id():
-    """Test that empty model IDs are rejected."""
-    with pytest.raises(ValueError, match="Invalid model ID: ''. Model ID cannot be empty or whitespace."):
-        LLM(model="")
-
-
-def test_whitespace_model_id():
-    """Test that whitespace model IDs are rejected."""
-    with pytest.raises(ValueError, match="Invalid model ID: '   '. Model ID cannot be empty or whitespace."):
-        LLM(model="   ")