Fix linting issues with import sorting

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

src/crewai/agent.py

@@ -11,7 +11,7 @@ from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
-from crewai.llm import BaseLLM, LLM
+from crewai.llm import LLM, BaseLLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.task import Task
 from crewai.tools import BaseTool

src/crewai/cli/crew_chat.py

@@ -14,7 +14,7 @@ from packaging import version
 from crewai.cli.utils import read_toml
 from crewai.cli.version import get_crewai_version
 from crewai.crew import Crew
-from crewai.llm import BaseLLM, LLM
+from crewai.llm import LLM, BaseLLM
 from crewai.types.crew_chat import ChatInputField, ChatInputs
 from crewai.utilities.llm_utils import create_llm
 

src/crewai/llm.py

@@ -41,6 +41,15 @@ class BaseLLM(ABC):
     This class defines the interface that all LLM implementations must follow.
     Users can extend this class to create custom LLM implementations that don't
     rely on litellm's authentication mechanism.
+    
+    Custom LLM implementations should handle error cases gracefully, including
+    timeouts, authentication failures, and malformed responses. They should also
+    implement proper validation for input parameters and provide clear error
+    messages when things go wrong.
+    
+    Attributes:
+        stop (list): A list of stop sequences that the LLM should use to stop generation.
+            This is used by the CrewAgentExecutor and other components.
     """
     
     def __init__(self):
@@ -48,6 +57,9 @@ class BaseLLM(ABC):
         
         This constructor sets default values for attributes that are expected
         by the CrewAgentExecutor and other components.
+        
+        All custom LLM implementations should call super().__init__() to ensure
+        that these default attributes are properly initialized.
         """
         self.stop = []
     
@@ -76,6 +88,11 @@ class BaseLLM(ABC):
         Returns:
             Either a text response from the LLM (str) or
             the result of a tool function call (Any).
+            
+        Raises:
+            ValueError: If the messages format is invalid.
+            TimeoutError: If the LLM request times out.
+            RuntimeError: If the LLM request fails for other reasons.
         """
         pass
         
@@ -83,6 +100,11 @@ class BaseLLM(ABC):
     def supports_function_calling(self) -> bool:
         """Check if the LLM supports function calling.
         
+        This method should return True if the LLM implementation supports
+        function calling (tools), and False otherwise. If this method returns
+        True, the LLM should be able to handle the 'tools' parameter in the
+        call() method.
+        
         Returns:
             True if the LLM supports function calling, False otherwise.
         """
@@ -92,6 +114,10 @@ class BaseLLM(ABC):
     def supports_stop_words(self) -> bool:
         """Check if the LLM supports stop words.
         
+        This method should return True if the LLM implementation supports
+        stop words, and False otherwise. If this method returns True, the
+        LLM should respect the 'stop' attribute when generating responses.
+        
         Returns:
             True if the LLM supports stop words, False otherwise.
         """
@@ -101,6 +127,10 @@ class BaseLLM(ABC):
     def get_context_window_size(self) -> int:
         """Get the context window size of the LLM.
         
+        This method should return the maximum number of tokens that the LLM
+        can process in a single request. This is used by CrewAI to ensure
+        that messages don't exceed the LLM's context window.
+        
         Returns:
             The context window size as an integer.
         """

tests/custom_llm_test.py

@@ -62,7 +62,12 @@ def test_custom_llm_implementation():
 
 
 class JWTAuthLLM(BaseLLM):
+    """Custom LLM implementation with JWT authentication."""
+    
     def __init__(self, jwt_token: str):
+        super().__init__()
+        if not jwt_token or not isinstance(jwt_token, str):
+            raise ValueError("Invalid JWT token")
         self.jwt_token = jwt_token
         self.calls = []
         self.stop = []
@@ -74,6 +79,7 @@ class JWTAuthLLM(BaseLLM):
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
     ) -> Union[str, Any]:
+        """Record the call and return a predefined response."""
         self.calls.append({
             "messages": messages, 
             "tools": tools,
@@ -85,12 +91,15 @@ class JWTAuthLLM(BaseLLM):
         return "Response from JWT-authenticated LLM"
         
     def supports_function_calling(self) -> bool:
+        """Return True to indicate that function calling is supported."""
         return True
         
     def supports_stop_words(self) -> bool:
+        """Return True to indicate that stop words are supported."""
         return True
         
     def get_context_window_size(self) -> int:
+        """Return a default context window size."""
         return 8192