fix: resolve mypy type errors across agent adapters and core modules

src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py

@@ -22,8 +22,10 @@ from crewai.utilities import Logger
 from crewai.utilities.converter import Converter
 
 try:
-    from langgraph.checkpoint.memory import MemorySaver
+    from langgraph.checkpoint.memory import (
-    from langgraph.prebuilt import create_react_agent
+        MemorySaver,  # type: ignore[import-not-found]
+    )
+    from langgraph.prebuilt import create_react_agent  # type: ignore[import-not-found]
 
     LANGGRAPH_AVAILABLE = True
 except ImportError:
@@ -55,7 +57,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
         llm: Any = None,
         max_iterations: int = 10,
         agent_config: Optional[dict[str, Any]] = None,
-        **kwargs,
+        **kwargs: Any,
     ):
         """Initialize the LangGraph agent adapter."""
         if not LANGGRAPH_AVAILABLE:
@@ -198,7 +200,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
             raise
 
     def create_agent_executor(
-        self, task=None, tools: Optional[list[BaseTool]] = None
+        self, task: Any = None, tools: Optional[list[BaseTool]] = None
     ) -> None:
         """Configure the LangGraph agent for execution."""
         self.configure_tools(tools)
@@ -222,6 +224,6 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
         """Convert output format if needed."""
         return Converter(llm=llm, text=text, model=model, instructions=instructions)
 
-    def configure_structured_output(self, task) -> None:
+    def configure_structured_output(self, task: Any) -> None:
         """Configure the structured output for LangGraph."""
         self._converter_adapter.configure_structured_output(task)

src/crewai/agents/agent_adapters/langgraph/structured_output_converter.py

@@ -1,4 +1,5 @@
 import json
+from typing import Any
 
 from crewai.agents.agent_adapters.base_converter_adapter import BaseConverterAdapter
 from crewai.utilities.converter import generate_model_description
@@ -7,14 +8,14 @@ from crewai.utilities.converter import generate_model_description
 class LangGraphConverterAdapter(BaseConverterAdapter):
     """Adapter for handling structured output conversion in LangGraph agents"""
 
-    def __init__(self, agent_adapter):
+    def __init__(self, agent_adapter: Any) -> None:
         """Initialize the converter adapter with a reference to the agent adapter"""
         self.agent_adapter = agent_adapter
-        self._output_format = None
+        self._output_format: str | None = None
         self._schema = None
         self._system_prompt_appendix = None
 
-    def configure_structured_output(self, task) -> None:
+    def configure_structured_output(self, task: Any) -> None:
         """Configure the structured output for LangGraph."""
         if not (task.output_json or task.output_pydantic):
             self._output_format = None
@@ -41,7 +42,7 @@ Important: Your final answer MUST be provided in the following structured format
 
 {self._schema}
 
-DO NOT include any markdown code blocks, backticks, or other formatting around your response. 
+DO NOT include any markdown code blocks, backticks, or other formatting around your response.
 The output should be raw JSON that exactly matches the specified schema.
 """
 

src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py

@@ -18,8 +18,8 @@ from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Logger
 
 try:
-    from agents import Agent as OpenAIAgent  # type: ignore
+    from agents import Agent as OpenAIAgent  # type: ignore[import-not-found]
-    from agents import Runner, enable_verbose_stdout_logging  # type: ignore
+    from agents import Runner, enable_verbose_stdout_logging
 
     from .openai_agent_tool_adapter import OpenAIAgentToolAdapter
 
@@ -40,13 +40,14 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
     step_callback: Any = Field(default=None)
     _tool_adapter: "OpenAIAgentToolAdapter" = PrivateAttr()
     _converter_adapter: OpenAIConverterAdapter = PrivateAttr()
+    agent_executor: Any = Field(default=None)
 
     def __init__(
         self,
         model: str = "gpt-4o-mini",
         tools: Optional[list[BaseTool]] = None,
-        agent_config: Optional[dict] = None,
+        agent_config: Optional[dict[str, Any]] = None,
-        **kwargs,
+        **kwargs: Any,
     ):
         if not OPENAI_AVAILABLE:
             raise ImportError(
@@ -109,6 +110,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
                     task=task,
                 ),
             )
+            assert hasattr(self, "agent_executor"), "agent_executor not initialized"
             result = self.agent_executor.run_sync(self._openai_agent, task_prompt)
             final_answer = self.handle_execution_result(result)
             crewai_event_bus.emit(
@@ -132,7 +134,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
             raise
 
     def create_agent_executor(
-        self, task=None, tools: Optional[list[BaseTool]] = None
+        self, task: Any = None, tools: Optional[list[BaseTool]] = None
     ) -> None:
         """
         Configure the OpenAI agent for execution.
@@ -171,7 +173,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
         tools = agent_tools.tools()
         return tools
 
-    def configure_structured_output(self, task) -> None:
+    def configure_structured_output(self, task: Any) -> None:
         """Configure the structured output for the specific agent implementation.
 
         Args:

src/crewai/agents/agent_adapters/openai_agents/structured_output_converter.py

@@ -1,5 +1,6 @@
 import json
 import re
+from typing import Any
 
 from crewai.agents.agent_adapters.base_converter_adapter import BaseConverterAdapter
 from crewai.utilities.converter import generate_model_description
@@ -19,14 +20,14 @@ class OpenAIConverterAdapter(BaseConverterAdapter):
         _output_model: The Pydantic model for the output
     """
 
-    def __init__(self, agent_adapter):
+    def __init__(self, agent_adapter: Any) -> None:
         """Initialize the converter adapter with a reference to the agent adapter"""
         self.agent_adapter = agent_adapter
         self._output_format = None
         self._schema = None
         self._output_model = None
 
-    def configure_structured_output(self, task) -> None:
+    def configure_structured_output(self, task: Any) -> None:
         """
         Configure the structured output for OpenAI agent based on task requirements.
 

src/crewai/crew.py

@@ -791,7 +791,12 @@ class Crew(FlowTrackable, BaseModel):
                 manager.tools = []
                 raise Exception("Manager agent should not have tools")
         else:
-            self.manager_llm = create_llm(self.manager_llm)
+            if self.manager_llm is None:
+                from crewai.utilities.llm_utils import create_default_llm
+
+                self.manager_llm = create_default_llm()
+            else:
+                self.manager_llm = create_llm(self.manager_llm)
             manager = Agent(
                 role=i18n.retrieve("hierarchical_manager_agent", "role"),
                 goal=i18n.retrieve("hierarchical_manager_agent", "goal"),

src/crewai/lite_agent.py

@@ -62,7 +62,7 @@ from crewai.utilities.agent_utils import (
 )
 from crewai.utilities.converter import generate_model_description
 from crewai.utilities.guardrail import process_guardrail
-from crewai.utilities.llm_utils import create_llm
+from crewai.utilities.llm_utils import create_default_llm, create_llm
 from crewai.utilities.printer import Printer
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
@@ -195,7 +195,10 @@ class LiteAgent(FlowTrackable, BaseModel):
     @model_validator(mode="after")
     def setup_llm(self) -> Self:
         """Set up the LLM and other components after initialization."""
-        self.llm = create_llm(self.llm)
+        if self.llm is None:
+            self.llm = create_default_llm()
+        else:
+            self.llm = create_llm(self.llm)
         if not isinstance(self.llm, BaseLLM):
             raise ValueError(
                 f"Expected LLM instance of type BaseLLM, got {type(self.llm).__name__}"