fix: resolve all mypy errors across crewai package

lib/crewai/src/crewai/agents/agent_adapters/base_converter_adapter.py

@@ -5,9 +5,12 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 import json
 import re
-from typing import TYPE_CHECKING, Any, Final, Literal
+from typing import TYPE_CHECKING, Final, Literal
 
-from crewai.utilities.pydantic_schema_utils import generate_model_description
+from crewai.utilities.pydantic_schema_utils import (
+    ModelDescription,
+    generate_model_description,
+)
 
 
 if TYPE_CHECKING:
@@ -41,7 +44,7 @@ class BaseConverterAdapter(ABC):
         """
         self.agent_adapter = agent_adapter
         self._output_format: Literal["json", "pydantic"] | None = None
-        self._schema: dict[str, Any] | None = None
+        self._schema: ModelDescription | None = None
 
     @abstractmethod
     def configure_structured_output(self, task: Task) -> None:
@@ -128,7 +131,7 @@ class BaseConverterAdapter(ABC):
     @staticmethod
     def _configure_format_from_task(
         task: Task,
-    ) -> tuple[Literal["json", "pydantic"] | None, dict[str, Any] | None]:
+    ) -> tuple[Literal["json", "pydantic"] | None, ModelDescription | None]:
         """Determine output format and schema from task requirements.
 
         This is a helper method that examines the task's output requirements

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

@@ -64,7 +64,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
         llm: Any = None,
         max_iterations: int = 10,
         agent_config: dict[str, Any] | None = None,
-        **kwargs,
+        **kwargs: Any,
     ) -> None:
         """Initialize the LangGraph agent adapter.
 

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -948,7 +948,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         )
         error_event_emitted = False
 
-        track_delegation_if_needed(func_name, args_dict, self.task)
+        track_delegation_if_needed(func_name, args_dict or {}, self.task)
 
         structured_tool: CrewStructuredTool | None = None
         if original_tool is not None:
@@ -965,7 +965,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         hook_blocked = False
         before_hook_context = ToolCallHookContext(
             tool_name=func_name,
-            tool_input=args_dict,
+            tool_input=args_dict or {},
             tool=structured_tool,  # type: ignore[arg-type]
             agent=self.agent,
             task=self.task,
@@ -991,7 +991,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
         elif not from_cache and func_name in available_functions:
             try:
-                raw_result = available_functions[func_name](**args_dict)
+                raw_result = available_functions[func_name](**(args_dict or {}))
 
                 if self.tools_handler and self.tools_handler.cache:
                     should_cache = True
@@ -1001,7 +1001,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         and callable(original_tool.cache_function)
                     ):
                         should_cache = original_tool.cache_function(
-                            args_dict, raw_result
+                            args_dict or {}, raw_result
                         )
                     if should_cache:
                         self.tools_handler.cache.add(
@@ -1030,7 +1030,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
         after_hook_context = ToolCallHookContext(
             tool_name=func_name,
-            tool_input=args_dict,
+            tool_input=args_dict or {},
             tool=structured_tool,  # type: ignore[arg-type]
             agent=self.agent,
             task=self.task,

lib/crewai/src/crewai/cli/config.py

@@ -77,7 +77,7 @@ CLI_SETTINGS_KEYS = [
 ]
 
 # Default values for CLI settings
-DEFAULT_CLI_SETTINGS = {
+DEFAULT_CLI_SETTINGS: dict[str, Any] = {
     "enterprise_base_url": DEFAULT_CREWAI_ENTERPRISE_URL,
     "oauth2_provider": CREWAI_ENTERPRISE_DEFAULT_OAUTH2_PROVIDER,
     "oauth2_audience": CREWAI_ENTERPRISE_DEFAULT_OAUTH2_AUDIENCE,

lib/crewai/src/crewai/cli/memory_tui.py

@@ -173,13 +173,13 @@ class MemoryTUI(App[None]):
         info = self._memory.info("/")
         tree.root.label = f"/ ({info.record_count} records)"
         tree.root.data = "/"
-        self._add_children(tree.root, "/", depth=0, max_depth=3)
+        self._add_scope_children(tree.root, "/", depth=0, max_depth=3)
         tree.root.expand()
         return tree
 
-    def _add_children(
+    def _add_scope_children(
         self,
-        parent_node: Tree.Node[str],
+        parent_node: Any,
         path: str,
         depth: int,
         max_depth: int,
@@ -191,7 +191,7 @@ class MemoryTUI(App[None]):
             child_info = self._memory.info(child)
             label = f"{child} ({child_info.record_count})"
             node = parent_node.add(label, data=child)
-            self._add_children(node, child, depth + 1, max_depth)
+            self._add_scope_children(node, child, depth + 1, max_depth)
 
     # -- Populating the OptionList -------------------------------------------
 

lib/crewai/src/crewai/cli/reset_memories_command.py

@@ -1,4 +1,5 @@
 import subprocess
+from typing import Any
 
 import click
 
@@ -6,7 +7,7 @@ from crewai.cli.utils import get_crews, get_flows
 from crewai.flow import Flow
 
 
-def _reset_flow_memory(flow: Flow) -> None:
+def _reset_flow_memory(flow: Flow[Any]) -> None:
     """Reset memory for a single flow instance.
 
     Handles Memory, MemoryScope (both have .reset()), and MemorySlice

lib/crewai/src/crewai/cli/update_crew.py

@@ -1,5 +1,6 @@
 import os
 import shutil
+from typing import Any
 
 import tomli_w
 
@@ -11,7 +12,7 @@ def update_crew() -> None:
     migrate_pyproject("pyproject.toml", "pyproject.toml")
 
 
-def migrate_pyproject(input_file, output_file):
+def migrate_pyproject(input_file: str, output_file: str) -> None:
     """
     Migrate the pyproject.toml to the new format.
 
@@ -23,8 +24,7 @@ def migrate_pyproject(input_file, output_file):
     # Read the input pyproject.toml
     pyproject_data = read_toml()
 
-    # Initialize the new project structure
+    new_pyproject: dict[str, Any] = {
-    new_pyproject = {
         "project": {},
         "build-system": {"requires": ["hatchling"], "build-backend": "hatchling.build"},
     }

lib/crewai/src/crewai/cli/utils.py

@@ -386,7 +386,7 @@ def fetch_crews(module_attr: Any) -> list[Crew]:
     return crew_instances
 
 
-def get_flow_instance(module_attr: Any) -> Flow | None:
+def get_flow_instance(module_attr: Any) -> Flow[Any] | None:
     """Check if a module attribute is a user-defined Flow subclass and return an instance.
 
     Args:
@@ -413,7 +413,7 @@ _SKIP_DIRS = frozenset(
 )
 
 
-def get_flows(flow_path: str = "main.py") -> list[Flow]:
+def get_flows(flow_path: str = "main.py") -> list[Flow[Any]]:
     """Get the flow instances from project files.
 
     Walks the project directory looking for files matching ``flow_path``
@@ -427,7 +427,7 @@ def get_flows(flow_path: str = "main.py") -> list[Flow]:
     Returns:
         A list of discovered Flow instances.
     """
-    flow_instances: list[Flow] = []
+    flow_instances: list[Flow[Any]] = []
     try:
         current_dir = os.getcwd()
         if current_dir not in sys.path:

lib/crewai/src/crewai/crews/crew_output.py

@@ -45,14 +45,14 @@ class CrewOutput(BaseModel):
             output_dict.update(self.pydantic.model_dump())
         return output_dict
 
-    def __getitem__(self, key):
+    def __getitem__(self, key: str) -> Any:
         if self.pydantic and hasattr(self.pydantic, key):
             return getattr(self.pydantic, key)
         if self.json_dict and key in self.json_dict:
             return self.json_dict[key]
         raise KeyError(f"Key '{key}' not found in CrewOutput.")
 
-    def __str__(self):
+    def __str__(self) -> str:
         if self.pydantic:
             return str(self.pydantic)
         if self.json_dict:

lib/crewai/src/crewai/events/handler_graph.py

@@ -6,6 +6,7 @@ handlers execute in correct order while maximizing parallelism.
 
 from collections import defaultdict, deque
 from collections.abc import Sequence
+from typing import Any
 
 from crewai.events.depends import Depends
 from crewai.events.types.event_bus_types import ExecutionPlan, Handler
@@ -45,7 +46,7 @@ class HandlerGraph:
 
     def __init__(
         self,
-        handlers: dict[Handler, list[Depends]],
+        handlers: dict[Handler, list[Depends[Any]]],
     ) -> None:
         """Initialize the dependency graph.
 
@@ -103,7 +104,7 @@ class HandlerGraph:
 
 def build_execution_plan(
     handlers: Sequence[Handler],
-    dependencies: dict[Handler, list[Depends]],
+    dependencies: dict[Handler, list[Depends[Any]]],
 ) -> ExecutionPlan:
     """Build an execution plan from handlers and their dependencies.
 
@@ -118,7 +119,7 @@ def build_execution_plan(
     Raises:
         CircularDependencyError: If circular dependencies are detected
     """
-    handler_dict: dict[Handler, list[Depends]] = {
+    handler_dict: dict[Handler, list[Depends[Any]]] = {
         h: dependencies.get(h, []) for h in handlers
     }
 

lib/crewai/src/crewai/events/listeners/tracing/first_time_trace_handler.py

@@ -65,9 +65,9 @@ class FirstTimeTraceHandler:
             self._gracefully_fail(f"Error in trace handling: {e}")
             mark_first_execution_completed(user_consented=False)
 
-    def _initialize_backend_and_send_events(self):
+    def _initialize_backend_and_send_events(self) -> None:
         """Initialize backend batch and send collected events."""
-        if not self.batch_manager:
+        if not self.batch_manager or not self.batch_manager.trace_batch_id:
             return
 
         try:
@@ -115,12 +115,13 @@ class FirstTimeTraceHandler:
         except Exception as e:
             self._gracefully_fail(f"Backend initialization failed: {e}")
 
-    def _display_ephemeral_trace_link(self):
+    def _display_ephemeral_trace_link(self) -> None:
         """Display the ephemeral trace link to the user and automatically open browser."""
         console = Console()
 
         try:
-            webbrowser.open(self.ephemeral_url)
+            if self.ephemeral_url:
+                webbrowser.open(self.ephemeral_url)
         except Exception:  # noqa: S110
             pass
 
@@ -158,7 +159,7 @@ To disable tracing later, do any one of these:
         console.print(panel)
         console.print()
 
-    def _show_tracing_declined_message(self):
+    def _show_tracing_declined_message(self) -> None:
         """Show message when user declines tracing."""
         console = Console()
 
@@ -184,15 +185,18 @@ To enable tracing later, do any one of these:
         console.print(panel)
         console.print()
 
-    def _gracefully_fail(self, error_message: str):
+    def _gracefully_fail(self, error_message: str) -> None:
         """Handle errors gracefully without disrupting user experience."""
         console = Console()
         console.print(f"[yellow]Note: {error_message}[/yellow]")
 
         logger.debug(f"First-time trace error: {error_message}")
 
-    def _show_local_trace_message(self):
+    def _show_local_trace_message(self) -> None:
         """Show message when traces were collected locally but couldn't be uploaded."""
+        if self.batch_manager is None:
+            return
+
         console = Console()
 
         panel_content = f"""

lib/crewai/src/crewai/events/types/agent_events.py

@@ -6,6 +6,7 @@ from collections.abc import Sequence
 from typing import Any
 
 from pydantic import ConfigDict, model_validator
+from typing_extensions import Self
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.events.base_events import BaseEvent
@@ -25,16 +26,9 @@ class AgentExecutionStartedEvent(BaseEvent):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @model_validator(mode="after")
-    def set_fingerprint_data(self):
+    def set_fingerprint_data(self) -> Self:
         """Set fingerprint data from the agent if available."""
-        if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
+        _set_agent_fingerprint(self, self.agent)
-            self.source_fingerprint = self.agent.fingerprint.uuid_str
-            self.source_type = "agent"
-            if (
-                hasattr(self.agent.fingerprint, "metadata")
-                and self.agent.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.agent.fingerprint.metadata
         return self
 
 
@@ -49,16 +43,9 @@ class AgentExecutionCompletedEvent(BaseEvent):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @model_validator(mode="after")
-    def set_fingerprint_data(self):
+    def set_fingerprint_data(self) -> Self:
         """Set fingerprint data from the agent if available."""
-        if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
+        _set_agent_fingerprint(self, self.agent)
-            self.source_fingerprint = self.agent.fingerprint.uuid_str
-            self.source_type = "agent"
-            if (
-                hasattr(self.agent.fingerprint, "metadata")
-                and self.agent.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.agent.fingerprint.metadata
         return self
 
 
@@ -73,16 +60,9 @@ class AgentExecutionErrorEvent(BaseEvent):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @model_validator(mode="after")
-    def set_fingerprint_data(self):
+    def set_fingerprint_data(self) -> Self:
         """Set fingerprint data from the agent if available."""
-        if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
+        _set_agent_fingerprint(self, self.agent)
-            self.source_fingerprint = self.agent.fingerprint.uuid_str
-            self.source_type = "agent"
-            if (
-                hasattr(self.agent.fingerprint, "metadata")
-                and self.agent.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.agent.fingerprint.metadata
         return self
 
 
@@ -140,3 +120,13 @@ class AgentEvaluationFailedEvent(BaseEvent):
     iteration: int
     error: str
     type: str = "agent_evaluation_failed"
+
+
+def _set_agent_fingerprint(event: BaseEvent, agent: BaseAgent) -> None:
+    """Set fingerprint data on an event from an agent object."""
+    fp = agent.security_config.fingerprint
+    if fp is not None:
+        event.source_fingerprint = fp.uuid_str
+        event.source_type = "agent"
+        if fp.metadata:
+            event.fingerprint_metadata = fp.metadata

lib/crewai/src/crewai/events/types/crew_events.py

@@ -15,21 +15,18 @@ class CrewBaseEvent(BaseEvent):
     crew_name: str | None
     crew: Crew | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
-        self.set_crew_fingerprint()
+        self._set_crew_fingerprint()
 
-    def set_crew_fingerprint(self) -> None:
+    def _set_crew_fingerprint(self) -> None:
-        if self.crew and hasattr(self.crew, "fingerprint") and self.crew.fingerprint:
+        if self.crew is not None and self.crew.fingerprint:
             self.source_fingerprint = self.crew.fingerprint.uuid_str
             self.source_type = "crew"
-            if (
+            if self.crew.fingerprint.metadata:
-                hasattr(self.crew.fingerprint, "metadata")
-                and self.crew.fingerprint.metadata
-            ):
                 self.fingerprint_metadata = self.crew.fingerprint.metadata
 
-    def to_json(self, exclude: set[str] | None = None):
+    def to_json(self, exclude: set[str] | None = None) -> Any:
         if exclude is None:
             exclude = set()
         exclude.add("crew")

lib/crewai/src/crewai/events/types/knowledge_events.py

@@ -11,7 +11,7 @@ class KnowledgeEventBase(BaseEvent):
     agent_role: str | None = None
     agent_id: str | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
         self._set_agent_params(data)
         self._set_task_params(data)

lib/crewai/src/crewai/events/types/llm_guardrail_events.py

@@ -13,7 +13,7 @@ class LLMGuardrailBaseEvent(BaseEvent):
     agent_role: str | None = None
     agent_id: str | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
         self._set_agent_params(data)
         self._set_task_params(data)
@@ -28,10 +28,10 @@ class LLMGuardrailStartedEvent(LLMGuardrailBaseEvent):
     """
 
     type: str = "llm_guardrail_started"
-    guardrail: str | Callable
+    guardrail: str | Callable[..., Any]
     retry_count: int
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         from crewai.tasks.hallucination_guardrail import HallucinationGuardrail
         from crewai.tasks.llm_guardrail import LLMGuardrail
 
@@ -39,7 +39,7 @@ class LLMGuardrailStartedEvent(LLMGuardrailBaseEvent):
 
         if isinstance(self.guardrail, (LLMGuardrail, HallucinationGuardrail)):
             self.guardrail = self.guardrail.description.strip()
-        elif isinstance(self.guardrail, Callable):
+        elif callable(self.guardrail):
             self.guardrail = getsource(self.guardrail).strip()
 
 

lib/crewai/src/crewai/events/types/mcp_events.py

@@ -15,7 +15,7 @@ class MCPEvent(BaseEvent):
     from_agent: Any | None = None
     from_task: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
         self._set_agent_params(data)
         self._set_task_params(data)

lib/crewai/src/crewai/events/types/reasoning_events.py

@@ -15,7 +15,7 @@ class ReasoningEvent(BaseEvent):
     agent_id: str | None = None
     from_agent: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
         self._set_task_params(data)
         self._set_agent_params(data)

lib/crewai/src/crewai/events/types/task_events.py

@@ -4,6 +4,15 @@ from crewai.events.base_events import BaseEvent
 from crewai.tasks.task_output import TaskOutput
 
 
+def _set_task_fingerprint(event: BaseEvent, task: Any) -> None:
+    """Set fingerprint data on an event from a task object."""
+    if task is not None and task.fingerprint:
+        event.source_fingerprint = task.fingerprint.uuid_str
+        event.source_type = "task"
+        if task.fingerprint.metadata:
+            event.fingerprint_metadata = task.fingerprint.metadata
+
+
 class TaskStartedEvent(BaseEvent):
     """Event emitted when a task starts"""
 
@@ -11,17 +20,9 @@ class TaskStartedEvent(BaseEvent):
     context: str | None
     task: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
-        # Set fingerprint data from the task
+        _set_task_fingerprint(self, self.task)
-        if hasattr(self.task, "fingerprint") and self.task.fingerprint:
-            self.source_fingerprint = self.task.fingerprint.uuid_str
-            self.source_type = "task"
-            if (
-                hasattr(self.task.fingerprint, "metadata")
-                and self.task.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.task.fingerprint.metadata
 
 
 class TaskCompletedEvent(BaseEvent):
@@ -31,17 +32,9 @@ class TaskCompletedEvent(BaseEvent):
     type: str = "task_completed"
     task: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
-        # Set fingerprint data from the task
+        _set_task_fingerprint(self, self.task)
-        if hasattr(self.task, "fingerprint") and self.task.fingerprint:
-            self.source_fingerprint = self.task.fingerprint.uuid_str
-            self.source_type = "task"
-            if (
-                hasattr(self.task.fingerprint, "metadata")
-                and self.task.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.task.fingerprint.metadata
 
 
 class TaskFailedEvent(BaseEvent):
@@ -51,17 +44,9 @@ class TaskFailedEvent(BaseEvent):
     type: str = "task_failed"
     task: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
-        # Set fingerprint data from the task
+        _set_task_fingerprint(self, self.task)
-        if hasattr(self.task, "fingerprint") and self.task.fingerprint:
-            self.source_fingerprint = self.task.fingerprint.uuid_str
-            self.source_type = "task"
-            if (
-                hasattr(self.task.fingerprint, "metadata")
-                and self.task.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.task.fingerprint.metadata
 
 
 class TaskEvaluationEvent(BaseEvent):
@@ -71,14 +56,6 @@ class TaskEvaluationEvent(BaseEvent):
     evaluation_type: str
     task: Any | None = None
 
-    def __init__(self, **data):
+    def __init__(self, **data: Any) -> None:
         super().__init__(**data)
-        # Set fingerprint data from the task
+        _set_task_fingerprint(self, self.task)
-        if hasattr(self.task, "fingerprint") and self.task.fingerprint:
-            self.source_fingerprint = self.task.fingerprint.uuid_str
-            self.source_type = "task"
-            if (
-                hasattr(self.task.fingerprint, "metadata")
-                and self.task.fingerprint.metadata
-            ):
-                self.fingerprint_metadata = self.task.fingerprint.metadata

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -8,7 +8,7 @@ from datetime import datetime
 import inspect
 import json
 import threading
-from typing import TYPE_CHECKING, Any, Literal, cast
+from typing import TYPE_CHECKING, Any, Literal, TypeVar, cast
 from uuid import uuid4
 
 from pydantic import BaseModel, Field, GetCoreSchemaHandler
@@ -22,7 +22,11 @@ from crewai.agents.parser import (
     AgentFinish,
     OutputParserError,
 )
-from crewai.core.providers.human_input import get_provider
+from crewai.core.providers.human_input import (
+    AsyncExecutorContext,
+    ExecutorContext,
+    get_provider,
+)
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.listeners.tracing.utils import (
     is_tracing_enabled_in_context,
@@ -89,7 +93,7 @@ from crewai.utilities.planning_types import (
     TodoList,
 )
 from crewai.utilities.printer import Printer
-from crewai.utilities.step_execution_context import StepExecutionContext
+from crewai.utilities.step_execution_context import StepExecutionContext, StepResult
 from crewai.utilities.string_utils import sanitize_tool_name
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
 from crewai.utilities.training_handler import CrewTrainingHandler
@@ -105,6 +109,8 @@ if TYPE_CHECKING:
     from crewai.tools.tool_types import ToolResult
     from crewai.utilities.prompts import StandardPromptResult, SystemPromptResult
 
+_RouteT = TypeVar("_RouteT", bound=str)
+
 
 class AgentExecutorState(BaseModel):
     """Structured state for agent executor flow.
@@ -446,29 +452,29 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             step failures reliably trigger replanning rather than being
             silently ignored.
         """
-        config = getattr(self.agent, "planning_config", None)
+        config = self.agent.planning_config
-        if config is not None and hasattr(config, "reasoning_effort"):
+        if config is not None:
             return config.reasoning_effort
         return "medium"
 
     def _get_max_replans(self) -> int:
         """Get max replans from planning config or default to 3."""
-        config = getattr(self.agent, "planning_config", None)
+        config = self.agent.planning_config
-        if config is not None and hasattr(config, "max_replans"):
+        if config is not None:
             return config.max_replans
         return 3
 
     def _get_max_step_iterations(self) -> int:
         """Get max step iterations from planning config or default to 15."""
-        config = getattr(self.agent, "planning_config", None)
+        config = self.agent.planning_config
-        if config is not None and hasattr(config, "max_step_iterations"):
+        if config is not None:
             return config.max_step_iterations
         return 15
 
     def _get_step_timeout(self) -> int | None:
         """Get per-step timeout from planning config or default to None."""
-        config = getattr(self.agent, "planning_config", None)
+        config = self.agent.planning_config
-        if config is not None and hasattr(config, "step_timeout"):
+        if config is not None:
             return config.step_timeout
         return None
 
@@ -1130,9 +1136,9 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
         # Process results: store on todos and log, then observe each.
         # asyncio.gather preserves input order, so zip gives us the exact
         # todo ↔ result (or exception) mapping.
-        step_results: list[tuple[TodoItem, object]] = []
+        step_results: list[tuple[TodoItem, StepResult]] = []
         for todo, item in zip(ready, gathered, strict=True):
-            if isinstance(item, Exception):
+            if isinstance(item, BaseException):
                 error_msg = f"Error: {item!s}"
                 todo.result = error_msg
                 self.state.todos.mark_failed(todo.step_number, result=error_msg)
@@ -1143,31 +1149,34 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
                     )
             else:
                 _returned_todo, result = item
-                todo.result = result.result
+                step_result = cast(StepResult, result)
+                todo.result = step_result.result
 
                 self.state.execution_log.append(
                     {
                         "type": "step_execution",
                         "step_number": todo.step_number,
-                        "success": result.success,
+                        "success": step_result.success,
-                        "result_preview": result.result[:200] if result.result else "",
+                        "result_preview": step_result.result[:200]
-                        "error": result.error,
+                        if step_result.result
-                        "tool_calls": result.tool_calls_made,
+                        else "",
-                        "execution_time": result.execution_time,
+                        "error": step_result.error,
+                        "tool_calls": step_result.tool_calls_made,
+                        "execution_time": step_result.execution_time,
                     }
                 )
 
                 if self.agent.verbose:
-                    status = "success" if result.success else "failed"
+                    status = "success" if step_result.success else "failed"
                     self._printer.print(
                         content=(
                             f"[Execute] Step {todo.step_number} {status} "
-                            f"({result.execution_time:.1f}s, "
+                            f"({step_result.execution_time:.1f}s, "
-                            f"{len(result.tool_calls_made)} tool calls)"
+                            f"{len(step_result.tool_calls_made)} tool calls)"
                         ),
-                        color="green" if result.success else "red",
+                        color="green" if step_result.success else "red",
                     )
-                step_results.append((todo, result))
+                step_results.append((todo, step_result))
 
         # Observe each completed step sequentially (observation updates shared state)
         effort = self._get_reasoning_effort()
@@ -1431,8 +1440,8 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             raise
 
     def _route_finish_with_todos(
-        self, default_route: str
+        self, default_route: _RouteT
-    ) -> Literal["native_finished", "agent_finished", "todo_satisfied"]:
+    ) -> _RouteT | Literal["todo_satisfied"]:
         """Helper to route finish events, checking for pending todos first.
 
         If there are pending todos, route to todo_satisfied instead of the
@@ -1448,7 +1457,7 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             current_todo = self.state.todos.current_todo
             if current_todo:
                 return "todo_satisfied"
-        return default_route  # type: ignore[return-value]
+        return default_route
 
     @router(call_llm_and_parse)
     def route_by_answer_type(
@@ -2063,7 +2072,7 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
         elif not self.state.current_answer and self.state.messages:
             # For native tools, results are in the message history as 'tool' roles
             # We take the content of the most recent tool results
-            tool_results = []
+            tool_results: list[str] = []
             for msg in reversed(self.state.messages):
                 if msg.get("role") == "tool":
                     tool_results.insert(0, str(msg.get("content", "")))
@@ -3003,7 +3012,7 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             Final answer after feedback.
         """
         provider = get_provider()
-        return provider.handle_feedback(formatted_answer, self)
+        return provider.handle_feedback(formatted_answer, cast("ExecutorContext", self))
 
     async def _ahandle_human_feedback(
         self, formatted_answer: AgentFinish
@@ -3017,7 +3026,9 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             Final answer after feedback.
         """
         provider = get_provider()
-        return await provider.handle_feedback_async(formatted_answer, self)
+        return await provider.handle_feedback_async(
+            formatted_answer, cast("AsyncExecutorContext", self)
+        )
 
     def _is_training_mode(self) -> bool:
         """Check if training mode is active.

lib/crewai/src/crewai/experimental/evaluation/agent_evaluator.py

@@ -37,11 +37,11 @@ class ExecutionState:
     current_agent_id: str | None = None
     current_task_id: str | None = None
 
-    def __init__(self):
+    def __init__(self) -> None:
-        self.traces = {}
+        self.traces: dict[str, Any] = {}
-        self.iteration = 1
+        self.iteration: int = 1
-        self.iterations_results = {}
+        self.iterations_results: dict[int, dict[str, list[AgentEvaluationResult]]] = {}
-        self.agent_evaluators = {}
+        self.agent_evaluators: dict[str, Sequence[BaseEvaluator] | None] = {}
 
 
 class AgentEvaluator:
@@ -295,7 +295,7 @@ class AgentEvaluator:
 
     def emit_evaluation_started_event(
         self, agent_role: str, agent_id: str, task_id: str | None = None
-    ):
+    ) -> None:
         crewai_event_bus.emit(
             self,
             AgentEvaluationStartedEvent(
@@ -313,7 +313,7 @@ class AgentEvaluator:
         task_id: str | None = None,
         metric_category: MetricCategory | None = None,
         score: EvaluationScore | None = None,
-    ):
+    ) -> None:
         crewai_event_bus.emit(
             self,
             AgentEvaluationCompletedEvent(
@@ -328,7 +328,7 @@ class AgentEvaluator:
 
     def emit_evaluation_failed_event(
         self, agent_role: str, agent_id: str, error: str, task_id: str | None = None
-    ):
+    ) -> None:
         crewai_event_bus.emit(
             self,
             AgentEvaluationFailedEvent(
@@ -341,7 +341,9 @@ class AgentEvaluator:
         )
 
 
-def create_default_evaluator(agents: list[Agent] | list[BaseAgent], llm: None = None):
+def create_default_evaluator(
+    agents: list[Agent] | list[BaseAgent], llm: None = None
+) -> AgentEvaluator:
     from crewai.experimental.evaluation import (
         GoalAlignmentEvaluator,
         ParameterExtractionEvaluator,

lib/crewai/src/crewai/experimental/evaluation/base_evaluator.py

@@ -8,7 +8,7 @@ from typing import TYPE_CHECKING, Any
 from pydantic import BaseModel, Field
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.llm import BaseLLM
+from crewai.llms.base_llm import BaseLLM
 from crewai.task import Task
 from crewai.utilities.llm_utils import create_llm
 
@@ -25,7 +25,7 @@ class MetricCategory(enum.Enum):
     PARAMETER_EXTRACTION = "parameter_extraction"
     TOOL_INVOCATION = "tool_invocation"
 
-    def title(self):
+    def title(self) -> str:
         return self.value.replace("_", " ").title()
 
 

lib/crewai/src/crewai/experimental/evaluation/evaluation_display.py

@@ -18,12 +18,12 @@ from crewai.utilities.types import LLMMessage
 
 
 class EvaluationDisplayFormatter:
-    def __init__(self):
+    def __init__(self) -> None:
         self.console_formatter = ConsoleFormatter()
 
     def display_evaluation_with_feedback(
         self, iterations_results: dict[int, dict[str, list[Any]]]
-    ):
+    ) -> None:
         if not iterations_results:
             self.console_formatter.print(
                 "[yellow]No evaluation results to display[/yellow]"
@@ -103,7 +103,7 @@ class EvaluationDisplayFormatter:
     def display_summary_results(
         self,
         iterations_results: dict[int, dict[str, list[AgentEvaluationResult]]],
-    ):
+    ) -> None:
         if not iterations_results:
             self.console_formatter.print(
                 "[yellow]No evaluation results to display[/yellow]"

lib/crewai/src/crewai/experimental/evaluation/evaluation_listener.py

@@ -1,6 +1,11 @@
+"""Event listener for collecting execution traces for evaluation."""
+
+from __future__ import annotations
+
 from collections.abc import Sequence
 from datetime import datetime
 from typing import Any
+from uuid import UUID
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.events.base_event_listener import BaseEventListener
@@ -30,47 +35,63 @@ class EvaluationTraceCallback(BaseEventListener):
     retrievals, and final output - all for use in agent evaluation.
     """
 
-    _instance = None
+    _instance: EvaluationTraceCallback | None = None
+    _initialized: bool = False
 
-    def __new__(cls):
+    def __new__(cls) -> EvaluationTraceCallback:
+        """Create or return the singleton instance."""
         if cls._instance is None:
             cls._instance = super().__new__(cls)
             cls._instance._initialized = False
         return cls._instance
 
-    def __init__(self):
+    def __init__(self) -> None:
-        if not hasattr(self, "_initialized") or not self._initialized:
+        """Initialize the evaluation trace callback."""
+        if not self._initialized:
             super().__init__()
-            self.traces = {}
+            self.traces: dict[str, Any] = {}
-            self.current_agent_id = None
+            self.current_agent_id: UUID | str | None = None
-            self.current_task_id = None
+            self.current_task_id: UUID | str | None = None
+            self.current_llm_call: dict[str, Any] = {}
             self._initialized = True
 
-    def setup_listeners(self, event_bus: CrewAIEventsBus):
+    def setup_listeners(self, event_bus: CrewAIEventsBus) -> None:
+        """Set up event listeners on the event bus.
+
+        Args:
+            event_bus: The event bus to register listeners on.
+        """
+
         @event_bus.on(AgentExecutionStartedEvent)
-        def on_agent_started(source, event: AgentExecutionStartedEvent):
+        def on_agent_started(source: Any, event: AgentExecutionStartedEvent) -> None:
             self.on_agent_start(event.agent, event.task)
 
         @event_bus.on(LiteAgentExecutionStartedEvent)
-        def on_lite_agent_started(source, event: LiteAgentExecutionStartedEvent):
+        def on_lite_agent_started(
+            source: Any, event: LiteAgentExecutionStartedEvent
+        ) -> None:
             self.on_lite_agent_start(event.agent_info)
 
         @event_bus.on(AgentExecutionCompletedEvent)
-        def on_agent_completed(source, event: AgentExecutionCompletedEvent):
+        def on_agent_completed(
+            source: Any, event: AgentExecutionCompletedEvent
+        ) -> None:
             self.on_agent_finish(event.agent, event.task, event.output)
 
         @event_bus.on(LiteAgentExecutionCompletedEvent)
-        def on_lite_agent_completed(source, event: LiteAgentExecutionCompletedEvent):
+        def on_lite_agent_completed(
+            source: Any, event: LiteAgentExecutionCompletedEvent
+        ) -> None:
             self.on_lite_agent_finish(event.output)
 
         @event_bus.on(ToolUsageFinishedEvent)
-        def on_tool_completed(source, event: ToolUsageFinishedEvent):
+        def on_tool_completed(source: Any, event: ToolUsageFinishedEvent) -> None:
             self.on_tool_use(
                 event.tool_name, event.tool_args, event.output, success=True
             )
 
         @event_bus.on(ToolUsageErrorEvent)
-        def on_tool_usage_error(source, event: ToolUsageErrorEvent):
+        def on_tool_usage_error(source: Any, event: ToolUsageErrorEvent) -> None:
             self.on_tool_use(
                 event.tool_name,
                 event.tool_args,
@@ -80,7 +101,9 @@ class EvaluationTraceCallback(BaseEventListener):
             )
 
         @event_bus.on(ToolExecutionErrorEvent)
-        def on_tool_execution_error(source, event: ToolExecutionErrorEvent):
+        def on_tool_execution_error(
+            source: Any, event: ToolExecutionErrorEvent
+        ) -> None:
             self.on_tool_use(
                 event.tool_name,
                 event.tool_args,
@@ -90,7 +113,9 @@ class EvaluationTraceCallback(BaseEventListener):
             )
 
         @event_bus.on(ToolSelectionErrorEvent)
-        def on_tool_selection_error(source, event: ToolSelectionErrorEvent):
+        def on_tool_selection_error(
+            source: Any, event: ToolSelectionErrorEvent
+        ) -> None:
             self.on_tool_use(
                 event.tool_name,
                 event.tool_args,
@@ -100,7 +125,9 @@ class EvaluationTraceCallback(BaseEventListener):
             )
 
         @event_bus.on(ToolValidateInputErrorEvent)
-        def on_tool_validate_input_error(source, event: ToolValidateInputErrorEvent):
+        def on_tool_validate_input_error(
+            source: Any, event: ToolValidateInputErrorEvent
+        ) -> None:
             self.on_tool_use(
                 event.tool_name,
                 event.tool_args,
@@ -110,14 +137,19 @@ class EvaluationTraceCallback(BaseEventListener):
             )
 
         @event_bus.on(LLMCallStartedEvent)
-        def on_llm_call_started(source, event: LLMCallStartedEvent):
+        def on_llm_call_started(source: Any, event: LLMCallStartedEvent) -> None:
             self.on_llm_call_start(event.messages, event.tools)
 
         @event_bus.on(LLMCallCompletedEvent)
-        def on_llm_call_completed(source, event: LLMCallCompletedEvent):
+        def on_llm_call_completed(source: Any, event: LLMCallCompletedEvent) -> None:
             self.on_llm_call_end(event.messages, event.response)
 
-    def on_lite_agent_start(self, agent_info: dict[str, Any]):
+    def on_lite_agent_start(self, agent_info: dict[str, Any]) -> None:
+        """Handle a lite agent execution start event.
+
+        Args:
+            agent_info: Dictionary containing agent information.
+        """
         self.current_agent_id = agent_info["id"]
         self.current_task_id = "lite_task"
 
@@ -132,10 +164,22 @@ class EvaluationTraceCallback(BaseEventListener):
             final_output=None,
         )
 
-    def _init_trace(self, trace_key: str, **kwargs: Any):
+    def _init_trace(self, trace_key: str, **kwargs: Any) -> None:
+        """Initialize a trace entry.
+
+        Args:
+            trace_key: The key to store the trace under.
+            **kwargs: Trace metadata to store.
+        """
         self.traces[trace_key] = kwargs
 
-    def on_agent_start(self, agent: BaseAgent, task: Task):
+    def on_agent_start(self, agent: BaseAgent, task: Task) -> None:
+        """Handle an agent execution start event.
+
+        Args:
+            agent: The agent that started execution.
+            task: The task being executed.
+        """
         self.current_agent_id = agent.id
         self.current_task_id = task.id
 
@@ -150,7 +194,14 @@ class EvaluationTraceCallback(BaseEventListener):
             final_output=None,
         )
 
-    def on_agent_finish(self, agent: BaseAgent, task: Task, output: Any):
+    def on_agent_finish(self, agent: BaseAgent, task: Task, output: Any) -> None:
+        """Handle an agent execution completion event.
+
+        Args:
+            agent: The agent that finished execution.
+            task: The task that was executed.
+            output: The agent's output.
+        """
         trace_key = f"{agent.id}_{task.id}"
         if trace_key in self.traces:
             self.traces[trace_key]["final_output"] = output
@@ -158,11 +209,17 @@ class EvaluationTraceCallback(BaseEventListener):
 
         self._reset_current()
 
-    def _reset_current(self):
+    def _reset_current(self) -> None:
+        """Reset the current agent and task tracking state."""
         self.current_agent_id = None
         self.current_task_id = None
 
-    def on_lite_agent_finish(self, output: Any):
+    def on_lite_agent_finish(self, output: Any) -> None:
+        """Handle a lite agent execution completion event.
+
+        Args:
+            output: The agent's output.
+        """
         trace_key = f"{self.current_agent_id}_lite_task"
         if trace_key in self.traces:
             self.traces[trace_key]["final_output"] = output
@@ -177,13 +234,22 @@ class EvaluationTraceCallback(BaseEventListener):
         result: Any,
         success: bool = True,
         error_type: str | None = None,
-    ):
+    ) -> None:
+        """Record a tool usage event in the current trace.
+
+        Args:
+            tool_name: Name of the tool used.
+            tool_args: Arguments passed to the tool.
+            result: The tool's output or error message.
+            success: Whether the tool call succeeded.
+            error_type: Type of error if the call failed.
+        """
         if not self.current_agent_id or not self.current_task_id:
             return
 
         trace_key = f"{self.current_agent_id}_{self.current_task_id}"
         if trace_key in self.traces:
-            tool_use = {
+            tool_use: dict[str, Any] = {
                 "tool": tool_name,
                 "args": tool_args,
                 "result": result,
@@ -191,7 +257,6 @@ class EvaluationTraceCallback(BaseEventListener):
                 "timestamp": datetime.now(),
             }
 
-            # Add error information if applicable
             if not success and error_type:
                 tool_use["error"] = True
                 tool_use["error_type"] = error_type
@@ -202,7 +267,13 @@ class EvaluationTraceCallback(BaseEventListener):
         self,
         messages: str | Sequence[dict[str, Any]] | None,
         tools: Sequence[dict[str, Any]] | None = None,
-    ):
+    ) -> None:
+        """Record an LLM call start event.
+
+        Args:
+            messages: The messages sent to the LLM.
+            tools: Tool definitions provided to the LLM.
+        """
         if not self.current_agent_id or not self.current_task_id:
             return
 
@@ -220,7 +291,13 @@ class EvaluationTraceCallback(BaseEventListener):
 
     def on_llm_call_end(
         self, messages: str | list[dict[str, Any]] | None, response: Any
-    ):
+    ) -> None:
+        """Record an LLM call completion event.
+
+        Args:
+            messages: The messages from the LLM call.
+            response: The LLM response object.
+        """
         if not self.current_agent_id or not self.current_task_id:
             return
 
@@ -229,17 +306,18 @@ class EvaluationTraceCallback(BaseEventListener):
             return
 
         total_tokens = 0
-        if hasattr(response, "usage") and hasattr(response.usage, "total_tokens"):
+        usage = getattr(response, "usage", None)
-            total_tokens = response.usage.total_tokens
+        if usage is not None:
+            total_tokens = getattr(usage, "total_tokens", 0)
 
         current_time = datetime.now()
-        start_time = None
+        start_time = (
-        if hasattr(self, "current_llm_call") and self.current_llm_call:
+            self.current_llm_call.get("start_time") if self.current_llm_call else None
-            start_time = self.current_llm_call.get("start_time")
+        )
 
         if not start_time:
             start_time = current_time
-        llm_call = {
+        llm_call: dict[str, Any] = {
             "messages": messages,
             "response": response,
             "start_time": start_time,
@@ -248,16 +326,28 @@ class EvaluationTraceCallback(BaseEventListener):
         }
 
         self.traces[trace_key]["llm_calls"].append(llm_call)
-
+        self.current_llm_call = {}
-        if hasattr(self, "current_llm_call"):
-            self.current_llm_call = {}
 
     def get_trace(self, agent_id: str, task_id: str) -> dict[str, Any] | None:
+        """Retrieve a trace by agent and task ID.
+
+        Args:
+            agent_id: The agent's identifier.
+            task_id: The task's identifier.
+
+        Returns:
+            The trace dictionary, or None if not found.
+        """
         trace_key = f"{agent_id}_{task_id}"
         return self.traces.get(trace_key)
 
 
 def create_evaluation_callbacks() -> EvaluationTraceCallback:
+    """Create and register an evaluation trace callback on the event bus.
+
+    Returns:
+        The configured EvaluationTraceCallback instance.
+    """
     from crewai.events.event_bus import crewai_event_bus
 
     callback = EvaluationTraceCallback()

lib/crewai/src/crewai/experimental/evaluation/experiment/result_display.py

@@ -8,10 +8,10 @@ from crewai.experimental.evaluation.experiment.result import ExperimentResults
 
 
 class ExperimentResultsDisplay:
-    def __init__(self):
+    def __init__(self) -> None:
         self.console = Console()
 
-    def summary(self, experiment_results: ExperimentResults):
+    def summary(self, experiment_results: ExperimentResults) -> None:
         total = len(experiment_results.results)
         passed = sum(1 for r in experiment_results.results if r.passed)
 
@@ -28,7 +28,9 @@ class ExperimentResultsDisplay:
 
         self.console.print(table)
 
-    def comparison_summary(self, comparison: dict[str, Any], baseline_timestamp: str):
+    def comparison_summary(
+        self, comparison: dict[str, Any], baseline_timestamp: str
+    ) -> None:
         self.console.print(
             Panel(
                 f"[bold]Comparison with baseline run from {baseline_timestamp}[/bold]",

lib/crewai/src/crewai/experimental/evaluation/experiment/runner.py

@@ -6,7 +6,7 @@ from typing import TYPE_CHECKING, Any
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.experimental.evaluation import AgentEvaluator, create_default_evaluator
-from crewai.experimental.evaluation.evaluation_display import (
+from crewai.experimental.evaluation.base_evaluator import (
     AgentAggregatedEvaluationResult,
 )
 from crewai.experimental.evaluation.experiment.result import (

lib/crewai/src/crewai/experimental/evaluation/json_parser.py

@@ -7,7 +7,8 @@ from typing import Any
 
 def extract_json_from_llm_response(text: str) -> dict[str, Any]:
     try:
-        return json.loads(text)
+        result: dict[str, Any] = json.loads(text)
+        return result
     except json.JSONDecodeError:
         pass
 
@@ -24,7 +25,8 @@ def extract_json_from_llm_response(text: str) -> dict[str, Any]:
         matches = re.findall(pattern, text, re.IGNORECASE | re.DOTALL)
         for match in matches:
             try:
-                return json.loads(match.strip())
+                parsed: dict[str, Any] = json.loads(match.strip())
+                return parsed
             except json.JSONDecodeError:  # noqa: PERF203
                 continue
     raise ValueError("No valid JSON found in the response")

lib/crewai/src/crewai/experimental/evaluation/metrics/goal_metrics.py

@@ -68,7 +68,7 @@ Evaluate how well the agent's output aligns with the assigned task goal.
         ]
         if self.llm is None:
             raise ValueError("LLM must be initialized")
-        response = self.llm.call(prompt)  # type: ignore[arg-type]
+        response = self.llm.call(prompt)
 
         try:
             evaluation_data: dict[str, Any] = extract_json_from_llm_response(response)

lib/crewai/src/crewai/experimental/evaluation/metrics/reasoning_metrics.py

@@ -224,7 +224,9 @@ Identify any inefficient reasoning patterns and provide specific suggestions for
                 raw_response=response,
             )
 
-    def _detect_loops(self, llm_calls: list[dict]) -> tuple[bool, list[dict]]:
+    def _detect_loops(
+        self, llm_calls: list[dict[str, Any]]
+    ) -> tuple[bool, list[dict[str, Any]]]:
         loop_details = []
 
         messages = []
@@ -272,7 +274,9 @@ Identify any inefficient reasoning patterns and provide specific suggestions for
 
         return intersection / union if union > 0 else 0.0
 
-    def _analyze_reasoning_patterns(self, llm_calls: list[dict]) -> dict[str, Any]:
+    def _analyze_reasoning_patterns(
+        self, llm_calls: list[dict[str, Any]]
+    ) -> dict[str, Any]:
         call_lengths = []
         response_times = []
 
@@ -345,7 +349,7 @@ Identify any inefficient reasoning patterns and provide specific suggestions for
             max_possible_slope = max(values) - min(values)
             if max_possible_slope > 0:
                 normalized_slope = slope / max_possible_slope
-                return max(min(normalized_slope, 1.0), -1.0)
+                return float(max(min(normalized_slope, 1.0), -1.0))
             return 0.0
         except Exception:
             return 0.0
@@ -384,7 +388,7 @@ Identify any inefficient reasoning patterns and provide specific suggestions for
 
         return float(np.mean(indicators)) if indicators else 0.0
 
-    def _get_call_samples(self, llm_calls: list[dict]) -> str:
+    def _get_call_samples(self, llm_calls: list[dict[str, Any]]) -> str:
         samples = []
 
         if len(llm_calls) <= 6:

lib/crewai/src/crewai/flow/flow_serializer.py

@@ -299,15 +299,15 @@ def _extract_all_methods_from_condition(
         return []
     if isinstance(condition, dict):
         conditions_list = condition.get("conditions", [])
-        methods: list[str] = []
+        dict_methods: list[str] = []
         for sub_cond in conditions_list:
-            methods.extend(_extract_all_methods_from_condition(sub_cond))
+            dict_methods.extend(_extract_all_methods_from_condition(sub_cond))
-        return methods
+        return dict_methods
     if isinstance(condition, list):
-        methods = []
+        list_methods: list[str] = []
         for item in condition:
-            methods.extend(_extract_all_methods_from_condition(item))
+            list_methods.extend(_extract_all_methods_from_condition(item))
-        return methods
+        return list_methods
     return []
 
 
@@ -476,7 +476,8 @@ def _detect_flow_inputs(flow_class: type) -> list[str]:
 
     # Check for inputs in __init__ signature beyond standard Flow params
     try:
-        init_sig = inspect.signature(flow_class.__init__)
+        init_method = flow_class.__init__  # type: ignore[misc]
+        init_sig = inspect.signature(init_method)
         standard_params = {
             "self",
             "persistence",

lib/crewai/src/crewai/flow/human_feedback.py

@@ -83,8 +83,11 @@ def _serialize_llm_for_context(llm: Any) -> dict[str, Any] | str | None:
     subclasses). Falls back to extracting the model string with provider
     prefix for unknown LLM types.
     """
-    if hasattr(llm, "to_config_dict"):
+    to_config: Callable[[], dict[str, Any]] | None = getattr(
-        return llm.to_config_dict()
+        llm, "to_config_dict", None
+    )
+    if to_config is not None:
+        return to_config()
 
     # Fallback for non-BaseLLM objects: just extract model + provider prefix
     model = getattr(llm, "model", None)
@@ -371,8 +374,13 @@ def human_feedback(
         ) -> Any:
             """Recall past HITL lessons and use LLM to pre-review the output."""
             try:
+                from crewai.memory.unified_memory import Memory
+
+                mem = flow_instance.memory
+                if not isinstance(mem, Memory):
+                    return method_output
                 query = f"human feedback lessons for {func.__name__}: {method_output!s}"
-                matches = flow_instance.memory.recall(query, source=learn_source)
+                matches = mem.recall(query, source=learn_source)
                 if not matches:
                     return method_output
 
@@ -404,6 +412,11 @@ def human_feedback(
         ) -> None:
             """Extract generalizable lessons from output + feedback, store in memory."""
             try:
+                from crewai.memory.unified_memory import Memory
+
+                mem = flow_instance.memory
+                if not isinstance(mem, Memory):
+                    return
                 llm_inst = _resolve_llm_instance()
                 prompt = _get_hitl_prompt("hitl_distill_user").format(
                     method_name=func.__name__,
@@ -435,7 +448,7 @@ def human_feedback(
                         ]
 
                 if lessons:
-                    flow_instance.memory.remember_many(lessons, source=learn_source)
+                    mem.remember_many(lessons, source=learn_source)
             except Exception:  # noqa: S110
                 pass  # non-critical: don't fail the flow because lesson storage failed
 

lib/crewai/src/crewai/hooks/decorators.py

@@ -122,7 +122,7 @@ def before_llm_call(
     """
     from crewai.hooks.llm_hooks import register_before_llm_call_hook
 
-    return _create_hook_decorator(  # type: ignore[return-value]
+    return _create_hook_decorator(  # type: ignore[no-any-return]
         hook_type="llm",
         register_function=register_before_llm_call_hook,
         marker_attribute="is_before_llm_call_hook",
@@ -176,7 +176,7 @@ def after_llm_call(
     """
     from crewai.hooks.llm_hooks import register_after_llm_call_hook
 
-    return _create_hook_decorator(  # type: ignore[return-value]
+    return _create_hook_decorator(  # type: ignore[no-any-return]
         hook_type="llm",
         register_function=register_after_llm_call_hook,
         marker_attribute="is_after_llm_call_hook",
@@ -237,7 +237,7 @@ def before_tool_call(
     """
     from crewai.hooks.tool_hooks import register_before_tool_call_hook
 
-    return _create_hook_decorator(  # type: ignore[return-value]
+    return _create_hook_decorator(  # type: ignore[no-any-return]
         hook_type="tool",
         register_function=register_before_tool_call_hook,
         marker_attribute="is_before_tool_call_hook",
@@ -293,7 +293,7 @@ def after_tool_call(
     """
     from crewai.hooks.tool_hooks import register_after_tool_call_hook
 
-    return _create_hook_decorator(  # type: ignore[return-value]
+    return _create_hook_decorator(  # type: ignore[no-any-return]
         hook_type="tool",
         register_function=register_after_tool_call_hook,
         marker_attribute="is_after_tool_call_hook",

lib/crewai/src/crewai/knowledge/source/base_knowledge_source.py

@@ -13,7 +13,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
     chunk_size: int = 4000
     chunk_overlap: int = 200
     chunks: list[str] = Field(default_factory=list)
-    chunk_embeddings: list[np.ndarray] = Field(default_factory=list)
+    chunk_embeddings: list[np.ndarray[Any, np.dtype[Any]]] = Field(default_factory=list)
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
     storage: KnowledgeStorage | None = Field(default=None)
@@ -28,7 +28,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
     def add(self) -> None:
         """Process content, chunk it, compute embeddings, and save them."""
 
-    def get_embeddings(self) -> list[np.ndarray]:
+    def get_embeddings(self) -> list[np.ndarray[Any, np.dtype[Any]]]:
         """Return the list of embeddings for the chunks."""
         return self.chunk_embeddings
 

lib/crewai/src/crewai/llm.py

@@ -2369,8 +2369,8 @@ class LLM(BaseLLM):
                     cb.strip() for cb in failure_callbacks_str.split(",") if cb.strip()
                 ]
 
-                litellm.success_callback = success_callbacks
+                litellm.success_callback = success_callbacks  # type: ignore[assignment]
-                litellm.failure_callback = failure_callbacks
+                litellm.failure_callback = failure_callbacks  # type: ignore[assignment]
 
     def __copy__(self) -> LLM:
         """Create a shallow copy of the LLM instance."""

lib/crewai/src/crewai/llms/providers/anthropic/completion.py

@@ -222,6 +222,7 @@ class AnthropicCompletion(BaseLLM):
         self.previous_thinking_blocks: list[ThinkingBlock] = []
         self.response_format = response_format
         # Tool search config
+        self.tool_search: AnthropicToolSearchConfig | None
         if tool_search is True:
             self.tool_search = AnthropicToolSearchConfig()
         elif isinstance(tool_search, AnthropicToolSearchConfig):

lib/crewai/src/crewai/mcp/client.py

@@ -1,22 +1,21 @@
 """MCP client with session management for CrewAI agents."""
 
 import asyncio
-from collections.abc import Callable
+from collections.abc import Callable, Coroutine
 from contextlib import AsyncExitStack
 from datetime import datetime
 import logging
+import sys
 import time
-from typing import Any, NamedTuple
+from typing import Any, NamedTuple, TypeVar
 
 from typing_extensions import Self
 
 
-# BaseExceptionGroup is available in Python 3.11+
+if sys.version_info >= (3, 11):
-try:
     from builtins import BaseExceptionGroup
-except ImportError:
+else:
-    # Fallback for Python < 3.11 (shouldn't happen in practice)
+    from exceptiongroup import BaseExceptionGroup
-    BaseExceptionGroup = Exception
 
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.mcp_events import (
@@ -47,8 +46,10 @@ MCP_TOOL_EXECUTION_TIMEOUT = 30
 MCP_DISCOVERY_TIMEOUT = 30  # Increased for slow servers
 MCP_MAX_RETRIES = 3
 
+_T = TypeVar("_T")
+
 # Simple in-memory cache for MCP tool schemas (duration: 5 minutes)
-_mcp_schema_cache: dict[str, tuple[dict[str, Any], float]] = {}
+_mcp_schema_cache: dict[str, tuple[list[dict[str, Any]], float]] = {}
 _cache_ttl = 300  # 5 minutes
 
 
@@ -134,11 +135,7 @@ class MCPClient:
         else:
             server_name = "Unknown MCP Server"
             server_url = None
-            transport_type = (
+            transport_type = self.transport.transport_type.value
-                self.transport.transport_type.value
-                if hasattr(self.transport, "transport_type")
-                else None
-            )
 
         return server_name, server_url, transport_type
 
@@ -542,7 +539,7 @@ class MCPClient:
         Returns:
             Cleaned arguments ready for MCP server.
         """
-        cleaned = {}
+        cleaned: dict[str, Any] = {}
 
         for key, value in arguments.items():
             # Skip None values
@@ -686,9 +683,9 @@ class MCPClient:
 
     async def _retry_operation(
         self,
-        operation: Callable[[], Any],
+        operation: Callable[[], Coroutine[Any, Any, _T]],
         timeout: int | None = None,
-    ) -> Any:
+    ) -> _T:
         """Retry an operation with exponential backoff.
 
         Args:

lib/crewai/src/crewai/mcp/tool_resolver.py

@@ -23,6 +23,7 @@ from crewai.mcp.config import (
     MCPServerSSE,
     MCPServerStdio,
 )
+from crewai.mcp.transports.base import BaseTransport
 from crewai.mcp.transports.http import HTTPTransport
 from crewai.mcp.transports.sse import SSETransport
 from crewai.mcp.transports.stdio import StdioTransport
@@ -285,6 +286,7 @@ class MCPToolResolver:
         independent transport so that parallel tool executions never share
         state.
         """
+        transport: BaseTransport
         if isinstance(mcp_config, MCPServerStdio):
             transport = StdioTransport(
                 command=mcp_config.command,

lib/crewai/src/crewai/mcp/transports/base.py

@@ -2,11 +2,17 @@
 
 from abc import ABC, abstractmethod
 from enum import Enum
-from typing import Any, Protocol
+from typing import Any
 
+from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream
+from mcp.shared.message import SessionMessage
 from typing_extensions import Self
 
 
+MCPReadStream = MemoryObjectReceiveStream[SessionMessage | Exception]
+MCPWriteStream = MemoryObjectSendStream[SessionMessage]
+
+
 class TransportType(str, Enum):
     """MCP transport types."""
 
@@ -16,22 +22,6 @@ class TransportType(str, Enum):
     SSE = "sse"
 
 
-class ReadStream(Protocol):
-    """Protocol for read streams."""
-
-    async def read(self, n: int = -1) -> bytes:
-        """Read bytes from stream."""
-        ...
-
-
-class WriteStream(Protocol):
-    """Protocol for write streams."""
-
-    async def write(self, data: bytes) -> None:
-        """Write bytes to stream."""
-        ...
-
-
 class BaseTransport(ABC):
     """Base class for MCP transport implementations.
 
@@ -46,8 +36,8 @@ class BaseTransport(ABC):
         Args:
             **kwargs: Transport-specific configuration options.
         """
-        self._read_stream: ReadStream | None = None
+        self._read_stream: MCPReadStream | None = None
-        self._write_stream: WriteStream | None = None
+        self._write_stream: MCPWriteStream | None = None
         self._connected = False
 
     @property
@@ -62,14 +52,14 @@ class BaseTransport(ABC):
         return self._connected
 
     @property
-    def read_stream(self) -> ReadStream:
+    def read_stream(self) -> MCPReadStream:
         """Get the read stream."""
         if self._read_stream is None:
             raise RuntimeError("Transport not connected. Call connect() first.")
         return self._read_stream
 
     @property
-    def write_stream(self) -> WriteStream:
+    def write_stream(self) -> MCPWriteStream:
         """Get the write stream."""
         if self._write_stream is None:
             raise RuntimeError("Transport not connected. Call connect() first.")
@@ -107,7 +97,7 @@ class BaseTransport(ABC):
         """Async context manager exit."""
         ...
 
-    def _set_streams(self, read: ReadStream, write: WriteStream) -> None:
+    def _set_streams(self, read: MCPReadStream, write: MCPWriteStream) -> None:
         """Set the read and write streams.
 
         Args:

lib/crewai/src/crewai/mcp/transports/http.py

@@ -1,17 +1,16 @@
 """HTTP and Streamable HTTP transport for MCP servers."""
 
 import asyncio
+import sys
 from typing import Any
 
 from typing_extensions import Self
 
 
-# BaseExceptionGroup is available in Python 3.11+
+if sys.version_info >= (3, 11):
-try:
     from builtins import BaseExceptionGroup
-except ImportError:
+else:
-    # Fallback for Python < 3.11 (shouldn't happen in practice)
+    from exceptiongroup import BaseExceptionGroup
-    BaseExceptionGroup = Exception
 
 from crewai.mcp.transports.base import BaseTransport, TransportType
 

lib/crewai/src/crewai/mcp/transports/stdio.py

@@ -122,11 +122,14 @@ class StdioTransport(BaseTransport):
             if self._process is not None:
                 try:
                     self._process.terminate()
+                    loop = asyncio.get_running_loop()
                     try:
-                        await asyncio.wait_for(self._process.wait(), timeout=5.0)
+                        await asyncio.wait_for(
+                            loop.run_in_executor(None, self._process.wait), timeout=5.0
+                        )
                     except asyncio.TimeoutError:
                         self._process.kill()
-                        await self._process.wait()
+                        await loop.run_in_executor(None, self._process.wait)
                 # except ProcessLookupError:
                 #     pass
                 finally:

lib/crewai/src/crewai/rag/chromadb/client.py

@@ -52,7 +52,7 @@ class ChromaDBClient(BaseClient):
     def __init__(
         self,
         client: ChromaDBClientType,
-        embedding_function: ChromaEmbeddingFunction,
+        embedding_function: ChromaEmbeddingFunction,  # type: ignore[type-arg]
         default_limit: int = 5,
         default_score_threshold: float = 0.6,
         default_batch_size: int = 100,

lib/crewai/src/crewai/rag/chromadb/types.py

@@ -23,7 +23,7 @@ from crewai.rag.core.base_client import BaseCollectionParams, BaseCollectionSear
 ChromaDBClientType = ClientAPI | AsyncClientAPI
 
 
-class ChromaEmbeddingFunctionWrapper(ChromaEmbeddingFunction):
+class ChromaEmbeddingFunctionWrapper(ChromaEmbeddingFunction):  # type: ignore[type-arg]
     """Base class for ChromaDB EmbeddingFunction to work with Pydantic validation."""
 
     @classmethod
@@ -85,7 +85,7 @@ class ChromaDBCollectionCreateParams(BaseCollectionParams, total=False):
 
     configuration: CollectionConfigurationInterface
     metadata: CollectionMetadata
-    embedding_function: ChromaEmbeddingFunction
+    embedding_function: ChromaEmbeddingFunction  # type: ignore[type-arg]
     data_loader: DataLoader[Loadable]
     get_or_create: bool
 

lib/crewai/src/crewai/rag/core/base_embeddings_provider.py

@@ -8,7 +8,7 @@ from pydantic_settings import BaseSettings, SettingsConfigDict
 from crewai.rag.core.base_embeddings_callable import EmbeddingFunction
 
 
-T = TypeVar("T", bound=EmbeddingFunction)
+T = TypeVar("T", bound=EmbeddingFunction)  # type: ignore[type-arg]
 
 
 class BaseEmbeddingsProvider(BaseSettings, Generic[T]):

lib/crewai/src/crewai/rag/core/types.py

@@ -1,7 +1,7 @@
 """Core type definitions for RAG systems."""
 
 from collections.abc import Sequence
-from typing import TypeVar
+from typing import Any, TypeVar
 
 import numpy as np
 from numpy import floating, integer, number
@@ -16,7 +16,7 @@ Embedding = NDArray[np.int32 | np.float32]
 Embeddings = list[Embedding]
 
 Documents = list[str]
-Images = list[np.ndarray]
+Images = list[np.ndarray[Any, np.dtype[np.generic]]]
 Embeddable = Documents | Images
 
 ScalarType = TypeVar("ScalarType", bound=np.generic)

lib/crewai/src/crewai/rag/embeddings/providers/custom/types.py

@@ -9,7 +9,7 @@ from typing_extensions import Required, TypedDict
 class CustomProviderConfig(TypedDict, total=False):
     """Configuration for Custom provider."""
 
-    embedding_callable: type[EmbeddingFunction]
+    embedding_callable: type[EmbeddingFunction]  # type: ignore[type-arg]
 
 
 class CustomProviderSpec(TypedDict, total=False):

lib/crewai/src/crewai/rag/embeddings/providers/google/genai_vertex_embedding.py

@@ -85,7 +85,7 @@ class GoogleGenAIVertexEmbeddingFunction(EmbeddingFunction[Documents]):
                 - output_dimensionality: Optional output embedding dimension (new SDK only)
         """
         # Handle deprecated 'region' parameter (only if it has a value)
-        region_value = kwargs.pop("region", None)  # type: ignore[typeddict-item]
+        region_value = kwargs.pop("region", None)  # type: ignore[typeddict-item,unused-ignore]
         if region_value is not None:
             warnings.warn(
                 "The 'region' parameter is deprecated, use 'location' instead. "
@@ -94,7 +94,7 @@ class GoogleGenAIVertexEmbeddingFunction(EmbeddingFunction[Documents]):
                 stacklevel=2,
             )
             if "location" not in kwargs or kwargs.get("location") is None:
-                kwargs["location"] = region_value  # type: ignore[typeddict-unknown-key]
+                kwargs["location"] = region_value  # type: ignore[typeddict-unknown-key,unused-ignore]
 
         self._config = kwargs
         self._model_name = str(kwargs.get("model_name", "textembedding-gecko"))
@@ -123,8 +123,10 @@ class GoogleGenAIVertexEmbeddingFunction(EmbeddingFunction[Documents]):
         )
 
         try:
-            import vertexai
+            import vertexai  # type: ignore[import-not-found]
-            from vertexai.language_models import TextEmbeddingModel
+            from vertexai.language_models import (  # type: ignore[import-not-found]
+                TextEmbeddingModel,
+            )
         except ImportError as e:
             raise ImportError(
                 "vertexai is required for legacy embedding models (textembedding-gecko*). "

lib/crewai/src/crewai/rag/embeddings/providers/voyageai/embedding_callable.py

@@ -18,7 +18,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction[Documents]):
             **kwargs: Configuration parameters for VoyageAI.
         """
         try:
-            import voyageai  # type: ignore[import-not-found]
+            import voyageai
 
         except ImportError as e:
             raise ImportError(
@@ -26,7 +26,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction[Documents]):
                 "Install it with: uv add voyageai"
             ) from e
         self._config = kwargs
-        self._client = voyageai.Client(
+        self._client = voyageai.Client(  # type: ignore[attr-defined]
             api_key=kwargs["api_key"],
             max_retries=kwargs.get("max_retries", 0),
             timeout=kwargs.get("timeout"),

lib/crewai/src/crewai/rag/qdrant/client.py

@@ -311,8 +311,7 @@ class QdrantClient(BaseClient):
             points = []
             for doc in batch_docs:
                 if _is_async_embedding_function(self.embedding_function):
-                    async_fn = cast(AsyncEmbeddingFunction, self.embedding_function)
+                    embedding = await self.embedding_function(doc["content"])
-                    embedding = await async_fn(doc["content"])
                 else:
                     sync_fn = cast(EmbeddingFunction, self.embedding_function)
                     embedding = sync_fn(doc["content"])
@@ -412,8 +411,7 @@ class QdrantClient(BaseClient):
             raise ValueError(f"Collection '{collection_name}' does not exist")
 
         if _is_async_embedding_function(self.embedding_function):
-            async_fn = cast(AsyncEmbeddingFunction, self.embedding_function)
+            query_embedding = await self.embedding_function(query)
-            query_embedding = await async_fn(query)
         else:
             sync_fn = cast(EmbeddingFunction, self.embedding_function)
             query_embedding = sync_fn(query)

lib/crewai/src/crewai/rag/qdrant/types.py

@@ -7,10 +7,10 @@ import numpy as np
 from pydantic import GetCoreSchemaHandler
 from pydantic_core import CoreSchema, core_schema
 from qdrant_client import (
-    AsyncQdrantClient,  # type: ignore[import-not-found]
+    AsyncQdrantClient,
-    QdrantClient as SyncQdrantClient,  # type: ignore[import-not-found]
+    QdrantClient as SyncQdrantClient,
 )
-from qdrant_client.models import (  # type: ignore[import-not-found]
+from qdrant_client.models import (
     FieldCondition,
     Filter,
     HasIdCondition,

lib/crewai/src/crewai/rag/qdrant/utils.py

@@ -5,10 +5,10 @@ from typing import TypeGuard
 from uuid import uuid4
 
 from qdrant_client import (
-    AsyncQdrantClient,  # type: ignore[import-not-found]
+    AsyncQdrantClient,
-    QdrantClient as SyncQdrantClient,  # type: ignore[import-not-found]
+    QdrantClient as SyncQdrantClient,
 )
-from qdrant_client.models import (  # type: ignore[import-not-found]
+from qdrant_client.models import (
     FieldCondition,
     Filter,
     MatchValue,

lib/crewai/src/crewai/rag/storage/base_rag_storage.py

@@ -16,7 +16,7 @@ class BaseRAGStorage(ABC):
         self,
         type: str,
         allow_reset: bool = True,
-        embedder_config: ProviderSpec | BaseEmbeddingsProvider | None = None,
+        embedder_config: ProviderSpec | BaseEmbeddingsProvider[Any] | None = None,
         crew: Any = None,
     ):
         self.type = type

lib/crewai/src/crewai/task.py

@@ -580,7 +580,7 @@ class Task(BaseModel):
             tools = tools or self.tools or []
 
             self.processed_by_agents.add(agent.role)
-            crewai_event_bus.emit(self, TaskStartedEvent(context=context, task=self))  # type: ignore[no-untyped-call]
+            crewai_event_bus.emit(self, TaskStartedEvent(context=context, task=self))
             result = await agent.aexecute_task(
                 task=self,
                 context=context,
@@ -662,12 +662,12 @@ class Task(BaseModel):
                 self._save_file(content)
             crewai_event_bus.emit(
                 self,
-                TaskCompletedEvent(output=task_output, task=self),  # type: ignore[no-untyped-call]
+                TaskCompletedEvent(output=task_output, task=self),
             )
             return task_output
         except Exception as e:
             self.end_time = datetime.datetime.now()
-            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))  # type: ignore[no-untyped-call]
+            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))
             raise e  # Re-raise the exception after emitting the event
         finally:
             clear_task_files(self.id)
@@ -694,7 +694,7 @@ class Task(BaseModel):
             tools = tools or self.tools or []
 
             self.processed_by_agents.add(agent.role)
-            crewai_event_bus.emit(self, TaskStartedEvent(context=context, task=self))  # type: ignore[no-untyped-call]
+            crewai_event_bus.emit(self, TaskStartedEvent(context=context, task=self))
             result = agent.execute_task(
                 task=self,
                 context=context,
@@ -777,12 +777,12 @@ class Task(BaseModel):
                 self._save_file(content)
             crewai_event_bus.emit(
                 self,
-                TaskCompletedEvent(output=task_output, task=self),  # type: ignore[no-untyped-call]
+                TaskCompletedEvent(output=task_output, task=self),
             )
             return task_output
         except Exception as e:
             self.end_time = datetime.datetime.now()
-            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))  # type: ignore[no-untyped-call]
+            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))
             raise e  # Re-raise the exception after emitting the event
         finally:
             clear_task_files(self.id)

lib/crewai/src/crewai/tasks/conditional_task.py

@@ -32,8 +32,8 @@ class ConditionalTask(Task):
     def __init__(
         self,
         condition: Callable[[Any], bool] | None = None,
-        **kwargs,
+        **kwargs: Any,
-    ):
+    ) -> None:
         super().__init__(**kwargs)
         self.condition = condition
 

lib/crewai/src/crewai/tasks/task_output.py

@@ -1,5 +1,7 @@
 """Task output representation and formatting."""
 
+from __future__ import annotations
+
 import json
 from typing import Any
 
@@ -44,7 +46,7 @@ class TaskOutput(BaseModel):
     messages: list[LLMMessage] = Field(description="Messages of the task", default=[])
 
     @model_validator(mode="after")
-    def set_summary(self):
+    def set_summary(self) -> TaskOutput:
         """Set the summary field based on the description.
 
         Returns:

lib/crewai/src/crewai/tools/agent_tools/add_image_tool.py

@@ -1,3 +1,5 @@
+from typing import Any
+
 from pydantic import BaseModel, Field
 
 from crewai.tools.base_tool import BaseTool
@@ -27,8 +29,8 @@ class AddImageTool(BaseTool):
         self,
         image_url: str,
         action: str | None = None,
-        **kwargs,
+        **kwargs: Any,
-    ) -> dict:
+    ) -> dict[str, Any]:
         action = action or i18n.tools("add_image")["default_action"]  # type: ignore
         content = [
             {"type": "text", "text": action},

lib/crewai/src/crewai/tools/agent_tools/ask_question_tool.py

@@ -1,3 +1,5 @@
+from typing import Any
+
 from pydantic import BaseModel, Field
 
 from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
@@ -20,7 +22,7 @@ class AskQuestionTool(BaseAgentTool):
         question: str,
         context: str,
         coworker: str | None = None,
-        **kwargs,
+        **kwargs: Any,
     ) -> str:
         coworker = self._get_coworker(coworker, **kwargs)
         return self._execute(coworker, question, context)

lib/crewai/src/crewai/tools/agent_tools/delegate_work_tool.py

@@ -1,3 +1,5 @@
+from typing import Any
+
 from pydantic import BaseModel, Field
 
 from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
@@ -22,7 +24,7 @@ class DelegateWorkTool(BaseAgentTool):
         task: str,
         context: str,
         coworker: str | None = None,
-        **kwargs,
+        **kwargs: Any,
     ) -> str:
         coworker = self._get_coworker(coworker, **kwargs)
         return self._execute(coworker, task, context)

lib/crewai/src/crewai/tools/mcp_native_tool.py

@@ -70,7 +70,7 @@ class MCPNativeTool(BaseTool):
         """Get the server name."""
         return self._server_name
 
-    def _run(self, **kwargs) -> str:
+    def _run(self, **kwargs: Any) -> str:
         """Execute tool using the MCP client session.
 
         Args:
@@ -98,7 +98,7 @@ class MCPNativeTool(BaseTool):
                 f"Error executing MCP tool {self.original_tool_name}: {e!s}"
             ) from e
 
-    async def _run_async(self, **kwargs) -> str:
+    async def _run_async(self, **kwargs: Any) -> str:
         """Async implementation of tool execution.
 
         A fresh ``MCPClient`` is created for every invocation so that

lib/crewai/src/crewai/tools/mcp_tool_wrapper.py

@@ -1,6 +1,8 @@
 """MCP Tool Wrapper for on-demand MCP server connections."""
 
 import asyncio
+from collections.abc import Callable, Coroutine
+from typing import Any
 
 from crewai.tools import BaseTool
 
@@ -16,9 +18,9 @@ class MCPToolWrapper(BaseTool):
 
     def __init__(
         self,
-        mcp_server_params: dict,
+        mcp_server_params: dict[str, Any],
         tool_name: str,
-        tool_schema: dict,
+        tool_schema: dict[str, Any],
         server_name: str,
     ):
         """Initialize the MCP tool wrapper.
@@ -54,7 +56,7 @@ class MCPToolWrapper(BaseTool):
         self._server_name = server_name
 
     @property
-    def mcp_server_params(self) -> dict:
+    def mcp_server_params(self) -> dict[str, Any]:
         """Get the MCP server parameters."""
         return self._mcp_server_params
 
@@ -68,7 +70,7 @@ class MCPToolWrapper(BaseTool):
         """Get the server name."""
         return self._server_name
 
-    def _run(self, **kwargs) -> str:
+    def _run(self, **kwargs: Any) -> str:
         """Connect to MCP server and execute tool.
 
         Args:
@@ -84,13 +86,15 @@ class MCPToolWrapper(BaseTool):
         except Exception as e:
             return f"Error executing MCP tool {self.original_tool_name}: {e!s}"
 
-    async def _run_async(self, **kwargs) -> str:
+    async def _run_async(self, **kwargs: Any) -> str:
         """Async implementation of MCP tool execution with timeouts and retry logic."""
         return await self._retry_with_exponential_backoff(
             self._execute_tool_with_timeout, **kwargs
         )
 
-    async def _retry_with_exponential_backoff(self, operation_func, **kwargs) -> str:
+    async def _retry_with_exponential_backoff(
+        self, operation_func: Callable[..., Coroutine[Any, Any, str]], **kwargs: Any
+    ) -> str:
         """Retry operation with exponential backoff, avoiding try-except in loop for performance."""
         last_error = None
 
@@ -119,7 +123,7 @@ class MCPToolWrapper(BaseTool):
         )
 
     async def _execute_single_attempt(
-        self, operation_func, **kwargs
+        self, operation_func: Callable[..., Coroutine[Any, Any, str]], **kwargs: Any
     ) -> tuple[str | None, str, bool]:
         """Execute single operation attempt and return (result, error_message, should_retry)."""
         try:
@@ -158,22 +162,23 @@ class MCPToolWrapper(BaseTool):
                 return None, f"Server response parsing error: {e!s}", True
             return None, f"MCP execution error: {e!s}", False
 
-    async def _execute_tool_with_timeout(self, **kwargs) -> str:
+    async def _execute_tool_with_timeout(self, **kwargs: Any) -> str:
         """Execute tool with timeout wrapper."""
         return await asyncio.wait_for(
             self._execute_tool(**kwargs), timeout=MCP_TOOL_EXECUTION_TIMEOUT
         )
 
-    async def _execute_tool(self, **kwargs) -> str:
+    async def _execute_tool(self, **kwargs: Any) -> str:
         """Execute the actual MCP tool call."""
         from mcp import ClientSession
         from mcp.client.streamable_http import streamablehttp_client
+        from mcp.types import TextContent
 
         server_url = self.mcp_server_params["url"]
 
         try:
-            # Wrap entire operation with single timeout
+
-            async def _do_mcp_call():
+            async def _do_mcp_call() -> str:
                 async with streamablehttp_client(
                     server_url, terminate_on_close=True
                 ) as (read, write, _):
@@ -183,17 +188,11 @@ class MCPToolWrapper(BaseTool):
                             self.original_tool_name, kwargs
                         )
 
-                        # Extract the result content
+                        if result.content:
-                        if hasattr(result, "content") and result.content:
+                            content_item = result.content[0]
-                            if (
+                            if isinstance(content_item, TextContent):
-                                isinstance(result.content, list)
+                                return content_item.text
-                                and len(result.content) > 0
+                            return str(content_item)
-                            ):
-                                content_item = result.content[0]
-                                if hasattr(content_item, "text"):
-                                    return str(content_item.text)
-                                return str(content_item)
-                            return str(result.content)
                         return str(result)
 
             return await asyncio.wait_for(
@@ -203,7 +202,7 @@ class MCPToolWrapper(BaseTool):
         except asyncio.CancelledError as e:
             raise asyncio.TimeoutError("MCP operation was cancelled") from e
         except Exception as e:
-            if hasattr(e, "__cause__") and e.__cause__:
+            if e.__cause__ is not None:
                 raise asyncio.TimeoutError(
                     f"MCP connection error: {e.__cause__}"
                 ) from e.__cause__

lib/crewai/src/crewai/utilities/evaluators/task_evaluator.py

@@ -81,7 +81,7 @@ class TaskEvaluator:
         """
         crewai_event_bus.emit(
             self,
-            TaskEvaluationEvent(evaluation_type="task_evaluation", task=task),  # type: ignore[no-untyped-call]
+            TaskEvaluationEvent(evaluation_type="task_evaluation", task=task),
         )
         evaluation_query = (
             f"Assess the quality of the task completed based on the description, expected output, and actual results.\n\n"
@@ -129,7 +129,7 @@ class TaskEvaluator:
         """
         crewai_event_bus.emit(
             self,
-            TaskEvaluationEvent(evaluation_type="training_data_evaluation"),  # type: ignore[no-untyped-call]
+            TaskEvaluationEvent(evaluation_type="training_data_evaluation"),
         )
 
         output_training_data = training_data[agent_id]

lib/crewai/src/crewai/utilities/file_store.py

@@ -12,16 +12,16 @@ from uuid import UUID
 
 
 if TYPE_CHECKING:
-    from aiocache import Cache
+    from aiocache import Cache  # type: ignore[import-untyped]
     from crewai_files import FileInput
 
 logger = logging.getLogger(__name__)
 
-_file_store: Cache | None = None
+_file_store: Cache | None = None  # type: ignore[no-any-unimported]
 
 try:
     from aiocache import Cache
-    from aiocache.serializers import PickleSerializer
+    from aiocache.serializers import PickleSerializer  # type: ignore[import-untyped]
 
     _file_store = Cache(Cache.MEMORY, serializer=PickleSerializer())
 except ImportError:

lib/crewai/src/crewai/utilities/guardrail.py

@@ -39,7 +39,7 @@ class GuardrailResult(BaseModel):
 
     @field_validator("result", "error")
     @classmethod
-    def validate_result_error_exclusivity(cls, v: Any, info) -> Any:
+    def validate_result_error_exclusivity(cls, v: Any, info: Any) -> Any:
         """Ensure that result and error are mutually exclusive based on success.
 
         Args:

lib/crewai/src/crewai/utilities/planning_types.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Literal
+from typing import Any, Literal
 from uuid import uuid4
 
 from pydantic import BaseModel, Field, field_validator
@@ -259,7 +259,7 @@ class StepObservation(BaseModel):
 
     @field_validator("suggested_refinements", mode="before")
     @classmethod
-    def coerce_single_refinement_to_list(cls, v):
+    def coerce_single_refinement_to_list(cls, v: Any) -> Any:
         """Coerce a single dict refinement into a list to handle LLM returning a single object."""
         if isinstance(v, dict):
             return [v]

lib/crewai/src/crewai/utilities/reasoning_handler.py

@@ -182,7 +182,7 @@ class AgentReasoning:
         if self.config.llm is not None:
             if isinstance(self.config.llm, LLM):
                 return self.config.llm
-            return create_llm(self.config.llm)
+            return cast(LLM, create_llm(self.config.llm))
         return cast(LLM, self.agent.llm)
 
     def handle_agent_reasoning(self) -> AgentReasoningOutput:

lib/crewai/src/crewai/utilities/rpm_controller.py

@@ -75,7 +75,7 @@ class RPMController(BaseModel):
         self._current_rpm = 0
 
     def _reset_request_count(self) -> None:
-        def _reset():
+        def _reset() -> None:
             self._current_rpm = 0
             if not self._shutdown_flag:
                 self._timer = threading.Timer(60.0, self._reset_request_count)

lib/crewai/src/crewai/utilities/streaming.py

@@ -60,7 +60,9 @@ def _extract_tool_call_info(
             StreamChunkType.TOOL_CALL,
             ToolCallChunk(
                 tool_id=event.tool_call.id,
-                tool_name=sanitize_tool_name(event.tool_call.function.name),
+                tool_name=sanitize_tool_name(event.tool_call.function.name)
+                if event.tool_call.function.name
+                else None,
                 arguments=event.tool_call.function.arguments,
                 index=event.tool_call.index,
             ),

lib/crewai/src/crewai/utilities/training_converter.py

@@ -76,7 +76,7 @@ Please provide ONLY the {field_name} field value as described:
 
 Respond with ONLY the requested information, nothing else.
 """
-        return self.llm.call(
+        result: str = self.llm.call(
             [
                 {
                     "role": "system",
@@ -85,6 +85,7 @@ Respond with ONLY the requested information, nothing else.
                 {"role": "user", "content": prompt},
             ]
         )
+        return result
 
     def _process_field_value(self, response: str, field_type: type | None) -> Any:
         response = response.strip()
@@ -104,7 +105,8 @@ Respond with ONLY the requested information, nothing else.
     def _parse_list(self, response: str) -> list[Any]:
         try:
             if response.startswith("["):
-                return json.loads(response)
+                parsed: list[Any] = json.loads(response)
+                return parsed
 
             items: list[str] = [
                 item.strip() for item in response.split("\n") if item.strip()

lib/crewai/tests/agents/test_agent_executor.py

@@ -1571,8 +1571,9 @@ class TestReasoningEffort:
         executor.agent.planning_config = None
         assert executor._get_reasoning_effort() == "medium"
 
-        # Case 3: planning_config without reasoning_effort attr → defaults to "medium"
+        # Case 3: planning_config with default reasoning_effort
-        executor.agent.planning_config = Mock(spec=[])
+        executor.agent.planning_config = Mock()
+        executor.agent.planning_config.reasoning_effort = "medium"
         assert executor._get_reasoning_effort() == "medium"
 
 

uv.lock

@@ -1241,7 +1241,7 @@ requires-dist = [
     { name = "json5", specifier = "~=0.10.0" },
     { name = "jsonref", specifier = "~=1.1.0" },
     { name = "lancedb", specifier = ">=0.29.2" },
-    { name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.74.9,<3" },
+    { name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.74.9,<=1.82.6" },
     { name = "mcp", specifier = "~=1.26.0" },
     { name = "mem0ai", marker = "extra == 'mem0'", specifier = "~=0.1.94" },
     { name = "openai", specifier = ">=1.83.0,<3" },