style: solve linter issues

Author: lucasgomide

src/crewai/agent.py

@@ -5,6 +5,7 @@
 from typing import (
     Any,
     Literal,
+    cast,
 )
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
@@ -326,7 +327,7 @@ def execute_task(
                 agent=self,
                 task=task,
             )
-            memory = contextual_memory.build_context_for_task(task, context)
+            memory = contextual_memory.build_context_for_task(task, context or "")
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
@@ -578,7 +579,7 @@ def create_agent_executor(
             agent=self,
             crew=self.crew,
             tools=parsed_tools,
-            prompt=prompt,
+            prompt=cast(dict[str, str], prompt),
             original_tools=raw_tools,
             stop_words=stop_words,
             max_iter=self.max_iter,
@@ -600,9 +601,7 @@ def get_delegation_tools(self, agents: list[BaseAgent]):
 
     def get_platform_tools(self, apps: list[PlatformAppOrAction]) -> list[BaseTool]:
         try:
-            from crewai_tools import (
-                CrewaiPlatformTools,  # type: ignore
-            )
+            from crewai_tools import CrewaiPlatformTools # type: ignore[import-untyped]
 
             return CrewaiPlatformTools(apps=apps)
         except Exception as e:

src/crewai/agents/agent_builder/base_agent.py

@@ -88,7 +88,7 @@ class BaseAgent(ABC, BaseModel):
             Abstract method to create an agent executor.
         get_delegation_tools(agents: list["BaseAgent"]):
             Abstract method to set the agents task tools for handling delegation and question asking to other agents in crew.
-        get_platform_tools(apps: list[PlatformApp], actions: list[str]):
+        get_platform_tools(apps: list[PlatformAppOrAction]):
             Abstract method to get platform tools for the specified list of applications and/or application/action combinations.
         get_output_converter(llm, model, instructions):
             Abstract method to get the converter class for the agent to create json/pydantic outputs.

src/crewai/crew.py

@@ -1080,7 +1080,7 @@ def _add_platform_tools(
     def _log_task_start(self, task: Task, role: str = "None"):
         if self.output_log_file:
             self._file_handler.log(
-                task_name=task.name, task=task.description, agent=role, status="started"
+                task_name=task.name or "unnamed_task", task=task.description, agent=role, status="started"
             )
 
     def _update_manager_tools(
@@ -1109,7 +1109,7 @@ def _process_task_result(self, task: Task, output: TaskOutput) -> None:
         role = task.agent.role if task.agent is not None else "None"
         if self.output_log_file:
             self._file_handler.log(
-                task_name=task.name,
+                task_name=task.name or "unnamed_task",
                 task=task.description,
                 agent=role,
                 status="completed",

src/crewai/utilities/training_handler.py

@@ -5,7 +5,7 @@
 
 
 class CrewTrainingHandler(PickleHandler):
-    def save_trained_data(self, agent_id: str, trained_data: dict[int, Any]) -> None:
+    def save_trained_data(self, agent_id: str, trained_data: dict[str, Any]) -> None:
         """Save the trained data for a specific agent.
 
         Args: