fix: Resolve type errors identified by mypy

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

src/crewai/tools/agent_tools/add_image_tool.py

@@ -7,6 +7,19 @@ from crewai.utilities import I18N
 
 i18n = I18N()
 
+def _get_add_image_tool_name() -> str:
+    """Safely get the tool name from i18n."""
+    tool_info = i18n.tools("add_image")
+    if isinstance(tool_info, dict):
+        return tool_info.get("name", "Add Image")
+    return "Add Image" # Default name if not a dict
+
+def _get_add_image_tool_description() -> str:
+    """Safely get the tool description from i18n."""
+    tool_info = i18n.tools("add_image")
+    if isinstance(tool_info, dict):
+        return tool_info.get("description", "Tool for adding images to the content")
+    return "Tool for adding images to the content" # Default description if not a dict
 
 class AddImageToolSchema(BaseModel):
     image_url: str = Field(..., description="The URL or path of the image to add")
@@ -18,10 +31,8 @@ class AddImageToolSchema(BaseModel):
 class AddImageTool(BaseTool):
     """Tool for adding images to the content"""
 
-    name: str = Field(default_factory=lambda: i18n.tools("add_image")["name"])  # type: ignore
+    name: str = Field(default_factory=_get_add_image_tool_name)
-    description: str = Field(
+    description: str = Field(default_factory=_get_add_image_tool_description)
-        default_factory=lambda: i18n.tools("add_image")["description"]
-    )  # type: ignore
     args_schema: type[BaseModel] = AddImageToolSchema
 
     def _run(

src/crewai/tools/agent_tools/base_agent_tools.py

@@ -81,13 +81,13 @@ class BaseAgentTool(BaseTool):
             available_agents = [agent.role for agent in self.agents]
             logger.debug(f"Available agents: {available_agents}")
 
-            agent = [  # type: ignore # Incompatible types in assignment (expression has type "list[BaseAgent]", variable has type "str | None")
+            matching_agents = [
                 available_agent
                 for available_agent in self.agents
                 if self.sanitize_agent_name(available_agent.role) == sanitized_name
             ]
             logger.debug(
-                f"Found {len(agent)} matching agents for role '{sanitized_name}'"
+                f"Found {len(matching_agents)} matching agents for role '{sanitized_name}'"
             )
         except (AttributeError, ValueError) as e:
             # Handle specific exceptions that might occur during role name processing
@@ -101,7 +101,7 @@ class BaseAgentTool(BaseTool):
                 error=str(e),
             )
 
-        if not agent:
+        if not matching_agents:
             # No matching agent found after sanitization
             return self.i18n.errors("agent_tool_unexisting_coworker").format(
                 coworkers="\n".join(
@@ -113,7 +113,7 @@ class BaseAgentTool(BaseTool):
                 error=f"No agent found with role '{sanitized_name}'",
             )
 
-        agent = agent[0]
+        agent: BaseAgent = matching_agents[0]
         try:
             task_with_assigned_agent = Task(
                 description=task,

src/crewai/tools/tool_usage.py

@@ -380,6 +380,7 @@ class ToolUsage:
             else ToolCalling
         )
         converter = Converter(
+            agent=None, # Agent not needed here as function calling is supported/used
             text=f"Only tools available:\n###\n{self._render()}\n\nReturn a valid schema for the tool, the tool name must be exactly equal one of the options, use this text to inform the valid output schema:\n\n### TEXT \n{tool_string}",
             llm=self.function_calling_llm,
             model=model,

src/crewai/utilities/evaluators/task_evaluator.py

@@ -65,13 +65,18 @@ class TaskEvaluator:
             instructions = f"{instructions}\n\nReturn only valid JSON with the following schema:\n```json\n{model_schema}\n```"
 
         converter = Converter(
+            agent=self.original_agent, # Pass agent
             llm=self.llm,
             text=evaluation_query,
             model=TaskEvaluation,
             instructions=instructions,
         )
 
-        return converter.to_pydantic()
+        result = converter.to_pydantic()
+        if isinstance(result, TaskEvaluation):
+            return result
+        else:
+            raise TypeError(f"Expected TaskEvaluation, got {type(result)}")
 
     def evaluate_training_data(
         self, training_data: dict, agent_id: str
@@ -134,6 +139,7 @@ class TaskEvaluator:
             instructions = f"{instructions}\n\nThe json should have the following structure, with the following keys:\n{model_schema}"
 
         converter = Converter(
+            agent=self.original_agent, # Pass agent
             llm=self.llm,
             text=evaluation_query,
             model=TrainingTaskEvaluation,
@@ -141,4 +147,7 @@ class TaskEvaluator:
         )
 
         pydantic_result = converter.to_pydantic()
-        return pydantic_result
+        if isinstance(pydantic_result, TrainingTaskEvaluation):
+            return pydantic_result
+        else:
+            raise TypeError(f"Expected TrainingTaskEvaluation, got {type(pydantic_result)}")