fix: type checking

src/crewai/agent.py

@@ -210,8 +210,7 @@ class Agent(BaseModel):
             Output of the agent
         """
         if self.tools_handler:
-            # type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
-            self.tools_handler.last_used_tool = {}
+            self.tools_handler.last_used_tool = {}  # type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
 
         task_prompt = task.prompt()
 
@@ -231,8 +230,8 @@ class Agent(BaseModel):
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
         tools = tools or self.tools
-        # type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
-        parsed_tools = self._parse_tools(tools)
+
+        parsed_tools = self._parse_tools(tools)  # type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
 
         self.create_agent_executor(tools=tools)
         self.agent_executor.tools = parsed_tools
@@ -399,8 +398,7 @@ class Agent(BaseModel):
 
         return copied_agent
 
-    # type: ignore # Function "langchain_core.tools.tool" is not valid as a type
-    def _parse_tools(self, tools: List[Any]) -> List[LangChainTool]:
+    def _parse_tools(self, tools: List[Any]) -> List[LangChainTool]:  # type: ignore # Function "langchain_core.tools.tool" is not valid as a type
         """Parse tools to be used for the task."""
         # tentatively try to import from crewai_tools import BaseTool as CrewAITool
         tools_list = []

src/crewai/crew.py

@@ -281,8 +281,8 @@ class Crew(BaseModel):
     ) -> Union[str, Dict[str, Any]]:
         """Starts the crew to work on its assigned tasks."""
         self._execution_span = self._telemetry.crew_execution_span(self)
-        # type: ignore # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
-        self._interpolate_inputs(inputs)
+
+        self._interpolate_inputs(inputs)  # type: ignore # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
         self._set_tasks_callbacks()
 
         i18n = I18N(prompt_file=self.prompt_file)
@@ -303,10 +303,8 @@ class Crew(BaseModel):
         if self.process == Process.sequential:
             result = self._run_sequential_process()
         elif self.process == Process.hierarchical:
-            # type: ignore # Unpacking a string is disallowed
-            result, manager_metrics = self._run_hierarchical_process()
-            # type: ignore # Cannot determine type of "manager_metrics"
-            metrics.append(manager_metrics)
+            result, manager_metrics = self._run_hierarchical_process()  # type: ignore # Unpacking a string is disallowed
+            metrics.append(manager_metrics)  # type: ignore # Cannot determine type of "manager_metrics"
         else:
             raise NotImplementedError(
                 f"The process '{self.process}' is not implemented yet."
@@ -316,7 +314,8 @@ class Crew(BaseModel):
             agent._token_process.get_summary() for agent in self.agents
         ]
         self.usage_metrics = {
-            key: sum([m[key] for m in metrics if m is not None]) for key in metrics[0]
+            key: sum([m[key] for m in metrics if m is not None])  # type: ignore # List comprehension has incompatible type List[Any | str]; expected List[bool]
+            for key in metrics[0]
         }
 
         return result
@@ -395,10 +394,10 @@ class Crew(BaseModel):
                 self._file_handler.log(agent=role, task=task_output, status="completed")
 
         self._finish_execution(task_output)
-        # type: ignore # Item "None" of "Agent | None" has no attribute "_token_process"
-        token_usage = task.agent._token_process.get_summary()
-        # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
-        return self._format_output(task_output, token_usage)
+
+        token_usage = task.agent._token_process.get_summary()  # type: ignore # Item "None" of "Agent | None" has no attribute "_token_process"
+
+        return self._format_output(task_output, token_usage)  # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
 
     def _run_hierarchical_process(self) -> Union[str, Dict[str, Any]]:
         """Creates and assigns a manager agent to make sure the crew completes the tasks."""
@@ -434,7 +433,7 @@ class Crew(BaseModel):
                 agent=manager, context=task_output, tools=manager.tools
             )
 
-            self._logger.log("debug", f"[{manager.role}] Task output: {task_output}")
+            self._logger.log("debug", f"[{manager.role}] Task ouptput: {task_output}")
 
             if self.output_log_file:
                 self._file_handler.log(
@@ -442,9 +441,9 @@ class Crew(BaseModel):
                 )
 
         self._finish_execution(task_output)
-        # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
+
         manager_token_usage = manager._token_process.get_summary()
-        return self._format_output(
+        return self._format_output(  # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
             task_output, manager_token_usage
         ), manager_token_usage
 
@@ -493,8 +492,8 @@ class Crew(BaseModel):
             )
             for task in self.tasks
         ]
-        # type: ignore # "interpolate_inputs" of "Agent" does not return a value (it only ever returns None)
-        [agent.interpolate_inputs(inputs) for agent in self.agents]
+
+        [agent.interpolate_inputs(inputs) for agent in self.agents]  # type: ignore # "interpolate_inputs" of "Agent" does not return a value (it only ever returns None)
 
     def _format_output(
         self, output: str, token_usage: Optional[Dict[str, Any]]

src/crewai/task.py

@@ -1,8 +1,8 @@
-from copy import deepcopy
 import os
 import re
 import threading
 import uuid
+from copy import deepcopy
 from typing import Any, Dict, List, Optional, Type
 
 from langchain_openai import ChatOpenAI
@@ -164,16 +164,13 @@ class Task(BaseModel):
             )
 
         if self.context:
-            # type: ignore # Incompatible types in assignment (expression has type "list[Never]", variable has type "str | None")
-            context = []
+            context = []  # type: ignore # Incompatible types in assignment (expression has type "list[Never]", variable has type "str | None")
             for task in self.context:
                 if task.async_execution:
                     task.thread.join()  # type: ignore # Item "None" of "Thread | None" has no attribute "join"
                 if task and task.output:
-                    # type: ignore # Item "str" of "str | None" has no attribute "append"
-                    context.append(task.output.raw_output)
-            # type: ignore # Argument 1 to "join" of "str" has incompatible type "str | None"; expected "Iterable[str]"
-            context = "\n".join(context)
+                    context.append(task.output.raw_output)  # type: ignore # Item "str" of "str | None" has no attribute "append"
+            context = "\n".join(context)  # type: ignore # Argument 1 to "join" of "str" has incompatible type "str | None"; expected "Iterable[str]"
 
         self.prompt_context = context
         tools = tools or self.tools
@@ -281,32 +278,26 @@ class Task(BaseModel):
 
             # try to convert task_output directly to pydantic/json
             try:
-                # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
-                exported_result = model.model_validate_json(result)
+                exported_result = model.model_validate_json(result)  # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
                 if self.output_json:
-                    # type: ignore # "str" has no attribute "model_dump"
-                    return exported_result.model_dump()
+                    return exported_result.model_dump()  # type: ignore # "str" has no attribute "model_dump"
                 return exported_result
             except Exception:
                 # sometimes the response contains valid JSON in the middle of text
                 match = re.search(r"({.*})", result, re.DOTALL)
                 if match:
                     try:
-                        # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
-                        exported_result = model.model_validate_json(match.group(0))
+                        exported_result = model.model_validate_json(match.group(0))  # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "model_validate_json"
                         if self.output_json:
-                            # type: ignore # "str" has no attribute "model_dump"
-                            return exported_result.model_dump()
+                            return exported_result.model_dump()  # type: ignore # "str" has no attribute "model_dump"
                         return exported_result
                     except Exception:
                         pass
 
-            # type: ignore # Item "None" of "Agent | None" has no attribute "function_calling_llm"
-            llm = self.agent.function_calling_llm or self.agent.llm
+            llm = self.agent.function_calling_llm or self.agent.llm  # type: ignore # Item "None" of "Agent | None" has no attribute "function_calling_llm"
 
             if not self._is_gpt(llm):
-                # type: ignore # Argument "model" to "PydanticSchemaParser" has incompatible type "type[BaseModel] | None"; expected "type[BaseModel]"
-                model_schema = PydanticSchemaParser(model=model).get_schema()
+                model_schema = PydanticSchemaParser(model=model).get_schema()  # type: ignore # Argument "model" to "PydanticSchemaParser" has incompatible type "type[BaseModel] | None"; expected "type[BaseModel]"
                 instructions = f"{instructions}\n\nThe json should have the following structure, with the following keys:\n{model_schema}"
 
             converter = Converter(
@@ -327,8 +318,7 @@ class Task(BaseModel):
 
         if self.output_file:
             content = (
-                # type: ignore # "str" has no attribute "json"
-                exported_result if not self.output_pydantic else exported_result.json()
+                exported_result if not self.output_pydantic else exported_result.json()  # type: ignore # "str" has no attribute "json"
             )
             self._save_file(content)
 
@@ -338,14 +328,12 @@ class Task(BaseModel):
         return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None
 
     def _save_file(self, result: Any) -> None:
-        # type: ignore # Value of type variable "AnyOrLiteralStr" of "dirname" cannot be "str | None"
-        directory = os.path.dirname(self.output_file)
+        directory = os.path.dirname(self.output_file)  # type: ignore # Value of type variable "AnyOrLiteralStr" of "dirname" cannot be "str | None"
 
         if directory and not os.path.exists(directory):
             os.makedirs(directory)
 
-        # type: ignore # Argument 1 to "open" has incompatible type "str | None"; expected "int | str | bytes | PathLike[str] | PathLike[bytes]"
-        with open(self.output_file, "w", encoding="utf-8") as file:
+        with open(self.output_file, "w", encoding="utf-8") as file:  # type: ignore # Argument 1 to "open" has incompatible type "str | None"; expected "int | str | bytes | PathLike[str] | PathLike[bytes]"
             file.write(result)
         return None
 

src/crewai/tools/agent_tools.py

@@ -78,7 +78,7 @@ class AgentTools(BaseModel):
             # {"task": "....", "coworker": "...."}
             agent_name = agent.casefold().replace('"', "").replace("\n", "")
 
-            agent = [
+            agent = [  # type: ignore # Incompatible types in assignment (expression has type "list[Agent]", variable has type "str | None")
                 available_agent
                 for available_agent in self.agents
                 if available_agent.role.casefold().replace("\n", "") == agent_name
@@ -98,9 +98,9 @@ class AgentTools(BaseModel):
             )
 
         agent = agent[0]
-        task = Task(
+        task = Task(  # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
             description=task,
             agent=agent,
             expected_output="Your best answer to your coworker asking you this, accounting for the context shared.",
         )
-        return agent.execute_task(task, context)
+        return agent.execute_task(task, context)  # type: ignore # "str" has no attribute "execute_task"

tests/cassettes/test_save_task_pydantic_output.yaml

@@ -1,111 +1,114 @@
 interactions:
 - request:
     body: !!binary |
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tests/crew_test.py

@@ -685,16 +685,16 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
         agents=[agent],
         tasks=[task],
         process=Process.hierarchical,
-        manager_llm=ChatOpenAI(temperature=0, model="gpt-4"),
+        manager_llm=ChatOpenAI(temperature=0, model="gpt-4o"),
     )
 
     result = crew.kickoff()
-    assert result == '"Howdy!"'
+    assert result == "Howdy!"
 
     assert crew.usage_metrics == {
-        "total_tokens": 507,
-        "prompt_tokens": 224,
-        "completion_tokens": 283,
+        "total_tokens": 1383,
+        "prompt_tokens": 1278,
+        "completion_tokens": 105,
         "successful_requests": 3,
     }
 

tests/task_test.py

@@ -367,6 +367,8 @@ def test_save_task_json_output():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_save_task_pydantic_output():
+    from langchain_openai import ChatOpenAI
+
     class ScoreOutput(BaseModel):
         score: int
 
@@ -375,6 +377,7 @@ def test_save_task_pydantic_output():
         goal="Score the title",
         backstory="You're an expert scorer, specialized in scoring titles.",
         allow_delegation=False,
+        llm=ChatOpenAI(model="gpt-4o"),
     )
 
     task = Task(
@@ -413,13 +416,13 @@ def test_increment_delegations_for_hierarchical_process():
         agents=[scorer],
         tasks=[task],
         process=Process.hierarchical,
-        manager_llm=ChatOpenAI(model="gpt-4-0125-preview"),
+        manager_llm=ChatOpenAI(model="gpt-4o"),
     )
 
     with patch.object(Task, "increment_delegations") as increment_delegations:
         increment_delegations.return_value = None
         crew.kickoff()
-        increment_delegations.assert_called_once
+        increment_delegations.assert_called_once()
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])