feat: add mypy as type checker, update code and add comment to reference (#591)

* fix: fix test actually running

* fix: fix test to not send request to openai

* fix: fix linting to remove cli files

* fix: exclude only files that breaks black

* fix: Fix all Ruff checkings on the code and Fix Test with repeated name

* fix: Change linter name on yml file

* feat: update pre-commit

* feat: remove need for isort on the code

* feat: add mypy as type checker, update code and add comment to reference

* feat: remove black linter

* feat: remove poetry to run the command

* feat: change logic to test mypy

* feat: update tests yml to try to fix the tests gh action

* feat: try to add just mypy to run on gh action

* feat: fix yml file

* feat: add comment to avoid issue on gh action

* feat: decouple pytest from the necessity of poetry install

* feat: change tests.yml to test different approach

* feat: change to poetry run

* fix: parameter field on yml file

* fix: update parameters to be on the pyproject

* fix: update pyproject to remove import untyped errors

.github/workflows/type-checker.yml

@@ -1,4 +1,3 @@
-
 name: Run Type Checks
 
 on: [pull_request]
@@ -12,19 +11,16 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
 
       - name: Setup Python
         uses: actions/setup-python@v4
         with:
-          python-version: '3.10'
+          python-version: "3.10"
 
       - name: Install Requirements
         run: |
-          sudo apt-get update &&
+          pip install mypy
-          pip install poetry &&
-          poetry lock &&
-          poetry install
 
       - name: Run type checks
-        run: poetry run pyright
+        run: mypy src

README.md

@@ -231,7 +231,7 @@ poetry run pytest
 ### Running static type checks
 
 ```bash
-poetry run pyright
+poetry run mypy
 ```
 
 ### Packaging

pyproject.toml

@@ -32,7 +32,7 @@ tools = ["crewai-tools"]
 
 [tool.poetry.group.dev.dependencies]
 isort = "^5.13.2"
-pyright = ">=1.1.350,<2.0.0"
+mypy = "1.10.0"
 autoflake = "^2.2.1"
 pre-commit = "^3.6.0"
 mkdocs = "^1.4.3"
@@ -52,6 +52,11 @@ python-dotenv = "1.0.0"
 [tool.poetry.scripts]
 crewai = "crewai.cli.cli:crewai"
 
+[tool.mypy]
+ignore_missing_imports = true
+disable_error_code = 'import-untyped'
+exclude = ["cli/templates/main.py", "cli/templates/crew.py"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

src/crewai/agent.py

@@ -204,7 +204,7 @@ class Agent(BaseModel):
             Output of the agent
         """
         if self.tools_handler:
-            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()
 
@@ -224,7 +224,7 @@ class Agent(BaseModel):
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
         tools = tools or self.tools
-        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
@@ -364,7 +364,7 @@ class Agent(BaseModel):
             thoughts += f"\n{observation_prefix}{observation}\n{llm_prefix}"
         return thoughts
 
-    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/agents/executor.py

@@ -35,7 +35,7 @@ class CrewAgentExecutor(AgentExecutor):
     crew: Any = None
     function_calling_llm: Any = None
     request_within_rpm_limit: Any = None
-    tools_handler: InstanceOf[ToolsHandler] = None
+    tools_handler: Optional[InstanceOf[ToolsHandler]] = None
     max_iterations: Optional[int] = 15
     have_forced_answer: bool = False
     force_answer_max_iterations: Optional[int] = None
@@ -189,7 +189,7 @@ class CrewAgentExecutor(AgentExecutor):
             intermediate_steps = self._prepare_intermediate_steps(intermediate_steps)
 
             # Call the LLM to see what to do.
-            output = self.agent.plan(
+            output = self.agent.plan(  # type: ignore #  Incompatible types in assignment (expression has type "AgentAction | AgentFinish | list[AgentAction]", variable has type "AgentAction")
                 intermediate_steps,
                 callbacks=run_manager.get_child() if run_manager else None,
                 **inputs,
@@ -275,8 +275,8 @@ class CrewAgentExecutor(AgentExecutor):
                 run_manager.on_agent_action(agent_action, color="green")
 
             tool_usage = ToolUsage(
-                tools_handler=self.tools_handler,
+                tools_handler=self.tools_handler,  # type: ignore # Argument "tools_handler" to "ToolUsage" has incompatible type "ToolsHandler | None"; expected "ToolsHandler"
-                tools=self.tools,
+                tools=self.tools,  # type: ignore # Argument "tools" to "ToolUsage" has incompatible type "Sequence[BaseTool]"; expected "list[BaseTool]"
                 original_tools=self.original_tools,
                 tools_description=self.tools_description,
                 tools_names=self.tools_names,

src/crewai/agents/tools_handler.py

@@ -8,13 +8,13 @@ from .cache.cache_handler import CacheHandler
 class ToolsHandler:
     """Callback handler for tool usage."""
 
-    last_used_tool: ToolCalling = {}
+    last_used_tool: ToolCalling = {}  # type: ignore # BUG?: Incompatible types in assignment (expression has type "Dict[...]", variable has type "ToolCalling")
-    cache: CacheHandler
+    cache: Optional[CacheHandler]
 
     def __init__(self, cache: Optional[CacheHandler] = None):
         """Initialize the callback handler."""
         self.cache = cache
-        self.last_used_tool = {}
+        self.last_used_tool = {}  # type: ignore # BUG?: same as above
 
     def on_tool_use(
         self,
@@ -23,7 +23,7 @@ class ToolsHandler:
         should_cache: bool = True,
     ) -> Any:
         """Run when tool ends running."""
-        self.last_used_tool = calling
+        self.last_used_tool = calling  # type: ignore # BUG?: Incompatible types in assignment (expression has type "Union[ToolCalling, InstructorToolCalling]", variable has type "ToolCalling")
         if self.cache and should_cache and calling.tool_name != CacheTools().name:
             self.cache.add(
                 tool=calling.tool_name,

src/crewai/crew.py

@@ -242,7 +242,7 @@ class Crew(BaseModel):
     def kickoff(self, inputs: Optional[Dict[str, Any]] = {}) -> str:
         """Starts the crew to work on its assigned tasks."""
         self._execution_span = self._telemetry.crew_execution_span(self)
-        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)
@@ -263,8 +263,8 @@ class Crew(BaseModel):
         if self.process == Process.sequential:
             result = self._run_sequential_process()
         elif self.process == Process.hierarchical:
-            result, manager_metrics = self._run_hierarchical_process()
+            result, manager_metrics = self._run_hierarchical_process()  # type: ignore # Unpacking a string is disallowed
-            metrics.append(manager_metrics)
+            metrics.append(manager_metrics)  # type: ignore # Cannot determine type of "manager_metrics"
 
         else:
             raise NotImplementedError(
@@ -284,7 +284,7 @@ class Crew(BaseModel):
         """Executes tasks sequentially and returns the final output."""
         task_output = ""
         for task in self.tasks:
-            if task.agent.allow_delegation:
+            if task.agent.allow_delegation:  # type: ignore #  Item "None" of "Agent | None" has no attribute "allow_delegation"
                 agents_for_delegation = [
                     agent for agent in self.agents if agent != task.agent
                 ]
@@ -357,23 +357,23 @@ class Crew(BaseModel):
                 )
 
         self._finish_execution(task_output)
-        return self._format_output(task_output), manager._token_process.get_summary()
+        return self._format_output(task_output), manager._token_process.get_summary()  # type: ignore # Incompatible return value type (got "tuple[str, Any]", expected "str")
 
-    def _set_tasks_callbacks(self) -> str:
+    def _set_tasks_callbacks(self) -> None:
         """Sets callback for every task suing task_callback"""
         for task in self.tasks:
             if not task.callback:
                 task.callback = self.task_callback
 
-    def _interpolate_inputs(self, inputs: Dict[str, Any]) -> str:
+    def _interpolate_inputs(self, inputs: Dict[str, Any]) -> None:
         """Interpolates the inputs in the tasks and agents."""
-        [task.interpolate_inputs(inputs) for task in self.tasks]
+        [task.interpolate_inputs(inputs) for task in self.tasks]  # type: ignore # "interpolate_inputs" of "Task" 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) -> str:
         """Formats the output of the crew execution."""
         if self.full_output:
-            return {
+            return {  # type: ignore # Incompatible return value type (got "dict[str, Sequence[str | TaskOutput | None]]", expected "str")
                 "final_output": output,
                 "tasks_outputs": [task.output for task in self.tasks if task],
             }

src/crewai/memory/contextual/contextual_memory.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory
 
 
@@ -32,7 +34,7 @@ class ContextualMemory:
         formatted_results = "\n".join([f"- {result}" for result in stm_results])
         return f"Recent Insights:\n{formatted_results}" if stm_results else ""
 
-    def _fetch_ltm_context(self, task) -> str:
+    def _fetch_ltm_context(self, task) -> Optional[str]:
         """
         Fetches historical data or insights from LTM that are relevant to the task's description and expected_output,
         formatted as bullet points.
@@ -44,10 +46,10 @@ class ContextualMemory:
         formatted_results = [
             suggestion
             for result in ltm_results
-            for suggestion in result["metadata"]["suggestions"]
+            for suggestion in result["metadata"]["suggestions"]  # type: ignore # Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         ]
         formatted_results = list(dict.fromkeys(formatted_results))
-        formatted_results = "\n".join([f"- {result}" for result in formatted_results])
+        formatted_results = "\n".join([f"- {result}" for result in formatted_results])  # type: ignore # Incompatible types in assignment (expression has type "str", variable has type "list[str]")
 
         return f"Historical Data:\n{formatted_results}" if ltm_results else ""
 
@@ -58,6 +60,6 @@ class ContextualMemory:
         """
         em_results = self.em.search(query)
         formatted_results = "\n".join(
-            [f"- {result['context']}" for result in em_results]
+            [f"- {result['context']}" for result in em_results]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         )
         return f"Entities:\n{formatted_results}" if em_results else ""

src/crewai/memory/entity/entity_memory.py

@@ -16,7 +16,7 @@ class EntityMemory(Memory):
         )
         super().__init__(storage)
 
-    def save(self, item: EntityMemoryItem) -> None:
+    def save(self, item: EntityMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
         """Saves an entity item into the SQLite storage."""
         data = f"{item.name}({item.type}): {item.description}"
         super().save(data, item.metadata)

src/crewai/memory/long_term/long_term_memory.py

@@ -18,10 +18,10 @@ class LongTermMemory(Memory):
         storage = LTMSQLiteStorage()
         super().__init__(storage)
 
-    def save(self, item: LongTermMemoryItem) -> None:
+    def save(self, item: LongTermMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
         metadata = item.metadata
         metadata.update({"agent": item.agent, "expected_output": item.expected_output})
-        self.storage.save(
+        self.storage.save(  # type: ignore # BUG?: Unexpected keyword argument "task_description","score","datetime" for "save" of "Storage"
             task_description=item.task,
             score=metadata["quality"],
             metadata=metadata,
@@ -29,4 +29,4 @@ class LongTermMemory(Memory):
         )
 
     def search(self, task: str, latest_n: int = 3) -> Dict[str, Any]:
-        return self.storage.load(task, latest_n)
+        return self.storage.load(task, latest_n)  # type: ignore # BUG?: "Storage" has no attribute "load"

src/crewai/memory/long_term/long_term_memory_item.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Union
+from typing import Any, Dict, Optional, Union
 
 
 class LongTermMemoryItem:
@@ -8,8 +8,8 @@ class LongTermMemoryItem:
         task: str,
         expected_output: str,
         datetime: str,
-        quality: Union[int, float] = None,
+        quality: Optional[Union[int, float]] = None,
-        metadata: Dict[str, Any] = None,
+        metadata: Optional[Dict[str, Any]] = None,
     ):
         self.task = task
         self.agent = agent

src/crewai/memory/memory.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict
+from typing import Any, Dict, Optional
 
 from crewai.memory.storage.interface import Storage
 
@@ -12,12 +12,16 @@ class Memory:
         self.storage = storage
 
     def save(
-        self, value: Any, metadata: Dict[str, Any] = None, agent: str = None
+        self,
+        value: Any,
+        metadata: Optional[Dict[str, Any]] = None,
+        agent: Optional[str] = None,
     ) -> None:
         metadata = metadata or {}
         if agent:
             metadata["agent"] = agent
-        self.storage.save(value, metadata)
+
+        self.storage.save(value, metadata)  # type: ignore # Maybe BUG? Should be self.storage.save(key, value, metadata)
 
     def search(self, query: str) -> Dict[str, Any]:
         return self.storage.search(query)

src/crewai/memory/short_term/short_term_memory.py

@@ -16,8 +16,8 @@ class ShortTermMemory(Memory):
         storage = RAGStorage(type="short_term", embedder_config=embedder_config)
         super().__init__(storage)
 
-    def save(self, item: ShortTermMemoryItem) -> None:
+    def save(self, item: ShortTermMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
         super().save(item.data, item.metadata, item.agent)
 
     def search(self, query: str, score_threshold: float = 0.35):
-        return self.storage.search(query=query, score_threshold=score_threshold)
+        return self.storage.search(query=query, score_threshold=score_threshold)  # type: ignore # BUG? The reference is to the parent class, but the parent class does not have this parameters

src/crewai/memory/short_term/short_term_memory_item.py

@@ -1,8 +1,10 @@
-from typing import Any, Dict
+from typing import Any, Dict, Optional
 
 
 class ShortTermMemoryItem:
-    def __init__(self, data: Any, agent: str, metadata: Dict[str, Any] = None):
+    def __init__(
+        self, data: Any, agent: str, metadata: Optional[Dict[str, Any]] = None
+    ):
         self.data = data
         self.agent = agent
         self.metadata = metadata if metadata is not None else {}

src/crewai/memory/storage/interface.py

@@ -7,5 +7,5 @@ class Storage:
     def save(self, key: str, value: Any, metadata: Dict[str, Any]) -> None:
         pass
 
-    def search(self, key: str) -> Dict[str, Any]:
+    def search(self, key: str) -> Dict[str, Any]:  # type: ignore
         pass

src/crewai/memory/storage/ltm_sqlite_storage.py

@@ -1,6 +1,6 @@
 import json
 import sqlite3
-from typing import Any, Dict, Union
+from typing import Any, Dict, List, Optional, Union
 
 from crewai.utilities import Printer
 from crewai.utilities.paths import db_storage_path
@@ -11,7 +11,9 @@ class LTMSQLiteStorage:
     An updated SQLite storage class for LTM data storage.
     """
 
-    def __init__(self, db_path=f"{db_storage_path()}/long_term_memory_storage.db"):
+    def __init__(
+        self, db_path: str = f"{db_storage_path()}/long_term_memory_storage.db"
+    ) -> None:
         self.db_path = db_path
         self._printer: Printer = Printer()
         self._initialize_db()
@@ -67,7 +69,9 @@ class LTMSQLiteStorage:
                 color="red",
             )
 
-    def load(self, task_description: str, latest_n: int) -> Dict[str, Any]:
+    def load(
+        self, task_description: str, latest_n: int
+    ) -> Optional[List[Dict[str, Any]]]:
         """Queries the LTM table by task description with error handling."""
         try:
             with sqlite3.connect(self.db_path) as conn:

src/crewai/memory/storage/rag_storage.py

@@ -2,7 +2,7 @@ import contextlib
 import io
 import logging
 import os
-from typing import Any, Dict
+from typing import Any, Dict, List, Optional
 
 from embedchain import App
 from embedchain.llm.base import BaseLlm
@@ -72,16 +72,16 @@ class RAGStorage(Storage):
         if allow_reset:
             self.app.reset()
 
-    def save(self, value: Any, metadata: Dict[str, Any]) -> None:
+    def save(self, value: Any, metadata: Dict[str, Any]) -> None:  # type: ignore # BUG?: Should be save(key, value, metadata)  Signature of "save" incompatible with supertype "Storage"
         self._generate_embedding(value, metadata)
 
-    def search(
+    def search(  # type: ignore # BUG?: Signature of "search" incompatible with supertype "Storage"
         self,
         query: str,
         limit: int = 3,
-        filter: dict = None,
+        filter: Optional[dict] = None,
         score_threshold: float = 0.35,
-    ) -> Dict[str, Any]:
+    ) -> List[Any]:
         with suppress_logging():
             try:
                 results = (

src/crewai/project/crew_base.py

@@ -1,11 +1,12 @@
 import inspect
 import os
 from pathlib import Path
-from crewai.utilities.parser import YamlParser
 
 import yaml
 from dotenv import load_dotenv
 
+from crewai.utilities.parser import YamlParser
+
 load_dotenv()
 
 
@@ -41,7 +42,7 @@ def CrewBase(cls):
         @staticmethod
         def load_yaml(config_path: str):
             with open(config_path, "r") as file:
-                parsedContent = YamlParser.parse(file)
+                parsedContent = YamlParser.parse(file)  # type: ignore # Argument 1 to "parse" has incompatible type "TextIOWrapper"; expected "YamlParser"
                 return yaml.safe_load(parsedContent)
 
     return WrappedClass

src/crewai/task.py

@@ -41,7 +41,7 @@ class Task(BaseModel):
     tools_errors: int = 0
     delegations: int = 0
     i18n: I18N = I18N()
-    thread: threading.Thread = None
+    thread: Optional[threading.Thread] = None
     prompt_context: Optional[str] = None
     description: str = Field(description="Description of the actual task.")
     expected_output: str = Field(
@@ -144,7 +144,7 @@ class Task(BaseModel):
             )
         return self
 
-    def execute(
+    def execute(  # type: ignore # Missing return statement
         self,
         agent: Agent | None = None,
         context: Optional[str] = None,
@@ -163,13 +163,13 @@ class Task(BaseModel):
             )
 
         if self.context:
-            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()
+                    task.thread.join()  # type: ignore # Item "None" of "Thread | None" has no attribute "join"
                 if task and task.output:
-                    context.append(task.output.raw_output)
+                    context.append(task.output.raw_output)  # type: ignore # Item "str" of "str | None" has no attribute "append"
-            context = "\n".join(context)
+            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
@@ -250,26 +250,26 @@ class Task(BaseModel):
 
             # try to convert task_output directly to pydantic/json
             try:
-                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:
-                    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:
-                        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:
-                            return exported_result.model_dump()
+                            return exported_result.model_dump()  # type: ignore # "str" has no attribute "model_dump"
                         return exported_result
                     except Exception:
                         pass
 
-            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):
-                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(
@@ -290,7 +290,7 @@ class Task(BaseModel):
 
         if self.output_file:
             content = (
-                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)
 
@@ -300,12 +300,12 @@ class Task(BaseModel):
         return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None
 
     def _save_file(self, result: Any) -> 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)
 
-        with open(self.output_file, "w") as file:
+        with open(self.output_file, "w") 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/tool_usage.py

@@ -82,6 +82,8 @@ class ToolUsage:
             self._printer.print(content=f"\n\n{error}\n", color="red")
             self.task.increment_tools_errors()
             return error
+
+        # BUG? The code below seems to be unreachable
         try:
             tool = self._select_tool(calling.tool_name)
         except Exception as e:
@@ -89,15 +91,15 @@ class ToolUsage:
             self.task.increment_tools_errors()
             self._printer.print(content=f"\n\n{error}\n", color="red")
             return error
-        return f"{self._use(tool_string=tool_string, tool=tool, calling=calling)}"
+        return f"{self._use(tool_string=tool_string, tool=tool, calling=calling)}"  # type: ignore # BUG?: "_use" of "ToolUsage" does not return a value (it only ever returns None)
 
     def _use(
         self,
         tool_string: str,
         tool: BaseTool,
         calling: Union[ToolCalling, InstructorToolCalling],
-    ) -> None:
+    ) -> None:  # TODO: Fix this return type
-        if self._check_tool_repeated_usage(calling=calling):
+        if self._check_tool_repeated_usage(calling=calling):  # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
             try:
                 result = self._i18n.errors("task_repeated_usage").format(
                     tool_names=self.tools_names
@@ -108,15 +110,16 @@ class ToolUsage:
                     tool_name=tool.name,
                     attempts=self._run_attempts,
                 )
-                result = self._format_result(result=result)
+                result = self._format_result(result=result)  # type: ignore #  "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
-                return result
+                return result  # type: ignore # Fix the reutrn type of this function
+
             except Exception:
                 self.task.increment_tools_errors()
 
-        result = None
+        result = None  # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
 
         if self.tools_handler.cache:
-            result = self.tools_handler.cache.read(
+            result = self.tools_handler.cache.read(  # type: ignore # Incompatible types in assignment (expression has type "str | None", variable has type "str")
                 tool=calling.tool_name, input=calling.arguments
             )
 
@@ -130,7 +133,7 @@ class ToolUsage:
 
                 if calling.arguments:
                     try:
-                        acceptable_args = tool.args_schema.schema()["properties"].keys()
+                        acceptable_args = tool.args_schema.schema()["properties"].keys()  # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "schema"
                         arguments = {
                             k: v
                             for k, v in calling.arguments.items()
@@ -142,7 +145,7 @@ class ToolUsage:
                             arguments = calling.arguments
                             result = tool._run(**arguments)
                         else:
-                            arguments = calling.arguments.values()
+                            arguments = calling.arguments.values()  # type: ignore # Incompatible types in assignment (expression has type "dict_values[str, Any]", variable has type "dict[str, Any]")
                             result = tool._run(*arguments)
                 else:
                     result = tool._run()
@@ -158,9 +161,10 @@ class ToolUsage:
                     ).message
                     self.task.increment_tools_errors()
                     self._printer.print(content=f"\n\n{error_message}\n", color="red")
-                    return error
+                    return error  # type: ignore # No return value expected
+
                 self.task.increment_tools_errors()
-                return self.use(calling=calling, tool_string=tool_string)
+                return self.use(calling=calling, tool_string=tool_string)  # type: ignore # No return value expected
 
             if self.tools_handler:
                 should_cache = True
@@ -169,9 +173,9 @@ class ToolUsage:
                 )
                 if (
                     hasattr(original_tool, "cache_function")
-                    and original_tool.cache_function
+                    and original_tool.cache_function  # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
                 ):
-                    should_cache = original_tool.cache_function(
+                    should_cache = original_tool.cache_function(  # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
                         calling.arguments, result
                     )
 
@@ -185,13 +189,13 @@ class ToolUsage:
             tool_name=tool.name,
             attempts=self._run_attempts,
         )
-        result = self._format_result(result=result)
+        result = self._format_result(result=result)  # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
-        return result
+        return result  # type: ignore # No return value expected
 
     def _format_result(self, result: Any) -> None:
         self.task.used_tools += 1
-        if self._should_remember_format():
+        if self._should_remember_format():  # type: ignore # "_should_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
-            result = self._remember_format(result=result)
+            result = self._remember_format(result=result)  # type: ignore # "_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
         return result
 
     def _should_remember_format(self) -> None:
@@ -202,15 +206,15 @@ class ToolUsage:
         result += "\n\n" + self._i18n.slice("tools").format(
             tools=self.tools_description, tool_names=self.tools_names
         )
-        return result
+        return result  # type: ignore # No return value expected
 
     def _check_tool_repeated_usage(
         self, calling: Union[ToolCalling, InstructorToolCalling]
     ) -> None:
         if not self.tools_handler:
-            return False
+            return False  # type: ignore # No return value expected
         if last_tool_usage := self.tools_handler.last_used_tool:
-            return (calling.tool_name == last_tool_usage.tool_name) and (
+            return (calling.tool_name == last_tool_usage.tool_name) and (  # type: ignore # No return value expected
                 calling.arguments == last_tool_usage.arguments
             )
 
@@ -292,14 +296,14 @@ class ToolUsage:
                     tool_input = self._validate_tool_input(self.action.tool_input)
                     arguments = ast.literal_eval(tool_input)
                 except Exception:
-                    return ToolUsageErrorException(
+                    return ToolUsageErrorException(  # type: ignore # Incompatible return value type (got "ToolUsageErrorException", expected "ToolCalling | InstructorToolCalling")
                         f'{self._i18n.errors("tool_arguments_error")}'
                     )
                 if not isinstance(arguments, dict):
-                    return ToolUsageErrorException(
+                    return ToolUsageErrorException(  # type: ignore # Incompatible return value type (got "ToolUsageErrorException", expected "ToolCalling | InstructorToolCalling")
                         f'{self._i18n.errors("tool_arguments_error")}'
                     )
-                calling = ToolCalling(
+                calling = ToolCalling(  # type: ignore # Unexpected keyword argument "log" for "ToolCalling"
                     tool_name=tool.name,
                     arguments=arguments,
                     log=tool_string,
@@ -310,7 +314,7 @@ class ToolUsage:
                 self._telemetry.tool_usage_error(llm=self.function_calling_llm)
                 self.task.increment_tools_errors()
                 self._printer.print(content=f"\n\n{e}\n", color="red")
-                return ToolUsageErrorException(
+                return ToolUsageErrorException(  # type: ignore # Incompatible return value type (got "ToolUsageErrorException", expected "ToolCalling | InstructorToolCalling")
                     f'{self._i18n.errors("tool_usage_error").format(error=e)}\nMoving on then. {self._i18n.slice("format").format(tool_names=self.tools_names)}'
                 )
             return self._tool_calling(tool_string)

src/crewai/utilities/converter.py

@@ -83,5 +83,5 @@ class Converter(BaseModel):
         )
         return new_prompt | self.llm | parser
 
-    def _is_gpt(self, llm) -> bool:
+    def _is_gpt(self, llm) -> bool:  # type: ignore # BUG? Name "_is_gpt" defined on line 20 hides name from outer scope
         return isinstance(llm, ChatOpenAI) and llm.openai_api_base is None

src/crewai/utilities/token_counter_callback.py

@@ -22,7 +22,7 @@ class TokenProcess:
     def sum_successful_requests(self, requests: int):
         self.successful_requests = self.successful_requests + requests
 
-    def get_summary(self) -> str:
+    def get_summary(self) -> Dict[str, Any]:
         return {
             "total_tokens": self.total_tokens,
             "prompt_tokens": self.prompt_tokens,