feat: cache i18n prompts for efficient use

lib/crewai/src/crewai/agents/agent_adapters/openai_agents/structured_output_converter.py

@@ -7,7 +7,7 @@ output conversion for OpenAI agents, supporting JSON and Pydantic model formats.
 from typing import Any
 
 from crewai.agents.agent_adapters.base_converter_adapter import BaseConverterAdapter
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import get_i18n
 
 
 class OpenAIConverterAdapter(BaseConverterAdapter):
@@ -59,7 +59,7 @@ class OpenAIConverterAdapter(BaseConverterAdapter):
             return base_prompt
 
         output_schema: str = (
-            I18N()
+            get_i18n()
             .slice("formatted_task_instructions")
             .format(output_format=self._schema)
         )

lib/crewai/src/crewai/agents/agent_builder/base_agent.py

@@ -29,7 +29,7 @@ from crewai.rag.embeddings.types import EmbedderConfig
 from crewai.security.security_config import SecurityConfig
 from crewai.tools.base_tool import BaseTool, Tool
 from crewai.utilities.config import process_config
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.logger import Logger
 from crewai.utilities.rpm_controller import RPMController
 from crewai.utilities.string_utils import interpolate_only
@@ -107,7 +107,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             Set private attributes.
     """
 
-    __hash__ = object.__hash__  # type: ignore
+    __hash__ = object.__hash__
     _logger: Logger = PrivateAttr(default_factory=lambda: Logger(verbose=False))
     _rpm_controller: RPMController | None = PrivateAttr(default=None)
     _request_within_rpm_limit: Any = PrivateAttr(default=None)
@@ -150,7 +150,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
     )
     crew: Any = Field(default=None, description="Crew to which the agent belongs.")
     i18n: I18N = Field(
-        default_factory=I18N, description="Internationalization settings."
+        default_factory=get_i18n, description="Internationalization settings."
     )
     cache_handler: CacheHandler | None = Field(
         default=None, description="An instance of the CacheHandler class."
@@ -180,8 +180,8 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         default_factory=SecurityConfig,
         description="Security configuration for the agent, including fingerprinting.",
     )
-    callbacks: list[Callable] = Field(
+    callbacks: list[Callable[[Any], Any]] = Field(
-        default=[], description="Callbacks to be used for the agent"
+        default_factory=list, description="Callbacks to be used for the agent"
     )
     adapted_agent: bool = Field(
         default=False, description="Whether the agent is adapted"
@@ -201,7 +201,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
 
     @model_validator(mode="before")
     @classmethod
-    def process_model_config(cls, values):
+    def process_model_config(cls, values: Any) -> dict[str, Any]:
         return process_config(values, cls)
 
     @field_validator("tools")
@@ -269,7 +269,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         return list(set(validated_mcps))
 
     @model_validator(mode="after")
-    def validate_and_set_attributes(self):
+    def validate_and_set_attributes(self) -> Self:
         # Validate required fields
         for field in ["role", "goal", "backstory"]:
             if getattr(self, field) is None:
@@ -301,7 +301,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             )
 
     @model_validator(mode="after")
-    def set_private_attrs(self):
+    def set_private_attrs(self) -> Self:
         """Set private attributes."""
         self._logger = Logger(verbose=self.verbose)
         if self.max_rpm and not self._rpm_controller:
@@ -313,7 +313,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         return self
 
     @property
-    def key(self):
+    def key(self) -> str:
         source = [
             self._original_role or self.role,
             self._original_goal or self.goal,
@@ -331,7 +331,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         pass
 
     @abstractmethod
-    def create_agent_executor(self, tools=None) -> None:
+    def create_agent_executor(self, tools: list[BaseTool] | None = None) -> None:
         pass
 
     @abstractmethod
@@ -443,5 +443,5 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             self._rpm_controller = rpm_controller
             self.create_agent_executor()
 
-    def set_knowledge(self, crew_embedder: EmbedderConfig | None = None):
+    def set_knowledge(self, crew_embedder: EmbedderConfig | None = None) -> None:
         pass

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

@@ -37,7 +37,7 @@ from crewai.utilities.agent_utils import (
     process_llm_response,
 )
 from crewai.utilities.constants import TRAINING_DATA_FILE
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.printer import Printer
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
 from crewai.utilities.training_handler import CrewTrainingHandler
@@ -65,7 +65,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
     def __init__(
         self,
-        llm: BaseLLM | Any | None,
+        llm: BaseLLM,
         task: Task,
         crew: Crew,
         agent: Agent,
@@ -106,7 +106,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             callbacks: Optional callbacks list.
             response_model: Optional Pydantic model for structured outputs.
         """
-        self._i18n: I18N = I18N()
+        self._i18n: I18N = get_i18n()
         self.llm = llm
         self.task = task
         self.agent = agent

lib/crewai/src/crewai/agents/parser.py

@@ -18,10 +18,10 @@ from crewai.agents.constants import (
     MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
     UNABLE_TO_REPAIR_JSON_RESULTS,
 )
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import get_i18n
 
 
-_I18N = I18N()
+_I18N = get_i18n()
 
 
 @dataclass

lib/crewai/src/crewai/crew.py

@@ -27,6 +27,7 @@ from pydantic import (
     model_validator,
 )
 from pydantic_core import PydanticCustomError
+from typing_extensions import Self
 
 from crewai.agent import Agent
 from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -70,7 +71,7 @@ from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
 from crewai.tools.agent_tools.agent_tools import AgentTools
-from crewai.tools.base_tool import BaseTool, Tool
+from crewai.tools.base_tool import BaseTool
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities.constants import NOT_SPECIFIED, TRAINING_DATA_FILE
 from crewai.utilities.crew.models import CrewContext
@@ -81,7 +82,7 @@ from crewai.utilities.formatter import (
     aggregate_raw_outputs_from_task_outputs,
     aggregate_raw_outputs_from_tasks,
 )
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import get_i18n
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.logger import Logger
 from crewai.utilities.planning_handler import CrewPlanner
@@ -195,7 +196,7 @@ class Crew(FlowTrackable, BaseModel):
     function_calling_llm: str | InstanceOf[LLM] | Any | None = Field(
         description="Language model that will run the agent.", default=None
     )
-    config: Json | dict[str, Any] | None = Field(default=None)
+    config: Json[dict[str, Any]] | dict[str, Any] | None = Field(default=None)
     id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
     share_crew: bool | None = Field(default=False)
     step_callback: Any | None = Field(
@@ -294,7 +295,9 @@ class Crew(FlowTrackable, BaseModel):
 
     @field_validator("config", mode="before")
     @classmethod
-    def check_config_type(cls, v: Json | dict[str, Any]) -> Json | dict[str, Any]:
+    def check_config_type(
+        cls, v: Json[dict[str, Any]] | dict[str, Any]
+    ) -> dict[str, Any]:
         """Validates that the config is a valid type.
         Args:
             v: The config to be validated.
@@ -310,7 +313,7 @@ class Crew(FlowTrackable, BaseModel):
         """set private attributes."""
 
         self._cache_handler = CacheHandler()
-        event_listener = EventListener()
+        event_listener = EventListener()  # type: ignore[no-untyped-call]
 
         if (
             is_tracing_enabled()
@@ -330,13 +333,13 @@ class Crew(FlowTrackable, BaseModel):
 
         return self
 
-    def _initialize_default_memories(self):
+    def _initialize_default_memories(self) -> None:
-        self._long_term_memory = self._long_term_memory or LongTermMemory()
+        self._long_term_memory = self._long_term_memory or LongTermMemory()  # type: ignore[no-untyped-call]
-        self._short_term_memory = self._short_term_memory or ShortTermMemory(
+        self._short_term_memory = self._short_term_memory or ShortTermMemory(  # type: ignore[no-untyped-call]
             crew=self,
             embedder_config=self.embedder,
         )
-        self._entity_memory = self.entity_memory or EntityMemory(
+        self._entity_memory = self.entity_memory or EntityMemory(  # type: ignore[no-untyped-call]
             crew=self, embedder_config=self.embedder
         )
 
@@ -380,7 +383,7 @@ class Crew(FlowTrackable, BaseModel):
         return self
 
     @model_validator(mode="after")
-    def check_manager_llm(self):
+    def check_manager_llm(self) -> Self:
         """Validates that the language model is set when using hierarchical process."""
         if self.process == Process.hierarchical:
             if not self.manager_llm and not self.manager_agent:
@@ -405,7 +408,7 @@ class Crew(FlowTrackable, BaseModel):
         return self
 
     @model_validator(mode="after")
-    def check_config(self):
+    def check_config(self) -> Self:
         """Validates that the crew is properly configured with agents and tasks."""
         if not self.config and not self.tasks and not self.agents:
             raise PydanticCustomError(
@@ -426,23 +429,20 @@ class Crew(FlowTrackable, BaseModel):
         return self
 
     @model_validator(mode="after")
-    def validate_tasks(self):
+    def validate_tasks(self) -> Self:
         if self.process == Process.sequential:
             for task in self.tasks:
                 if task.agent is None:
                     raise PydanticCustomError(
                         "missing_agent_in_task",
-                        (
+                        "Sequential process error: Agent is missing in the task with the following description: {description}",
-                            f"Sequential process error: Agent is missing in the task "
+                        {"description": task.description},
-                            f"with the following description: {task.description}"
-                        ),  # type: ignore # Dynamic string in error message
-                        {},
                     )
 
         return self
 
     @model_validator(mode="after")
-    def validate_end_with_at_most_one_async_task(self):
+    def validate_end_with_at_most_one_async_task(self) -> Self:
         """Validates that the crew ends with at most one asynchronous task."""
         final_async_task_count = 0
 
@@ -505,7 +505,9 @@ class Crew(FlowTrackable, BaseModel):
         return self
 
     @model_validator(mode="after")
-    def validate_async_task_cannot_include_sequential_async_tasks_in_context(self):
+    def validate_async_task_cannot_include_sequential_async_tasks_in_context(
+        self,
+    ) -> Self:
         """
         Validates that if a task is set to be executed asynchronously,
         it cannot include other asynchronous tasks in its context unless
@@ -527,7 +529,7 @@ class Crew(FlowTrackable, BaseModel):
         return self
 
     @model_validator(mode="after")
-    def validate_context_no_future_tasks(self):
+    def validate_context_no_future_tasks(self) -> Self:
         """Validates that a task's context does not include future tasks."""
         task_indices = {id(task): i for i, task in enumerate(self.tasks)}
 
@@ -561,7 +563,7 @@ class Crew(FlowTrackable, BaseModel):
         """
         return self.security_config.fingerprint
 
-    def _setup_from_config(self):
+    def _setup_from_config(self) -> None:
         """Initializes agents and tasks from the provided config."""
         if self.config is None:
             raise ValueError("Config should not be None.")
@@ -628,12 +630,12 @@ class Crew(FlowTrackable, BaseModel):
 
             for agent in train_crew.agents:
                 if training_data.get(str(agent.id)):
-                    result = TaskEvaluator(agent).evaluate_training_data(
+                    result = TaskEvaluator(agent).evaluate_training_data(  # type: ignore[arg-type]
                         training_data=training_data, agent_id=str(agent.id)
                     )
                     CrewTrainingHandler(filename).save_trained_data(
                         agent_id=str(agent.role),
-                        trained_data=result.model_dump(),  # type: ignore[arg-type]
+                        trained_data=result.model_dump(),
                     )
 
             crewai_event_bus.emit(
@@ -684,12 +686,8 @@ class Crew(FlowTrackable, BaseModel):
             self._set_tasks_callbacks()
             self._set_allow_crewai_trigger_context_for_first_task()
 
-            i18n = I18N(prompt_file=self.prompt_file)
-
             for agent in self.agents:
-                agent.i18n = i18n
+                agent.crew = self
-                # type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
-                agent.crew = self  # type: ignore[attr-defined]
                 agent.set_knowledge(crew_embedder=self.embedder)
                 # TODO: Create an AgentFunctionCalling protocol for future refactoring
                 if not agent.function_calling_llm:  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
@@ -753,10 +751,12 @@ class Crew(FlowTrackable, BaseModel):
         inputs = inputs or {}
         return await asyncio.to_thread(self.kickoff, inputs)
 
-    async def kickoff_for_each_async(self, inputs: list[dict]) -> list[CrewOutput]:
+    async def kickoff_for_each_async(
+        self, inputs: list[dict[str, Any]]
+    ) -> list[CrewOutput]:
         crew_copies = [self.copy() for _ in inputs]
 
-        async def run_crew(crew, input_data):
+        async def run_crew(crew: Self, input_data: Any) -> CrewOutput:
             return await crew.kickoff_async(inputs=input_data)
 
         tasks = [
@@ -775,7 +775,7 @@ class Crew(FlowTrackable, BaseModel):
         self._task_output_handler.reset()
         return results
 
-    def _handle_crew_planning(self):
+    def _handle_crew_planning(self) -> None:
         """Handles the Crew planning."""
         self._logger.log("info", "Planning the crew execution")
         result = CrewPlanner(
@@ -793,7 +793,7 @@ class Crew(FlowTrackable, BaseModel):
         output: TaskOutput,
         task_index: int,
         was_replayed: bool = False,
-    ):
+    ) -> None:
         if self._inputs:
             inputs = self._inputs
         else:
@@ -825,19 +825,21 @@ class Crew(FlowTrackable, BaseModel):
         self._create_manager_agent()
         return self._execute_tasks(self.tasks)
 
-    def _create_manager_agent(self):
+    def _create_manager_agent(self) -> None:
-        i18n = I18N(prompt_file=self.prompt_file)
         if self.manager_agent is not None:
             self.manager_agent.allow_delegation = True
             manager = self.manager_agent
             if manager.tools is not None and len(manager.tools) > 0:
                 self._logger.log(
-                    "warning", "Manager agent should not have tools", color="orange"
+                    "warning",
+                    "Manager agent should not have tools",
+                    color="bold_yellow",
                 )
                 manager.tools = []
                 raise Exception("Manager agent should not have tools")
         else:
             self.manager_llm = create_llm(self.manager_llm)
+            i18n = get_i18n(prompt_file=self.prompt_file)
             manager = Agent(
                 role=i18n.retrieve("hierarchical_manager_agent", "role"),
                 goal=i18n.retrieve("hierarchical_manager_agent", "goal"),
@@ -895,7 +897,7 @@ class Crew(FlowTrackable, BaseModel):
             tools_for_task = self._prepare_tools(
                 agent_to_use,
                 task,
-                cast(list[Tool] | list[BaseTool], tools_for_task),
+                tools_for_task,
             )
 
             self._log_task_start(task, agent_to_use.role)
@@ -915,7 +917,7 @@ class Crew(FlowTrackable, BaseModel):
                 future = task.execute_async(
                     agent=agent_to_use,
                     context=context,
-                    tools=cast(list[BaseTool], tools_for_task),
+                    tools=tools_for_task,
                 )
                 futures.append((task, future, task_index))
             else:
@@ -927,7 +929,7 @@ class Crew(FlowTrackable, BaseModel):
                 task_output = task.execute_sync(
                     agent=agent_to_use,
                     context=context,
-                    tools=cast(list[BaseTool], tools_for_task),
+                    tools=tools_for_task,
                 )
                 task_outputs.append(task_output)
                 self._process_task_result(task, task_output)
@@ -965,7 +967,7 @@ class Crew(FlowTrackable, BaseModel):
         return None
 
     def _prepare_tools(
-        self, agent: BaseAgent, task: Task, tools: list[Tool] | list[BaseTool]
+        self, agent: BaseAgent, task: Task, tools: list[BaseTool]
     ) -> list[BaseTool]:
         # Add delegation tools if agent allows delegation
         if hasattr(agent, "allow_delegation") and getattr(
@@ -1002,21 +1004,21 @@ class Crew(FlowTrackable, BaseModel):
             tools = self._add_mcp_tools(task, tools)
 
         # Return a list[BaseTool] compatible with Task.execute_sync and execute_async
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _get_agent_to_use(self, task: Task) -> BaseAgent | None:
         if self.process == Process.hierarchical:
             return self.manager_agent
         return task.agent
 
+    @staticmethod
     def _merge_tools(
-        self,
+        existing_tools: list[BaseTool],
-        existing_tools: list[Tool] | list[BaseTool],
+        new_tools: list[BaseTool],
-        new_tools: list[Tool] | list[BaseTool],
     ) -> list[BaseTool]:
         """Merge new tools into existing tools list, avoiding duplicates."""
         if not new_tools:
-            return cast(list[BaseTool], existing_tools)
+            return existing_tools
 
         # Create mapping of tool names to new tools
         new_tool_map = {tool.name: tool for tool in new_tools}
@@ -1027,63 +1029,62 @@ class Crew(FlowTrackable, BaseModel):
         # Add all new tools
         tools.extend(new_tools)
 
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _inject_delegation_tools(
         self,
-        tools: list[Tool] | list[BaseTool],
+        tools: list[BaseTool],
         task_agent: BaseAgent,
         agents: list[BaseAgent],
     ) -> list[BaseTool]:
         if hasattr(task_agent, "get_delegation_tools"):
             delegation_tools = task_agent.get_delegation_tools(agents)
             # Cast delegation_tools to the expected type for _merge_tools
-            return self._merge_tools(tools, cast(list[BaseTool], delegation_tools))
+            return self._merge_tools(tools, delegation_tools)
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _inject_platform_tools(
         self,
-        tools: list[Tool] | list[BaseTool],
+        tools: list[BaseTool],
         task_agent: BaseAgent,
     ) -> list[BaseTool]:
         apps = getattr(task_agent, "apps", None) or []
 
         if hasattr(task_agent, "get_platform_tools") and apps:
             platform_tools = task_agent.get_platform_tools(apps=apps)
-            return self._merge_tools(tools, cast(list[BaseTool], platform_tools))
+            return self._merge_tools(tools, platform_tools)
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _inject_mcp_tools(
         self,
-        tools: list[Tool] | list[BaseTool],
+        tools: list[BaseTool],
         task_agent: BaseAgent,
     ) -> list[BaseTool]:
         mcps = getattr(task_agent, "mcps", None) or []
         if hasattr(task_agent, "get_mcp_tools") and mcps:
             mcp_tools = task_agent.get_mcp_tools(mcps=mcps)
-            return self._merge_tools(tools, cast(list[BaseTool], mcp_tools))
+            return self._merge_tools(tools, mcp_tools)
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _add_multimodal_tools(
-        self, agent: BaseAgent, tools: list[Tool] | list[BaseTool]
+        self, agent: BaseAgent, tools: list[BaseTool]
     ) -> list[BaseTool]:
         if hasattr(agent, "get_multimodal_tools"):
             multimodal_tools = agent.get_multimodal_tools()
-            # Cast multimodal_tools to the expected type for _merge_tools
             return self._merge_tools(tools, cast(list[BaseTool], multimodal_tools))
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _add_code_execution_tools(
-        self, agent: BaseAgent, tools: list[Tool] | list[BaseTool]
+        self, agent: BaseAgent, tools: list[BaseTool]
     ) -> list[BaseTool]:
         if hasattr(agent, "get_code_execution_tools"):
             code_tools = agent.get_code_execution_tools()
             # Cast code_tools to the expected type for _merge_tools
             return self._merge_tools(tools, cast(list[BaseTool], code_tools))
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _add_delegation_tools(
-        self, task: Task, tools: list[Tool] | list[BaseTool]
+        self, task: Task, tools: list[BaseTool]
     ) -> list[BaseTool]:
         agents_for_delegation = [agent for agent in self.agents if agent != task.agent]
         if len(self.agents) > 1 and len(agents_for_delegation) > 0 and task.agent:
@@ -1092,25 +1093,21 @@ class Crew(FlowTrackable, BaseModel):
             tools = self._inject_delegation_tools(
                 tools, task.agent, agents_for_delegation
             )
-        return cast(list[BaseTool], tools)
+        return tools
 
-    def _add_platform_tools(
+    def _add_platform_tools(self, task: Task, tools: list[BaseTool]) -> list[BaseTool]:
-        self, task: Task, tools: list[Tool] | list[BaseTool]
-    ) -> list[BaseTool]:
         if task.agent:
             tools = self._inject_platform_tools(tools, task.agent)
 
-        return cast(list[BaseTool], tools or [])
+        return tools or []
 
-    def _add_mcp_tools(
+    def _add_mcp_tools(self, task: Task, tools: list[BaseTool]) -> list[BaseTool]:
-        self, task: Task, tools: list[Tool] | list[BaseTool]
-    ) -> list[BaseTool]:
         if task.agent:
             tools = self._inject_mcp_tools(tools, task.agent)
 
-        return cast(list[BaseTool], tools or [])
+        return tools or []
 
-    def _log_task_start(self, task: Task, role: str = "None"):
+    def _log_task_start(self, task: Task, role: str = "None") -> None:
         if self.output_log_file:
             self._file_handler.log(
                 task_name=task.name,  # type: ignore[arg-type]
@@ -1120,7 +1117,7 @@ class Crew(FlowTrackable, BaseModel):
             )
 
     def _update_manager_tools(
-        self, task: Task, tools: list[Tool] | list[BaseTool]
+        self, task: Task, tools: list[BaseTool]
     ) -> list[BaseTool]:
         if self.manager_agent:
             if task.agent:
@@ -1129,7 +1126,7 @@ class Crew(FlowTrackable, BaseModel):
                 tools = self._inject_delegation_tools(
                     tools, self.manager_agent, self.agents
                 )
-        return cast(list[BaseTool], tools)
+        return tools
 
     def _get_context(self, task: Task, task_outputs: list[TaskOutput]) -> str:
         if not task.context:
@@ -1280,7 +1277,7 @@ class Crew(FlowTrackable, BaseModel):
 
         return required_inputs
 
-    def copy(self):
+    def copy(self) -> Crew:  # type: ignore[override]
         """
         Creates a deep copy of the Crew instance.
 
@@ -1311,7 +1308,7 @@ class Crew(FlowTrackable, BaseModel):
         manager_agent = self.manager_agent.copy() if self.manager_agent else None
         manager_llm = shallow_copy(self.manager_llm) if self.manager_llm else None
 
-        task_mapping = {}
+        task_mapping: dict[str, Any] = {}
 
         cloned_tasks = []
         existing_knowledge_sources = shallow_copy(self.knowledge_sources)
@@ -1373,7 +1370,6 @@ class Crew(FlowTrackable, BaseModel):
             )
             for task in self.tasks
         ]
-        # type: ignore # "interpolate_inputs" of "Agent" does not return a value (it only ever returns None)
         for agent in self.agents:
             agent.interpolate_inputs(inputs)
 
@@ -1463,7 +1459,7 @@ class Crew(FlowTrackable, BaseModel):
             )
             raise
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return (
             f"Crew(id={self.id}, process={self.process}, "
             f"number_of_agents={len(self.agents)}, "
@@ -1520,7 +1516,9 @@ class Crew(FlowTrackable, BaseModel):
             if (system := config.get("system")) is not None:
                 name = config.get("name")
                 try:
-                    reset_fn: Callable = cast(Callable, config.get("reset"))
+                    reset_fn: Callable[[Any], Any] = cast(
+                        Callable[[Any], Any], config.get("reset")
+                    )
                     reset_fn(system)
                     self._logger.log(
                         "info",
@@ -1551,7 +1549,9 @@ class Crew(FlowTrackable, BaseModel):
             raise RuntimeError(f"{name} memory system is not initialized")
 
         try:
-            reset_fn: Callable = cast(Callable, config.get("reset"))
+            reset_fn: Callable[[Any], Any] = cast(
+                Callable[[Any], Any], config.get("reset")
+            )
             reset_fn(system)
             self._logger.log(
                 "info",
@@ -1564,7 +1564,7 @@ class Crew(FlowTrackable, BaseModel):
                 f"Failed to reset {name} memory: {e!s}"
             ) from e
 
-    def _get_memory_systems(self):
+    def _get_memory_systems(self) -> dict[str, Any]:
         """Get all available memory systems with their configuration.
 
         Returns:
@@ -1572,10 +1572,10 @@ class Crew(FlowTrackable, BaseModel):
             display names.
         """
 
-        def default_reset(memory):
+        def default_reset(memory: Any) -> Any:
             return memory.reset()
 
-        def knowledge_reset(memory):
+        def knowledge_reset(memory: Any) -> Any:
             return self.reset_knowledge(memory)
 
         # Get knowledge for agents
@@ -1635,7 +1635,7 @@ class Crew(FlowTrackable, BaseModel):
         for ks in knowledges:
             ks.reset()
 
-    def _set_allow_crewai_trigger_context_for_first_task(self):
+    def _set_allow_crewai_trigger_context_for_first_task(self) -> None:
         crewai_trigger_payload = self._inputs and self._inputs.get(
             "crewai_trigger_payload"
         )

lib/crewai/src/crewai/lite_agent.py

@@ -61,7 +61,7 @@ from crewai.utilities.agent_utils import (
 from crewai.utilities.converter import generate_model_description
 from crewai.utilities.guardrail import process_guardrail
 from crewai.utilities.guardrail_types import GuardrailCallable, GuardrailType
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.printer import Printer
 from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -90,8 +90,6 @@ class LiteAgent(FlowTrackable, BaseModel):
     """
 
     model_config = {"arbitrary_types_allowed": True}
-
-    # Core Agent Properties
     id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
     role: str = Field(description="Role of the agent")
     goal: str = Field(description="Goal of the agent")
@@ -102,8 +100,6 @@ class LiteAgent(FlowTrackable, BaseModel):
     tools: list[BaseTool] = Field(
         default_factory=list, description="Tools at agent's disposal"
     )
-
-    # Execution Control Properties
     max_iterations: int = Field(
         default=15, description="Maximum number of iterations for tool usage"
     )
@@ -120,24 +116,17 @@ class LiteAgent(FlowTrackable, BaseModel):
     )
     request_within_rpm_limit: Callable[[], bool] | None = Field(
         default=None,
-        description="Callback to check if the request is within the RPM limit",
+        description="Callback to check if the request is within the RPM8 limit",
     )
     i18n: I18N = Field(
-        default_factory=I18N, description="Internationalization settings."
+        default_factory=get_i18n, description="Internationalization settings."
     )
-
-    # Output and Formatting Properties
     response_format: type[BaseModel] | None = Field(
         default=None, description="Pydantic model for structured output"
     )
     verbose: bool = Field(
         default=False, description="Whether to print execution details"
     )
-    callbacks: list[Callable] = Field(
-        default_factory=list, description="Callbacks to be used for the agent"
-    )
-
-    # Guardrail Properties
     guardrail: GuardrailType | None = Field(
         default=None,
         description="Function or string description of a guardrail to validate agent output",
@@ -145,17 +134,12 @@ class LiteAgent(FlowTrackable, BaseModel):
     guardrail_max_retries: int = Field(
         default=3, description="Maximum number of retries when guardrail fails"
     )
-
-    # State and Results
     tools_results: list[dict[str, Any]] = Field(
         default_factory=list, description="Results of the tools used by the agent."
     )
-
-    # Reference of Agent
     original_agent: BaseAgent | None = Field(
         default=None, description="Reference to the agent that created this LiteAgent"
     )
-    # Private Attributes
     _parsed_tools: list[CrewStructuredTool] = PrivateAttr(default_factory=list)
     _token_process: TokenProcess = PrivateAttr(default_factory=TokenProcess)
     _cache_handler: CacheHandler = PrivateAttr(default_factory=CacheHandler)
@@ -165,6 +149,7 @@ class LiteAgent(FlowTrackable, BaseModel):
     _printer: Printer = PrivateAttr(default_factory=Printer)
     _guardrail: GuardrailCallable | None = PrivateAttr(default=None)
     _guardrail_retry_count: int = PrivateAttr(default=0)
+    _callbacks: list[TokenCalcHandler] = PrivateAttr(default_factory=list)
 
     @model_validator(mode="after")
     def setup_llm(self) -> Self:
@@ -174,15 +159,13 @@ class LiteAgent(FlowTrackable, BaseModel):
             raise ValueError(
                 f"Expected LLM instance of type BaseLLM, got {type(self.llm).__name__}"
             )
-
-        # Initialize callbacks
         token_callback = TokenCalcHandler(token_cost_process=self._token_process)
         self._callbacks = [token_callback]
 
         return self
 
     @model_validator(mode="after")
-    def parse_tools(self):
+    def parse_tools(self) -> Self:
         """Parse the tools and convert them to CrewStructuredTool instances."""
         self._parsed_tools = parse_tools(self.tools)
 
@@ -201,7 +184,7 @@ class LiteAgent(FlowTrackable, BaseModel):
                 )
             self._guardrail = cast(
                 GuardrailCallable,
-                LLMGuardrail(description=self.guardrail, llm=self.llm),
+                cast(object, LLMGuardrail(description=self.guardrail, llm=self.llm)),
             )
 
         return self
@@ -209,8 +192,8 @@ class LiteAgent(FlowTrackable, BaseModel):
     @field_validator("guardrail", mode="before")
     @classmethod
     def validate_guardrail_function(
-        cls, v: Callable | str | None
+        cls, v: GuardrailCallable | str | None
-    ) -> Callable | str | None:
+    ) -> GuardrailCallable | str | None:
         """Validate that the guardrail function has the correct signature.
 
         If v is a callable, validate that it has the correct signature.
@@ -559,7 +542,7 @@ class LiteAgent(FlowTrackable, BaseModel):
         self._show_logs(formatted_answer)
         return formatted_answer
 
-    def _show_logs(self, formatted_answer: AgentAction | AgentFinish):
+    def _show_logs(self, formatted_answer: AgentAction | AgentFinish) -> None:
         """Show logs for the agent's execution."""
         crewai_event_bus.emit(
             self,
@@ -574,4 +557,4 @@ class LiteAgent(FlowTrackable, BaseModel):
         self, text: str, role: Literal["user", "assistant", "system"] = "assistant"
     ) -> None:
         """Append a message to the message list with the given role."""
-        self._messages.append(cast(LLMMessage, format_message_for_llm(text, role=role)))
+        self._messages.append(format_message_for_llm(text, role=role))

lib/crewai/src/crewai/task.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from collections.abc import Callable
 from concurrent.futures import Future
 from copy import copy as shallow_copy
 import datetime
@@ -29,6 +28,7 @@ from pydantic import (
     model_validator,
 )
 from pydantic_core import PydanticCustomError
+from typing_extensions import Self
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.events.event_bus import crewai_event_bus
@@ -52,7 +52,7 @@ from crewai.utilities.guardrail_types import (
     GuardrailType,
     GuardrailsType,
 )
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.printer import Printer
 from crewai.utilities.string_utils import interpolate_only
 
@@ -90,7 +90,7 @@ class Task(BaseModel):
     used_tools: int = 0
     tools_errors: int = 0
     delegations: int = 0
-    i18n: I18N = Field(default_factory=I18N)
+    i18n: I18N = Field(default_factory=get_i18n)
     name: str | None = Field(default=None)
     prompt_context: str | None = None
     description: str = Field(description="Description of the actual task.")
@@ -207,8 +207,8 @@ class Task(BaseModel):
     @field_validator("guardrail")
     @classmethod
     def validate_guardrail_function(
-        cls, v: str | Callable | None
+        cls, v: str | GuardrailCallable | None
-    ) -> str | Callable | None:
+    ) -> str | GuardrailCallable | None:
         """
         If v is a callable, validate that the guardrail function has the correct signature and behavior.
         If v is a string, return it as is.
@@ -265,11 +265,11 @@ class Task(BaseModel):
 
     @model_validator(mode="before")
     @classmethod
-    def process_model_config(cls, values):
+    def process_model_config(cls, values: dict[str, Any]) -> dict[str, Any]:
         return process_config(values, cls)
 
     @model_validator(mode="after")
-    def validate_required_fields(self):
+    def validate_required_fields(self) -> Self:
         required_fields = ["description", "expected_output"]
         for field in required_fields:
             if getattr(self, field) is None:
@@ -418,14 +418,14 @@ class Task(BaseModel):
         return self
 
     @model_validator(mode="after")
-    def check_tools(self):
+    def check_tools(self) -> Self:
         """Check if the tools are set."""
         if not self.tools and self.agent and self.agent.tools:
-            self.tools.extend(self.agent.tools)
+            self.tools = self.agent.tools
         return self
 
     @model_validator(mode="after")
-    def check_output(self):
+    def check_output(self) -> Self:
         """Check if an output type is set."""
         output_types = [self.output_json, self.output_pydantic]
         if len([type for type in output_types if type]) > 1:
@@ -437,7 +437,7 @@ class Task(BaseModel):
         return self
 
     @model_validator(mode="after")
-    def handle_max_retries_deprecation(self):
+    def handle_max_retries_deprecation(self) -> Self:
         if self.max_retries is not None:
             warnings.warn(
                 "The 'max_retries' parameter is deprecated and will be removed in CrewAI v1.0.0. "
@@ -518,7 +518,7 @@ 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))
+            crewai_event_bus.emit(self, TaskStartedEvent(context=context, task=self))  # type: ignore[no-untyped-call]
             result = agent.execute_task(
                 task=self,
                 context=context,
@@ -576,12 +576,13 @@ class Task(BaseModel):
                 )
                 self._save_file(content)
             crewai_event_bus.emit(
-                self, TaskCompletedEvent(output=task_output, task=self)
+                self,
+                TaskCompletedEvent(output=task_output, task=self),  # type: ignore[no-untyped-call]
             )
             return task_output
         except Exception as e:
             self.end_time = datetime.datetime.now()
-            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))
+            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))  # type: ignore[no-untyped-call]
             raise e  # Re-raise the exception after emitting the event
 
     def prompt(self) -> str:
@@ -786,7 +787,7 @@ Follow these guidelines:
             return OutputFormat.PYDANTIC
         return OutputFormat.RAW
 
-    def _save_file(self, result: dict | str | Any) -> None:
+    def _save_file(self, result: dict[str, Any] | str | Any) -> None:
         """Save task output to a file.
 
         Note:
@@ -838,7 +839,7 @@ Follow these guidelines:
             ) from e
         return
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return f"Task(description={self.description}, expected_output={self.expected_output})"
 
     @property

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

@@ -1,6 +1,14 @@
-from crewai.agents.agent_builder.base_agent import BaseAgent
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
 from crewai.tools.agent_tools.ask_question_tool import AskQuestionTool
 from crewai.tools.agent_tools.delegate_work_tool import DelegateWorkTool
+from crewai.utilities.i18n import get_i18n
+
+
+if TYPE_CHECKING:
+    from crewai.agents.agent_builder.base_agent import BaseAgent
     from crewai.tools.base_tool import BaseTool
     from crewai.utilities.i18n import I18N
 
@@ -10,7 +18,7 @@ class AgentTools:
 
     def __init__(self, agents: list[BaseAgent], i18n: I18N | None = None) -> None:
         self.agents = agents
-        self.i18n = i18n if i18n is not None else I18N()
+        self.i18n = i18n if i18n is not None else get_i18n()
 
     def tools(self) -> list[BaseTool]:
         """Get all available agent tools"""

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

@@ -1,12 +1,12 @@
 import logging
+from typing import Any
 
 from pydantic import Field
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.task import Task
 from crewai.tools.base_tool import BaseTool
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
-
 
 
 logger = logging.getLogger(__name__)
@@ -17,7 +17,7 @@ class BaseAgentTool(BaseTool):
 
     agents: list[BaseAgent] = Field(description="List of available agents")
     i18n: I18N = Field(
-        default_factory=I18N, description="Internationalization settings"
+        default_factory=get_i18n, description="Internationalization settings"
     )
 
     def sanitize_agent_name(self, name: str) -> str:
@@ -40,7 +40,7 @@ class BaseAgentTool(BaseTool):
         return normalized.replace('"', "").casefold()
 
     @staticmethod
-    def _get_coworker(coworker: str | None, **kwargs) -> str | None:
+    def _get_coworker(coworker: str | None, **kwargs: Any) -> str | None:
         coworker = coworker or kwargs.get("co_worker") or kwargs.get("coworker")
         if coworker:
             is_list = coworker.startswith("[") and coworker.endswith("]")
@@ -83,7 +83,7 @@ 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")
+            agent = [
                 available_agent
                 for available_agent in self.agents
                 if self.sanitize_agent_name(available_agent.role) == sanitized_name

lib/crewai/src/crewai/tools/tool_usage.py

@@ -7,10 +7,10 @@ import json
 from json import JSONDecodeError
 from textwrap import dedent
 import time
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Literal
 
 import json5
-from json_repair import repair_json  # type: ignore[import-untyped,import-error]
+from json_repair import repair_json  # type: ignore[import-untyped]
 
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.tool_usage_events import (
@@ -28,7 +28,7 @@ from crewai.utilities.agent_utils import (
     render_text_description_and_args,
 )
 from crewai.utilities.converter import Converter
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.printer import Printer
 
 
@@ -39,7 +39,18 @@ if TYPE_CHECKING:
     from crewai.llm import LLM
     from crewai.task import Task
 
-OPENAI_BIGGER_MODELS = [
+
+OPENAI_BIGGER_MODELS: list[
+    Literal[
+        "gpt-4",
+        "gpt-4o",
+        "o1-preview",
+        "o1-mini",
+        "o1",
+        "o3",
+        "o3-mini",
+    ]
+] = [
     "gpt-4",
     "gpt-4o",
     "o1-preview",
@@ -81,7 +92,7 @@ class ToolUsage:
         action: Any = None,
         fingerprint_context: dict[str, str] | None = None,
     ) -> None:
-        self._i18n: I18N = agent.i18n if agent else I18N()
+        self._i18n: I18N = agent.i18n if agent else get_i18n()
         self._printer: Printer = Printer()
         self._telemetry: Telemetry = Telemetry()
         self._run_attempts: int = 1
@@ -100,12 +111,14 @@ class ToolUsage:
         # Set the maximum parsing attempts for bigger models
         if (
             self.function_calling_llm
-            and self.function_calling_llm in OPENAI_BIGGER_MODELS
+            and self.function_calling_llm.model in OPENAI_BIGGER_MODELS
         ):
             self._max_parsing_attempts = 2
             self._remember_format_after_usages = 4
 
-    def parse_tool_calling(self, tool_string: str):
+    def parse_tool_calling(
+        self, tool_string: str
+    ) -> ToolCalling | InstructorToolCalling | ToolUsageError:
         """Parse the tool string and return the tool calling."""
         return self._tool_calling(tool_string)
 
@@ -153,7 +166,7 @@ class ToolUsage:
         tool: CrewStructuredTool,
         calling: ToolCalling | InstructorToolCalling,
     ) -> str:
-        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)
+        if self._check_tool_repeated_usage(calling=calling):
             try:
                 result = self._i18n.errors("task_repeated_usage").format(
                     tool_names=self.tools_names
@@ -163,7 +176,7 @@ class ToolUsage:
                     tool_name=tool.name,
                     attempts=self._run_attempts,
                 )
-                return self._format_result(result=result)  # type: ignore #  "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
+                return self._format_result(result=result)
 
             except Exception:
                 if self.task:
@@ -241,7 +254,7 @@ class ToolUsage:
                     try:
                         acceptable_args = tool.args_schema.model_json_schema()[
                             "properties"
-                        ].keys()  # type: ignore
+                        ].keys()
                         arguments = {
                             k: v
                             for k, v in calling.arguments.items()
@@ -276,19 +289,19 @@ class ToolUsage:
                         self._printer.print(
                             content=f"\n\n{error_message}\n", color="red"
                         )
-                    return error  # type: ignore # No return value expected
+                    return error
 
                 if self.task:
                     self.task.increment_tools_errors()
-                return self.use(calling=calling, tool_string=tool_string)  # type: ignore # No return value expected
+                return self.use(calling=calling, tool_string=tool_string)
 
             if self.tools_handler:
                 should_cache = True
                 if (
                     hasattr(available_tool, "cache_function")
-                    and available_tool.cache_function  # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
+                    and available_tool.cache_function
                 ):
-                    should_cache = available_tool.cache_function(  # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
+                    should_cache = available_tool.cache_function(
                         calling.arguments, result
                     )
 
@@ -300,7 +313,7 @@ class ToolUsage:
             tool_name=tool.name,
             attempts=self._run_attempts,
         )
-        result = self._format_result(result=result)  # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
+        result = self._format_result(result=result)
         data = {
             "result": result,
             "tool_name": tool.name,
@@ -508,7 +521,7 @@ class ToolUsage:
                     self.task.increment_tools_errors()
                 if self.agent and self.agent.verbose:
                     self._printer.print(content=f"\n\n{e}\n", color="red")
-                return ToolUsageError(  # type: ignore # Incompatible return value type (got "ToolUsageError", expected "ToolCalling | InstructorToolCalling")
+                return ToolUsageError(
                     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)
@@ -567,7 +580,7 @@ class ToolUsage:
         # If all parsing attempts fail, raise an error
         raise Exception(error_message)
 
-    def _emit_validate_input_error(self, final_error: str):
+    def _emit_validate_input_error(self, final_error: str) -> None:
         tool_selection_data = {
             "agent_key": getattr(self.agent, "key", None) if self.agent else None,
             "agent_role": getattr(self.agent, "role", None) if self.agent else None,
@@ -636,7 +649,7 @@ class ToolUsage:
 
     def _prepare_event_data(
         self, tool: Any, tool_calling: ToolCalling | InstructorToolCalling
-    ) -> dict:
+    ) -> dict[str, Any]:
         event_data = {
             "run_attempts": self._run_attempts,
             "delegations": self.task.delegations if self.task else 0,
@@ -660,7 +673,7 @@ class ToolUsage:
 
         return event_data
 
-    def _add_fingerprint_metadata(self, arguments: dict) -> dict:
+    def _add_fingerprint_metadata(self, arguments: dict[str, Any]) -> dict[str, Any]:
         """Add fingerprint metadata to tool arguments if available.
 
         Args:

lib/crewai/src/crewai/utilities/i18n.py

@@ -1,5 +1,6 @@
 """Internationalization support for CrewAI prompts and messages."""
 
+from functools import lru_cache
 import json
 import os
 from typing import Literal
@@ -108,3 +109,19 @@ class I18N(BaseModel):
             return self._prompts[kind][key]
         except Exception as e:
             raise Exception(f"Prompt for '{kind}':'{key}'  not found.") from e
+
+
+@lru_cache(maxsize=None)
+def get_i18n(prompt_file: str | None = None) -> I18N:
+    """Get a cached I18N instance.
+
+    This function caches I18N instances to avoid redundant file I/O and JSON parsing.
+    Each unique prompt_file path gets its own cached instance.
+
+    Args:
+        prompt_file: Optional custom prompt file path. Defaults to None (uses built-in prompts).
+
+    Returns:
+        Cached I18N instance.
+    """
+    return I18N(prompt_file=prompt_file)

lib/crewai/src/crewai/utilities/prompts.py

@@ -1,29 +1,38 @@
+"""Prompt generation and management utilities for CrewAI agents."""
+
 from __future__ import annotations
 
-from typing import Any, TypedDict
+from typing import Annotated, Any, Literal, TypedDict
 
 from pydantic import BaseModel, Field
 
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N, get_i18n
 
 
 class StandardPromptResult(TypedDict):
     """Result with only prompt field for standard mode."""
 
-    prompt: str
+    prompt: Annotated[str, "The generated prompt string"]
 
 
 class SystemPromptResult(StandardPromptResult):
     """Result with system, user, and prompt fields for system prompt mode."""
 
-    system: str
+    system: Annotated[str, "The system prompt component"]
-    user: str
+    user: Annotated[str, "The user prompt component"]
+
+
+COMPONENTS = Literal["role_playing", "tools", "no_tools", "task"]
 
 
 class Prompts(BaseModel):
-    """Manages and generates prompts for a generic agent."""
+    """Manages and generates prompts for a generic agent.
 
-    i18n: I18N = Field(default_factory=I18N)
+    Notes:
+        - Need to refactor so that prompt is not tightly coupled to agent.
+    """
+
+    i18n: I18N = Field(default_factory=get_i18n)
     has_tools: bool = Field(
         default=False, description="Indicates if the agent has access to tools"
     )
@@ -36,7 +45,7 @@ class Prompts(BaseModel):
     response_template: str | None = Field(
         default=None, description="Custom response prompt template"
     )
-    use_system_prompt: bool | None = Field(
+    use_system_prompt: bool = Field(
         default=False,
         description="Whether to use the system prompt when no custom templates are provided",
     )
@@ -48,7 +57,7 @@ class Prompts(BaseModel):
         Returns:
             A dictionary containing the constructed prompt(s).
         """
-        slices: list[str] = ["role_playing"]
+        slices: list[COMPONENTS] = ["role_playing"]
         if self.has_tools:
             slices.append("tools")
         else:
@@ -77,7 +86,7 @@ class Prompts(BaseModel):
 
     def _build_prompt(
         self,
-        components: list[str],
+        components: list[COMPONENTS],
         system_template: str | None = None,
         prompt_template: str | None = None,
         response_template: str | None = None,

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

@@ -13,7 +13,6 @@ from crewai.events.types.reasoning_events import (
 )
 from crewai.llm import LLM
 from crewai.task import Task
-from crewai.utilities.i18n import I18N
 
 
 class ReasoningPlan(BaseModel):
@@ -62,7 +61,6 @@ class AgentReasoning:
         agent: The agent performing the reasoning.
         llm: The language model used for reasoning.
         logger: Logger for logging events and errors.
-        i18n: Internationalization utility for retrieving prompts.
     """
 
     def __init__(self, task: Task, agent: Agent) -> None:
@@ -76,7 +74,6 @@ class AgentReasoning:
         self.agent = agent
         self.llm = cast(LLM, agent.llm)
         self.logger = logging.getLogger(__name__)
-        self.i18n = I18N()
 
     def handle_agent_reasoning(self) -> AgentReasoningOutput:
         """Public method for the reasoning process that creates and refines a plan for the task until the agent is ready to execute it.
@@ -163,8 +160,7 @@ class AgentReasoning:
             llm=self.llm,
             prompt=reasoning_prompt,
             task=self.task,
-            agent=self.agent,
+            reasoning_agent=self.agent,
-            i18n=self.i18n,
             backstory=self.__get_agent_backstory(),
             plan_type="initial_plan",
         )
@@ -208,8 +204,7 @@ class AgentReasoning:
                     llm=self.llm,
                     prompt=refine_prompt,
                     task=self.task,
-                    agent=self.agent,
+                    reasoning_agent=self.agent,
-                    i18n=self.i18n,
                     backstory=self.__get_agent_backstory(),
                     plan_type="refine_plan",
                 )
@@ -238,14 +233,14 @@ class AgentReasoning:
         self.logger.debug(f"Using function calling for {prompt_type} reasoning")
 
         try:
-            system_prompt = self.i18n.retrieve("reasoning", prompt_type).format(
+            system_prompt = self.agent.i18n.retrieve("reasoning", prompt_type).format(
                 role=self.agent.role,
                 goal=self.agent.goal,
                 backstory=self.__get_agent_backstory(),
             )
 
             # Prepare a simple callable that just returns the tool arguments as JSON
-            def _create_reasoning_plan(plan: str, ready: bool = True):
+            def _create_reasoning_plan(plan: str, ready: bool = True) -> str:
                 """Return the reasoning plan result in JSON string form."""
                 return json.dumps({"plan": plan, "ready": ready})
 
@@ -281,7 +276,9 @@ class AgentReasoning:
             )
 
             try:
-                system_prompt = self.i18n.retrieve("reasoning", prompt_type).format(
+                system_prompt = self.agent.i18n.retrieve(
+                    "reasoning", prompt_type
+                ).format(
                     role=self.agent.role,
                     goal=self.agent.goal,
                     backstory=self.__get_agent_backstory(),
@@ -326,7 +323,7 @@ class AgentReasoning:
         """
         available_tools = self.__format_available_tools()
 
-        return self.i18n.retrieve("reasoning", "create_plan_prompt").format(
+        return self.agent.i18n.retrieve("reasoning", "create_plan_prompt").format(
             role=self.agent.role,
             goal=self.agent.goal,
             backstory=self.__get_agent_backstory(),
@@ -357,7 +354,7 @@ class AgentReasoning:
         Returns:
             str: The refine prompt.
         """
-        return self.i18n.retrieve("reasoning", "refine_plan_prompt").format(
+        return self.agent.i18n.retrieve("reasoning", "refine_plan_prompt").format(
             role=self.agent.role,
             goal=self.agent.goal,
             backstory=self.__get_agent_backstory(),
@@ -405,8 +402,7 @@ def _call_llm_with_reasoning_prompt(
     llm: LLM,
     prompt: str,
     task: Task,
-    agent: Agent,
+    reasoning_agent: Agent,
-    i18n: I18N,
     backstory: str,
     plan_type: Literal["initial_plan", "refine_plan"],
 ) -> str:
@@ -416,17 +412,16 @@ def _call_llm_with_reasoning_prompt(
         llm: The language model to use.
         prompt: The prompt to send to the LLM.
         task: The task for which the agent is reasoning.
-        agent: The agent performing the reasoning.
+        reasoning_agent: The agent performing the reasoning.
-        i18n: Internationalization utility for retrieving prompts.
         backstory: The agent's backstory.
         plan_type: The type of plan being created ("initial_plan" or "refine_plan").
 
     Returns:
         The LLM response.
     """
-    system_prompt = i18n.retrieve("reasoning", plan_type).format(
+    system_prompt = reasoning_agent.i18n.retrieve("reasoning", plan_type).format(
-        role=agent.role,
+        role=reasoning_agent.role,
-        goal=agent.goal,
+        goal=reasoning_agent.goal,
         backstory=backstory,
     )
 
@@ -436,6 +431,6 @@ def _call_llm_with_reasoning_prompt(
             {"role": "user", "content": prompt},
         ],
         from_task=task,
-        from_agent=agent,
+        from_agent=reasoning_agent,
     )
     return str(response)