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feat: cache i18n prompts for efficient use

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This commit is contained in:
Greyson LaLonde
2025-11-03 07:39:05 -05:00
committed by GitHub
parent 40932af3fa
commit 60332e0b19
13 changed files with 227 additions and 201 deletions
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4
lib/crewai/src/crewai/agents/agent_adapters/openai_agents/structured_output_converter.py
View File

@@ -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)
)

22
lib/crewai/src/crewai/agents/agent_builder/base_agent.py
View File

@@ -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(
default=[], description="Callbacks to be used for the agent"
callbacks: list[Callable[[Any], Any]] = Field(
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

6
lib/crewai/src/crewai/agents/crew_agent_executor.py
View File

@@ -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

4
lib/crewai/src/crewai/agents/parser.py
View File

@@ -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

164
lib/crewai/src/crewai/crew.py
View File

@@ -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):
self._long_term_memory = self._long_term_memory or LongTermMemory()
self._short_term_memory = self._short_term_memory or ShortTermMemory(
def _initialize_default_memories(self) -> None:
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( # 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",
(
f"Sequential process error: Agent is missing in the task "
f"with the following description: {task.description}"
), # type: ignore # Dynamic string in error message
{},
"Sequential process error: Agent is missing in the task with the following description: {description}",
{"description": task.description},
)
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
# 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.crew = self
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):
i18n = I18N(prompt_file=self.prompt_file)
def _create_manager_agent(self) -> None:
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[Tool] | list[BaseTool],
new_tools: list[Tool] | list[BaseTool],
existing_tools: list[BaseTool],
new_tools: 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 cast(list[BaseTool], tools)
return self._merge_tools(tools, delegation_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 cast(list[BaseTool], tools)
return self._merge_tools(tools, platform_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 cast(list[BaseTool], tools)
return self._merge_tools(tools, mcp_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(
self, task: Task, tools: list[Tool] | list[BaseTool]
) -> list[BaseTool]:
def _add_platform_tools(self, task: Task, tools: 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(
self, task: Task, tools: list[Tool] | list[BaseTool]
) -> list[BaseTool]:
def _add_mcp_tools(self, task: Task, tools: 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"
)

37
lib/crewai/src/crewai/lite_agent.py
View File

@@ -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
) -> Callable | str | None:
cls, v: GuardrailCallable | 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))

33
lib/crewai/src/crewai/task.py
View File

@@ -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
) -> str | Callable | None:
cls, v: str | GuardrailCallable | 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

16
lib/crewai/src/crewai/tools/agent_tools/agent_tools.py
View File

@@ -1,8 +1,16 @@
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.tools.base_tool import BaseTool
from crewai.utilities.i18n import I18N
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
class AgentTools:
@@ -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"""

10
lib/crewai/src/crewai/tools/agent_tools/base_agent_tools.py
View File

@@ -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

51
lib/crewai/src/crewai/tools/tool_usage.py
View File

@@ -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:

17
lib/crewai/src/crewai/utilities/i18n.py
View File

@@ -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)

29
lib/crewai/src/crewai/utilities/prompts.py
View File

@@ -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
user: str
system: Annotated[str, "The system prompt component"]
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,

35
lib/crewai/src/crewai/utilities/reasoning_handler.py
View File

@@ -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,
i18n=self.i18n,
reasoning_agent=self.agent,
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,
i18n=self.i18n,
reasoning_agent=self.agent,
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,
i18n: I18N,
reasoning_agent: Agent,
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.
i18n: Internationalization utility for retrieving prompts.
reasoning_agent: The agent performing the reasoning.
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(
role=agent.role,
goal=agent.goal,
system_prompt = reasoning_agent.i18n.retrieve("reasoning", plan_type).format(
role=reasoning_agent.role,
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)