mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-09 08:08:32 +00:00
Moving copy functionality from Agent to BaseAgent
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@@ -267,31 +267,6 @@ class Agent(BaseAgent):
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def get_output_converter(self, llm, text, model, instructions):
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return Converter(llm=llm, text=text, model=model, instructions=instructions)
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def copy(self):
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"""Create a deep copy of the Agent."""
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exclude = {
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"id",
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"_logger",
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"_rpm_controller",
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"_request_within_rpm_limit",
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"_token_process",
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"agent_executor",
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"tools",
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"tools_handler",
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"cache_handler",
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"llm",
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}
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# Copy llm and clear callbacks
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existing_llm = shallow_copy(self.llm)
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existing_llm.callbacks = []
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copied_data = self.model_dump(exclude=exclude)
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copied_data = {k: v for k, v in copied_data.items() if v is not None}
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copied_agent = Agent(**copied_data, llm=existing_llm, tools=self.tools)
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return copied_agent
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def _parse_tools(self, tools: List[Any]) -> List[LangChainTool]:
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"""Parse tools to be used for the task."""
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tools_list = []
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@@ -1,6 +1,7 @@
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import uuid
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from abc import ABC, abstractmethod
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from typing import Any, Dict, List, Optional
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from copy import copy as shallow_copy
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from typing import Any, Dict, List, Optional, TypeVar
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from pydantic import (
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UUID4,
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@@ -18,6 +19,8 @@ from crewai.agents import CacheHandler, ToolsHandler
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from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
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from crewai.utilities import I18N, Logger, RPMController
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T = TypeVar("T", bound="BaseAgent")
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class BaseAgent(ABC, BaseModel):
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"""Abstract Base Class for all third party agents compatible with CrewAI.
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@@ -187,10 +190,30 @@ class BaseAgent(ABC, BaseModel):
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"""Get the converter class for the agent to create json/pydantic outputs."""
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pass
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@abstractmethod
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def copy(self):
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"""Create a copy of the agent."""
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pass
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def copy(self: T) -> T:
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"""Create a deep copy of the Agent."""
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exclude = {
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"id",
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"_logger",
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"_rpm_controller",
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"_request_within_rpm_limit",
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"_token_process",
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"agent_executor",
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"tools",
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"tools_handler",
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"cache_handler",
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"llm",
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}
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# Copy llm and clear callbacks
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existing_llm = shallow_copy(self.llm)
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existing_llm.callbacks = []
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copied_data = self.model_dump(exclude=exclude)
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copied_data = {k: v for k, v in copied_data.items() if v is not None}
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copied_agent = type(self)(**copied_data, llm=existing_llm, tools=self.tools)
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return copied_agent
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def interpolate_inputs(self, inputs: Dict[str, Any]) -> None:
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"""Interpolate inputs into the agent description and backstory."""
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