CrewAI integra-se perfeitamente com a abrangente lista de ferramentas do LangChain, todas as quais podem ser usadas com CrewAI.
import os
from dotenv import load_dotenv
from crewai import Agent, Task, Crew
from crewai.tools import BaseTool
from pydantic import Field
from langchain_community.utilities import GoogleSerperAPIWrapper
# Set up your SERPER_API_KEY key in an .env file, eg:
# SERPER_API_KEY=<your api key>
load_dotenv()
search = GoogleSerperAPIWrapper()
class SearchTool(BaseTool):
name: str = "Search"
description: str = "Useful for search-based queries. Use this to find current information about markets, companies, and trends."
search: GoogleSerperAPIWrapper = Field(default_factory=GoogleSerperAPIWrapper)
def _run(self, query: str) -> str:
"""Execute the search query and return results"""
try:
return self.search.run(query)
except Exception as e:
return f"Error performing search: {str(e)}"
# Create Agents
researcher = Agent(
role='Research Analyst',
goal='Gather current market data and trends',
backstory="""You are an expert research analyst with years of experience in
gathering market intelligence. You're known for your ability to find
relevant and up-to-date market information and present it in a clear,
actionable format.""",
tools=[SearchTool()],
verbose=True
)
# rest of the code ...
Conclusão
As ferramentas são fundamentais para ampliar as capacidades dos agentes CrewAI, permitindo que realizem uma ampla variedade de tarefas e colaborem de forma eficaz.
Ao construir soluções com CrewAI, aproveite tanto ferramentas personalizadas quanto existentes para potencializar seus agentes e aprimorar o ecossistema de IA. Considere utilizar tratamento de erros, mecanismos de cache e a flexibilidade dos argumentos das ferramentas para otimizar o desempenho e as capacidades dos seus agentes.