Agente de investigación con CrewAI

from crewai import Agent, Crew, Task
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool

@tool
def web_search(query: str, max_results: int = 3) -> str:
    """Search the web for current information."""
    from tavily import TavilyClient
    client = TavilyClient()
    results = client.search(query, max_results=max_results)
    return "\n\n".join(
        f"**{r['title']}**\n{r['content']}" for r in results["results"]
    )

agent = Agent(
    role="Specialist",
    goal="You are a research assistant. Search the web to gather information, then synthesize findings into a structured report with citations.",
    tools=[web_search],
    llm=ChatOpenAI(model="gpt-4o"),
)

task = Task(
    description="Compare the latest developments in AI agent frameworks in 2025",
    expected_output="Detailed response",
    agent=agent,
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result.raw)