Agente de investigación con LangChain

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"]
    )

model = ChatOpenAI(model="gpt-4o")
model_with_tools = model.bind_tools([web_search])
response = model_with_tools.invoke([
    ("system", "You are a research assistant. Search the web to gather information, then synthesize findings into a structured report with citations."),
    ("user", "Compare the latest developments in AI agent frameworks in 2025"),
])