Agent badawczy z LangGraph

from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from langgraph.prebuilt import create_react_agent

@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 = create_react_agent(
    ChatOpenAI(model="gpt-4o"),
    tools=[web_search],
    prompt="You are a research assistant. Search the web to gather information, then synthesize findings into a structured report with citations.",
)

result = await agent.ainvoke({
    "messages": [("user", "Compare the latest developments in AI agent frameworks in 2025")]
})
print(result["messages"][-1].content)