Research Agent with Deep Agents

from deepagents import create_deep_agent
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 = create_deep_agent(
    model="anthropic:claude-sonnet-4-5-20250929",
    tools=[web_search],
    system_prompt="You are a research assistant. Search the web to gather information, then synthesize findings into a structured report with citations.",
)

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