构建定时研究智能体

from langchain.tools import tool


@tool(parse_docstring=True)
def web_search(query: str) -> str:
    """Search the web for a query and return result snippets.

    Args:
        query: The search query.
    """
    # Replace this stub with a call to your search provider.
    return f"Top results for '{query}': ..."

import { tool } from "langchain";
import { z } from "zod";

export const webSearch = tool(
  async ({ query }) => {
    // Replace this stub with a call to your search provider.
    return `Top results for '${query}': ...`;
  },
  {
    name: "web_search",
    description: "Search the web for a query and return result snippets.",
    schema: z.object({
      query: z.string().describe("The search query."),
    }),
  },
);

from managed_deepagents import define_deep_agent

from tools.search import web_search

agent = define_deep_agent(
    name="research-assistant",
    model="openai:gpt-5.5",
    tools=[web_search],
)

import { defineDeepAgent } from "managed-deepagents";

import { webSearch } from "./tools/search";

export const agent = defineDeepAgent({
  name: "research-assistant",
  model: "openai:gpt-5.5",
  tools: [webSearch],
});

uv sync
mda dev .

npm install
mda dev .

from managed_deepagents import define_schedule

schedule = define_schedule(
    cron="0 8 * * 1-5",
    timezone="America/Los_Angeles",
    prompt="Summarize what you learned yesterday and list open questions.",
)

import { defineSchedule } from "managed-deepagents";

export const schedule = defineSchedule({
  cron: "0 8 * * 1-5",
  timezone: "America/Los_Angeles",
  prompt: "Summarize what you learned yesterday and list open questions.",
});