Google ADK

import * as weave from "weave";
import { FunctionTool, Gemini, InMemoryRunner, LlmAgent } from "@google/adk";
import { WeaveAdkPlugin } from "weave";
import { z } from "zod";

const GEMINI_API_KEY = process.env.GEMINI_API_KEY

const wikipediaSearchTool = new FunctionTool({
  name: "wikipedia_search",
  description: "Search Wikipedia for a topic and return its title and intro paragraph.",
  parameters: z.object({
    query: z.string().describe("The topic to search for"),
  }),
  execute: async ({ query }) => {
    const url = new URL("https://en.wikipedia.org/w/api.php");
    url.search = new URLSearchParams({
      action: "query",
      generator: "search",
      gsrsearch: query,
      gsrlimit: "1",
      prop: "extracts",
      exintro: "true",
      explaintext: "true",
      format: "json",
    }).toString();

    const response = await fetch(url, { headers: { "User-Agent": "weave-demo" } });
    const data = await response.json();
    const page = Object.values(data.query.pages)[0] as { title: string; extract: string };
    return { title: page.title, extract: page.extract };
  },
});

async function main() {
  await weave.init("<your-team>/<your-project-name>");

  const agent = new LlmAgent({
    name: "research_assistant",
    description: "Answers research questions using Wikipedia.",
    instruction:
      "You are a research assistant. Use the wikipedia_search tool to look up " +
      "topics when needed, and cite the article titles you used.",
    model: new Gemini({ model: "gemini-2.5-flash", apiKey: GEMINI_API_KEY }),
    tools: [wikipediaSearchTool],
  });

  const APP_NAME = "weave-adk-example";
  const USER_ID = "example-user";

  const runner = new InMemoryRunner({
    agent,
    appName: APP_NAME,
    plugins: [new WeaveAdkPlugin()],
  });
  const session = await runner.sessionService.createSession({
    appName: APP_NAME,
    userId: USER_ID,
  });

  const questions = [
    "Who founded Anthropic?",
    "What is Claude (the AI assistant)?",
    "Summarize what we discussed in one sentence.",
  ];

  for (const question of questions) {
    console.log(`USER: ${question}`);
    for await (const event of runner.runAsync({
      userId: USER_ID,
      sessionId: session.id,
      newMessage: {
        role: "user",
        parts: [{ text: question }],
      },
    })) {
      const text = event.content?.parts
        ?.map(part => part.text)
        .filter(Boolean)
        .join("");
      if (text) {
        console.log(`AGENT: ${text}\n`);
      }
    }
  }

  await weave.flushOTel();
}

main().catch(console.error);