Google 集成

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      googleSearch: {},
    },
  ]);

const res = await llm.invoke("Who won the latest World Series?");
console.log(res.text);

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
  {
    googleSearch: {
      timeRangeFilter: {
        startTime: "2025-01-01T00:00:00Z",
        endTime: "2025-12-31T23:59:59Z",
      },
    },
  },
]);

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      codeExecution: {},
    },
  ]);

const res = await llm.invoke("Calculate the 100th Fibonacci number.");
console.log(res.contentBlocks);

for (const block of res.contentBlocks) {
  if (block.type === "tool_code") {
    console.log("Code:", block.toolCode);
  } else if (block.type === "tool_result") {
    console.log("Result:", block.toolResult);
  }
}

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      urlContext: {},
    },
  ]);

const res = await llm.invoke("Summarize this page: https://js.langchain.com/");
console.log(res.text);

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      googleMaps: {},
    },
  ]);

const res = await llm.invoke("What are the best coffee shops near Times Square?");
console.log(res.text);

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      googleMaps: {
        enableWidget: true,
    },
  },
]);

const res = await llm.invoke("Find Italian restaurants in downtown Chicago");

// 从锚定元数据中访问小部件上下文令牌
const groundingMetadata = res.response_metadata?.groundingMetadata;
console.log(groundingMetadata?.googleMapsWidgetContextToken);

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      fileSearch: {
      fileSearchStoreNames: ["fileSearchStores/my-store-123"],
    },
  },
]);

const res = await llm.invoke("What does the report say about Q4 revenue?");
console.log(res.text);

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      computerUse: {
      environment: "ENVIRONMENT_BROWSER",
    },
  },
]);

import { ChatGoogle } from "@langchain/google";

const llm = new ChatGoogle("gemini-2.5-flash")
  .bindTools([
    {
      mcpServers: [
      {
        name: "my-mcp-server",
        streamableHttpTransport: {
          url: "https://my-mcp-server.example.com/mcp",
        },
      },
    ],
  },
]);

const res = await llm.invoke("Use the tools from the MCP server to help me.");
console.log(res.text);

import { ChatGoogle } from "@langchain/google";

const projectId = "YOUR_PROJECT_ID";
const datastoreId = "YOUR_DATASTORE_ID";

const llm = new ChatGoogle({
  model: "gemini-2.5-pro",
  platformType: "gcp",
}).bindTools([
  {
    retrieval: {
      vertexAiSearch: {
        datastore: `projects/${projectId}/locations/global/collections/default_collection/dataStores/${datastoreId}`,
      },
      disableAttribution: false,
    },
  },
]);

const res = await llm.invoke(
  "What is the score of Argentina vs Bolivia football game?"
);
console.log(res.text);