使用多模態 AI 模型產生內容的非同步範例

程式碼範例:示範如何使用非同步功能,透過生成式 AI 模型執行作業

程式碼範例

Go

在試用這個範例之前,請先按照Go使用用戶端程式庫的 Vertex AI 快速入門中的操作說明進行設定。 詳情請參閱 Vertex AI Go API 參考說明文件

如要向 Vertex AI 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"

	"google.golang.org/genai"
)

// generateWithTextAsyncStream shows how to stream a text generation response.
func generateWithTextAsyncStream(w io.Writer) error {
	ctx := context.Background()

	client, err := genai.NewClient(ctx, &genai.ClientConfig{
		HTTPOptions: genai.HTTPOptions{APIVersion: "v1"},
	})
	if err != nil {
		return fmt.Errorf("failed to create genai client: %w", err)
	}

	modelName := "gemini-2.5-flash"

	contents := []*genai.Content{
		{
			Role: "user",
			Parts: []*genai.Part{
				{Text: "Compose a song about the adventures of a time-traveling squirrel."},
			},
		},
	}

	for resp, err := range client.Models.GenerateContentStream(ctx, modelName, contents, &genai.GenerateContentConfig{
		ResponseModalities: []string{"TEXT"}}) {
		if err != nil {
			return fmt.Errorf("failed to generate content: %w", err)
		}

		chunk := resp.Text()

		fmt.Fprintln(w, chunk)
	}

	// Example output (streamed piece by piece):
	// (Verse 1)
	// Pip was a squirrel, a regular chap,
	//Burying acorns, enjoying a nap.
	//One sunny morning, beneath the old pine,
	//He dug up a thing, incredibly fine.
	//A tiny contraption, with gears and a gleam,
	//It pulsed with a power, a
	// time-traveling dream.
	//He nudged it with curiosity, twitching his nose,
	//And *poof!* went the world, as everyone knows...
	//
	//(Chorus)
	//Oh, Pip the squirrel, with his bushy brown tail,
	//Through the time stream he'd often sail!
	// ...

	return nil
}

Java

在試用這個範例之前,請先按照Java使用用戶端程式庫的 Vertex AI 快速入門中的操作說明進行設定。 詳情請參閱 Vertex AI Java API 參考說明文件

如要向 Vertex AI 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。


import com.google.genai.Client;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.HttpOptions;
import java.util.concurrent.CompletableFuture;

public class TextGenerationAsyncWithText {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String modelId = "gemini-2.5-flash";
    generateContent(modelId);
  }

  // Generates text asynchronously with text input
  public static String generateContent(String modelId) {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests.
    try (Client client =
        Client.builder()
            .location("global")
            .vertexAI(true)
            .httpOptions(HttpOptions.builder().apiVersion("v1").build())
            .build()) {

      CompletableFuture<GenerateContentResponse> asyncResponse =
          client.async.models.generateContent(
              modelId, "Compose a song about the adventures of a time-traveling squirrel.", null);

      String response = asyncResponse.join().text();
      System.out.print(response);
      // Example response:
      // (Verse 1)
      // In an oak tree, so leafy and green,
      // Lived Squeaky the squirrel, a critter unseen.
      // Just burying nuts, a routine so grand,
      // ...

      return response;
    }
  }
}

Node.js

在試用這個範例之前,請先按照Node.js使用用戶端程式庫的 Vertex AI 快速入門中的操作說明進行設定。 詳情請參閱 Vertex AI Node.js API 參考說明文件

如要向 Vertex AI 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

const {GoogleGenAI} = require('@google/genai');

const GOOGLE_CLOUD_PROJECT = process.env.GOOGLE_CLOUD_PROJECT;
const GOOGLE_CLOUD_LOCATION = process.env.GOOGLE_CLOUD_LOCATION || 'global';

async function generateText(
  projectId = GOOGLE_CLOUD_PROJECT,
  location = GOOGLE_CLOUD_LOCATION
) {
  const client = new GoogleGenAI({
    vertexai: true,
    project: projectId,
    location: location,
  });

  const response = await client.models.generateContent({
    model: 'gemini-2.5-flash',
    contents:
      'Compose a song about the adventures of a time-traveling squirrel.',
    config: {
      responseMimeType: 'text/plain',
    },
  });

  console.log(response.text);

  // Example response:
  // (Verse 1)
  // Sammy the nugget, a furry little friend
  // Had a knack for adventure, beyond all comprehend

  return response.text;
}

Python

在試用這個範例之前,請先按照Python使用用戶端程式庫的 Vertex AI 快速入門中的操作說明進行設定。 詳情請參閱 Vertex AI Python API 參考說明文件

如要向 Vertex AI 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

from google import genai
from google.genai.types import GenerateContentConfig, HttpOptions

client = genai.Client(http_options=HttpOptions(api_version="v1"))
model_id = "gemini-2.5-flash"

response = await client.aio.models.generate_content(
    model=model_id,
    contents="Compose a song about the adventures of a time-traveling squirrel.",
    config=GenerateContentConfig(
        response_modalities=["TEXT"],
    ),
)

print(response.text)
# Example response:
# (Verse 1)
# Sammy the squirrel, a furry little friend
# Had a knack for adventure, beyond all comprehend

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例,請參閱Google Cloud 範例瀏覽器