使用生成式模型建立即時通訊工作階段

這個範例示範如何使用生成模型建立對話工作階段。

程式碼範例

Go

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vertex AI 快速入門導覽課程」中的 Go 設定說明操作。詳情請參閱 Vertex AI Go API 參考文件。

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機制」。

import (
	"context"
	"fmt"
	"io"

	"google.golang.org/genai"
)

// generateChatWithText shows how to generate chat using a text prompt.
func generateChatWithText(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"
	history := []*genai.Content{
		{
			Role: genai.RoleUser,
			Parts: []*genai.Part{
				{Text: "Hello there"},
			},
		},
		{
			Role: "model",
			Parts: []*genai.Part{
				{Text: "Great to meet you. What would you like to know?"},
			},
		},
	}
	chatSession, err := client.Chats.Create(ctx, modelName, nil, history)
	if err != nil {
		return fmt.Errorf("failed to create genai chat session: %w", err)
	}
	contents := genai.Part{Text: "Tell me a story."}
	resp, err := chatSession.SendMessage(ctx, contents)
	if err != nil {
		return fmt.Errorf("failed to send message: %w", err)
	}

	respText := resp.Text()

	fmt.Fprintln(w, respText)
	// Example response:
	// Okay, settle in. Let me tell you a story about a quiet cartographer, but not of lands and seas.
	// ...
	// In the sleepy town of Oakhaven, nestled between the Whispering Hills and the Murmuring River, lived a woman named Elara.
	// ...

	return nil
}

Java

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vertex AI 快速入門導覽課程」中的 Java 設定說明操作。詳情請參閱 Vertex AI Java API 參考文件。

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機制」。

import com.google.genai.Chat;
import com.google.genai.Client;
import com.google.genai.types.Content;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.HttpOptions;
import com.google.genai.types.Part;

public class TextGenerationChatWithText {

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

  // Shows how to create a chat session
  public static String generateContent(String modelId) {
    // Client Initialization. Once created, it can be reused for multiple requests.
    try (Client client =
        Client.builder()
            .location("global")
            .vertexAI(true)
            .httpOptions(HttpOptions.builder().apiVersion("v1").build())
            .build()) {

      // Create a new chat session
      Chat chatSession = client.chats.create(modelId);

      GenerateContentResponse response = chatSession.sendMessage("Tell me a story");
      System.out.print(response.text());
      // Example response:
      //
      // In the heart of the Whispering Peaks lay the Valley of Silent Echoes, a place perpetually
      // shrouded in a twilight mist. No birds sang there, no rivers flowed, and the few trees that
      // clung to its edges were gnarled and bare...
      return response.text();
    }
  }
}

Node.js

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vertex AI 快速入門導覽課程」中的 Node.js 設定說明操作。詳情請參閱 Vertex AI Node.js API 參考文件。

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機制」。

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 chatSession = client.chats.create({
    model: 'gemini-2.5-flash',
    history: [
      {
        role: 'user',
        parts: [{text: 'Hello'}],
      },
      {
        role: 'model',
        parts: [{text: 'Great to meet you. What would you like to know?'}],
      },
    ],
  });

  const response = await chatSession.sendMessage({message: 'Tell me a story.'});
  console.log(response.text);

  // Example response:
  // Okay, here's a story for you:
  // ...

  return response.text;
}

Python

在試用這個範例之前，請先按照「使用用戶端程式庫的 Vertex AI 快速入門導覽課程」中的 Python 設定說明操作。詳情請參閱 Vertex AI Python API 參考文件。

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機制」。

from google import genai
from google.genai.types import HttpOptions, ModelContent, Part, UserContent

client = genai.Client(http_options=HttpOptions(api_version="v1"))
chat_session = client.chats.create(
    model="gemini-2.5-flash",
    history=[
        UserContent(parts=[Part(text="Hello")]),
        ModelContent(
            parts=[Part(text="Great to meet you. What would you like to know?")],
        ),
    ],
)
response = chat_session.send_message("Tell me a story.")
print(response.text)
# Example response:
# Okay, here's a story for you:
# ...

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 瀏覽器範例。