将系统说明设置为 Gemini 1.5 Pro

此示例展示了如何将系统说明设置为 Gemini 1.5 Pro。

代码示例

C#

在尝试此示例之前,请按照《Vertex AI 快速入门:使用客户端库》中的 C# 设置说明执行操作。 如需了解详情,请参阅 Vertex AI C# API 参考文档

如需向 Vertex AI 进行身份验证,请设置应用默认凭证。如需了解详情,请参阅为本地开发环境设置身份验证


using Google.Cloud.AIPlatform.V1;
using System;
using System.Threading.Tasks;

public class SystemInstruction
{
    public async Task<string> SetSystemInstruction(
        string projectId = "your-project-id",
        string location = "us-central1",
        string publisher = "google",
        string model = "gemini-2.0-flash-001")
    {

        var predictionServiceClient = new PredictionServiceClientBuilder
        {
            Endpoint = $"{location}-aiplatform.googleapis.com"
        }.Build();

        string prompt = @"User input: I like bagels.
Answer:";

        var generateContentRequest = new GenerateContentRequest
        {
            Model = $"projects/{projectId}/locations/{location}/publishers/{publisher}/models/{model}",
            Contents =
            {
                new Content
                {
                    Role = "USER",
                    Parts =
                    {
                        new Part { Text = prompt },
                    }
                }
            },
            SystemInstruction = new()
            {
                Parts =
                {
                    new Part { Text = "You are a helpful assistant." },
                    new Part { Text = "Your mission is to translate text in English to French." },
                }
            }
        };

        GenerateContentResponse response = await predictionServiceClient.GenerateContentAsync(generateContentRequest);

        string responseText = response.Candidates[0].Content.Parts[0].Text;
        Console.WriteLine(responseText);

        return responseText;
    }
}

Node.js

在尝试此示例之前,请按照《Vertex AI 快速入门:使用客户端库》中的 Node.js 设置说明执行操作。 如需了解详情,请参阅 Vertex AI Node.js API 参考文档

如需向 Vertex AI 进行身份验证,请设置应用默认凭证。如需了解详情,请参阅为本地开发环境设置身份验证

const {VertexAI} = require('@google-cloud/vertexai');

/**
 * TODO(developer): Update these variables before running the sample.
 */
async function set_system_instruction(projectId = 'PROJECT_ID') {
  const vertexAI = new VertexAI({project: projectId, location: 'us-central1'});

  const generativeModel = vertexAI.getGenerativeModel({
    model: 'gemini-2.0-flash-001',
    systemInstruction: {
      parts: [
        {text: 'You are a helpful language translator.'},
        {text: 'Your mission is to translate text in English to French.'},
      ],
    },
  });

  const textPart = {
    text: `
    User input: I like bagels.
    Answer:`,
  };

  const request = {
    contents: [{role: 'user', parts: [textPart]}],
  };

  const resp = await generativeModel.generateContent(request);
  const contentResponse = await resp.response;
  console.log(JSON.stringify(contentResponse));
}

后续步骤

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