Définir les instructions système sur Gemini 1.5 Pro
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Cet exemple montre comment définir des instructions système pour Gemini 1.5 Pro.
Exemple de code
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[[["Facile à comprendre","easyToUnderstand","thumb-up"],["J'ai pu résoudre mon problème","solvedMyProblem","thumb-up"],["Autre","otherUp","thumb-up"]],[["Difficile à comprendre","hardToUnderstand","thumb-down"],["Informations ou exemple de code incorrects","incorrectInformationOrSampleCode","thumb-down"],["Il n'y a pas l'information/les exemples dont j'ai besoin","missingTheInformationSamplesINeed","thumb-down"],["Problème de traduction","translationIssue","thumb-down"],["Autre","otherDown","thumb-down"]],[],[],[],null,["# Set system instructions to Gemini 1.5 Pro\n\nThis sample shows you how to set system instructions to Gemini 1.5 Pro.\n\nCode sample\n-----------\n\n### C#\n\n\nBefore trying this sample, follow the C# setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI C# API\nreference documentation](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n using https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.html;\n using System;\n using System.Threading.Tasks;\n\n public class SystemInstruction\n {\n public async Task\u003cstring\u003e SetSystemInstruction(\n string projectId = \"your-project-id\",\n string location = \"us-central1\",\n string publisher = \"google\",\n string model = \"gemini-2.0-flash-001\")\n {\n\n var predictionServiceClient = new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.PredictionServiceClientBuilder.html\n {\n Endpoint = $\"{location}-aiplatform.googleapis.com\"\n }.Build();\n\n string prompt = @\"User input: I like bagels.\n Answer:\";\n\n var generateContentRequest = new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentRequest.html\n {\n Model = $\"projects/{projectId}/locations/{location}/publishers/{publisher}/models/{model}\",\n Contents =\n {\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Content.html\n {\n Role = \"USER\",\n Parts =\n {\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { Text = prompt },\n }\n }\n },\n SystemInstruction = new()\n {\n Parts =\n {\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { Text = \"You are a helpful assistant.\" },\n new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Part.html { Text = \"Your mission is to translate text in English to French.\" },\n }\n }\n };\n\n https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentResponse.html response = await predictionServiceClient.GenerateContentAsync(generateContentRequest);\n\n string responseText = response.https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentResponse.html#Google_Cloud_AIPlatform_V1_GenerateContentResponse_Candidates[0].https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.Content.html.Parts[0].Text;\n Console.WriteLine(responseText);\n\n return responseText;\n }\n }\n\n### Node.js\n\n\nBefore trying this sample, follow the Node.js setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Node.js API\nreference documentation](/nodejs/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n const {VertexAI} = require('https://cloud.google.com/nodejs/docs/reference/vertexai/latest/overview.html');\n\n /**\n * TODO(developer): Update these variables before running the sample.\n */\n async function set_system_instruction(projectId = 'PROJECT_ID') {\n const vertexAI = new https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({project: projectId, location: 'us-central1'});\n\n const generativeModel = vertexAI.https://cloud.google.com/nodejs/docs/reference/vertexai/latest/vertexai/vertexai.html({\n model: 'gemini-2.0-flash-001',\n systemInstruction: {\n parts: [\n {text: 'You are a helpful language translator.'},\n {text: 'Your mission is to translate text in English to French.'},\n ],\n },\n });\n\n const textPart = {\n text: `\n User input: I like bagels.\n Answer:`,\n };\n\n const request = {\n contents: [{role: 'user', parts: [textPart]}],\n };\n\n const resp = await generativeModel.generateContent(request);\n const contentResponse = await resp.response;\n console.log(JSON.stringify(contentResponse));\n }\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=generativeaionvertexai)."]]