Mulai 29 April 2025, model Gemini 1.5 Pro dan Gemini 1.5 Flash tidak tersedia di project yang belum pernah menggunakan model ini, termasuk project baru. Untuk mengetahui detailnya, lihat
Versi dan siklus proses model.
Pembuatan teks interaktif dengan chatbot
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Contoh ini menunjukkan cara menggunakan model Gemini untuk membuat teks secara interaktif.
Contoh kode
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],[],[],[],null,["# Interactive text generation with a chatbot\n\nThis sample demonstrates how to use the Gemini model to generate text interactively.\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.Collections.Generic;\n using System.Threading.Tasks;\n\n public class MultiTurnChatSample\n {\n public async Task\u003cstring\u003e GenerateContent(\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 // Create a chat session to keep track of the context\n ChatSession chatSession = new ChatSession($\"projects/{projectId}/locations/{location}/publishers/{publisher}/models/{model}\", location);\n\n string prompt = \"Hello.\";\n Console.WriteLine($\"\\nUser: {prompt}\");\n\n string response = await chatSession.SendMessageAsync(prompt);\n Console.WriteLine($\"Response: {response}\");\n\n prompt = \"What are all the colors in a rainbow?\";\n Console.WriteLine($\"\\nUser: {prompt}\");\n\n response = await chatSession.SendMessageAsync(prompt);\n Console.WriteLine($\"Response: {response}\");\n\n prompt = \"Why does it appear when it rains?\";\n Console.WriteLine($\"\\nUser: {prompt}\");\n\n response = await chatSession.SendMessageAsync(prompt);\n Console.WriteLine($\"Response: {response}\");\n\n return response;\n }\n\n private class ChatSession\n {\n private readonly string _modelPath;\n private readonly https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.PredictionServiceClient.html _predictionServiceClient;\n\n private readonly List\u003cContent\u003e _contents;\n\n public ChatSession(string modelPath, string location)\n {\n _modelPath = modelPath;\n\n _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 // Initialize contents to send over in every request.\n _contents = new List\u003cContent\u003e();\n }\n\n public async Task\u003cstring\u003e SendMessageAsync(string prompt)\n {\n var content = 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 _contents.Add(content);\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 = _modelPath,\n GenerationConfig = new https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerationConfig.html\n {\n Temperature = 0.9f,\n TopP = 1,\n TopK = 32,\n CandidateCount = 1,\n MaxOutputTokens = 2048\n }\n };\n generateContentRequest.Contents.AddRange(_contents);\n\n https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.GenerateContentResponse.html response = await _predictionServiceClient.https://cloud.google.com/dotnet/docs/reference/Google.Cloud.AIPlatform.V1/latest/Google.Cloud.AIPlatform.V1.PredictionServiceClient.html#Google_Cloud_AIPlatform_V1_PredictionServiceClient_GenerateContentAsync_Google_Cloud_AIPlatform_V1_GenerateContentRequest_Google_Api_Gax_Grpc_CallSettings_(generateContentRequest);\n\n _contents.Add(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);\n\n return 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 }\n }\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)."]]