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Controlled generation JSON output with predefined schema
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This code sample demonstrates how to use the `response_mime_type` and `response_schema` parameters to get a response that follows the JSON format and schema that you've defined.
Code sample
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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],[],[],[],null,["# Controlled generation JSON output with predefined schema\n\nThis code sample demonstrates how to use the \\`response_mime_type\\` and \\`response_schema\\` parameters to get a response that follows the JSON format and schema that you've defined.\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 public async Task\u003cstring\u003e GenerateContentWithResponseSchema2(\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 PredictionServiceClientBuilder\n {\n Endpoint = $\"{location}-aiplatform.googleapis.com\"\n }.Build();\n\n var responseSchema = new OpenApiSchema\n {\n Type = Type.Array,\n Items = new()\n {\n Type = Type.Object,\n Properties =\n {\n [\"rating\"] = new() { Type = Type.Integer },\n [\"flavor\"] = new() { Type = Type.String }\n },\n Required = { \"rating\", \"flavor\" }\n }\n };\n\n string prompt = @\"\n Reviews from our social media:\n\n - \"\"Absolutely loved it! Best ice cream I've ever had.\"\" Rating: 4, Flavor: Strawberry Cheesecake\n - \"\"Quite good, but a bit too sweet for my taste.\"\" Rating: 1, Flavor: Mango Tango\";\n\n var generateContentRequest = new GenerateContentRequest\n {\n Model = $\"projects/{projectId}/locations/{location}/publishers/{publisher}/models/{model}\",\n Contents =\n {\n new Content\n {\n Role = \"USER\",\n Parts =\n {\n new Part { Text = prompt }\n }\n }\n },\n GenerationConfig = new GenerationConfig\n {\n ResponseMimeType = \"application/json\",\n ResponseSchema = responseSchema\n },\n };\n\n GenerateContentResponse response = await predictionServiceClient.GenerateContentAsync(generateContentRequest);\n\n string responseText = response.Candidates[0].Content.Parts[0].Text;\n Console.WriteLine(responseText);\n\n return responseText;\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)."]]