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Embeddings
Zoltan Juhasz edited this page May 2, 2023
·
1 revision
Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
More info: https://platform.openai.com/docs/api-reference/embeddings
static async Task Main(string[] args)
{
// This example demonstrates, how you can use embedding feature of OpenAI.
// This feature is useful for search, clustering, recommendations, anomaly detection, etc
// More information: https://platform.openai.com/docs/guides/embeddings/what-are-embeddings
//
// The very first step to create an account at OpenAI: https://platform.openai.com/
// Using the loggedIn account, navigate to https://platform.openai.com/account/api-keys
// Here you can create apiKey(s)
using var host = Host.CreateDefaultBuilder(args)
.ConfigureServices((builder, services) =>
{
services.AddForgeOpenAI(options => {
options.AuthenticationInfo = builder.Configuration["OpenAI:ApiKey"]!;
});
})
.Build();
IOpenAIService openAi = host.Services.GetService<IOpenAIService>()!;
EmbeddingsRequest request = new EmbeddingsRequest();
request.InputTextsForEmbeddings.Add("The food was delicious and the waiter...");
HttpOperationResult<EmbeddingsResponse> response =
await openAi.EmbeddingsService
.GetAsync(request, CancellationToken.None)
.ConfigureAwait(false);;
if (response.IsSuccess)
{
Console.WriteLine(response.Result!);
}
else
{
Console.WriteLine(response);
}
}