yandex_gpt_rest_api 0.4.0

Dart package for calling the Foundation Models RESTfull API.

yandex_gpt_rest_api

UNDER WORK

The signature of the methods may change.

Getting started

Create YandexGptApi instance.

final api = YandexGptApiClient(
  token: AuthToken.iam("your_token"),
  catalog: "your_catalog_id", // Not necessary
);

Now you can use the Foundation Models API.

API capabilities

Text Generation

Generate text

void main() async {
  final response = await api.generateText(
    TextGenerationRequest(
      modelUri: GModel.yandexGpt('folder_id'),
      messages: const [
        Message.system("Some joke"),
        Message.user("Generate joke"),
      ],
    ),
  );
  print(response.alternatives.first.message);
  print(response.usage.totalTokens);
}

Generate async text

UNDER_WORK

void main() async {
  final response = await api.generateAsyncText(
    TextGenerationRequest(
      model: GModel.yandexGpt('folder_id'),
      messages: const [
        Message.system("Some joke"),
        Message.user("Generate joke"),
      ],
    ),
  );
  print(response.done);
}

Tokenize

Tokenize completion

void main() async {
  final response = await api.tokenizeCompletion(
    TextGenerationRequest(
      model: GModel.yandexGpt('folder_id'),
      messages: const [
        Message.system("Some joke"),
        Message.user("Generate joke"),
      ],
    ),
  );
  print(response.tokens.length);
}

Tokenize text

void main() async {
  final response = await api.tokenizeText(
    TokenizeTextRequest(
      model: GModel.yandexGpt('folder_id'),
      text: 'some_response_text',
    ),
  );
  print(response.tokens.length);
}

Embeddings

void main() async {
  final response = await api.getTextEmbedding(
    EmbeddingRequest(
      model: VModel.documentation('folder_id'),
      text: 'Some text',
    ),
  );
  print(response.embedding);
}