Skip to content

vladcto/yandex-gpt-rest-api

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

75 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

YandexGPT API Client

Test CI codecov

Dart library for working with YandexGPT API.

Getting started

Create YandexGptApi instance.

// For passing BaseOptions or Dio use other constructors.
final api = YandexGptApi(
  token: AuthToken.api("your_token"), // or AuthToken.iam
  // Not necessary, by default uses catalog from AuthToken account.
  catalog: "catalog_id?",
);

Now you can use the YandexGPT API.

API calls

The names of methods YandexGptApi are same to the names of API methods.

Available API calls:

Text Generation

When generating large text with configured small dio.options.receiveTimeout a timeout error may occur.

Generate sync text

final response = await api.generateText(
  TextGenerationRequest(
    model: 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

The generateAsyncText returns the Operation object.

For handling Operation you can use getOperationTextGenerate.

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

Fetch async generation status

final asyncText = await api.generateAsyncText(/*request*/);
final response = await api.getOperationTextGenerate(asyncText.id);
print(response.done);
Tokenize

Tokenize completion

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

final response = await api.tokenizeText(
  TokenizeTextRequest(
    model: GModel.yandexGpt('folder_id'),
    text: 'some_response_text',
  ),
);
print(response.tokens.length);
Embeddings

Text embedding

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

Handling errors

It is enough to catch an error of type ApiError.

try {
  await api.generateText(/*request*/);
} on ApiError catch (e) {
  // Handle YandexGPT API errors
} on DioException catch (e) {
  // Handle network errors
}

If you need information about the error:

try {
  await api.generateText(/*request*/);
} on DetailedApiError catch (e) {
  // Handle DetailedApiError
} on ShortApiError catch (e) {
  // Handle ShortApiError
} on DioException catch (e) {
  // Handle network errors
}

Cancel requests

To cancel requests use Dio CancelToken by passing API requests with cancelToken param.

The handling cancellation is similar to the example from the Dio doc.

About

A library for using YandexGPT API, such as generating text and obtain embeddings.

Topics

Resources

License

Stars

Watchers

Forks

Languages