queryNLPTableQA method

Future<List<ApiResponseNLPTableQA?>?> queryNLPTableQA({
  1. required ApiQueryNLPTableQA taskParameters,
  2. required String model,
})

queryNLPTableQA

NLP query for the table question answering task. Don’t know SQL? Don’t want to dive into a large spreadsheet? Ask questions in plain english!

taskParameters Parameter set for the task

[model The model to use for the task

Implementation

Future<List<ApiResponseNLPTableQA?>?> queryNLPTableQA(
    {required ApiQueryNLPTableQA taskParameters,
    required String model}) async {
  final response = await _withHttpInfo(taskParameters.toJson(), model);

  if (response.statusCode >= HttpStatus.badRequest) {
    throw ApiException(response.statusCode, await _decodeBodyBytes(response));
  }
  // When a remote server returns no body with a status of 204, we shall not decode it.
  // At the time of writing this, `dart:convert` will throw an "Unexpected end of input"
  // FormatException when trying to decode an empty string.
  if (response.body.isNotEmpty &&
      response.statusCode != HttpStatus.noContent) {
    final responseBody = await _decodeBodyBytes(response);
    return [
      (await apiClient.deserializeAsync(
          responseBody, 'List<QueryNLPTableQATask>'))
    ];
  }
  return null;
}