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aiofarsava.LanguageModelApi

All URIs are relative to https://api.farsava.ir/v1

Method HTTP request Description
get_language_model_by_id GET /speech/languagemodels/{languageModelId} GET /speech/languagemodels/{languageModelId}
get_language_model_list GET /speech/languagemodels GET /speech/languagemodels
train_language_model POST /speech/languagemodels POST /speech/languagemodels

get_language_model_by_id

LanguageModelResult get_language_model_by_id(language_model_id)

GET /speech/languagemodels/{languageModelId}

Retrieving the status of a language model with specified languageModelId. A language model is ready to use when its status is trained. ***

Example

  • Bearer (JWT) Authentication (bearerAuth):
from __future__ import print_function
import time
import aiofarsava
from aiofarsava.rest import ApiException
from pprint import pprint
configuration = aiofarsava.Configuration()
# Configure Bearer authorization (JWT): bearerAuth
configuration.access_token = 'YOUR_BEARER_TOKEN'

# create an instance of the API class
api_instance = aiofarsava.LanguageModelApi(aiofarsava.ApiClient(configuration))
language_model_id = 'language_model_id_example' # str | Id of the language model.

try:
    # GET /speech/languagemodels/{languageModelId}
    api_response = api_instance.get_language_model_by_id(language_model_id)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling LanguageModelApi->get_language_model_by_id: %s\n" % e)

Parameters

Name Type Description Notes
language_model_id str Id of the language model.

Return type

LanguageModelResult

Authorization

bearerAuth

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

[Back to top] [Back to API list] [Back to Model list] [Back to README]

get_language_model_list

list[LanguageModelResult] get_language_model_list()

GET /speech/languagemodels

Returns list of user available language models. Each user can access general language models plus their own custom trained language models. ***

Example

  • Bearer (JWT) Authentication (bearerAuth):
from __future__ import print_function
import time
import aiofarsava
from aiofarsava.rest import ApiException
from pprint import pprint
configuration = aiofarsava.Configuration()
# Configure Bearer authorization (JWT): bearerAuth
configuration.access_token = 'YOUR_BEARER_TOKEN'

# create an instance of the API class
api_instance = aiofarsava.LanguageModelApi(aiofarsava.ApiClient(configuration))

try:
    # GET /speech/languagemodels
    api_response = api_instance.get_language_model_list()
    pprint(api_response)
except ApiException as e:
    print("Exception when calling LanguageModelApi->get_language_model_list: %s\n" % e)

Parameters

This endpoint does not need any parameter.

Return type

list[LanguageModelResult]

Authorization

bearerAuth

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

[Back to top] [Back to API list] [Back to Model list] [Back to README]

train_language_model

LanguageModelResult train_language_model(language_model_train_request_body)

POST /speech/languagemodels

Train a custom language model using pharases provided by user. Returning a languageModelId for accessing the language model later and using this custom language model to transcribe audios. Using custom language models will boost accuracy for specific keywords/phrases and can be used for a domain-specific speech recognition. ***

Example

  • Bearer (JWT) Authentication (bearerAuth):
from __future__ import print_function
import time
import aiofarsava
from aiofarsava.rest import ApiException
from pprint import pprint
configuration = aiofarsava.Configuration()
# Configure Bearer authorization (JWT): bearerAuth
configuration.access_token = 'YOUR_BEARER_TOKEN'

# create an instance of the API class
api_instance = aiofarsava.LanguageModelApi(aiofarsava.ApiClient(configuration))
language_model_train_request_body = aiofarsava.LanguageModelTrainRequestBody() # LanguageModelTrainRequestBody | A json object including a name and a corpora. Corpora is a array of text data to train a custom model. This text data can be keywords/phrases. All values in the array must be a string. Name is an arbitary string you set for the custom language model name.

try:
    # POST /speech/languagemodels
    api_response = api_instance.train_language_model(language_model_train_request_body)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling LanguageModelApi->train_language_model: %s\n" % e)

Parameters

Name Type Description Notes
language_model_train_request_body LanguageModelTrainRequestBody A json object including a name and a corpora. Corpora is a array of text data to train a custom model. This text data can be keywords/phrases. All values in the array must be a string. Name is an arbitary string you set for the custom language model name.

Return type

LanguageModelResult

Authorization

bearerAuth

HTTP request headers

  • Content-Type: application/json
  • Accept: application/json

[Back to top] [Back to API list] [Back to Model list] [Back to README]