chore(STT): remove add_corpus from adapter as it accepts form data

Author: ehdsouza

watson_developer_cloud/speech_to_text_v1_adapter.py

@@ -216,91 +216,3 @@ def recognize_using_websocket(self,
                           http_proxy_host,
                           http_proxy_port,
                           self.verify)
-
-    def add_corpus(self,
-                   customization_id,
-                   corpus_name,
-                   corpus_file,
-                   allow_overwrite=None,
-                   **kwargs):
-        """
-        Add a corpus.
-
-        Adds a single corpus text file of new training data to a custom language model.
-        Use multiple requests to submit multiple corpus text files. You must use
-        credentials for the instance of the service that owns a model to add a corpus to
-        it. Adding a corpus does not affect the custom language model until you train the
-        model for the new data by using the **Train a custom language model** method.
-        Submit a plain text file that contains sample sentences from the domain of
-        interest to enable the service to extract words in context. The more sentences you
-        add that represent the context in which speakers use words from the domain, the
-        better the service's recognition accuracy. For guidelines about adding a corpus
-        text file and for information about how the service parses a corpus file, see
-        [Preparing a corpus text
-        file](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#prepareCorpus).
-        The call returns an HTTP 201 response code if the corpus is valid. The service
-        then asynchronously processes the contents of the corpus and automatically
-        extracts new words that it finds. This can take on the order of a minute or two to
-        complete depending on the total number of words and the number of new words in the
-        corpus, as well as the current load on the service. You cannot submit requests to
-        add additional corpora or words to the custom model, or to train the model, until
-        the service's analysis of the corpus for the current request completes. Use the
-        **List a corpus** method to check the status of the analysis.
-        The service auto-populates the model's words resource with any word that is not
-        found in its base vocabulary; these are referred to as out-of-vocabulary (OOV)
-        words. You can use the **List custom words** method to examine the words resource,
-        using other words method to eliminate typos and modify how words are pronounced as
-        needed.
-        To add a corpus file that has the same name as an existing corpus, set the
-        `allow_overwrite` parameter to `true`; otherwise, the request fails. Overwriting
-        an existing corpus causes the service to process the corpus text file and extract
-        OOV words anew. Before doing so, it removes any OOV words associated with the
-        existing corpus from the model's words resource unless they were also added by
-        another corpus or they have been modified in some way with the **Add custom
-        words** or **Add a custom word** method.
-        The service limits the overall amount of data that you can add to a custom model
-        to a maximum of 10 million total words from all corpora combined. Also, you can
-        add no more than 30 thousand custom (OOV) words to a model; this includes words
-        that the service extracts from corpora and words that you add directly.
-
-        :param str customization_id: The customization ID (GUID) of the custom language
-        model. You must make the request with service credentials created for the instance
-        of the service that owns the custom model.
-        :param str corpus_name: The name of the corpus for the custom language model. When
-        adding a corpus, do not include spaces in the name; use a localized name that
-        matches the language of the custom model; and do not use the name `user`, which is
-        reserved by the service to denote custom words added or modified by the user.
-        :param file corpus_file: A plain text file that contains the training data for the
-        corpus. Encode the file in UTF-8 if it contains non-ASCII characters; the service
-        assumes UTF-8 encoding if it encounters non-ASCII characters. With cURL, use the
-        `--data-binary` option to upload the file for the request.
-        :param bool allow_overwrite: If `true`, the specified corpus or audio resource
-        overwrites an existing corpus or audio resource with the same name. If `false`,
-        the request fails if a corpus or audio resource with the same name already exists.
-        The parameter has no effect if a corpus or audio resource with the same name does
-        not already exist.
-        :param dict headers: A `dict` containing the request headers
-        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
-        :rtype: DetailedResponse
-        """
-        if customization_id is None:
-            raise ValueError('customization_id must be provided')
-        if corpus_name is None:
-            raise ValueError('corpus_name must be provided')
-        if corpus_file is None:
-            raise ValueError('corpus_file must be provided')
-        headers = {}
-        if 'headers' in kwargs:
-            headers.update(kwargs.get('headers'))
-        params = {'allow_overwrite': allow_overwrite}
-        data = corpus_file
-        url = '/v1/customizations/{0}/corpora/{1}'.format(
-            *self._encode_path_vars(customization_id, corpus_name))
-        response = self.request(
-            method='POST',
-            url=url,
-            headers=headers,
-            params=params,
-            data=data,
-            accept_json=True)
-        return response