Remove article generation.

Author: Julien Salinas

README.md

@@ -2,7 +2,7 @@
 
 This is the Python client for the [NLP Cloud](https://nlpcloud.io) API. See the [documentation](https://docs.nlpcloud.io) for more details.
 
-NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.
+NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.
 
 You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
 
@@ -159,16 +159,6 @@ client.asr("Your url")
 
 The above command returns a JSON object.
 
-### Blog Post Generation Endpoint
-
-Call the `article_generation()` method and pass the title of your blog post:
-
-```python
-client.article_generation("<Your title>")
-```
-
-The above command returns a JSON object.
-
 ### Chatbot Endpoint
 
 Call the `chatbot()` method and pass your input. As an option, you can also pass a context and conversation history that is a list of dictionnaries. Each dictionnary is made of an `input` and a `response` from the chatbot.

nlpcloud/__init__.py

@@ -46,21 +46,6 @@ def ad_generation(self, keywords):
 
         return r.json()
 
-    def article_generation(self, title):
-        payload = {
-            "title": title
-        }
-
-        r = requests.post(
-            "{}/{}".format(self.root_url, "article-generation"), json=payload, headers=self.headers)
-
-        try:
-            r.raise_for_status()
-        except HTTPError as err:
-            raise HTTPError(str(err) + ": " + str(r.text))
-
-        return r.json()
-
     def asr(self, url=None, encoded_file=None, input_language=None):
         payload = {
             "url": url,

setup.py

@@ -4,7 +4,7 @@
     name='nlpcloud',
     version='1.0.41',
     description='Python client for the NLP Cloud API',
-    long_description="NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, grammar and spelling correction, keywords and keyphrases extraction, chatbot, product description and ad generation, intent classification, text generation, image generation, blog post generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, speech synthesis, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.\n\nThis is the Python client for the API.\n\nMore details here: https://nlpcloud.io\n\nDocumentation: https://docs.nlpcloud.io\n\nGithub: https://github.com/nlpcloud/nlpcloud-python",
+    long_description="NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, grammar and spelling correction, keywords and keyphrases extraction, chatbot, product description and ad generation, intent classification, text generation, image generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, speech synthesis, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.\n\nThis is the Python client for the API.\n\nMore details here: https://nlpcloud.io\n\nDocumentation: https://docs.nlpcloud.io\n\nGithub: https://github.com/nlpcloud/nlpcloud-python",
     packages=['nlpcloud'],
     author='Julien Salinas',
     author_email='[email protected]',