Python Client For NLP Cloud

This is the Python client for the NLP Cloud API. See the documentation 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, 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.

If you face an issue, don't hesitate to raise it as a Github issue. Thanks!

Installation

Install via pip.

pip install nlpcloud

Examples

Here is a full example that summarizes a text using Facebook's Bart Large CNN model, with a fake token:

import nlpcloud

client = nlpcloud.Client("bart-large-cnn", "4eC39HqLyjWDarjtT1zdp7dc")
client.summarization("""One month after the United States began what has become a 
  troubled rollout of a national COVID vaccination campaign, the effort is finally 
  gathering real steam. Close to a million doses -- over 951,000, to be more exact -- 
  made their way into the arms of Americans in the past 24 hours, the U.S. Centers 
  for Disease Control and Prevention reported Wednesday. That s the largest number 
  of shots given in one day since the rollout began and a big jump from the 
  previous day, when just under 340,000 doses were given, CBS News reported. 
  That number is likely to jump quickly after the federal government on Tuesday 
  gave states the OK to vaccinate anyone over 65 and said it would release all 
  the doses of vaccine it has available for distribution. Meanwhile, a number 
  of states have now opened mass vaccination sites in an effort to get larger 
  numbers of people inoculated, CBS News reported.""")

Here is a full example that does the same thing, but on a GPU:

import nlpcloud

client = nlpcloud.Client("bart-large-cnn", "4eC39HqLyjWDarjtT1zdp7dc", True)
client.summarization("""One month after the United States began what has become a 
  troubled rollout of a national COVID vaccination campaign, the effort is finally 
  gathering real steam. Close to a million doses -- over 951,000, to be more exact -- 
  made their way into the arms of Americans in the past 24 hours, the U.S. Centers 
  for Disease Control and Prevention reported Wednesday. That s the largest number 
  of shots given in one day since the rollout began and a big jump from the 
  previous day, when just under 340,000 doses were given, CBS News reported. 
  That number is likely to jump quickly after the federal government on Tuesday 
  gave states the OK to vaccinate anyone over 65 and said it would release all 
  the doses of vaccine it has available for distribution. Meanwhile, a number 
  of states have now opened mass vaccination sites in an effort to get larger 
  numbers of people inoculated, CBS News reported.""")

Here is a full example that does the same thing, but on a French text:

import nlpcloud

client = nlpcloud.Client("bart-large-cnn", "4eC39HqLyjWDarjtT1zdp7dc", True, "fra_Latn")
client.summarization("""Sur des images aériennes, prises la veille par un vol de surveillance 
  de la Nouvelle-Zélande, la côte d’une île est bordée d’arbres passés du vert 
  au gris sous l’effet des retombées volcaniques. On y voit aussi des immeubles
  endommagés côtoyer des bâtiments intacts. « D’après le peu d’informations
  dont nous disposons, l’échelle de la dévastation pourrait être immense, 
  spécialement pour les îles les plus isolées », avait déclaré plus tôt 
  Katie Greenwood, de la Fédération internationale des sociétés de la Croix-Rouge.
  Selon l’Organisation mondiale de la santé (OMS), une centaine de maisons ont
  été endommagées, dont cinquante ont été détruites sur l’île principale de
  Tonga, Tongatapu. La police locale, citée par les autorités néo-zélandaises,
  a également fait état de deux morts, dont une Britannique âgée de 50 ans,
  Angela Glover, emportée par le tsunami après avoir essayé de sauver les chiens
  de son refuge, selon sa famille.""")

A json object is returned:

{
  "summary_text": "Over 951,000 doses were given in the past 24 hours. That's the largest number of shots given in one day since the  rollout began. That number is likely to jump quickly after the federal government gave states the OK to vaccinate anyone over 65. A number of states have now opened mass vaccination sites."
}

Usage

Client Initialization

Pass the model you want to use and the NLP Cloud token to the client during initialization.

The model can either be a pretrained model like en_core_web_lg, bart-large-mnli... but also one of your custom models, using custom_model/<model id> (e.g. custom_model/2568). See the documentation for a comprehensive list of all the models available.

Your token can be retrieved from your NLP Cloud dashboard.

import nlpcloud

client = nlpcloud.Client("<model>", "<your token>")

If you want to use a GPU, pass gpu=True.

import nlpcloud

client = nlpcloud.Client("<model>", "<your token>", gpu=True)

If you want to use the multilingual add-on in order to process non-English texts, pass lang="<your language code>". For example, if you want to process French text, you should set lang="fra_Latn".

import nlpcloud

client = nlpcloud.Client("<model>", "<your token>", lang="<your language code>")

If you want to make asynchronous requests, pass asynchronous=True.

import nlpcloud

client = nlpcloud.Client("<model>", "<your token>", asynchronous=True)

If you are making asynchronous requests, you will always receive a quick response containing a URL. You should then poll this URL with async_result() on a regular basis (every 10 seconds for example) in order to check if the result is available. Here is an example:

client.async_result("https://api.nlpcloud.io/v1/get-async-result/21718218-42e8-4be9-a67f-b7e18e03b436")

The above command returns a JSON object when the response is ready. It returns None otherwise.