FeersumNLU API Wrappers

This git repo hosts Python language wrappers and cURL examples for the FeersumNLU & FeersumVision RESTful HTTP APIs. FeersumNLU & FeersumVision are the language and image comprehension components of Feersum Engine https://www.feersum.io .

Overview

FeersumNLU & FeersumVision provide machine comprehension for natural chat-like interactions with your users. The components are designed to be flexible enough to work with any language, even in markets where large bodies of labelled data do not exist yet.

Our in-house comprehension models are based on the latest research and can be setup for various specialised verticals like finance and health. The APIs are also designed such that a user may add multi-lingual Natural Language Understanding (NLU) and image comprehension to their application without requiring a deep understanding of NLU and computer vision theory.

The examples in this repo demonstrate commonly required NLU and vision functions. The language wrappers are auto-generated from an API Swagger spec available at https://nlu.playground.feersum.io:443/nlu/v2/swagger.json. The cURL examples of direct HTTP access are in the examples_curl folder.

(Note: This repo is currently being updated with more examples. You may subscribe to receive notifications about updates at https://libraries.io/pypi/feersum_nlu )

Features

Current NLU features include natural language FAQ's, detection of the user's intent and sentiment, information extraction, entity extraction, and text-based language identification.

Current vision features include image classification and information extraction.

Installing

Please have a look at the examples in the repo. It is also recommended that you create a Python virtual environment and then follow one of the install options below to run the examples. The examples were tested with Python 3.5 and 3.6.

Creating a Python Virtual Environment

To get started with the Python wrappers install Python 3.5 (or 3.6) and pip. Then do:

$ virtualenv -p /usr/local/bin/python3.5 .pyenv
$ source .pyenv/bin/activate
$ pip install pip-tools
$ pip install appdirs

If you don't have virtualenv installed first run:

$ pip install virtualenv
$ sudo /usr/bin/easy_install virtualenv

Install Option 1 - Using make

Clone the repo and then to install the dependencies required to run the module's examples run:

$ make requirements
$ make deps

Install Option 2 - Using setuptools

Alternatively clone the repo and then install the feersum_nlu wrapper module into your Python environment using setuptools:

$ make requirements
$ make deps
$ python setup.py install

The benefit of installing the feersum_nlu module into you Python environment is that you can more easily use it in your own projects.

Install Option 3 - Using pip

The feersum_nlu wrapper module is also available from the Python Package Index https://pypi.python.org/pypi/feersum_nlu. To install it using pip run:

$ pip install feersum_nlu

The benefit of installing the feersum_nlu module into you Python environment is that you can more easily use it in your own projects.

Running the Examples

If you use an IDE like PyCharm you can simply open the folder you cloned the source to (e.g. feersum-nlu-api-wrappers) with the IDE.

Or to start executing example notebooks install Jupyter with

$ pip install jupyter

and then run:

$ jupyter notebook

The notebooks are all in the example_notebooks folder.

Alternatively run the example python scripts in the examples folder from the terminal e.g.:

$ PYTHONPATH=. python examples/faq_matcher.py

Remember to set your API token in the example scripts and notebooks.

The FeersumNLU Playground Server

A FeersumNLU playground instance of the RESTful web service is hosted at nlu.playground.feersum.io:443/nlu/v2 You may use this URL to run the examples given in this repo.

You'll need an authentication token to access the service, so email us at [email protected] and we'll send you a token to use. Some autogenerated API documentation is available at https://nlu.playground.feersum.io/ui/

Note that this is just a playground instance. Please contact us at [email protected] for a variety of hosting options including containerised solutions.

Making your Own API Wrapper

This Python language wrapper was generated using the swagger-codegen toolchain. The full process is in the makefile target called update_spec. To update the Python wrapper run:

$ make update_spec

To generate an API wrapper for another language modify the command to use a different generator. See https://github.com/swagger-api/swagger-codegen#to-generate-a-sample-client-library for some more details.

To generate a PHP wrapper, for example, change the generate command to something like:

$ swagger-codegen generate -i swagger/swagger.yaml -l php -c swagger/swagger_codegen-python_config.json -o swagger/build_php