Python and other language wrappers for the FeersumNLU http api.
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FeersumNLU API Wrappers

This git repo hosts Python and other language wrappers for the FeersumNLU RESTful HTTP API. FeersumNLU is the natural language understanding component of Feersum Engine .

The HTTP API is designed such that a user may apply multi-lingual Natural Language Understanding (NLU) to their application domain without requiring a deep understanding of NLU theory. The examples in this repo demonstrate commonly required NLU functions and how to access them. There are also some cURL examples of direct HTTP access in the examples_curl folder.

These language wrappers and examples are for version 2.0.23 of the HTTP API. The language wrappers are auto-generated from a Swagger spec of the API available at

(Note: This repo is currently being updated with more examples. You may subscribe to update notifications at )


FeersumNLU provides natural language understanding solutions for chat-based interactions, where messages from the end-user may be long or very short. Our product is also designed to be language-agnostic, which means it can be scaled to work with any language, even in markets where large bodies of labelled data do not exist. Our Natural Language Understanding models are developed locally, and can be modified to provide solutions for specialised industries like finance or health.


FeersumNLU makes use of open-source building blocks like NLTK, sklearn, PyTorch and Duckling, as well as algorithms we've developed in-house. We build on all elements to support a growing list of local and international languages.

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


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 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 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/

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 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 and we'll send you a token to use. Some autogenerated API documentation is available at

Note that this is just a playground instance. Please contact us at 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 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