How I did customize "rasa-nlu-trainer" as my own tool - The Koch Family
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How I did customize "rasa-nlu-trainer" as my own tool


Check out my implementation here

Background

I wanted to have a tool for human beings to classify intents and extract entities of texts which were obtained from a raw dataset such as Rocket.chat's conversation, Maluuba Frames or here. Then, the output (labeled texts) could be consumed by an NLU tool such as Rasa NLU.

rasa-nlu-trainer was a potential one which I didn't need to build an app from scratch. However, I needed to add more of my own features to fulfill my needs. They were:

1. Loading/displaying raw texts stored by a database such as MongoDB
2. Manually labeling intents and entities for the loaded texts
3. Persisting labeled texts into the database

I firstly did look up what rasa-nlu-trainer's technologies were used in order to see how to implement my mentioned features.

At first glance

rasa-nlu-trainer was bootstrapped with Create React App. Create React App is a tool to create a React app with no build configuration, as it said. This tool is also recommended by the official React.js tutorial. I actually was very new to React.js. I wondered what problem Creat React App tried to solve so that I first wanted to set up a project without Create React App. I followed this post.

Well, let me say if I built a React app from scratch then I needed to do some manual configurations for Webpack and Babel including webpack.config.json and .babelrc

Then, I tried to use Create React App, and I followed this guide. All right, let me say Create React App helped me create a React boilerplate project with hiding Webpack and Babel's configuration so that as a developer I only needed to focus on writing production code.

The nuts and bolts

I went on starting to watch how rasa-nlu-trainer's source code was organized and what its techniques are used.

Folder structure

1. Auto-created stuff by Create React App
   - public/index.html
   - src/index.js
2. Overrides
   - They didn't use "react-script", they created their own way instead! That was the reason why some additional folder/files were added such as server.js, scripts and config.

Used technologies

- Programming language: Javascript
- Babel: ES6 transpiler
- Project bundle: Webpack
- Dependencies management: npm
- Backend: Node.js
- Fronted framework/project-based: React.js
- React model storing: React-Redux
- React UI extension components: Ant Design
- TypeScript

Hooray! Welcome me to Javascript world!

Architecture

- index.js: Provider{store} <---> LocaleProvider ---> App
- How "separation of concerns" works: import and  export
- Global data (store) is immutable and only changed by files actions.js and reducer.js

Proposed changes

Finally, I could start to add my needs to the existing rasa-nlu-trainer app. I listed out what my features:
- Creating an overview page as a custom React component to display all loaded texts
- Customizing the existing page for classifying intents and extracting entities.
- Implementing Node.js methods to load/stores texts (as JSON)  which stored in MongoDB

The rule of thumb was I needed to follow the mentioned architecture for modifying the global data which were managed by React-Redux.

You can take a look at the changes from this pull request.

Conclusion

Sometimes, the best way to learn new techs is to get down into an existing tool and customize it with your own needs. 💪

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