Sentiment Analysis

This project exemplifies how to consume the Shipped Brain API by making a prediction to the Sentiment Analysis model.

The app was built using Angular 9.

Authenticate requests

In /src/app/interceptors/auth.interceptor.ts replace <your_token> with your Shipped Brain token.

In a real world use case, we recommend NOT storing your authorization token the way we did here for demonstration purposes, but instead choose a safer alternative (i.e: environment variables).

const token: string = '<your_token>'

To find out your token, login to your Shipped Brain account, access the Dashboard and copy it from its respective area.

Note

When cloning this repository, before running the app you must install the npm packages with:

npm run install

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Angular info

This project was generated with Angular CLI version 9.1.14.

Development server

Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via Protractor.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI README.