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https://github.com/watson-developer-cloud/natural-language-classifier-nodejs

Deprecated: this demo will receive no further updates
https://github.com/watson-developer-cloud/natural-language-classifier-nodejs

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Deprecated: this demo will receive no further updates

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Deprecated: this repo has been archived and will not receive further updates. It is being left in read-only mode for documentation purposes, but the code should not be considered current.


πŸš€ Natural Language Classifier Sample Application


This Node.js app demonstrates some of the Natural Language Classifier service features.




Travis


semantic-release

The IBM Watsonβ„’ Natural Language Classifier service applies deep learning techniques to make predictions about the best predefined classes for short sentences or phrases. The classes can trigger a corresponding action in an application, such as directing a request to a location or person, or answering a question. After training, the service returns information for texts that it hasn't seen before. The response includes the name of the top classes and confidence values.

![demo](public/demo.gif)

You can view a [demo](https://natural-language-classifier-demo.ng.bluemix.net/) of this app.

## Prerequisites

1. Sign up for an [IBM Cloud account](https://cloud.ibm.com/registration/).
1. Download the [IBM Cloud CLI](https://cloud.ibm.com/docs/cli/index.html#overview).
1. Create an instance of the Natural Language Classifier service and get your credentials:
- Go to the [Natural Language Classifier](https://cloud.ibm.com/catalog/services/natural-language-classifier) page in the IBM Cloud Catalog.
- Log in to your IBM Cloud account.
- Click **Create**.
- Click **Show** to view the service credentials.
- Copy the `apikey` value.
- Copy the `url` value.

## Configuring the application

1. The Natural Language Classifier service must be trained before you can successfully use this application. The training data is provided in the file `training/weather_data_train.csv`.
If you have `username` and `password` credentials, train a classifier by using the following command:

```sh
curl -i -u "apikey":"" \
-F training_data=@training/weather_data_train.csv \
-F training_metadata="{\"language\":\"en\",\"name\":\"TutorialClassifier\"}" \
"/v1/classifiers"
```
Make sure to replace `` and ``.
After running the command, copy the value for `classifier_id`.

2. In the application folder, copy the *.env.example* file and create a file called *.env*

```
cp .env.example .env
```

7. Open the *.env* file and add the service credentials that you obtained in the previous step.

Example *.env* file that configures the `apikey` and `url` for a Natural Language Classifier service instance hosted in the US East region:

```
NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY=X4rbi8vwZmKpXfowaS3GAsA7vdy17Qh7km5D6EzKLHL2
NATURAL_LANGUAGE_CLASSIFIER_URL=https://gateway.watsonplatform.net/natural-language-classifier/api
```

8. Add the `CLASSIFIER_ID` to the previous properties

```
CLASSIFIER_ID=522be-7b41-ab44-dec3-g1eab2ha73c6
```

## Running locally

1. Install the dependencies

```
npm install
```

1. Run the application

```
npm start
```

1. View the application in a browser at `localhost:3000`

## Deploying to IBM Cloud as a Cloud Foundry Application

1. Login to IBM Cloud with the [IBM Cloud CLI](https://cloud.ibm.com/docs/cli/index.html#overview)

```
ibmcloud login
```

1. Target a Cloud Foundry organization and space.

```
ibmcloud target --cf
```

1. Edit the *manifest.yml* file. Change the **name** field to something unique.
For example, `- name: my-app-name`.
1. Deploy the application

```
ibmcloud app push
```

1. View the application online at the app URL.
For example: https://my-app-name.mybluemix.net

## Directory structure

```none
.
β”œβ”€β”€ app.js // express routes
β”œβ”€β”€ config // express configuration
β”‚Β Β  β”œβ”€β”€ error-handler.js
β”‚Β Β  β”œβ”€β”€ express.js
β”‚Β Β  └── security.js
β”œβ”€β”€ manifest.yml
β”œβ”€β”€ package.json
β”œβ”€β”€ public // static resources
β”œβ”€β”€ server.js // entry point
β”œβ”€β”€ test // unit tests
β”œβ”€β”€ training
β”‚Β Β  └── weather_data_train.csv // training file
└── views // react components
```

## License

This sample code is licensed under Apache 2.0.
Full license text is available in [LICENSE](LICENSE).

## Contributing

See [CONTRIBUTING](CONTRIBUTING.md).

## Open Source @ IBM

Find more open source projects on the
[IBM Github Page](http://ibm.github.io/).