google-actions-server

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google-actions-server

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A Node.js server for your Google Actions

google-actions-server 최신버젼 다운로드

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<p align="center">
  <img src="https://cloud.githubusercontent.com/assets/1699357/21663314/b022ace0-d2df-11e6-8713-9f68b1c3ee3b.png" width="350">
</p>
<h2 align="center">GAS: Google Assistant Server
    <a href="https://circleci.com/gh/manekinekko/google-actions-server"><img src="https://circleci.com/gh/manekinekko/google-actions-server.svg?style=svg"/></a>
</h2>
<p align="center">A Node.js server for your <a href="https://developers.google.com/actions/">Google Assistant</a> (and <a href="https://madeby.google.com/home/">Google Home</a>).</p>

### Get it from NPM

```bash
npm i -S @manekinekko/google-actions-server
```

### Get it from Yarn

```bash
$ yarn add @manekinekko/google-actions-server
```
## How to use it

See the [GAS Starter](https://github.com/manekinekko/google-actions-starter) for more details.

## GAS API

Here is the simplest guide in order to use GAS:

```javascript
import { ActionServer } from '@manekinekko/google-actions-server';

const agent = new ActionServer();

agent.welcome((assistant) => {
    agent.ask('Welcome Home. How can I help');
});

agent.intent(ActionServer.intent.action.TEXT, (assistant) => {

// reads the user's request
  const userInput = assistant.getRawInput();

})

// start listening for commands (on port 8080)
agent.listen();

```

### Intents

Available intents are:

#### ActionServer.intent.action.MAIN

This intent is triggered when users invoke your action by name, such as "talk to <YOUR ACTION NAME HERE>". This intent si required for every action package.

#### ActionServer.intent.action.TEXT

This intent is triggered when users speak input and you receive the input as a request to your fulfillment endpoint.

#### ActionServer.intent.action.PERMISSION

Triggered if Google Assistant needs to ask the user for more permissions (not implemented yet by GAS)

### ActionServer

#### ActionServer(port = 8080)

Create an HTTP server and set it to listen on port `port` (default: 8080).

### Agent

Calling `new ActionServer()` will return an `Agent` instance, which exposes the following API:

#### agent.intent(name, callback)

Register a `callback` with an intent of type `ActionServer.intent.action.*`. When invoked, the `callback` function receives an instance of **[ActionsSdkAssistant](https://developers.google.com/actions/reference/ActionsSdkAssistant)**. For instance:

```javascript
agent.welcome(ActionServer.intent.action.TEXT, (assistant) => {
  // assistant
});
```

#### agent.welcome(callback)

Register a `callback` with the **ActionServer.intent.action.MAIN** intent. This is the same as:

```
agent.intent(ActionServer.intent.action.MAIN, (assistant) => {
  // assistant
});
```

Register a `callback` with the **ActionServer.intent.action.MAIN** intent. This is the same as:

#### agent.listen()

Starts the GAS server on port `8080` (the default port). This method **must be** called after you have registered all of your intents.

#### agent.ask(message)

A convenient method that abstracts away the `assistant.ask()` configuration. Typically, with `assistant.ask()` you have to:

```javascript
const inputPrompt = assistant.buildInputPrompt(isSsml, message, noInputs);
assistant.data = previousState;
assistant.ask(inputPrompt);
```

With `agent.ask()`, you can just pass it the message:

```javascript
agent.ask(message);
```

Of course, you can still call `assistant.ask()` if you want to provide a configuration.

#### setGreetings(greetings)

A convenient method to set a list of greeting messages that you will play randomly to the user.

#### getRandomGreeting()

A convenient method to get a random greeting message set using `agent.setGreetings()`.

#### randomGreeting()

A convenient method that will trigger a random greeting message for you.

#### setConversationMessages(conversationMessages)

A convenient method to set a list of random conversations asking the user for another query. For instant: `How can I help?` or `Do you have another request?`.

#### getRandomConversationMessage()

A convenient method to get a random conversation message set using `agent.setConversationMessages()`.

#### agent.train(dataSetKey, data, fields = ['data']))

This method is used to provide a set of data that will be used by `agent.matchUserRequest()`. This could be the data that will be used by the assistant to interact with the user, or a set of Hot Words such as:

```javascript
this.agent.train('hot_words', [
    'what time is it?',
    'tell me the time',
    `what's the time`,
    //...
]);
```

Here is another use case, let's say you want to provide a decision list:

```javascript
const decisionList = [
    {
        'scenario': 'I have one existing Observable, and I want to change each emitted value to be a constant value',
        'operator': 'mapTo'
    },
    {
        'scenario': 'I have one existing Observable, and I want to change each emitted value to be a value calculated through a formula',
        'operator': 'map'
    },
    ...
];
```

You would then provide it to GAS like so:

```javascript
const fields = ['operator', 'scenario'];
this.agent.train('decision_list', decisionList, fields);
```

Please note that the `fields` option has been provided since the items inside this decision list are stored in key/value pairs.

**IMPORTANT: the first field (in the sample above: `operator`) will be used as the reference field: the field that will be returned by `agent.matchUserRequest()`.**

#### matchUserRequest(dataSetKey, rawInput, responseCallback, lookupOptions = {})

**NOTE:** GAS uses [elasticlunr](https://github.com/weixsong/elasticlunr.js) that performs the [Full-Text Search](https://en.wikipedia.org/wiki/Full-text_search) technique to retrieve the matched documents.

Use this method to match the user's input with a set of data provided in `agent.train()`.

For instance, let's say you have the `decisionList` list from the example above; in order to find a matched document you would call `agent.matchUserRequest()` like so:

```javascript
// get the user's input
const rawInput = assistant.getRawInput();

// provide a lookup configuration (see below)
const lookupOptions = {...};

// the callback that will be called
const responseCallback = (foundDocuments, rawInput) => { ... };

// run the search operation
const matchedDocuments = this.agent.matchUserRequest('decision_list', rawInput, responseCallback, lookupOptions);
```

The `matchedDocuments` would then contain the matched documents based on the `rawInput` string. In some case you may get false-positives, documents that are not relevant to the intended search question.
In this case, you may provide a `lookupOptions` object in order to configure/tweak the search operation.

**NOTE:** if no documents are found, an empty array is returned.

##### threshold

You can provide the `threshold` property to filter out the false-positives. `threshold` can be either a Number or a Function.

Using a number:

```javascript
const lookupOptions = {
    threshold: 0.6
};
```

When using a function, it will be provided with the current entry from the data set. You can access the `score` property on that entry:

```javascript
const lookupOptions = {
    threshold: entry => {
        return entry.score > 0.6;
    }
};
```

##### fields

The fields property is a [elasticlunr configuration query](https://github.com/weixsong/elasticlunr.js#52-configuration-query). For instance, we could provide the following configuration for the example from above:

```javascript
const lookupOptions = {
    fields: {
        scenario: {
            boost: 2,
            bool: 'AND',
            expand: true
        },
        operator: {
            boost: 1
        }
    }
};
```

See [elasticlunr configuration query](https://github.com/weixsong/elasticlunr.js#52-configuration-query) for more details.

#### fetch(url, responseCallback, useCache = true)

A convenient method to fetch a remote document. Useful if you want to get more information from a remote website. For instance:

```javascript
agent.fetch(url, (error, content) => {
    if (error) {
        console.error(error);
    }
    else {
        console.log(content);
    }
});

```

# Disclaimer

The current implementation is still a POC. It's obviously missing lots of features. Please open issues to discuss any feature you want to be added, submit suggestions, or anything else...
All contributions are welcome ;)

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