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Generic conversation bot

Project description

A simple conversation bot with ability of reading the dialogue scripts from JSON files.

Installation

The packages are publish on Github NPM repository.

npm install @dplocki/generic-conversation-bot

Internal architecture

The bot (class Bot) is a state machine. The state contain the logic of reaction on received message (from user). The reaction is collection of actions. User input, provide also memory cache.

State

State is an object. Each state need to implements two methods: *beforeMessage() and *analyse(message).

Both return collection of actions (as generator). The beforeMessage is called when bot is change its internal state. The analyse method is called when Bot receive the new message.

class State {
    *beforeMessage() {
    }

    *analyse(message) {
    }
}

States available by default

  • ChooseState - Similar in work as switch code
  • IfElse - Similar in work as if else code
  • MoveNextState - Displays the given text, no matter the input will call all provided actions
  • WaitForActivationState - The starting state, bot will ignore all input until given phrase (like: "hi") will be given

Actions

Each action is function. The action is taking two parameters:

  • bot - the Bot object
  • message - the whole message object received by the Bot

The return value of action is ignored.

function action(bot, message) {
}

For simplicity the the action builders are store in the actions.js file. Those are functions returning actions functions.

Actions available by default

  • response(text) - Sets the response of Bot
  • staySilence() - Removes all response
  • setState(state) - Sets the given state as next one
  • endConversation() - Resets the Bot
  • jumpToState(stateName) - Sets the state from states list by its name
  • remember(key, value) - Saves the value in memory on provided key
  • rememberInputAs(key) - Saves the input (user message, only text) in memory on provided key
  • increaseRemembered(key) - Increase the value from memory on key by one (if value is not numeric, will be replace by 1)
  • decreaseRemembered(key) - Decrease the value from memory on key by one (if value is not numeric, will be replace by -1)

Parser

The Bot state machine can be loaded from JSON file. The file needs to be parsed first.

The parser is provided by ParserBuilder object. You can create parser containing additional states, actions or preparser actions.

const states = new ParserBuilder()
    .addCustomActions(require('./actions'))
    .addCustomStates(require('./states'))
    .addPreParsers(require('./preParsers'));
    .parse(
        JSON.parse(fs.readFileSync('input.json', 'utf8'))
    );

The input file

The json file contain an array of objects. Each of it need to have two attributes: type and name.

[
    {
        "type": "type_of_state",
        "name": "name_of_state"
    }
]

The parsing process transform the file into the object, where key is name of state.

Preparser

The preparser are called before the parsing process, for given pre-states. To call them you need provide two attribute: pre_parser and pre_states.

[
    {
        "pre_parser": "pre_parser_name",
        "pre_states": [
            { },
            { }
        ]
    }
]

The pre_parser value indicate which preparser needs to be called on given pre_states. The result: the collection of ready-to-parsing-states, will be input for parsing.

Example of preprocessor

function preprocessor(state, index, allStates) {
    return state;
};

Examples

Both example bot can use BitClient. The function use the Node readline module for terminal usage.

Running examples

All require installation of package.

Simple

A linear conversation. The bot will ask about name and use it back.

The example demonstrate the memory usage.

Quiz

A linear conversation. The bot will ask few simple question and save the results showing the summary on the end.

The example demonstrate own additional (the SummaryState class) state.

Exam

A nonlinear exam conversation. The bot will ask few simple question but user can skip and returning to them letter. Bot will summaries the result on end.

The example demonstrate preparser.

Tests

The unit test are based on Mocha.

Running

npm test