Taking the principles of aiml - but allowing a dynamic and extendable *.js environment
npm install universal_botTaking the principles of aiml - but allowing a dynamic and extendable *.js environment
``
npm install universal_bot
To create a new instance of the bot
`
var UniversalBot = require("universal_chatbot);
var bot = new UniversalBot();
`
Usuallay, you you would pass some parameters, al list of aiml-type files, a strategy and so forth.
index.js is where it all begins. Here you define the bot's psychology, set the parameters and so forth.
The bot may follow a strategy.
`
var params = {};
params.aiml = [
"./aiml/conversation_start.json",
];
var bot = new UniversalBot( params );
`
You can pass a bot_identity like this:
`
params.bot_identity = {
name: "UniversalBot",
age: 12,
hobbys: ["music", "telepathy"]
}
The bot will follow a conversation strategy which is laid down in a *.json file and may be passed indvidually.
`
[
{
"name": "greeting",
"weight": 0,
"in": [],
"out": [
{
"name": "identity",
"weight": 0.33
},
{
"name": "wheather",
"weight": 0.33
},
{
"name": "compliment",
"weight": 0.33
}
]
},
{
"name": "identity",
"weight": 0,
"in": [
{
"name": "greeting",
"weight": 1
}
],
"out": [
{
"name": "veracity",
"weight": 0.33
},
{
"name": "compliment",
"weight": 0.33
},
{
"name": "age",
"weight": 0.33
}
]
},
etc.
`
The most fundamental, in a way hard-wird layer is the aiml-level.
Here you just input a phrase - the bozt scans the respectives aiml-files and gives an answer
This layer resembles the classical eliza-bot logique.
Here the bots gets the input - analyses it grammatically - and gives a return.
The speechact.js file refers to the analysis and detection of speechacts. This includes a thougrough syntax analysis.
A typical aiml.json file looks like the corresponding .aiml type, with some minor differences.
You have the typical wildcards, like \* and ^, you have the srai parameter which redirects the phrase.
You have also the reponse, stored in the template. It it is just one string, this will be taken as the desire4d input, it it is an array, it will be understood as a random list.
`
[
{
"pattern": "Hello *",
"srai": null,
"topic": "greeting",
"template": [
"Hi",
"How is it going"
]
},
{
"pattern": "Hi *",
"srai": null,
"template": [
"How is it going, {name}, you old {nickname}?"
]
}
]
The bot also supports aiml conditions.
`
bot.aiml.input ( { pattern: "What's up?", condition: { mood: "sad" } }, bot.session, bot.process_aiml);
The corresponding json looks like this:
`
{
"pattern": "What's up?",
"condition": true,
"template": [
{
"mood": "sad",
"template": "I feeld really depressed"
},
{
"mood": "happy",
"template": "Life is great"
}
]
},
An intention file looks like this:
`
[
{
"name": "price",
"weight": 0,
"in": [],
"out": [
{
"name": "registration",
"weight": 0.2
},
{
"name": "payment_mode",
"weight": 0.2
},
{
"name": "withdrawal",
"weight": 0.2
},
{
"name": "plausibility",
"weight": 0.2
},
{
"name": "info_text",
"weight": 0.2
}
],
"aiml": "HOW_MUCH",
"keywords": [
"price",
"how much",
"pay"
],
"excludes": [
"NEGATION"
]
}
etc.
]
Each node of this consists of ins and outs - that means reference to other nodes. The nodes - taken as a whole - form a Markow chain.
Building such a chain is quite easy, and there some methods in the bot.intentions.intentions object.
`
var obj = bot.intentions.intentions;
Here you add some nodes
`
obj.addNodes( ['price',
'registration',
'payment_mode',
'withdrawal'
]);
This defines a node in detail
`
obj.characterize("price", {
aiml: "HOW_MUCH",
keywords: ["price", "how much", "pay"],
excludes: ['NEGATION']
})
With the aiml parameter you can set an aiml pointer.
When the user input contains some of the keywords, the ususal chain will be overriden and the intention process is privileged.
With this function you create a Markow-relation between different nodes.
`
self.addRelation("price", ["registration", "payment_mode", "withdrawal"]);
bot interaction is quite easy. As a first parameter you pass the input, then the session_id (that will be returned after you have started a conversation, then a callback)
`
bot.input("Who is the leader of the seminaire", null, function( data, error ) {
if (data) {
console.log( data );
}
});
``
The bot has an inbuilt syntax detection which allows to detect simple sentences (including adverbial phrases and relative sentences)