This template powers our system at Simply API

(This is a much complex system to work with !)

• Provide your chatbot's details in the .env.example file
• Change the input as you like in index.js
• Run the project and you are ready to go

• Train your AI in the corpus.json file
• Run javascript/dynamic response using pipelines.md for specific intent (type)
• DO NOT edit the conf.json file !!
• Use the response anywhere ! You can make an API or use in your application

• NLP (Natural Language Processing) is an CPU and RAM intensive system.
• Training the ML model is the most computationally intensive task
• DO NOT run this project on a potato !

It is your job to train the AI. The more you train, the more smarter it gets.

You can train the ai in two ways

• The easy one

Using the nlpjs module, you can train the system with functions

You can get the manager from the train(nlp) function in index.js

// ------------------------------------
// These should be in a async function !
// ------------------------------------

// Training the input-type relation (user.testing is the type here)
manager.addDocument(
    'en',
    'im testing you',
    'user.testing'
  ); 

// Response for the type of the input (user.testing is the type here)
manager.addAnswer( 
     'en', 
     'user.testing', 
     'I hope to pass the tests. Feel free to test me often' 
   );

await manager.train();

• The hard one

You can directly edit the corpus.json to train it. (Prone to more errors)

Template

{
  "intent": "user.testing", // Initializing the type
  "utterances": [ // Training the input-type relation (user.testing is the type here)
    "im testing you",
    "thats a test"
  ],
  "answers": [ // Array of Response for the type of the input (user.testing is the type here)
    "I hope to pass your tests. Feel free to test me often",
    "Test me often.",
  ]
}

• Extras

You need to send a dynamic URL for a specific type of input. But how ?

Its via using pipelines.md !

Template

you need to train the input-type relation in corpus.json

{
  "intent": "doubt.qna",
  "utterances": [
    "What is wikipedia",
    "What is Ferrari",
    "What is an atom",
    "What is curtain",
    "What is github"
  ]
}

where

• the doubt.qna is the type of input
• the utterances are the inputs to define its type

you need to dynamically respond via pipelines.md

# onIntent(doubt.qna)
// compiler=javascript

{ The JS code }

where

• the doubt.qna is the type of input
• the { The JS code } is your Javascript code for dynamic response