============

jsharmony-ai

============

AI extensions for jsHarmony

Installation

``
npm install jsharmony-ai
`

Then, in app.config.js or app.config.local.js, initialize the module:

`
var jsHarmonyAI = require('jsharmony-ai');

exports = module.exports = function(jsh, config, dbconfig){
jsh.AddModule(new jsHarmonyAI());

var configAI = config.modules['jsHarmonyAI'];
if (configAI) {
configAI.OpenAI.apiKey = '...';
}
}
`

Text Prompt

`
var jsHarmonyAI = jsh.Modules['jsHarmonyAI'];
var rslt = await jsHarmonyAI.prompt('How has Artificial Intelligence advanced over the years?');
`

Typed Prompt

A typed prompt can return a "number", "string", "string_arr", or "bool"
`
var jsHarmonyAI = jsh.Modules['jsHarmonyAI'];
var rslt = await jsHarmonyAI.typedPrompt('number', 'How many bytes are in a kilobyte? Please only return the number by itself.');
`

Chat Bot

`
var jsHarmonyAI = jsh.Modules['jsHarmonyAI'];
var chatServer = new jsHarmonyAI.ChatServer();
var chatScript = [
//Message
{ chat: 'Welcome to the coffee bot.' },

//User Prompt
{ prompt: 'What is your favorite coffee?', key: 'Favorite Coffee', instruction: 'Keep asking until the user provides their favorite coffee. Return only the type of coffee', },

//Information Synthesis
{ synthesize: 'Determine the answer to the following question: What are similar coffees the user might enjoy?', format: 'string_arr', key: '$Similar Coffee' },

//Custom Functions & Report Generation
{
exec: async function(client){
var coffeeReport = chatServer.applyTemplate(fs.readFileSync('./reportTemplate.txt').toString(), client.vars);
client.send('assistant','Please find your customized coffee report below:');
client.send('assistant','\n'+coffeeReport, { format: 'pre' });
client.continueChatScript();
}
},
];
var defaultVars = {
'Coffee Shop': "Jake's Coffee",
};
chatServer.run({ defaultChatScript: chatScript, defaultVars: defaultVars });
`

Image Generation

`
var jsHarmonyAI = jsh.Modules['jsHarmonyAI'];
var url = await jsHarmonyAI.promptImage('Draw a futuristic mainframe computer');
require('child_process').exec('"c:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe" "'+url+'"');
`

Vector Database Indexing

`
var jsHarmonyAI = jsh.Modules['jsHarmonyAI'];
var vectorDb = await new jsHarmonyAI.VectorDb({
getEmbedding: async function(content){ return await (await jsHarmonyAI.getEmbedding(content))[0]; },
fields: {
page: 'number',
title: 'string',
}
});
await vectorDb.index(pages[0], { title: 'jsHarmony Tutorials', page: 1 });
await vectorDb.index(pages[1], { title: 'jsHarmony Tutorials', page: 2 });
await vectorDb.save();
`

Vector Database Search

`
var vectorDb = await new jsHarmonyAI.VectorDb({
getEmbedding: async function(content){ return (await jsHarmonyAI.getEmbedding(content))[0]; }
});
var rslt = await vectorDb.searchVector('What animal does Ursus fight?',{
where: { title: 'How can I define a grid model?' }
// or { numericField: { eq: value } }
});
``