iod-node v0.1.3

Note: this library is depreciated. All future work will be done here.

Node JS client library for IDOL OnDemand

Basic library to help with calling IDOL OnDemand APIs http://idolondemand.com.

What is IDOL OnDemand?

IDOL OnDemand is a set of over 70 APIs for handling all sorts of unstructured data. Here are just some of our APIs' capabilities:

• Speech to text
• OCR
• Text extraction
• Indexing documents
• Smart search
• Language identification
• Concept extraction
• Sentiment analysis
• Web crawlers
• Machine learning

For a full list of all the APIs and to try them out, check out https://www.idolondemand.com/developer/apis

Installation

To install, run the following command:

npm install iod-node

If you want to install the latest module directly from Github, use the following command:

npm install git+https://github.com/HP-IDOL-OnDemand/iod-node

Include it

var iod = require('iod-node')
client = new iod.IODClient('http://api.idolondemand.com','apikey')

Callbacks

var callback = function(err,resp,body){
  console.log(body)
}

We can define our callbacks as functions and pass them as arguments

var data = {'text' : 'I like cats'}
client.call('analyzesentiment', callback, data)

Or, we can use the .on('data') hook to do the same thing.

client.call('analyzesentiment',data).on('data',callback)

The order of the arguments after the API name doesn't matter when passed, so all of these are the equivalent.

//1
client.call('analyzesentiment', data, callback)
//2
client.call(data, 'analyzesentiment', callback)
//3
client.call(data, callback, 'analyzesentiment')

Async calls

While node will mostly deal with things asynchronously, IDOL OnDemand offers server side asynchronous call method which should be used with large files and slow queries. Pass a boolean for the async parameter.

client.call('analyzesentiment', data, callback, true)

Posting files

File posting is handled using the "file" parameter name which is used for all current file postings in IDOL OnDemand

var data = {'file' : 'test.txt'}
client.call('analyzesentiment', data, callback)