Libraries tagged by isan

This library is an implementation of the php-extended/php-parser-interface based on a lexer for handling its data

Go to Download

Phonon is an open source HTML, CSS and JavaScript agnostic framework that allows to create a website or a hybrid Web app.

Go to Download

PHPRtfLite is an API enabling developers to create rtf documents with php. This fork add fixes for PHP8.

Go to Download

TAO is an Open Source e-Testing platform that empowers you to build, deliver, and share innovative and engaging assessments online – in any language or subject matter.

Go to Download

Novactive eZ 2FA Bundle is an eZ Platform bundle that provides two-factor authentication for your ezplatform project

Go to Download

Netgen Site Bundle is an Ibexa bundle that implements common features that are used by Netgen to implement websites

Go to Download

eZ Publish Legacy (aka LegacyStack in 5.x. Is an updated version of eZ Publish 4.x capable of being combined with Ibexa OSS)

Go to Download

eZ Platform Search is an eZ Publish legacy extension that integrates eZ Platform search capabilities into eZ Publish legacy

Go to Download

Plastic is an Elasticsearch ODM and mapper for Laravel. It renders the developer experience more enjoyable while using Elasticsearch by providing a fluent syntax for mapping , querying and storing eloquent models.

Go to Download

WP CLI Seed Command is an extension for WP-CLI to seed database with sample data

Go to Download

The lake-admin is an admin package.

Go to Download

A port of the CoffeeScript compiler to PHP. (See http://github.com/alxlit/coffeescript-php, this is an exact fork to fix minimum stability on the last release)

Go to Download

Koongo is an ultimate product data feed management tool that streamlines the process of product data export from Magento 2 store to any of 500+ price comparison websites, online marketplaces, and affiliate networks worldwide. Koongo helps you upload your product data to selling channels like Google Shopping, Shop.com, Facebook, Rakuten, Twenga, Bol.com, Beslist.nl, Bing Ads, and more.

Go to Download

Altax is an extensible deployment tool for PHP.

Go to Download

# Introduction **INDA (INtelligent Data Analysis)** is an [Intervieweb](https://www.intervieweb.it/hrm/) AI solution provided as a RESTful API. The INDA pricing model is *credits-based*, which means that a certain number of credits is associated to each API request. Hence, users have to purchase a certain amount of credits (established according to their needs) which will be reduced at each API call. INDA accepts and processes a user's request only if their credits quota is grater than - or, at least, equal to - the number of credits required by that request. To obtain further details on the pricing, please visit our [site](https://inda.ai) or contact us. INDA HR embraces a wide range of functionalities to manage the main elements of a recruitment process: + [**candidate**](https://api.inda.ai/hr/docs/v2/#tag/Resume-Management) (hereafter also referred to as **resume** or **applicant**), or rather a person looking for a job; + [**job advertisement**](https://api.inda.ai/hr/docs/v2/#tag/JobAd-Management) (hereafter also referred to as **job ad**), which is a document that collects all the main information and details about a job vacancy; + [**application**](https://api.inda.ai/hr/docs/v2/#tag/Application-Management), that binds candidates to job ads; it is generated whenever a candidate applies for a job. Each of them has a specific set of methods that grants users the ability to create, read, update and delete the relative documents, plus some special features based on AI approaches (such as *document parsing* or *semantic search*). They can be explored in their respective sections. Data about the listed document types can be enriched by connecting them to other INDA supported entities, such as [**companies**](https://api.inda.ai/hr/docs/v2/#tag/Company-Management) and [**universities**](https://api.inda.ai/hr/docs/v2/#tag/Universities), so that recruiters may get a better and more detailed idea on the candidates' experiences and acquired skills. All the functionalities mentioned above are meant to help recruiters during the talent acquisition process, by exploiting the power of AI systems. Among the advantages a recruiter has by using this kind of systems, tackling the bias problem is surely one of the most relevant. Bias in recruitment is a serious issue that affect both recruiters and candidates, since it may cause wrong hiring decisions. As we care a lot about this problem, we are constantly working on reduce the bias in original data so that INDA results may be as fair as possible. As of now, in order to tackle the bias issue, INDA automatically ignores specific fields (such as name, gender, age and nationality) during the initial processing of each candidate data. Furthermore, we decided to let users collect data of various types, including personal or sensitive details, but we do not allow their usage if it is different from statistical purposes; our aim is to discourage recruiters from focusing on candidates' personal information, and to put their attention on the candidate's skills and abilities. We want to help recruiters to prevent any kind of bias while searching for the most valuable candidates they really need. The following documentation is addressed both to developers, in order to provide all technical details for INDA integration, and to managers, to guide them in the exploration of the implementation possibilities. The host of the API is [https://api.inda.ai/hr/v2/](https://api.inda.ai/hr/v2/). We recommend to check the API version and build (displayed near the documentation title). You can contact us at [email protected] in case of problems, suggestions, or particular needs. The search panel on the left can be used to navigate through the documentation and provides an overview of the API structure. On the right, you can find (*i*) the url of the method, (*ii*) an example of request body (if present), and (*iii*) an example of response for each response code. Finally, in the central section of each API method, you can find (*i*) a general description of the purpose of the method, (*ii*) details on parameters and request body schema (if present), and (*iii*) details on response schema, error models, and error codes.

Go to Download