Libraries tagged by Modul IS

Yii2-comments is a behavior and a set of widgets to enable generic commenting on Yii2-ActiveRecord-Models

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Rinvex Tags is a polymorphic Laravel package, for tag management. You can tag any eloquent model with ease, and utilize the awesomeness of Sluggable, and Translatable models out of the box.

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Rinvex Statistics is a lightweight, yet detailed package for tracking and recording user visits across your Laravel application. With only one simple query per request, important data is being stored, and later a cronjob crush numbers to extract meaningful stories from within the haystack.

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Rinvex Composer is an intuitive package that leverages the Composer Plugin API, offering enhanced installation features, that allow packages to be installed outside the standard vendor directory and executing custom scripts during the install, update, and uninstall phases.

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Eloquent Guardian is a simple permissions system for your users. While there are many other packages for permissions, this one solves everything in the most eloquent way.

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Cortex Tenants is a frontend layer for the contextually intelligent polymorphic Laravel package, for single db multi-tenancy. You can completely isolate tenants data with ease using the same database, with full power and control over what data to be centrally shared, and what to be tenant related and therefore isolated from others.

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Cortex Categories is a frontend layer for the polymorphic Laravel package, for category management. You can categorize any eloquent model with ease, and utilize the power of Nested Sets, and the awesomeness of Sluggable, and Translatable models out of the box.

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Cortex Auth is a frontend layer for the powerful authentication, authorization and verification package rinvex/laravel-auth on top of Laravel. It has all required controllers, views, routes, and other required assets to run a fully functional user management system with complete dashboard out of the box.

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A Laravel Eloquent model trait for linkable resource

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User consent module for laravel

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Automatically scale down and rotate uploaded images for Silverstripe. This module is based on axllent's version.

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This dataset contains all the countries in the world. They are translateable in different languages. It is also possible to get the flag from said countries. The model is extendable so you can extend and overide all functionality if needed.

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More speed with Cache Routing. This module is part of the Learn ZF2 book

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This module is a PHP module that enables the user to find the country, region, city, etc

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# 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.

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