Libraries tagged by cnerta

MonsterID is a method to generate a unique monster image based upon a certain identifier (IP address, email address, whatever). It can be used to automatically provide personal avatar images in blog comments or other community services.

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Improved UI for certain aspects of the admin area

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Provides an ability to bind a route slug to the certain Extbase Action endpoint

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Patch for CVE-2025-54236(a.k.a Session Reaper) which allows customer account takeover and RCE under certain conditions. This patch is actually a Magento 2 extension and universal compatible for Magento 2.3 & 2.4. If you cannot upgrade Magento or cannot apply the official hotfix, try this one.

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Validate that a certain value is a valid CSS color string in Laravel 5

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PACE (Progress Automatically Certain to Entertain) - Automatic page load progress bar for Yii PHP Framework

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Bookworm estimates how much time is needed to read a certain piece of text.

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PHPStan rule for strings that match certain conditions

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A class to allow WordPress plugins to check certain runtime requirements before activation.

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This package is a little helper to check if a given IP address is in a certain IP range.

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The Yii2 JWT extension is a tool for implementing JWT (JSON Web Token) authentication in Yii2 applications. It allows developers to create APIs that require authentication and authorization, ensuring that only authorized users can access certain resources. The extension provides a simple and flexible way to implement JWT authentication in Yii2, using the JWT library and following the JWT specification. It includes support for creating and verifying JWT tokens, as well as handling token expiration and refresh. The Yii2 JWT extension can be easily integrated into any Yii2 application, making it a powerful tool for API authentication and authorization.

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A Laravel package to track popularity of entries(by Models) in a website at a certain time.

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Automatically refresh the Filament sidebar navigation when certain events occur, ensuring menu items and badges are always up to date.

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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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This TYPO3 extension checks the size of all database tables and/or the size of all log files at regular intervals. If a certain size is exceeded, a mail can be sent. There is a separate scheduler task for each check.

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