Libraries tagged by Application Develop

This Laravel Livewire package simplifies the implementation of dynamic, responsive modals in your web applications. With a focus on seamless integration and flexibility, this package allows developers to easily create and manage modals without the need for JavaScript or additional front-end dependencies. Featuring out-of-the-box support for multiple modal instances, dynamic content, and customizable design options, it’s perfect for crafting modern, interactive interfaces. Whether you need confirmation dialogs, form modals, or notification pop-ups, this package delivers a clean, reusable solution for your Livewire-powered applications.

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Empower Your Laravel Journey: Unleash the Power of Helpers! Unlock a world of possibilities with our standard creation and seamless utilization of helpers within the Laravel framework. Our solution offers a simple, efficient, and elegant way to execute your application's custom methods from any class or view, making development a breeze. Supercharge your Laravel project and elevate your coding experience with our Helper Library.

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This Composer package provides a seamless integration for testing SEO aspects of your Laravel applications. Compatible with both Pest and PHPUnit, it offers a collection of tools and assertions specifically designed to evaluate on-page SEO elements like meta tags, title tags, canonical URLs, and structured data. By automating SEO testing, this plugin ensures that your application consistently adheres to best SEO practices, helping you catch potential SEO issues early in the development cycle.

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QCubed is a PHP framework for rapid web development. Building on top of jQuery, with OOP at its core, QCubed provides a powerful solution for building database-driven Web 2.0 applications.

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Eloquent Regex brings the simplicity and elegance to regular expressions. Designed for Laravel developers, this package offers a fluent, intuitive interface for building and executing regex patterns in your PHP applications.

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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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Fresns officially developed website engine, integrated to run in the main application.

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Laravel API Response is a powerful and flexible package that provides a standardized way to structure API responses in Laravel applications. It offers a range of features to enhance your API development experience, including consistent response formatting, conditional responses, pagination support, rate limiting, and more.

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Laraship is a Platform built on Laravel for Rapid Development, it helps Agents, Startups, and even individuals to save time building their Web Applications and websites using well-structured code.

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Cashfree's Payout APIs provide developers with a streamlined pathway to integrate advanced payout capabilities into their applications, platforms and websites.

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The assegai/common package is a collection of commonly used utility classes and functions for AssegaiPHP projects. This package provides a set of tools that are designed to make it easier for developers to perform common tasks such as working with arrays, strings, and paths. The package also includes classes for handling errors and logging, as well as a simple yet powerful configuration management system. The package is designed to be lightweight, with minimal dependencies, and is fully compatible with any AssegaiPHP based project. Whether you're building a small web application or a large enterprise system, assegai/common provides the essential building blocks you need to get started quickly and easily.

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Aspose.BarCode for Cloud is a REST API for Linear, 2D and postal barcode generation and recognition in the cloud. API recognizes and generates barcode images in a variety of formats. Barcode REST API allows to specify barcode image attributes like image width, height, border style and output image format in order to customize the generation process. Developers can also specify the barcode type and text attributes such as text location and font styles in order to suit the application requirements.

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Pocketframe is a lightweight yet powerful PHP framework designed to simplify modern web application development. With its intuitive structure, elegant syntax, and modular approach, Pocketframe helps developers build scalable, high-performance applications effortlessly.

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Extends the dockworker application to deploy and develop php applications via a consistent and unified workflow.

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This Add-On for Bancha helps Developer-Teams in the process of creating Bancha Applications.

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