Libraries tagged by model support

Blazing fast Views with model-driven approach, Blade and multi-namespace support.

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This extension provide application configuration support stored in database.

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Enable database support for Illuminate\Database in Kirby

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Provides support for UUID key type in Eloquent models

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Project installation support extension for the Yii2 framework

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Eloquent Settings allows you to bind key-value pairs to any Laravel Eloquent model. It supports even casting for boolean, float or integer types.

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Convert eloquent date attributes to jalali (Persian) dates on the fly. (supports model propery access, toJson, toString and toArray).

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Adds support for creating Route Model bindings to an authenticated user in Laravel

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Adds support for bundle-specific models for Drupal 8 entities.

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Taggable Trait for using tag inside Laravel Eloquent models, with Baum's Nested Set pattern support.

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Small but feature rich ORM, has extensible models and builders, baked in upload functionality, supporting multiple backends (rackspace, ftp), polymorphic associations, form builders, nested forms, validators

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Laravel licensing package with polymorphic assignment to any model, activation keys, expirations/renewals, and seat control via LicenseUsage. Supports offline verification with public-key–signed tokens, a CLI to generate/rotate/revoke keys, and an extensible architecture via config and contracts.

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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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Ready-to-use Laravel models and relations for country (ISO 3166), language (ISO 639-1), and currency (ISO 4217) information with multi-language support.

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WPORM is a lightweight, Eloquent-inspired ORM for WordPress plugins and themes. It provides expressive, fluent query building, model relationships, schema management, attribute casting, and event hooks—while fully supporting the WordPress database API and table prefixing. WPORM makes it easy to build modern, maintainable database code in any WordPress project.

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