Libraries tagged by automatize

Adds a page type that automatically builds a sitemap from the view tree. Works with Multisites module.

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Automatically detects issues from browser on site and notifies by email, chat or ticket system via Bugsnag.

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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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Automatically generate beautiful API documentation for your Laravel API routes using annotations.

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The module developed by Iceshop fully automatically loads the full product information in your Magento web store database

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The module developed by Iceshop fully automatically loads the full product information in your Magento web store database

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Automatic generation of API documentation for Laravel applications.

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A Silverstripe image gallery allowing multi image upload and automatic generation of thumbnail gallery with popups

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Die Erweiterung 'Seitenteaser' stellt Inhaltselemente bereit, die automatisch aus bestehenden Seiten Seitenteaser generieren. Hierfür wird auf das Seitenbild (terminal42/contao-pageimage) zurückgegriffen, falls vorhanden, ansonsten auf das erste verwendete Bild in der Seite verwendet. Außerdem wird der Seitentitel und die Seitenbeschreibung verwendet. Dies kann überschrieben werden, wenn in der Seite Extraeingaben für den Teaser Titel und die Teaserbeschreibung gemacht werden. Im Startpunkt der Webseite kann eingestellt werden, welche Bildgröße verwendet und, ob ein Text angezeigt werden soll.

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A Contao bundle that automatically sets the username based on the user email address.

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Laravel Fine tuner is a package designed for the Laravel framework that automates the fine-tuning of OpenAI models. It simplifies the process of adjusting model parameters to optimize performance, tailored specifically for Laravel applications. This tool is ideal for developers looking to enhance AI capabilities in their projects efficiently, with minimal manual intervention.

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A Magento module which facilitates automatic purging of static assets from HTTP caches such as browser cache, CDN, Varnish, etc using best practices outlined within the HTML5 boilerplate community.

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Bundle for extended workflow management and automation

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Automates the process of updating assets version in Symfony 5 projects still using parameters.yml

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A text filter for automatic email obfuscation using Javascript or CSS fallback

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