Libraries tagged by theme management

Pico is a flat file CMS, this means there is no administration backend and database to deal with. You simply create .md files in the "content" folder and that becomes a page.

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DB Craft is a CodeIgniter4 Seeder, Migration Generator. Automatic Migration Generation: DB-Craft provides a simple command-line interface to generate migration files automatically based on the connected database. This feature allows developers to keep track of database schema changes and easily apply them to different environments. Table-Specific Migrations: Developers can also generate migration files for specific tables, providing granular control over database changes. This flexibility allows for efficient database management and versioning. Seeding Support: DB-Craft includes functionality to generate seeders, enabling developers to populate their database with initial data. This feature is especially useful for setting up sample data or populating reference tables.

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The KunstmaanPagePartBundle forms the basis of our content management framework. A page built using a composition of blocks names pageparts. These pageparts allow you to fully separate the data from the presentation so non-technical webmasters can manage the website. Every page can have it's own list of possible pageparts, and pageparts are easy to create for your specific project to allow for rapid development.

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To build your perfect website you probably need images, video's or maybe even a presentation too. The Kunstmaan Media Bundle handles all those media assets and centralizes them so you can find your content just the way you like it: fast and efficiently. No central asset management module is useful without some pretty advanced image editing functionality. To provide this we have integrated the Aviary image editing service right from the interface.

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Pico is a flat file CMS, this means there is no administration backend and database to deal with. You simply create .md files in the "content" folder and that becomes a page.

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LLM Compatibility Layer - Routes the LLM provider calls of third-party AI extensions through nr-llm at runtime, so its provider management, budgets and telemetry apply without modifying them.

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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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Declarative, PostgreSQL-native management of materialized views: define views as versioned SQL, synchronise, rebuild, refresh (concurrently) and read them safely. Runs on Doctrine DBAL or a bare PDO connection.

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TYPO3 YouTube Integration - Using Youtube TYPO3 Extension you can display your YouTube videos directly on your TYPO3 site within a video box, allowing visitors to view them without being redirected to www.youtube.com. It easily integrates all YouTube features, such as Simple Video, Channel and Playlist management, Live-streaming, and engagement options such as likes and subscribe.

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A Filament log viewer (1.x for Filament 3, 2.x for Filament 4) that filters Laravel log entries by the process that produced them — cron, queue, booking, live chat, and anything else you configure.

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TYPO3 Event Manager - Event Manager is a full-featured events management extension that lets you create multiple events and get them listed on your website. Event Manager provides a user-friendly interface that allows you to effortlessly create and customize events.

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User Group Management - This is a Backend-related extension to manage both Backend and Frontend users from the edit form of Backend/Frontend groups. Easily assign users to groups or remove them from groups.

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Idea management for Contao 5: members submit ideas through a regular form, editors answer them in the back end, and a content element lists them in the front end.

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Magento2\Adobe Commerce module to view logs from admin interface and archive them by cron

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The common management is designed to combine two or more running sps with their values and commands for sharing them between them.

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