Libraries tagged by tall stack

Meet our all-in-one TYPO3 Social Login and Register extension, which allows users to log in and register using various social media accounts directly from your TYPO3 frontend. With this extension, users can easily access your site using popular platforms like Facebook, Google, Twitter, LinkedIn, Instagram, OpenID, Apple, Discord, Keycloak, Slack, Telegram, Dropbox, and more. Get seamless, one-click frontend login with the TYPO3 Social Login extension. Explore the Demo, Product Page, Documentation & Support: https://t3planet.com/typo3-social-login-extension

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A Laravel package for easy Slack notifications about posts published on subscribed Facebook's fanpages.

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Fügt Call To Action Buttons an einer Seite hinzu

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All you need to quickly create REST controllers

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### 1. **Module Overview:** - **Name:** Brand Inventory Manager - **Purpose:** The module dynamically lists all the brands that have products currently in stock on the website, allowing customers to view and browse products by brand. This list updates automatically based on the store's inventory. ### 2. **Key Features:** - **Dynamic Brand Listing:** - The module generates a list of brands that have at least one product in stock. - The list is updated in real-time based on changes in inventory levels (e.g., if a brand's products go out of stock, that brand is removed from the list). - **Filter by Inventory:** - Customers can filter the brand list by product availability, ensuring they only see brands with products they can purchase immediately. - **Brand Page:** - Each brand name in the list is clickable, leading to a dedicated brand page. - The brand page displays all in-stock products for that brand, with options for sorting, filtering, and searching within the brand's catalog. - **SEO-Friendly URLs:** - The module creates SEO-friendly URLs for each brand page, enhancing visibility on search engines. - **Inventory-Based Brand Widget:** - A widget can be placed on various parts of the website (e.g., homepage, sidebar, footer) that highlights popular or new brands with available stock. - **Admin Configuration:** - The admin can configure how brands are displayed (e.g., sorting by popularity, alphabetical order, etc.). - Options to include or exclude specific brands regardless of inventory (e.g., always show premium brands). - **Caching Mechanism:** - To ensure performance, the module uses caching to store brand lists, refreshing only when inventory changes occur. ### 3. **Integration with Other Features:** - **Product Pages:** On each product page, the brand name is linked to the corresponding brand page. - **Search Functionality:** When customers search for a brand name, the search results include the brand page and all relevant products. ### 4. **Customizable Design:** - The module’s front-end is fully customizable, allowing the store’s design team to style the brand listing and pages in line with the overall website design. ### 5. **Reporting and Analytics:** - The module provides reports on brand performance, showing metrics such as which brands are viewed most frequently, which have the highest sales, etc. ### 6. **Multi-Store Support:** - For stores with multiple websites or store views, the module supports configuration per store view, allowing different brands to be highlighted in different regions or languages. This Magento module would be particularly useful for e-commerce stores with diverse product offerings across many brands, ensuring that customers have an efficient way to find and purchase products by their favorite brands.has context menu

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Removes the getVersion call from the Stock Laravel MemcachedConnector

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show price for configurable product when all children are out of stock.

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The Catalog API allows users to search for and locate an eBay catalog product that is a direct match for the product that they wish to sell. Listing against an eBay catalog product helps insure that all listings (based off of that catalog product) have complete and accurate information. In addition to helping to create high-quality listings, another benefit to the seller of using catalog information to create listings is that much of the details of the listing will be prefilled, including the listing title, the listing description, the item specifics, and a stock image for the product (if available). Sellers will not have to enter item specifics themselves, and the overall listing process is a lot faster and easier.

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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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