Libraries tagged by detached

The Metadata API provides crucial configuration details necessary for managing listings across various eBay marketplaces. This includes retrieving detailed eBay category listing policies, such as supported item conditions and multiple-variation structures; accessing sales tax jurisdiction information for setting up tax tables in supported countries; and obtaining hazardous material and product safety label data for regulatory compliance in listing flows. The API is essential for sellers and developers needing up-to-date, marketplace-specific policy and jurisdictional information to accurately create and manage their listings.

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The Browse API lets shoppers search eBay listings by keyword, category, GTIN, product, charity, compatibility criteria, or image, and refine results with filters such as aspects, compatibility, field values, and UI parameters through the item_summary resource.The item resource lets applications retrieve detailed information for a specific item or all items in an item group, and check whether a product is compatible with a specified item, such as whether a specific vehicle is compatible with a specific part. The item resource also supports legacy item identifiers alongside RESTful item IDs, which use different formats. This helps developers work with stored or historical legacy item IDs when using the Browse API.All methods in the Browse API require an Application access token, which is obtained using the client credentials grant flow.

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Advanced News Search for TYPO3 - Enhance your TYPO3 News Extension with the Advanced TYPO3 News Extension. Expand your news search capabilities with detailed, precise results and the ability to filter content by specific fields using the Advanced Extension. This extension incorporates specially crafted search algorithms to ensure both speed and relevance in your searches.

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The Kunstmaan Cookie Bundle provides a cookie bar; detailed pop-up window and a similar page explaining each type of cookie used on the website.

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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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A comprehensive change logs tracking package for Laravel 11+ that automatically tracks all model changes (create, update, delete, restore) with detailed audit trails

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收货地址智能解析工具，支持从非结构化文本中提取姓名、手机号、身份证号、省市区、详细地址等字段，适用于电商、物流、CRM 等系统 | An intelligent address parser that extracts name, phone number, ID number, region, and detailed address from unstructured text—perfect for e-commerce, logistics, and CRM systems.

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A comprehensive package for managing country data in Laravel applications, including multilingual support, geographic coordinates, and detailed metadata for seamless integration with Laravel.

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This package introduces new eloquent events for sync(), attach(), detach() or updateExistingPivot() methods on BelongsToMany relation.

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Capture and monitor detailed error logs with nice dashboard and UI.

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Rinvex Statistics is a lightweight, yet detailed package for tracking and recording user visits across your Laravel application. With only one simple query per request, important data is being stored, and later a cronjob crush numbers to extract meaningful stories from within the haystack.

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Locate - The users country, preferred language and other facts will be detected. Depending on configurable rules the user can be redirected to other languages or pages. Locate also provides geo blocking for configurable pages in configurable countries.

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Provide more detailed information about a place on the board on viewonline page.

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A framework-agnostic PHP library of Tunisian utilities: phone number, CIN, RIB, car plate, postal code, and tax ID validation, plus currency and date formatting for the Tunisian locale.

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A PHP framework for writing (forked) multi process daemons

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