Libraries tagged by grader

Vortos Audit — enterprise-grade unified audit spine. One append-only, hash-chained, per-scope/per-tenant event store with controlled action vocabulary, sensitivity classification, impersonation-chain capture, async (Kafka) ingestion, partitioned storage, retention + cold-storage tiering, keyset query, and signed per-tenant export. Replaces per-app hand-rolled audit tables.

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A powerful notification system for FilamentPHP that handles multi-channel notifications with template management, scheduling, and real-time delivery. Built for developers who need enterprise-grade notifications without the complexity.

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A professional-grade auditing UI for Filament PHP. Transform raw laravel-auditing data into a powerful, centralized 'Blackbox' flight recorder with beautiful diffs, relationship-aware timelines, and advanced filtering.

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Enterprise-grade WhatsApp Cloud API integration for Laravel with multi-phone support, batch processing, and AI agent workflows.

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Production-grade inline image CAPTCHA field for Filament forms (PHP GD, zero image persistence).

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Enterprise-grade maker-checker (four-eyes) approval workflow for Laravel. Multi-role approvals, conditional rules engine, delegation, audit trail, bulk actions, and auto-intercept via Eloquent events.

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A fast, modern PHP router with production-grade middleware, signed & temporary URLs, smart responses and first-class route caching.

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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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Import content into your concrete5 sites. Cross-grade from version 5.6, 5.7 and more.

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A robust, production-grade Laravel package for SAP Business One HTTP integration, supporting both OData and custom (non-OData) SAP Service Layer (SML) endpoints.

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A professional-grade webhook management system for Laravel applications

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Production-grade communications domain for Laravel - outbound, inbound, and internal communication recording with Laravel Notifications integration

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【正方教务】爬虫，支持成绩查询、考试查询、课表查询、四六级成绩查询、四六级报名、选课查询、修改密码、获取用户菜单等功能，并且解析数据成易读格式，符合 psr 规范，拿来即用

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Production-grade logging and monitoring platform for Laravel applications

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WebPA is an online peer assessment system for higher education institutions. It is designs for teams of students doing groupwork. The system allows participating students to assess themselves and their peers to calculate a final grade for each student, which is a weighted result based on the collective peer feedback and the final mark for the group work by an instructor.

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