Libraries tagged by code gen

Memio's linter, a set of constraint that check models for syntax errors

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Production-ready PHP library for building and parsing VietQR (NAPAS FastFund 24/7 IBFT) QR codes compliant with EMVCo 1.5.2 specification.

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Zeus Echoo is filamentphp form component to record audio from your browser

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A Laravel barcode generator based on TCPDF barcode library

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Barcode Generation Package inspired by Nicola Asuni.

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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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Generate and manage Laravel model schemas with automatic validation, documentation, and migration helpers for better data structure management.

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API reference for Zernio. Authenticate with a Bearer API key. Base URL: https://zernio.com/api Versioning and deprecation: all endpoints are versioned in the URL path (current version: /v1). Breaking changes only ship in a new path version; existing versions keep working. Deprecated operations are marked 'deprecated: true' in this spec and announced in the changelog (https://zernio.com/changelog) before removal. Errors: every 4xx/5xx response is application/json with a machine-readable 'code' and a human-readable 'error' message (see the ErrorResponse schema). Request ids: responses carry an X-Request-Id header with the id we log the request under. Quote it when reporting a problem. A valid x-request-id you send is reused as that id.

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A tiny QRCode generator (single file, no dependencies)

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Generate images and SVGs with AI from the Media Library on Varbase 11, with the AI Media module: a "Generate image with AI" tab right after Image and a "Generate SVG with AI" tab right after SVG Image, saving into those media types, with the permission granted to the editorial roles. No custom PHP or shell code.

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Generate OpenAPI 3.2 and 3.1 documentation for a Laravel API automatically, from the real types in your code.

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Class generation favicon for browsers and devices Android, Apple, Windows and display of html code. It supports a large number of settings such as margins, color, compression, three different methods of crop and screen orientation.

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Generate 59 barcode types (QR, Data Matrix, Aztec, MaxiCode, PDF417, EAN/UPC, GS1-128, GS1 DataBar, Code 128, postal codes and more) as SVG, PNG, PDF, EPS or text. Pure PHP, GS1 validation, styled QR codes.

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Dashboard Builder is a PHP based data driven visualization & business analytics tool, a machine learning delivers insights, written in PHP with an added layer of drag-and-drop flexibility which helps predicting the future with ease and no code required.

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A generic PHP package that can generate all sorts of random voucher/coupon codes. Laravel compatible.

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