Libraries tagged by test selection

Laravel Profanity Filter - Powerful PHP package for detecting, filtering, and masking profanity in multiple languages. Supports leet speak, custom word lists, case sensitivity, and seamless Laravel integration.

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The official Copyleaks PHP SDK. Copyleaks is the integrity layer for your tech stack that helps organizations and individuals understand what's human-made and original, AI-generated, or manipulated across text, image, audio and video. This SDK covers AI Text Detection, AI Image Detection, AI Video Detection, Plagiarism Checker, Image Plagiarism Detection, Grammar Checker and Text Moderation.

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Use the Talon.One API to integrate with your application and to manage applications and campaigns: - Use the operations in the [Integration API section](#integration-api) to integrate with our platform. - Use the operation in the [Management API section](#management-api) to manage applications and campaigns. ## Determining the base URL of the endpoints The API is available at the same hostname as your Campaign Manager deployment. For example, if you access the Campaign Manager at `https://yourbaseurl.talon.one/`, the URL for the [updateCustomerSessionV2](https://docs.talon.one/integration-api#tag/Customer-sessions/operation/updateCustomerSessionV2) endpoint is `https://yourbaseurl.talon.one/v2/customer_sessions/{Id}`.

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Framework-agnostic PII detection and redaction for text strings

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NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, grammar and spelling correction, keywords and keyphrases extraction, chatbot, product description and ad generation, intent classification, text generation, image generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, speech synthesis, embeddings, and dependency parsing. It is ready for production, served through a REST API. This is the PHP client for the API. More details here: https://nlpcloud.com. Documentation: https://docs.nlpcloud.com. Github: https://github.com/nlpcloud/nlpcloud-php

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HTML assertions for PHPUnit and Pest: check rendered HTML with CSS selectors, never as a string. With PHPStan rules, a Rector rule and a skill for AI coding agents.

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The missing RESTful API component to CakePHP's bake console. Create RESTful API skeletions in seconds.

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The payments API is used to create a session to offer Klarna's payment methods as part of your checkout. As soon as the purchase is completed the order should be read and handled using the [`Order Management API`](https://docs.klarna.com/api/ordermanagement). **Note:** Examples provided in this section includes full payloads, including all supported fields , required and optionals. In order to implement a best in class request we recommend you don't include customer details when initiating a payment session. Refer to [Initiate a payment](https://docs.klarna.com/klarna-payments/integrate-with-klarna-payments/step-1-initiate-a-payment/) section for further details. Read more on [Klarna payments](https://docs.klarna.com/klarna-payments/).

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CryptoManana is a cryptography framework for boosting your project's security.

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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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Cyrillic text encoding detection class

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Zero-runtime-dependency Persian (Farsi) toolkit for PHP 8.1+: validators for national ID, legal ID, bank card, Sheba/IBAN, phone, postal code, bill ID and license plate; Toman/Rial money with an Amount value object; formatters (number to words and back, ordinals, time-ago); text tools (slug, script detection, character normalization, ZWNJ half-space, keyboard-layout fix) and digit conversion.

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QuickREST - a WordPress plugin which speeds up REST API requests by selective loading of plugins.

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Automatic alternative (alt) text for images using object detection with pre-trained model.

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Natural Language Processing tools for TYPO3 with language detection, stemming, stop words filtering, and text clustering

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