Libraries tagged by text analytics

TextPerfection is a powerful content rewriting and enhancement plugin that helps you achieve text perfection. With advanced algorithms and linguistic analysis, TextPerfection offers intelligent suggestions and optimizations to transform your written content into a refined and professional masterpiece. Elevate the quality of your text, enhance readability, and ensure impeccable grammar and structure with TextPerfection. Whether you're a writer, blogger, or content creator, TextPerfection empowers you to produce compelling and flawless text that captivates your audience and leaves a lasting impression. Experience the art of text perfection with this essential tool for every wordsmith and communicator

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Use the Analyze API to analyze any external asset and return details based on the type of analysis requested. Currently supports the following analysis options: * [AI Vision - Tagging](https://cloudinary.com/documentation/cloudinary_ai_vision_addon#tagging_mode) * [AI Vision - Moderation](https://cloudinary.com/documentation/cloudinary_ai_vision_addon#moderation_mode) * [AI Vision - General](https://cloudinary.com/documentation/cloudinary_ai_vision_addon#general_mode) * [Google tagging](https://cloudinary.com/documentation/google_auto_tagging_addon) * [Captioning](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#ai_based_image_captioning) * [Cld Fashion](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Coco](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Lvis](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Unidet](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Human Anatomy](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Cld Text](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) * [Shop Classifier](https://cloudinary.com/documentation/cloudinary_ai_content_analysis_addon#supported_content_aware_detection_models) **Notes**: * The Analyze API is currently in development and is available as a Public Beta, which means we value your feedback, so please feel free to [share any thoughts with us](https://support.cloudinary.com/hc/en-us/requests/new). * The analysis options require an active subscription to the relevant add-on. Learn more about [registering for add-ons](https://cloudinary.com/documentation/cloudinary_add_ons#registering_for_add_ons). The API supports both Basic Authentication using your Cloudinary API Key and API Secret (which can be found on the Dashboard page of your [Cloudinary Console](https://console.cloudinary.com/pm)) or OAuth2 ([Contact support](https://support.cloudinary.com/hc/en-us/requests/new) for more information regarding OAuth).

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A string helper for PHP. It includes some useful methods and possibly other features.

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A trait that can be included on eloquent models to utilize the Aylien text analysis php sdk

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A library for processing and analyzing media content, providing tools for audio, video, and text analysis.

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Sentiment is a sentiment classifier. It uses a model of words that are categorised as positive, negative or neutral, and a naive bayes algorithm to calculate sentiment. To improve accuracy, Sentiment removes 'noise' words.

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A collection of fast and easy to use attributed string classes for PHP. Attributed strings can have multiple attributes for each character of the string and are for example used for word processors and natural language processing.

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Abstraction library for code coverage analysis

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A lightweight PHP library for basic text analysis operations like summarization, sentiment analysis, keyword extraction, and classification.

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Laravel machine learning based Text Sentiment Analysis package from VamanAI.com

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PHP Chain is a natural language processing library for PHP, inspired by the popular LangChain in Python. This library offers a modular and extensible approach to building NLP pipelines, allowing PHP developers to easily integrate natural language capabilities into their applications. PHP Chain supports a variety of NLP tasks, including but not limited to tokenization, semantic analysis, and text generation, providing a fluent interface and adaptable tool chains for different linguistic processing needs.

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A PHP SDK for the AssemblyAI API, enabling speech-to-text transcription and real-time audio analysis functionalities.

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Paragon Processing PlatformThis document is to provide a detailed description of how a developer or software solution provider can integrate with the Paragon Processing Platform (Paragon Platform). The Paragon Platform is for developers who wish to use Paragon's processing services within their software applications. The Paragon Platform can stand alone as a web-based storefront with (or without) attached card readers or may be used in combination with point-of-sale (POS) and order entry applications.The Paragon Platform accepts payments in many forms, including check, credit, debit, gift, loyalty and EBT cards. Payments may be taken online, over the telephone, from a mobile phone and at physical store locations. In addition to handling large volumes of payment transactions, the Paragon Platform manages and settles batches, protects sensitive card information, administers billing contracts and produces operational and analytical reports. Application Programming Interfaces (APIs) With our API, software systems and devices communicate with the Paragon Platform by exchanging messages. Client Application formulates a message and transmits the request to the Paragon Platform. The Paragon Platform translates the request and relays it to the Payment Processing Network. The Payment Processing Network processes the request and returns a response to the Paragon Platform. The Paragon Platform translates the response and relays it to the Client Application.The Path to Integration Step 1: Open a Test Account Visit https://developer.paragonsolutions.com/testaccount to register for a free test account. Once registered you have instant access to your test account credentials and all the documentation you need to get started. Head over to the library and make sure to check out all of our API's to learn about the Paragon Processing Platform transaction requests and responses.Step 2: Code & CertifyOnce in the Paragon Development portal, begin your certification or have an experienced Paragon integration specialist guide you through the testing process. Once coding and testing are completed submit your request for certification. Our team will then perform a detailed review of your integration to make sure your integration meets all your business requirements for success. Step 3: Go Live!After final review and testing your software solution is ready to begin taking live payments! We know, an integration that is easy sounds too good to be true. Don't take our word for it, start your integration today! Developer NotesInstall your development platform according to its product documentation.Read through all the steps before you get started. We recommend reviewing the rest of this guide to familiarize yourself with the Paragon Processing Platform's terms, capabilities, web services and operations.

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Pre-escaped error messages in 'symplify' error format, container aware test case and other useful extensions for PHPStan

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Services to aid phpstan analysis on CakePHP projects

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