Libraries tagged by php bot
tajawal/lodash-php
2574 Downloads
A full-on PHP manipulation utility-belt that provides support for the usual functional.
lunalabs-srl/slimpay-php
2215 Downloads
A simple PHP package to integrate the SlimPay checkout on your application that supports both iframe and redirect checkout
inda-hr/php_sdk
794 Downloads
# 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.
cryptoapis.io/php-sdk
5864 Downloads
Crypto APIs is a trusted API provider for crypto & blockchain applications. We provide live and historical data for both Crypto market and Blockchain protocols.
php-telegram-bot/fluent-keyboard
832 Downloads
Fluent Keyboard builder for ReplyKeyboardMarkup and InlineKeyboardMarkup.
cryptoman0/fb-messenger-sdk
2837 Downloads
Facebook Messenger Bot php sdk
botasis/telegram-client
1588 Downloads
Yet another PHP Telegram bot client
fab2s/dt0
202 Downloads
Dt0, a DTO PHP implementation than can both secure mutability and implement convenient ways to take control over input and output in various format
yabx/telegram
1575 Downloads
Telegram Bot API SDK for PHP 8.1+
radyakaze/phptelebot
686 Downloads
Telegram bot framework written in PHP.
m1roff/telegram-api-helpers
165 Downloads
PHP Helper functions for Telegram Bot API
brocosan/studio-addons
25301 Downloads
Fork of botman/studio-addons to be used with PHP 8 and Laravel 9. BotMan Studio specific addons.
webpajooh/telebot
202 Downloads
A minimal library to develop your new Telegram bot
vlsv/telegram-data-validator
174 Downloads
The Telegram Data Validator is a PHP library for validating the integrity of initData received from a Telegram mini-application. It uses HMAC-SHA-256 for data integrity checks.
pharaonic/laravel-agents-detector
334 Downloads
Laravel Agents (Devices, Operation Systems, Browsers, Bots).