Libraries tagged by amon
matchish/laravel-scout-elasticsearch
696381 Downloads
Search among multiple models with ElasticSearch and Laravel Scout
analog/analog
1318573 Downloads
Fast, flexible, easy PSR-3-compatible PHP logging package with dozens of handlers.
soosyze/kses
23269 Downloads
An HTML/XHTML filter written in PHP. Checks on attribute values. Can be used to avoid Cross-Site Scripting (XSS), Buffer Overflows and Denial of Service attacks, among other things.
rokka/utils
149452 Downloads
Some utility methods for rokka to be shared among projects
mmamedov/page-cache
10562 Downloads
PageCache is a lightweight PHP library for full page cache. It uses various strategies to differentiate among separate versions of the same page.
islandora/crayfish-commons
149878 Downloads
Shared code amongst Islandora Crayfish microservices
cion/laravel-text-to-speech
18507 Downloads
This package creates a shared API to easily use Text to Speech functionalities amongst different TTS providers.
phing/task-visualizer
66169 Downloads
VisualizerTask creates buildfile maps, these diagrams display calls and depends among targets.
netglue/realip-helpers
29645 Downloads
PSR-15 Middleware for detecting the real client ip amongst other helpers.
inda-hr/php_sdk
235 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.
expalmer/php-bad-words
30023 Downloads
PHP Bad words filtering. Checks for existence of bad word in a string but checks too an alone word or among the string
automattic/jetpack-my-jetpack
16504 Downloads
WP Admin page with information and configuration shared among all Jetpack stand-alone plugins
zan/common-bundle
6840 Downloads
Common code shared among many Symfony applications
steamulo/elastica-fast-populate-bundle
5408 Downloads
Improves performance of fos:elastica:populate command from FOSElasticaBundle by distributing the work among consumers.
mouf/database.dao-interface
25638 Downloads
This package only contains a basic interface for implementing common DAO methods. Those DAOs will be used by BCE forms among other things.