Libraries tagged by nitro

# Introduction ## Overview Note: This is the specification of the DP-DHL Group Parcel DE Returns API. This web service allows business customers to create return labels on demand. # Scenarios ## Main Scenario: Creating a returnlabel This is achieved by posting a return order to the URI '/rest/orders'. The service will respond with a return label. ## Querying to get receiver locations The single scenario supported by this service is the determination of the receiver's location. This is achieved by getting a location to the URI '/rest/locations'. The service will respond with a Receiver. # Technical Note on Authorization This API supports __two alternative ways__ to authorize yourself: 1. Combination of Apikey and Basic Authentication which you can provide with every call. 2. OAuth2 Password Flow: After having obtained your access token once, you provide this token as bearer token. You can try it out here. More details can be found when clicking on "Authorize".

Go to Download

Library of code introduced throughout Modernizing Legacy Applications in PHP.

Go to Download

The Service that facilitates integration with PrimeVue tables by introducing easy pagination, filtering and sorting.

Go to Download

Laravel SDK for Keycloak token management - store, refresh, and introspect OAuth tokens

Go to Download

# 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.

Go to Download

This package introduces the join magic for eloquent models and relations.

Go to Download

Web application for Bernard. Offers introspection, api and monitoring.

Go to Download

Polyfills for URL-related functions introduced in BuddyPress 12.0.

Go to Download

Goodenberg is a library of components, helpers and examples for building modern WordPress sites and applications withthe block editor and all other features introduced with Gutenberg.

Go to Download

Token-lean toolkit for Laravel projects, built for MCP and other low-token AI integrations: a lexical index (classes, routes, views, frontend files, with pluggable schema extraction) and a driver-agnostic database introspection tool (list tables, describe schema, run guarded queries, optional Spatie Permission mapping).

Go to Download

GEMVC development CLI: codegen, admin tools, database introspection. Internal ecosystem package — install with --dev only.

Go to Download

Drupal site introspection and test content management for Bolt CLI

Go to Download

Implements the Akamai {OPEN} EdgeGrid Authentication specified by https://developer.akamai.com/introduction/Client_Auth.html

Go to Download

Derafu: Backbone Dispatcher - Generic Invocation and Introspection for Backbone Services

Go to Download

This module enhances Magento’s wishlist by introducing Ajax add-to wishlist (without page reload) and possibility to style already selected wishlist icons on products

Go to Download