10 Application(s) results for #react
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iris-testops-hub

App for collecting, storing and analyzing autotest results

M
Max March
Docker
AI
0.0 (0)22 Feb, 2026 39

fhir-frontend-react-lovable

Lovable react frontend for FHIR

Evgeny Shvarov
Docker
IPM
AI
0.0 (0)26 Mar, 2025 390

InterSystems Ideas Waiting to be Implemented

AI extensibility Prompt keyword for Class and Method implementation. Also Prompt macro generator.

To accelerate capability of growing code generation. This proposal suggests new extensibility facilities and hooks that can be democratized to community and / or fulfilled by commercial partners. To add Training metadata to Refine a Large Language Model for code, a "Prompt Input" is associated with an expected "Code Output", as part of a class definition. This provide structured keywords to describe: * The expected output * And / Or Chain-of-thought to generate the correct output | /// The following Prompt describes the full implementation of the class Class alwo.Calculator [Abstract, Prompt = "Provides methods to Add, Subtract, Multiply and divide given numbers." ] { /// The following Prompt describes the full implementation of the method ClassMethod Add(arg1 As %Float, arg2 As %Float) As %Float [ Prompt ="Add numeric arguments and return result." ] { return arg1 + arg2 } ClassMethod Subtract(arg1 as %Float, arg2 As %Float) { &Prompt("Subtract numeric arguments and return result") ) } | The Prompt macro generates code based on the context of the method it is within. Once resolved, it automatically comments out the processed macro. | ClassMethod Subtract(arg1 as %Float, arg2 As %Float) { //&Prompt("Subtract arguments and return the result") return arg1 - arg2 //&Prompt("Model alwogen-objectscript-7.1.3") ) | The generator leveraged at compilation time could be configured in a similar way to how source control is configured for a namespace. Configuration could lock / exclude packages from being processed in this way. A "\prompt" compilation flag could be used to control the default environment behavior and editor compilation behavior. For example to force reprocessing of previously resolved prompts due to a newer more capable version of code Large Language Model, then a "\prompt=2" could be applied. Different models or third-party services could be applied depending the language of the given method. When redacting source code by "deployment", the existing "deploy" facility could be extended to also ensure removal of "Prompt" metadata from code.

A
by Alex Woodhead

3

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EduVerse

Accessible Learning Assistant

R
Rolano Rebelo
Python
AI
0.0 (0)11 Nov, 2024 119

Database Growth - Data Collection and Analysis

The two continued repos are linked at the end of DataCollection.

A
Ariel Glikman
Docker
4.0 (2)04 Aug, 2024 318

realworld-intersystems-iris

InterSystems IRIS Starter kit for new RealWorld framework implementations

Dmitry Maslennikov
Docker
IPM
5.0 (1)25 Mar, 2024 695 34

iris-python-machinelearn

Machine learning application Python IRIS

André Dienes Friedrich
Docker
Python
ML
ML
4.5 (1)22 Sep, 2023 449

ehh2022-diabro

Application by team robomeow for European Healthcare Hackathon.

M
Maksym Shcherban
0.0 (0)28 Nov, 2022 231

React-UI-Global

Application with toolkit for globals

E
Evgeniy Potapov
Docker
Python
4.0 (1)08 Apr, 2022 403

Airplane React, Material UI, and REST API

Development of a System using React, Material UI and REST API IRIS.

F
Flavio Lucio Naves Junior
Docker
3.0 (1)16 Mar, 2021 498

BeI-MultiModel

We've used a IRIS backend that is called via a REST-API from a react frontend application.

i
ivo Ver Eecke
Docker
IPM
4.0 (3)25 Jan, 2021 347