Application Name | Developer | Made with | Rating | Last updated | Views | Installs |
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iris-graphql-demoExample of using GraphQL with InterSystems IRIS with Graphene, S | A | Docker Python | 5.0 (1) | 27 Nov, 2024 | ||
![]() recomendacao-filmes-intersystemsExample of using Vector Search for movie recommendations | D | Docker Python | 5.0 (1) | 16 Nov, 2024 | ||
InterSystems Ideas Waiting to be ImplementedAI 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 3Votes1Comments | ||||||
![]() iris-errors-analysis-graphAnalyze errors on the IRIS portal generate statistical graphs. | L | Docker Python IPM AI | 1.8 (2) | 28 Jul, 2024 | ||
iris-email-analyzer-appIris Email Analyzer for suspicious or confidential content. | E | Docker Python IPM AI | 4.5 (1) | 23 Jul, 2024 | ||
flask-irisA quick guide / template to use Flask and IRIS side by side. | H | Python | 0.0 (0) | 06 Oct, 2023 | ||
![]() iris-recorder-helperThe simplest app for records transcribe to text on python | IPM AI | 4.5 (1) | 22 Sep, 2023 | |||
![]() IRIS-FlaskBlogRealworld Application using Flask, SQLAlchemy, and InterSystems IRIS | Docker Python | 5.0 (1) | 06 Sep, 2023 | |||
isc-cloud-sql-python-demoA simple python and flask app with IRIS Cloud SQL on back | Python | 5.0 (1) | 23 Mar, 2023 | |||
iris-python-flask-api-templateThe simplest template with REST CRUD for InterSystems IRIS | L | Docker Python | 4.5 (1) | 17 Aug, 2022 | ||
![]() iris-globals-graphDBUse Globals to Store and Retrieve Graph Database Structure | Docker Python | 5.0 (1) | 09 Apr, 2022 | |||
![]() iris-python-appsPython IRIS Dashboard, Data Sciences, Plotting and Visualization | Docker Python | 4.0 (1) | 23 Feb, 2022 |