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Application Name | Developer | Made with | Rating | Last updated | Views | Installs |
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![]() iris-AgenticAINext generation of autonomous AI Agentic Application | Docker Python AI | 5.0 (1) | 06 Apr, 2025 | |||
![]() langchain-iris-toolInterSystems IRIS LangChain Tool and AI Agent to ask IRIS | Docker Python IPM AI | 5.0 (1) | 05 Apr, 2025 | |||
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 | ||||||
![]() bg-iris-agentAI IRIS Agent | Docker IPM AI | 5.0 (1) | 04 Apr, 2025 | |||
![]() Intersystems-MonitoringEnable monitoring of IRIS instances via Elastic Discover | IPM | 4.5 (3) | 02 Apr, 2025 | |||
![]() Facilis[ˈfäkɪlʲɪs̠] Facilis – Effortless API Interoperability with AI | Docker Python AI | 5.0 (1) | 01 Apr, 2025 | |||
DeepSeeWebRenderer for DeepSee Dashboards in Browser with MDX2JSON as a Serverside and JS web-client | Docker IPM | 4.5 (2) | 01 Apr, 2025 | |||
iris-data-analysisImplementing data query and analysis | l | Docker Python IPM AI | 4.0 (1) | 01 Apr, 2025 | ||
iris-waveform-demoDemo project storing HL7 timeseries (waveform) data in IRIS | A | Docker | 0.0 (0) | 01 Apr, 2025 | ||
![]() iris-easybotA Fast, Simple, Experimental Chatbot Framework Using IRIS Vector Search. | E | Docker Python AI | 5.0 (1) | 31 Mar, 2025 | ||
iris-speed-testShow how fast InterSystems IRIS is compared to other competitors | F | Docker | 5.0 (1) | 31 Mar, 2025 | ||
![]() oncoragIRIS-integrated RAG pipeline for oncology data curation | P | Docker Python AI | 0.0 (0) | 30 Mar, 2025 | ||
iris-clinical-assistantNatural language querying of patient clinical data. | D | Python AI | 0.0 (0) | 30 Mar, 2025 | ||
![]() tootIRIS Vector powered Whistle-and-Sing to Search for Music | A | Docker AI ML ML | 4.0 (1) | 30 Mar, 2025 | ||
![]() Vitals LabEnhancing Caregiver Support through accessible AI tools. | G | Python AI ML ML | 0.0 (0) | 30 Mar, 2025 | ||
pax-ai-irisHybrid Framework for Anomaly Detection: IRIS, Embd Python, AI | AI ML ML | 0.0 (0) | 28 Mar, 2025 | |||
AiAssistantUsing vector search to assist large language models in generatin | X | Docker IPM AI | 4.5 (1) | 27 Mar, 2025 | ||
![]() IRIS-Intelligent-Butler# IRIS-Intelligent Butler IRIS Intelligent Butler is an AI intel | Docker Python IPM AI ML ML | 4.0 (1) | 27 Mar, 2025 | |||
![]() AnalyzeThisEasily transform a CSV file/Table/SQL query into a personalized preview of InterSystems IRIS BI | P | Docker IPM | 5.0 (3) | 26 Mar, 2025 | ||
React Native Frontend for FHIR by LovableA React-Native frontend UI for FHIR server generated by Lovable | AI | 0.0 (0) | 26 Mar, 2025 | |||
![]() mcp-server-irisInterSystems IRIS MCP server | Python AI | 0.0 (0) | 26 Mar, 2025 | |||
![]() IRIS internal WebSocket ClientUsing %Net.WebSocket feature available in IRIS | Docker IPM | 4.0 (1) | 21 Mar, 2025 | |||
isc-codetidyServer-side code standards enforcement for ObjectScript | IPM | 4.0 (1) | 20 Mar, 2025 | |||
ks-iris-libIRIS / IRIS Health utilities library | Docker IPM | 5.0 (1) | 15 Mar, 2025 | |||
TaskListEasy and convienient Project Manager for small groups we use. | I | AI | 0.0 (0) | 14 Mar, 2025 | ||
![]() ollama-ai-irisUsing Ollama LLM (as an alternative to OpenAI) with IRIS | R | Python AI | 0.0 (0) | 12 Mar, 2025 | ||
![]() iris-fhir-templateFHIR Server template for InterSystems IRIS for Health | Docker IPM | 5.0 (2) | 12 Mar, 2025 | |||
pxw-debugLog debug output | P | Docker IPM | 5.0 (1) | 08 Mar, 2025 | ||
objectscript-errorsExample class which reproduces typical ObjectScript errors | Docker IPM | 5.0 (1) | 05 Mar, 2025 | |||
iris-watched-statusStatus that automatically detects and handles errors. | D | IPM | 0.0 (0) | 05 Mar, 2025 | ||
X-rAI-iris-healthInterSystems IRIS for Health Data Analytics with Explainable AI | R | Python AI ML ML | 0.0 (0) | 05 Mar, 2025 |