6 Application(s) results for #nlp
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iris-GenLab

Application support Machine Learning, LLM, NLP, PALM and OpenAI

Muhammad Waseem
Docker
Python
IPM
AI
5.0 (1)21 Sep, 2023 793

FHIR - AI and OpenAPI Chain

Call any FHIR API with natural language input. OpenAI. LangChain

Ikram Shah
Docker
Python
IPM
AI
0.0 (0)07 Jul, 2023 768

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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iknow-utils

Bundles a few reusable IRIS NLP utilities for common scenarios

B
Benjamin De Boe
IPM
AI
4.8 (2)17 Jan, 2023 176 1

iKnow

The iKnow Natural Language Processing technology was originally developed in Belgium and then acquired by InterSystems in 2010. In February 2020, InterSystems published the technology to open source, expanding the possible use cases for it beyond embedded use from the InterSystems IRIS Data Platform. iKnow is open to community contributions to enhance the engine, language models and interfaces for use in text exploration, information extraction and machine learning use cases.

B
Benjamin De Boe
Python
AI
0.0 (0)05 Jul, 2021 962

website-analyzer

InterSystems IRIS NLP Analyzer to websites. Extract all website content with the app crawler and analyze into Text Analytics Domain Explorer and in the BI User Portal.

Yuri Marx
Docker
AI
5.0 (1)24 Dec, 2020 471

Twitter Sentiment Analysis with IRIS

Use IRIS Natural Language Processing and its interoperability capabilities to fetch realtime tweets and analyze their sentiment as well as their metadata.

A
Amir Samary
Docker
AI
0.0 (0)24 Oct, 2019 605