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In the previous article, we saw in detail about Connectors, that let user upload their file and get it converted into embeddings and store it to IRIS DB. In this article, we'll explore different retrieval options that IRIS AI Studio offers - Semantic Search, Chat, Recommender and Similarity.

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Question
· 21 hr ago
How are Stream saved?

Hi, I was working with %sStream.FileBynary and following the doc when I find an info that I'm not sure of.
In the part of the doc where it talks about saving streams, it does not precise where it is saved.
I tried to fill my stream, then rewind, then set the file and finally saved.
And it puts in my default directory with the temporary name.
If I do a zwrite of my stream, I get these properties about the file and directory.
(StoreFile) = "zKc2m8v1.stream"
(NormalizedDirectory) = "C:\InterSystems\Community\mgr\user\stream\"

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Considering new business interest in applying Generative-AI to local commercially sensitive private data and information, without exposure to public clouds. Like a match needs the energy of striking to ignite, the Tech lead new "activation energy" challenge is to reveal how investing in GPU hardware could support novel competitive capabilities. The capability can reveal the use-cases that provide new value and savings.

Sharpening this axe begins with a functional protocol for running LLMs on a local laptop.

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DNA Similarity and Classification was developed as a REST API utilizing InterSystems Vector Search technology to investigate genetic similarities and efficiently classify DNA sequences. This is an application that utilizes artificial intelligence techniques, such as machine learning, enhanced by vector search capabilities, to classify genetic families and identify known similar DNAs from an unknown input DNA.

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TL;DR

This article introduces using the langchain framework supported by IRIS for implementing a Q&A chatbot, focusing on Retrieval Augmented Generation (RAG). It explores how IRIS Vector Search within langchain-iris facilitates storage, retrieval, and semantic search of data, enabling precise and up-to-date responses to user queries. Through seamless integration and processes like indexing and retrieval/generation, RAG applications powered by IRIS enable the capabilities of GenAI systems for InterSystems developers.

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Hello developers,

Our project was designed to optimize patient clinical outcomes by reducing hospitalization time and supporting the development of resident and novice physicians. Additionally, it contributes to lowering financial waste in the healthcare system by improving the monitoring of pregnant patients, thereby decreasing risks and enhancing their safety.

Using the most accessible tool, the smartphone, was the obvious choice to make patients' lives easier.

https://www.youtube.com/embed/OL3kdE-JL4c?si=HV6kopsNGJLCVSdl
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The introduction of InterSystems' "Vector Search" marks a paradigm shift in data processing. This cutting-edge technology employs an embedding model to transform unstructured data, such as text, into structured vectors, resulting in significantly enhanced search capabilities. Inspired by this breakthrough, we've developed a specialized search engine tailored to companies.

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Hi,

I have succesfully installed IRIS client on MacOS (see bottom half of this post). What's next? How do I access the menu to launch IRIS Client, access Studio, and connect to remote server etc??

Thanks,

W

----------------------------------------------------------------------------------------------------------

$$> sudo sh /Users/xxx/Downloads/HealthConnect-2023.1.3.517.0-macx64/irisinstall_client

Password:

Your system type is 'Mac OS X/x86/64-bit'.

Enter a destination directory for client components.

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Hi Community,

Here is a brief walkthrough on the capabilities of IRIS AI Studio platform. It covers one complete flow from loading data into IRIS DB as vector embeddings and retrieving information through 4 different channels (search, chat, recommender and similarity). In the latest release, added docker support for local installation and live version to explore.

https://www.youtube.com/embed/X1gzz3Qs2dw
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Hi Team,

I am trying to use the inbuilt class: EnsLib.HL7.Service.FileService to pass through an HL7 ADT message as a part of an HL7 to FHIR transformation. We have a client requirement, where we are receiving an NTE segment as a part of the ADT message. I am trying to map the NTE segment to an OBX Segment. I need to implement a counter for OBX segment whenever a NTE segment is found and map the NTE fields to the new OBX segment

How do I implement the counter for OBX?

Thanks

Santosh

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Hi guys,

I try to make a test of encryption, decryption of a simple text.

I can crypt my text, but I can't decrypt it, do you see somewhere a dummy error of my part ?

Thanks for help

ClassMethod UnitTest()

{

set inputPlainText = "David"

// get private key

set privKeyFileName = "C:\temp\toto.pem"

set privobjCharFile = ##class(%Stream.FileCharacter).%New()

set privobjCharFile.Filename = privKeyFileName

set privKey = privobjCharFile.Read()

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I don't have a current project where I am needing to create a new operation that uses SOAP at the moment but as someone who still has some SOAP connections in her Production, I was curious if VSCode had an equivalent to the SOAP Wizard that helped create all of the SOAP classes needed based on the provided WSDL? Does anyone know? Or has this become a manual process?

Thanks in advance for help curbing my curiosity!

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In Cache End of file throws error but in IRIS no indication of End of file. I have to do an explicit $ZOF. How are you handling/detecting End of File in IRIS?

In cache this line will throw End of file error - F PREC=1:1 U FILE R REC D SOMETHING

But in IRIS this goes to forever, has anyone noticed this behaviour in IRIS?

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Problem

Do you resonate with this - A capability and impact of a technology being truly discovered when it's packaged in a right way to it's audience. Finest example would be, how the Generative AI took off when ChatGPT was put in the public for easy access and not when Transformers/RAG's capabilities were identified. At least a much higher usage came in, when the audience were empowered to explore the possibilities.

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In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions.

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