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 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 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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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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Hi Community,

In this article, I will introduce my application iris-image-vector-search.
The image vector retrieval demo uses IRIS Embedded Python and OpenAI CLIP model to convert images into 512 dimensional vector data. Through the new feature of Vector Search, VECTOR-COSINE is used to calculate similarity and display high similarity images.

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Announcement
· May 15
Documentation New Look

The InterSystems documentation new look is pretty awesome. The integrated pervious release documentation are single page is really useful.

Dark mode and collapse the side bar option is cool!

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Hi,

I have a spring-boot Java application which has Quartz Scheduler (spring-boot-quartz-starter) dependency, and uses IRIS DB.
There is a problem with making Quartz Scheduler work with IRIS since there is a blob field expected in two tables, but IRIS is using longvarbinary type.
Can you provide me with clues on how to resolve this?

I am using org.quartz.impl.jdbcjobstore.StdJDBCDelegate driverDelegateClass.

This is the error:
MisfireHandler: Error handling misfires: Couldn't retrieve trigger: invalid stream header: 41434544

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I would dearly love to avoid manually creating a SEF or XSD file to get the X12 832 (4010) schema into IRIS, but I have been hard pressed to find either downloadable resources or commercial options. The typical recommendation, edi-dev, seems to just do tooling that will help create SEF files, but no longer sells actual SEF files.

Anybody got any good resources that might have these schema files?

Thanks for any help!

Cordially,

Jonathan

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Hi Community,

In this article, I will introduce my application iris-VectorLab along with step by step guide to performing vector operations.

IRIS-VectorLab is a web application that demonstrates the functionality of Vector Search with the help of embedded python. It leverages the functionality of the Python framework SentenceTransformers for state-of-the-art sentence embeddings.

Application Features

  • Text to Embeddings Translation.
  • VECTOR-typed Data Insertion.
  • View Vector Data
  • Perform Vector Search by using VECTOR_DOT_PRODUCT and VECTOR_COSINE functions.
  • Demonstrate the difference between normal and vector search
  • HuggingFace Text generation with the help of GPT2 LLM (Large Language Model) model and Hugging Face pipeline

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We are experimenting with IIS, as the PWS will be gone in newer versions.

The code which is executed, takes 15ms to run. If we execute it through PWS (REST), there is some overhead and the total execution time is 40ms, which is acceptable. However, if we go through IIS, it takes 150ms or sometimes even more.

Both PWS and IIS are running on the same server as IRIS in this case. No optimisations have been done on IIS.

Any suggestions on where to look/what to optimize on IIS?

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I am trying to create my first call to our Epic FHIR Repository from Health Connect using Samples-FHIRStarter now that I have OAuth2.0 connection tested/working with our Epic Interconnect URL.

When I take a patient example from our Epic environment and test it through Data.BPL.PatientRecordCollector within the Namespace, I keep getting a 404 - File or directory not found

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Hi Developers,

Join us at the upcoming Developer Roundtable on April 25th at 9 am ET | 3 pm CET. 📍
We will have 2 topics covered by the invited experts and open discussion as always.

Tech Talks:
Practical Usage of Embedded Python - by Stefan Wittmann Product Manager, InterSystems

Recording:

https://www.youtube.com/embed/a6VH4Hg5TmI
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