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Hi Community

In this article, I will introduce my application irisChatGPT which is built on LangChain Framework.

First of all, let us have a brief overview of the framework.

The entire world is talking about ChatGPT and how Large Language Models(LLMs) have become so powerful and has been performing beyond expectations, giving human-like conversations. This is just the beginning of how this can be applied to every enterprise and every domain!

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Article
· Sep 18, 2023 7m read
Vectors support, well almost

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

  • Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
  • Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
  • Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

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For several years now Visual Studio Code has supported the notebook coding paradigm with a maturing UX and an API that is enabling a notebook extensions ecosystem to grow. One of the best-known notebook platforms is Jupyter Notebooks. A Microsoft team publishes an extension that allows VS Code to handle .ipynb notebook files. These can either work against a local Python environment or connect to a Jupyter Server, which typically hosts remote Python environments with beefier resources.

What if your InterSystems IRIS environments, whether local on your workstation or remote in your organization / cloud, could operate as Jupyter Servers? And not only for Embedded Python but also for ObjectScript and SQL

"If we build it, will they come?"

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Hi colleagues!

InterSystems Grand Prix 2023 unites all the key features of InterSystems IRIS Data Platform!

Thus we invite you to use the following features and collect additional technical bonuses that will help you to win the prize!

Here we go!

  • LLM AI or LangChain usage: Chat GPT, Bard and others - 6
  • InterSystems FHIR SQL Builder- 5
  • InterSystems FHIR - 3
  • IntegratedML - 4
  • Native API - 3
  • Embedded Python - 4
  • Interoperability - 3
  • Production EXtension(PEX) - 2
  • Adaptive Analytics (AtScale) Cubes usage - 3
  • Tableau, PowerBI, Logi usage - 3
  • InterSystems IRIS BI - 3
  • Columnar Index Usage - 1
  • Docker container usage - 2
  • ZPM Package deployment - 2
  • Online Demo - 2
  • Unit Testing - 2
  • Implement InterSystems Community Idea - 4
  • First Article on Developer Community - 2
  • Second Article On DC - 1
  • Code Quality pass - 1
  • First Time Contribution - 3
  • Video on YouTube - 3

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While starting the development with IRIS we have a distribution kit or in case of Docker we are pulling the docker image and then often we need to initialize it and setup the development environment. We might need to create databases, namespaces, turn on/off some services, create resources. We often need to import code and data into IRIS instance and run some custom code to init the solution.

Lajos Simicska declares war on Viktor Orban: "It's either him or me!" - The  Budapest Beacon

And there plenty of templates on Open Exchange where we suggest how to init REST, Interoperability, Analytics, Fullstack and many other templates with ObjectScript. What if we want to use only Python to setup the development environment for Embedded Python project with IRIS?

So, the recent release of Embedded Python template is the pure python boilerplate that could be a starting point for developers that build python projects with no need to use and learn ObjectScript. This article expresses how this template could be used to initialize IRIS. Here we go!

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Hi Community,

We're pleased to invite you to the upcoming webinar in Hebrew:

👉 Leveraging Embedded Python in Hebrew 👈

🗓️ Date & time: September 12th, 3:00 PM IDT

https://www.youtube.com/embed/shr7yMRj83Q?si=EGmYxBk0v-2j6j6c
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Problem

In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.

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With the advent of Embedded Python, a myriad of use cases are now possible from within IRIS directly using Python libraries for more complex operations. One such operation is the use of natural language processing tools such as textual similarity comparison.

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Hi all,
I am trying to execute a query like the below code.
set statement = ##class(%ResultSet).%New("some_class:query_method"). // here query method is empty and with rowspec some columname

statement.Execute(param1)

I want to fetch data type of column value returned from above. eg - Name - VARCHAR, amount - INTEGER etc.
How can I get it. Or if not possible directly. Is there any other way to validate or get datatype of values returned. Line we have type() in python3

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I recently had the need to monitor from HealthConnect the records present in a NoSQL database in the Cloud, more specifically Cloud Firestore, deployed in Firebase. With a quick glance I could see how easy it would be to create an ad-hoc Adapter to make the connection taking advantage of the capabilities of Embedded Python, so I got to work.

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Written in reply to community post for can Python create HL7 Message dynamically.

Pre-requisites and setup

Use an integration enabled namespace.
Note: USER namespace is not enabled for interoperability by default.
If following suggest create a new interoperatibility namespace to explore functionality.

# Switch to
ZN "[Interoperability Namespace Name]"

# Launch interactive Python shell:
Do $SYSTEM.Python.Shell()

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Hey Developers,

Start watching the new video on InterSystems Developers YouTube:

Using Embedded Python as a Jupyter Notebook Server @ Global Summit 2023

https://www.youtube.com/embed/77oPUfltu0o
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Earlier this year I announced availability of a VS Code extension for coding in ObjectScript, Embedded Python or SQL using the notebook paradigm popularized by Jupyter. Today I published a maintenance release to correct a "getting started" problem.

Here's a video of the installation steps from the extension's README:

Why not try it for yourself?

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Methods written in ObjectScript can use pass-by-reference arguments to return information to the caller. Python doesn’t support pass-by-reference arguments, so Embedded Python in IRIS doesn’t support them either. That's it, that's the end of the post, hope you liked it. 😉 But wait, what about the Classic Rock & Roll?

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Hi All,

We're doing our first babysteps with embedded Python and IRIS with an interoperability solution. We want to convert a CSV file to an Excel xlt file.

As service we've got a EnsLib.File.PassthroughService which picks up a csv file

As operation we've got a EnsLib.File.PassthroughOperation which writes the Excel file.

In the middle:

We've created an Business Process with an %Stream.GlobalCharacter in the Request and a %Stream.GlobalCharacter in the Response.

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I'm proud to announce the new release of iris-pex-embedded-python (v2.3.1) with a new command line interface.

This command line is called iop for Interoperability On Python.

First I would like to present in few words the project the main changes since the version 1.

A breif history of the project

Version 1.0 was a proof of concept to show how the interoperability framework of IRIS can be used with a python first approach while remaining compatible with any existing ObjectScript code.

What does it mean? It means that any python developer can use the IRIS interoperability framework without any knowledge of ObjectScript.

Example :

from grongier.pex import BusinessOperation

class MyBusinessOperation(BusinessOperation):

    def on_message(self, request):
        self.log.info("Received request")

Great, isn't it?

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Hi Community

In this article, I will introduce my application IRIS-GenLab.

IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.

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