#Vector Search

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Vector search is a method used in information retrieval and machine learning to find similar items based on their mathematical representations as vectors. In this approach, each item is represented as a high-dimensional vector, with each dimension corresponding to a feature or characteristic of the item. Vector search algorithms then compare these vectors to find similar items, such as having similar features or being close together in the vector space. Read more here.

Hi Community,

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

👉 Hebrew Webinar: GenAI + RAG - Leveraging Intersystems IRIS as your Vector DB👈

📅 Date & time: February 26th, 3:00 PM IDT

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Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 2 – Python and Vector Search

Since we have access to the data from our external table, we can use everything that Iris has to offer with this data. Let's, for example, read the data from our external table and generate a polynomial regression with it.

For more information on using python with Iris, see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=AFL_epython

Let's now consume the data from the external database to calculate a polynomial regression. To do this, we will use a python code to run a SQL that will read our MySQL table and turn it into a pandas dataframe:

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Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 1 - SQL Gateway

Hello

In this article we will look at the use of SQL Gateway in Iris. SQL Gateway allows Iris to have access to tables from other (external) database via ODBC or JDBC. We can access Tables or Views from various databases, such as Oracle, PostgreSQL, SQL Server, MySQL and others.

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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ First Vector Search on IRIS

https://www.youtube.com/embed/Q2CPHViuLmc
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InterSystems announces General Availability of InterSystems IRIS, InterSystems IRIS for Health, and HealthShare Health Connect 2024.3

The 2024.3 release of InterSystems IRIS® data platform, InterSystems IRIS® for Health, and HealthShare® Health Connect is now Generally Available (GA).

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Article
· Nov 11, 2024 3m read
EduVerse: Accessible Learning Assistant

🌍 Inclusion & Innovation in Education 🌍
Our project reimagines learning for all students, with a focus on accessibility and interactive experiences. Built with the goal of making education engaging and inclusive, the tool is designed to support students of all abilities in learning complex material in an intuitive way.

💡 What It Does
This educational app transforms lesson presentations into interactive study sessions:

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Welcome to the third and final publication of our articles dedicated to the development of RAG applications based on LLM models. In this final article, we will see, based on our small example project, how we can find the most appropriate context for the question we want to send to our LLM model and for this we will make use of the vector search functionality included in IRIS.

Meme Creator - Funny Context Meme Generator at MemeCreator.org!

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Article
· Mar 21, 2024 2m read
Left Side Functions in ObjectScript

In ObjectScript you have a wide collection of functions that return some value
typically:

set variable = $somefunction(param1,param2, ...)

There is nothing special about that.
But there is a set of functions that I classify as LEFT SIDED
The specialty of them is that you can use them also on the left of the equal operator
as a target in the SET command:

set $somefunction(param1,param2, ...) = value

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We've recently made available a new version of InterSystems IRIS in the Vector Search Early Access Program, featuring a new Approximate Nearest Neighbor index based upon the Hierarchical Navigable Small World (HNSW) indexing algorithm.

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Announcement
· Sep 19, 2024
[Video] What Are Embeddings?

Hi, Community!

Want to dive deeper into the concepts of vector searches and embeddings? Learn from an InterSystems expert:

What Are Embeddings?

https://www.youtube.com/embed/WAKwI-ijoQE?utm_source=youtube&utm_medium=social&utm_campaign=WAKwI-ijoQE
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Hey Developers,

Play the new video on InterSystems Developers YouTube:

⏯ Chatbots are all the RAGe: Generative AI with InterSystems IRIS @ Global Summit 2024

https://www.youtube.com/embed/mj6NshZ4T0U
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Hi Community,

Play the new video on InterSystems Developers YouTube:

⏯ InterSystems IRIS Vector Search and the Python Ecosystem @ Global Summit 2024

https://www.youtube.com/embed/XVEvUOxJUrw
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Hi, Community!

Curious how a retrieval-augmented generation (RAG) application works? Take a look at this demonstration:

Exploring a Basic RAG Application

https://www.youtube.com/embed/bYzAziVjwRA?utm_source=youtube&utm_medium=social&utm_campaign=bYzAziVjwRA
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Hi, Community!

Are you building generative AI applications? See how a retrieval-augmented generation (RAG) architecture can help:

Exploring the Benefits of RAG

https://www.youtube.com/embed/NSYVHiJPRas?utm_source=youtube&utm_medium=social&utm_campaign=NSYVHiJPRas
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Artificial intelligence (AI) has transformative potential for driving value and insights from data. As we progress toward a world where nearly every application will be AI-driven, developers building those applications will need the right tools to create experiences from these applications. Tools like vector search are essential for enabling efficient and accurate retrieval of relevant information from massive datasets when working with large language models.

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image

Hi Community,

In this article, I will introduce my application iris-RAG-Gen .

Iris-RAG-Gen is a generative AI Retrieval-Augmented Generation (RAG) application that leverages the functionality of IRIS Vector Search to personalize ChatGPT with the help of the Streamlit web framework, LangChain, and OpenAI. The application uses IRIS as a vector store.

Application Features

  • Ingest Documents (PDF or TXT) into IRIS
  • Chat with the selected Ingested document
  • Delete Ingested Documents
  • OpenAI ChatGPT

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In the previous article we presented the d[IA]gnosis application developed to support the coding of diagnoses in ICD-10. In this article we will see how InterSystems IRIS for Health provides us with the necessary tools for the generation of vectors from the ICD-10 code list using a pre-trained language model, its storage and the subsequent search for similarities on all these generated vectors.

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Translated from the Spanish Community Article Contest.

Following the latest programming contest on OEX I had some surprising observation.
There were almost exclusive applications based on AI in combination with pre-cooked Py modules.
But digging deeper, all examples used the same technical pieces of IRIS.

Seen from point of view of IRIS it was pretty much the same whether searching for text
or searching for images or other pattern. It ended in almost exchangeable methods.

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Current triage systems often rely on the experience of admitting physicians. This can lead to delays in care for some patients, especially when faced with inexperienced residents or non-critical symptoms. Additionally, it can result in unnecessary hospital admissions, straining resources and increasing healthcare costs.

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ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.

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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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ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model (Hochbaum, Rosenstock, & Kegels, 1952) as a psychological framework to craft empathetic replies.

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