#Embedded Python

Hello Community,

SQL language remains the most practical way to retrieve information stored in a database.

The JSON format is very often used in data exchange.

It is therefore common to seek to obtain data in JSON format from SQL queries.

Below you will find simple examples that can help you meet this need using ObjectScript and Python code.

Hello,

I became aware of Python in the early 2000s when I started automating tasks. Some of our processes utilized python scripts. I never figured it out very well, and we decided to do away with Python because nobody on our team was familiar with it.

I will give you some additional information on my first embedded Python package.
it is written as a mix of python and ObjectScript to take the best of both worlds.

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.

I developed iris-log-viewer on a work laptop using an older version of IRIS. My messages.log file has nearly 10k lines. I noticed it takes a couple of seconds to read messages.log file line by line, import each line into a persistent class, and display messages on my screen. I wonder if Python can speed up the process.

We continue with the series of articles based on the QuinielaML application.

In today's article I will describe how to work with the Embedded Python functionality available in InterSystems products.

As my entry into InterSystems Developer Tools Contest happening now I have been working on an alternative to the Console Log Viewer web page provided as part of InterSystems IRIS Management Portal. Console log is a file called messages.log. It is what InterSystems support asks me to send to them when I open a support ticket.

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

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.

Introduction

Accessing Amazon S3 (Simple Storage Service) buckets programmatically is a common requirement for many applications. However, setting up and managing AWS accounts is daunting and expensive, especially for small-scale projects or local development environments. In this article, we'll explore how to overcome this hurdle by using Localstack to simulate AWS services. Localstack mimics most AWS services, meaning one can develop and test applications without incurring any costs or relying on an internet connection, which can be incredibly useful for rapid development and debugging. We used ObjectScript with embedded Python to communicate with Intersystems IRIS and AWS simultaneously. Before beginning, ensure you have Python and Docker installed on your system. When Localstack is set up and running, the bucket can be created and used.

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.

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.