It's been a long time since I didn't write an update post on IoP.

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So what's new since IoP command line interface was released?

Two new big features were added to IoP:
- Rebranding: the grongier.pex module was renamed to iop to reflect the new name of the project.
- Async support: IoP now supports async functions and coroutines.

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I implemented a Python Flask application for the 2024 Python Contest with a page that provides common form fields for an outgoing email such as the To and CC fields. And it lets you input a message as well as uploading text based attachments.

Then using LlamaIndex in Python, the app analyzes the content you put in and returns to you in a result box if there is anything that should stop you from sending that email.

Take a look at the Github repo here.

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For a long time I have wanted to learn the Django framework, but another more pressing project has always taken priority. Like many developers, I use python when it comes to machine learning, but when I first learned web programming PHP was still enjoying primacy, and so when it was time for me to pick up a new complicated framework for creating web applications to publish my machine learning work, I still turned to PHP.

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Hi all,

Some days ago, I've seen a youtuber talking about how to create a neural network (sorry, is in spanish)

https://www.youtube.com/embed/iX_on3VxZzk
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently.

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Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • Step1: Install required libraries

  • Step2: Create patterns and responses file

  • Step3: Train the Model

  • Step4: Create ChatBot Application based on the trained model

So Let us start.

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Question
· Jul 10, 2024
Component registration

When registering the components: I used this command:
"Utils.migrate("/external/src/CoreModel/Python/settings.py)" ;
The error appears: "An error has occurred: iris.cls: error finding class",
I changed with these two lines:
result = subprocess.run(["iop", "-m", "/external/src/CoreModel/Python/settings.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True)
subprocess.run(["iop", "-m", "/external/src/CoreModel/Python/settings.py"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, check=True)

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Hi Developers!

Here are the technology bonuses for the InterSystems Python Contest 2024 that will give you extra points in the voting:

  • IRIS Vector Search usage - 3
  • Python Pex Interoperability - 3
  • Python in BPL - 2
  • WSGI Web Apps - 2
  • Python libs: sqlalchemy and dbt - 2
  • LLM AI or LangChain usage: Chat GPT, Bard and others - 3
  • NoObjectScriptLine - 3
  • Hugginface - 2
  • Docker container usage - 2
  • ZPM Package deployment - 2
  • Online Demo - 2
  • Implement InterSystems Community Idea - 4
  • Find a bug in Embedded Python - 2
  • First Article on Developer Community - 2
  • Second Article On DC - 1
  • First Time Contribution - 3
  • Video on YouTube - 3
  • YouTube Short - 1

See the details below.<--break->

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Hi Developers!

This is the second post on the resources for Developers. This part is about Open Exchange

Using Open Exchange to Learn InterSystems

InterSystems Open Exchange is a applications gallery of tools, connectors, and libraries which InterSystems Developers submit to share the experience, approaches and do business. All the applications are either built with InterSystems data platforms or are intended to use for development with InterSystems data platforms.

If you are a beginner developer you can take a look at applications in Technology Example category. All the applications in this category come with open source code repositories, so you are able to run the samples and examples in a docker container with IRIS on your laptop or in the cloud IRIS sandbox. Examples:

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Hello everyone,

Recently, I've been working on a Business Process that processes a large JSON FHIR message containing up to 50k requests in an array within the JSON.

Currently, the code imports the JSON as a dynamic object from the original message stream, obtains an iterator from it, and processes each request one at a time in a loop.

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Article
· Mar 18, 2024 10m read
Pandas for KPIs in InterSystems IRIS BI

Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

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Hi,

In my Iris Installation I cannot use python. When I try to install external libraries I get no OPENSSL_Applink:

$ pwd
/cygdrive/c/InterSystems/IRIS2/bin
$ ./irispip install --target ../Mgr/python/ pandas
OPENSSL_Uplink(00007FFBEC2F7068,08): no OPENSSL_Applink

I get the same error when I try to install a wheel file:

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We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

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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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