In vscode objectscript extension, when you push "Ctrl + Slash" in the editor window, the comment delimiter "#;" is inserted. This feature helps me a lot to write comments in sources. But currently it does not have any options to change "#;" to other characters.
Hello everyone, After upgrade to InterSystems ObjectScriptv2.12.3 extension an annoying "bulb" occured in the beggining of code line. If point upon it, there are some actions being offered. In my case, an action "Wrap in try/catch" is alwaysamong them, even if the code line is already within try/catch block. Another action which appears sometimes is "Extract to method". If accept, new method is inserted into the class with only one line body inside. IMHO, not too clever "AI solution" as well.
there is a setting in VSCode "objectscript.export: {noStorage: ture} " allow export cls from server to client, without storage definition.
However, wheneven I complied and save cls in my vscode client, the storage definition was added back. If I don't want it, I have to deleted the part manually.
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.
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