#Generative AI (GenAI)

I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:

ollama-ai-iris/data/prompts/medical_progress_notes_prompt.txt at main · oliverwilms/ollama-ai-iris
 

I combined @Rodolfo Pscheidt Jr https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

I attempted to run

python3 query_data.

My use case is I want AI to extract six pieces of key information from medical visit notes.

It works okay with notes from Epic patient portals. I am struggling with one of my own visit Summaries. So far I have not been able to instruct ollama to give me a JSON response where it gave me what I am asking for.

My original medical_progress_notes_prompt was:

Medical progress note:
---
(document)
---

You are an expert in analyzing medical progress notes.

I combined @Rodolfo Pscheidt https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

My own project is https://github.com/oliverwilms/ollama-ai-iris

I can run load_data.py and it connects to IRIS (same container).

When I try to run query_data.py https://github.com/oliverwilms/ollama-ai-iris/blob/main/query_data.py , it cannot connect to ollama:

ConnectionError: Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible.

I wonder if I need to add in query_data.

I want to provide a shortcut to the D.C. A.I. from a hotkey which will automatically populate the question field here - https://community.intersystems.com/ask-dc-ai.

Is there a way to construct this URL such that it will populate the "Ask a Programming Question" field (and better yet, execute the query)?

Thanks!

I try to get a vector from calling GetEmbedding, but i failed to convert it into a vector 

Here is a simplyfied sample class: 

Class User.myclass Extends %Persistent
{ Property myVECTOR As %Vector(CAPTION = "Vector");

Property myProperty As %String(MAXLEN = 40) [ Required ];

}

here the GetEmbedding part from User.mymethods:

...
ClassMethod GetEmbedding(sentences As %String) As %String [ Language = python ]
{
  import sentence_transformers   model = sentence_transformer