Initial Release
A generative AI application built on InterSystems IRIS for Health that enables natural language querying of patient clinical data.
The IRIS Clinical Assistant leverages vector embeddings and large language models to provide an intuitive way to query patient data stored in FHIR format. Using a Retrieval Augmented Generation (RAG) approach, the system enables natural language queries about patient conditions, medications, and procedures.
The solution follows a Retrieval Augmented Generation (RAG) architecture:
git clone https://github.com/dianamindroc/iris-clinical-assistant.git
cd iris-clinical-assistant
conda create --name intersystemscontest python=3.10
conda activate intersystemscontest
pip install -r requirements.txt
docker-compose up -d
docker exec -it iris session iris
zn ""
zpm "install fhir-server"
Now you can exit the container by entering HALT
.
Additionally, we need to make sure that Admin has SQL privileges. For this, go to dashboard, go to System Administration -> Security -> Users -> Go, click on Admin and Roles, Assign %All.
Install IRIS driver wheel (can be downloaded from IRIS website, it was already downloaded and placed in the wheels folder)
cd wheels
pip install intersystems_irispython-3.2.0-py3-none-any.whl
.env
, make sure to update IRIS username, password, namespace and add a HuggingFace token for LLM inference.cd ..
python -m app.app