A sample application that shows off Generative AI use cases for Healthcare / Life Sciences (HCLS)
Select a directory to clone repo into
git clone https://github.com/aaronlutkowitz2/genai_app_hcls_general
cd genai_app_hcls_general/Install requirements, including Streamlit
pip install -r requirements.txtOptionally, test locally
export PROJECT_ID=$(gcloud info --format='value(config.project)')
streamlit run app.py Two options, create a docker container and then push the Artifact Registry or directly build & deploy to Cloud Run.
build docker image (you need to install docker first)
docker build . -t genai_hcls login to your GCP account to carry code
export PROJECT_ID=$(gcloud info --format='value(config.project)')
gcloud config set project $PROJECT_ID
gcloud auth application-default login build docker container on container registry
export PROJECT_ID=$(gcloud info --format='value(config.project)')
gcloud builds submit --tag gcr.io/${PROJECT_ID}/genai-hclsGo to Cloud Run in your GCP project, create (or update) an app to point to the newest container in Container Registry --> genai_hcls
gcloud run deploy genai-hcls --image gcr.io/${PROJECT_ID}/genai-hcls --allow-unauthenticatedIf there's any auth issues, go to IAM page to add more permissions to the cloud compute engine service account
If there's an issue with one of the container commands, test that docker code works on docker (locally)
docker run -p 8080:8080 --name test_container genai_hclsNote: you may have to delete test_container first - Then the URL should work with latest code
docker rm test_containerdocker build . -t genai_hclsgcloud builds submit --tag gcr.io/cloudadopt/genai_hcls --timeout=2hdocker build . -t genai_hcagcloud builds submit --tag gcr.io/cloudadopt/genai_hca --timeout=2h virtualenv -p python3 venvsource venv/bin/activate