Step-by-step instructions

Run the Application Locally

1. Clone/upload this folder (gemini-streamlit-demo) to Cloud Shell, or use Cloud Shell Editor. The important files are:

   • app.py
   • requirements.txt
   • Dockerfile

2. Setup the Python virtual environment:

   In Cloud Shell, execute the following commands:

   python3 -m venv gemini-streamlit-env
   source gemini-streamlit-env/bin/activate
   pip install -r requirements.txt

3. Setup environment variables:

   In Cloud Shell, execute the following commands:

   export GCP_PROJECT=[PROJECT_ID]
   export GCP_REGION='us-central1'

4. To run the application locally, execute the following command:

   In Cloud Shell, execute the following command:

   streamlit run app.py \
     --browser.serverAddress=localhost \
     --server.enableCORS=false \
     --server.enableXsrfProtection=false \
     --server.port 8080

5. View the output at http://localhost:8080

Build and Deploy the Application to Cloud Run

1. Setup environment variables:

   In Cloud Shell, execute the following commands:

   export GCP_PROJECT=[PROJECT_ID]
   export GCP_REGION='us-central1'

2. Build the Docker image for the application and push it to Artifact Registry

   In Cloud Shell, execute the following commands:

   export AR_REPO='gemini-streamlit-repo'  # Dashes, no underscores
   export SERVICE_NAME='gemini-streamlit-demo' # Dashes, no underscores
   
   #make sure you are in the active directory for 'gemini-streamlit-demo'
   gcloud artifacts repositories create "$AR_REPO" --location="$GCP_REGION" --repository-format=Docker
   gcloud builds submit --tag "$GCP_REGION-docker.pkg.dev/$GCP_PROJECT/$AR_REPO/$SERVICE_NAME"

3. Deploy the service in Cloud Run with the image that we had built and had pushed to the Artifact Registry in the previous step:

   In Cloud Shell, execute the following command:

   gcloud run deploy "$SERVICE_NAME" \
     --port=8080 \
     --image="$GCP_REGION-docker.pkg.dev/$GCP_PROJECT/$AR_REPO/$SERVICE_NAME" \
     --allow-unauthenticated \
     --region=$GCP_REGION \
     --platform=managed  \
     --project=$GCP_PROJECT \
     --set-env-vars=GCP_PROJECT=$GCP_PROJECT,GCP_REGION=$GCP_REGION