AIND Metadata Viz

metadata visualizations

Usage

Clone the repository and cd into the folder

Create a virtual environment and install the package, then launch panel.

python -m venv .venv
source .venv/bin/activate (or .venv/bin/Scripts/activate on Windows)
pip install -e .
panel serve ./src/aind_metadata_viz/app.py --show

Release

We directly expose the process/port on the internal AI network. To update and restart:

To update build

ssh ibs-davidf-vm2
cd aind-metadata-viz
git pull

To restart

ps aux | grep panel
kill pid
./start_viz.sh

start_viz.sh is:

#!/bin/bash -x

cd ~/aind-metadata-viz

source .venv/bin/activate
pip install -e .

nohup panel serve ./src/aind_metadata_viz/app.py --allow-websocket-origin=10.128.141.92:5006 > ~/logfile.log 2>&1 &

The process (should) auto-restart on reboot. See crontab -e

CI/CD

There is a Dockerfile which includes the entrypoint to launch the app.

Local dev

1. Build the Docker image locally and run a Docker container:

docker build -t aind-metadata-viz .
docker run -e ALLOW_WEBSOCKET_ORIGIN=localhost:8000 -p 8000:8000 aind-metadata-viz

2. Navigate to 'localhost:8000` to view the app.

AWS

1. On pushes to the dev or main branch, a GitHub Action will run to publish a Docker image to ghcr.io/allenneuraldynamics/aind-metadata-viz:dev or ghcr.io/allenneuraldynamics/aind-metadata-viz:latest.
2. The image can be used by a ECS Service in AWS to run a task container. Application Load Balancer can be used to serve the container from ECS. Please note that the task must be configured with the correct env variables (e.g. API_GATEWAY_HOST, ALLOW_WEBSOCKET_ORIGIN).