machine-learning-exchange · RRM123 · Mar 29, 2022 · Mar 29, 2022 · Mar 29, 2022 · Mar 29, 2022
diff --git a/README.md b/README.md
@@ -13,11 +13,6 @@ Allows upload, registration, execution, and deployment of:
  - Datasets
  - Notebooks
 
-For more details about the project please follow this [announcement blog post](https://lfaidata.foundation/blog/2021/09/28/machine-learning-exchange-mlx/). 
-
-
-<img src="docs/images/mlx.png" height="90%" width="90%">
-
 Additionally it provides:
 
  - Automated sample pipeline code generation to execute registered models, datasets and notebooks
@@ -28,6 +23,12 @@ Additionally it provides:
  - Serving engine by [KFServing](https://github.com/kubeflow/kfserving)
  - Model Metadata schemas
 
+For more details about the project please follow this [announcement blog post](https://lfaidata.foundation/blog/2021/09/28/machine-learning-exchange-mlx/). 
+
+
+<img src="docs/images/mlx.png" height="90%" width="90%">
+
+
 ## 1. Deployment
 <img src="docs/images/mlx-architecture-4.png" height="40%" width="40%">
 
@@ -66,13 +67,21 @@ oc get route -n istio-system
 
 ## 3. Import Data and AI Assets in MLX Catalog
 
-[Import data and AI assets using MLX's catalog importer](/docs/import-assets.md)
+For information on how to import data and AI assets using MLX's catalog importer, use this [guide](/docs/import-assets.md).
 
 ## 4. Use MLX
 
-[MLX Usage Instructions](/docs/usage-steps.md)
-
-## 5. Troubleshooting
+For information on how to use MLX and create assets check out this [guide](/docs/usage-steps.md).
+
+## 5. How to Contribute
+
+Contributions can be made to either the UI or API.
+
+For information about adding new features, bug fixing, communication
+or UI and API setup, please refer to this [document](CONTRIBUTING.md).
+
+
+## 6. Troubleshooting
 
 [MLX Troubleshooting Instructions](/docs/troubleshooting.md)
 

diff --git a/dashboard/origin-mlx/OLD_README.md b/dashboard/origin-mlx/OLD_README.md
diff --git a/dashboard/origin-mlx/README.md b/dashboard/origin-mlx/README.md
@@ -4,6 +4,8 @@
 
 This repo contains the code for the front end UI of the Machine Learning Exchange project.
 
+### Starting the MLX UI locally
+
 To run this app, you'll need a current version of Node.js installed.
 
 1. First, clone this repo:
@@ -72,15 +74,34 @@ docker push <your docker user-id>/<repo name>:<tag name>
 ```
 
 ## (Re-)Deploy to Kubernetes Cluster
+For information on how to deploy MLX on a Kubernetes Cluster or OpenShift on IBM Cloud, check out the guide [here](../../docs/mlx-setup.md).
+Once the cluster has been deployed, the MLX UI will need to be redeployed after changes to the UI code have been made.
 
 Change the Docker image tag in the deployment spec server/mlx-ui.yml from image: ibmandrewbutler/open-ui:add-homepage to image: <your_docker_user_id>/<repo name>:<tag name> and then run:
 
 ```Bash
 kubectl delete -f ./dashboard/origin-mlx/mlx-ui.yml
 kubectl apply -f ./dashboard/origin-mlx/mlx-ui.yml
 ```
+Change the image in `./dashboard/origin-mlx/mlx-ui.yml` or `./manifests/base/mlx-deployments/mlx-ui.yaml` under the container with the name mlx-ui at spec.template.spec.containers. Either:
+```
+kubectl delete -f /manifests/base/mlx-deployments/mlx-ui.yaml
+kubectl apply -f /manifests/base/mlx-deployments/mlx-ui.yaml
+```
+or
+```
+kubectl delete -f /dashboard/origin-mlx/mlx-ui.yml
+kubectl apply -f /dashboard/origin-mlx/mlx-ui.yml
+```
 
 ## UI Development with Docker Compose
+For information on how to get started with Docker Compose before making any changes to the UI code, check out the [Quick Start Guide](../../quickstart/README.md) and take a look at the [docker-compose.yaml](../../quickstart/docker-compose.yaml) file to understand how the individual services like `mysql`, `minio`, `mlx-api`, `mlx-ui`, etc. are working together.
+
+The Docker Compose stack can be brought up and taken down by running the following commands. The `--project-name` tag keeps the docker compose network and the volumes (stored assets) separate from the quickstart for development. Each docker compose project has separate network and volumes which can be viewed using [Docker Desktop](https://www.docker.com/products/docker-desktop/):
+```Bash
+docker compose --project-name  mlx  up
+docker compose --project-name  mlx  down
+```
 
 You can test most code changes without a Kubernetes cluster. A K8s cluster is only
 required to `run` the generated sample pipeline code. Running the Quickstart with
@@ -116,7 +137,7 @@ docker compose rm -v -f
 docker volume prune -f
 ```
 
-### Terminal 2 - Start the UI server
+### Terminal 2 - Start the MLX UI locally
 
 Navigate to the UI source folder:
 
@@ -185,6 +206,9 @@ which matches a previous request and the difference of the time between the two
 
 To invalidate or hard reset the cache, navigate to the settings page (clicking the three dots at the bottom of the sidebar) and click on the `Reset Cache` button.
 
+# Development Guidlines:
+For information on UI code structure, design principles, etc. check out the [MLX UI Developer Guide](developer-guide.md).
+
 # Project Overview:
 
 ![MLX Overview](src/images/image1.png)
diff --git a/dashboard/origin-mlx/developer-guide.md b/dashboard/origin-mlx/developer-guide.md
@@ -23,62 +23,6 @@ Lifecycle Methods:
 
 Each component has several “lifecycle methods” that you can override to run code at particular times in the process. Putting functions in different lifecycle methods will cause the function to be run at a specific point in a component's lifecycle. An example of this is running a function after a component is being unmounted (removed or refreshed).
 
-## Startup
-
-General Startup Instructions: https://github.com/machine-learning-exchange/mlx/tree/main/dashboard/origin-mlx
-
-### Starting the MLX UI locally
-
-To run this app, you'll need a current version of Node.js installed.
-
-1. First, clone this repo:
-```Bash
-git clone https://github.com/machine-learning-exchange/mlx.git
-```
-
-2. Next, install the dependencies by running this command from within the newly created directory:
-```Bash
-npm install
-```
-
-3. Start the app with the following command:
-```Bash
-npm start
-```
-
-4. The app should now be accessible in your web browser at:
-```
-http://localhost:3000
-```
-
-### Starting the MLX UI locally with Docker API
-```
-git clone https://github.com/machine-learning-exchange/mlx.git
-cd mlx/
-cd dashboard/origin-mlx/
-rm -rf package-lock.json 
-npm install
-export REACT_APP_API="localhost:8080"
-export REACT_APP_RUN="false"
-export REACT_APP_UPLOAD="true"
-export REACT_APP_DISABLE_LOGIN="true"
-npm start
-```
-
-### Building an MLX UI Image
-
-```
-cd dashboard/origin-mlx
-docker build -t <your docker user-id>/<repo name>:<tag name> -f Dockerfile .
-docker push <your docker user-id>/<repo name>:<tag name>
-```
-
-### Change the UI image on a cluster deployment
-Change the image in /manifests/base/mlx-deployments/mlx-ui.yaml under the container with the name mlx-ui at spec.template.spec.containers
-```
-kubectl delete -f /manifests/base/mlx-deployments/mlx-ui.yaml
-kubectl apply -f /manifests/base/mlx-deployments/mlx-ui.yaml
-```
 
 ## UI File Structure
 
@@ -133,3 +77,5 @@ src/styles/ contains most (>90%) of the page styling in css. If the style needs
 
 
 src/lib/api/ contains all of the calls to the MLX API. If some API call is going wrong, it will likely be an issue in this folder.
+
+For more information on UI Setup and Deployment go [here](README.md)