docs: added sustainability and scaling docs. Various other changes to…

… the docs

Dockerfile

@@ -44,4 +44,4 @@ RUN pip3 install --no-cache-dir chembl_structure_pipeline --no-deps
 
 COPY ./app /code/app
 
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--workers", "4"]
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--workers", "4", "--reload"]

app/main.py

@@ -3,7 +3,8 @@
 from fastapi.responses import RedirectResponse
 from fastapi_versioning import VersionedFastAPI
 
-from .routers import chem, converters, depict, tools, ocsr
+from .routers import chem, converters, depict, tools
+#, ocsr
 from fastapi.middleware.cors import CORSMiddleware
 
 from prometheus_fastapi_instrumentator import Instrumentator
@@ -28,7 +29,7 @@
 app.include_router(converters.router)
 app.include_router(depict.router)
 app.include_router(tools.router)
-app.include_router(ocsr.router)
+# app.include_router(ocsr.router)
 
 app = VersionedFastAPI(
     app,

docs/.vitepress/config.ts

@@ -3,7 +3,7 @@ import { defineConfig } from 'vitepress'
 // https://vitepress.dev/reference/site-config
 export default defineConfig({
   title: "Cheminformatics Python Microservice",
-  description: "This set of essential and valuable microservices is designed to be accessed via API calls to support cheminformatics. Generally, it is designed to work with SMILES-based inputs and could be used to translate between different machine-readable representations, get Natural Product (NP) likeliness scores, visualize chemical structures, and generate descriptors. In addition, the microservices also host an instance of STOUT and another instance of DECIMER (two deep learning models for IUPAC name generation and optical chemical structure recognition, respectively).",
+  description: "This set of essential and valuable microservices is designed to be accessed via API calls to support cheminformatics. Generally, it is designed to work with SMILES-based inputs and could be used to translate between different machine-readable representations, get Natural Product (NP) likeliness scores, visualize chemical structures, and generate descriptors. In addition, the microservice also host an instance of STOUT and another instance of DECIMER (two deep learning models for IUPAC name generation and optical chemical structure recognition, respectively).",
 
   themeConfig: {
     search: {
@@ -30,6 +30,7 @@ export default defineConfig({
           { text: 'Introduction', link: '/introduction' },
           { text: 'Versions', link: '/versions' },
           { text: 'Architecture', link: '/architecture' },
+          { text: 'Sustainability', link: '/sustainability' },
         ]
       },
       {
@@ -38,6 +39,7 @@ export default defineConfig({
           { text: 'Docker', link: '/docker' },
           { text: 'Cluster Deployment (K8S)', link: '/cluster-deployment' },
           { text: 'Standalone (Python virtual environment)', link: '/standalone' },
+          { text: 'Scaling', link: '/scaling' },
         ]
       },
       {
@@ -53,7 +55,7 @@ export default defineConfig({
       {
         text: 'Development',
         items: [
-          { text: 'Local Installation', link: '/installation' },
+          { text: 'Local Setup', link: '/installation' },
           { text: 'License', link: '/license' },
           { text: 'Issues/Feature requests', link: '/issues' },
           { text: 'Contributors', link: '/contributors' }

docs/chem.md

@@ -12,6 +12,6 @@ Under the CHEM module, CPM exposes functions and routines offered by cheminforma
       width="100%"
       height="720"
       style="border:none"
-      src="https://dev.api.naturalproducts.net/v1/docs#/chem">
+      src="https://dev.api.naturalproducts.net/latest/docs#/chem">
   </iframe>
 </div>

docs/cluster-deployment.md

@@ -2,19 +2,25 @@
 outline: deep
 ---
 
-# Kubernetes deployment via Helm.
-Cheminformatics Python Microservices comes packaged with [Helm](https://helm.sh/docs/) chart which simplifies the deployment and management of applications on [Kubernetes](https://kubernetes.io/) by providing a convenient package manager interface. By following the steps outlined in this documentation, you can easily deploy this microservice using [Helm](https://helm.sh/docs/), enabling efficient and reproducible deployments in your [Kubernetes](https://kubernetes.io/) cluster.
+# Kubernetes deployment (K8S)
 
-Please refer to Helm’s [documentation](https://helm.sh/docs/) to get started.
+## Helm Charts - v0.1.6
+
+Cheminformatics Python Microservices comes packaged with a [Helm](https://helm.sh/docs/) chart, that makes it easy to deploy and manage (scale) containers on [Kubernetes](https://kubernetes.io/) via a convenient package manager interface. 
+
+By following the steps outlined in this documentation, you can easily deploy this microservice using [Helm](https://helm.sh/docs/).
+
+For more information about Helm Charts based deployment please refer to official [Helm documentation](https://helm.sh/docs/).
 
 **Prerequisites:**
 
 Before proceeding with the deployment, ensure that you have the following:
 
 Kubernetes cluster: Set up a functioning Kubernetes cluster with kubectl configured to interact with the cluster.
+
 Helm: [Install Helm](https://helm.sh/docs/docs/intro/install/) on your local machine or the machine from which you'll be deploying the application. 
 
-### Deploy the chart:
+## Deployment using CPM Helm Chart
 *  **Add repo:** Once Helm has been set up correctly, add the repo as follows: 
 ```bash
     helm repo add repo-helm-charts https://nfdi4chem.github.io/repo-helm-charts/
@@ -35,7 +41,7 @@ kubectl get services
 ```
 * **Upgrading and Managing Deployments:** To upgrade an existing deployment, Use the `helm upgrade` command to apply the changes to the existing release e.g.
 ```bash
-helm upgrade myrelease repo-helm-charts/cheminfo-microservice-0.0.2
+helm upgrade myrelease repo-helm-charts/cheminfo-microservice-0.1.6
 ```
 
 * **Uninstalling the Chart:** To remove a deployed chart and associated resources, use the helm uninstall command:
@@ -45,10 +51,12 @@ helm uninstall myrelease
 This will delete all resources created by the chart, including pods, services, and any other Kubernetes objects.
 
 
-# Deployment to Google Kubernetes Engine(GKE) using Helm.
+
+## Google Kubernetes Engine(GKE)
+
 This documentation will guide you through the process of deploying the CPM application in [Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine) using [Helm](https://helm.sh/docs/). Here we provide a step-by-step instructions to help you set up your environment, install Helm, and dpeloy the CPM application in the Google Kubernetes Cluster.
 
-## Prerequisites
+### Prerequisites
 Before you begin, ensure you have the following prerequisites in place:
 * Google Cloud Platform (GCP) Account: You need a GCP account to create a GKE cluster and use other GCP services.
 * In the Google Cloud console, on the project selector page, select or [create a Google Cloud project](https://cloud.google.com/resource-manager/docs/creating-managing-projects).
@@ -57,7 +65,7 @@ Before you begin, ensure you have the following prerequisites in place:
     * Go to [Google Cloud Console](https://console.cloud.google.com/)
     * Click on the 'Activate Cloud Shell' button located at the top of the Google Cloud console window.
 
-###  Step 1: Create a GKE Cluster
+####  Step 1: Create a GKE Cluster
 A GKE cluster consists of a pool of Compute Engine VM instances running [Kubernetes](https://kubernetes.io/), the open source cluster orchestration system that powers GKE.
 1. Navigate to [Google Kubernetes Engine](https://console.cloud.google.com/kubernetes) page in Google Cloud console.
 2. Click on the Create icon.
@@ -77,11 +85,11 @@ A GKE cluster consists of a pool of Compute Engine VM instances running [Kuberne
 
 6. Click on `Create` button and wait for the Cluster to be ready.
 
-### Step2: Connect to Cluster
+#### Step2: Connect to Cluster
 1. After you cluster is created you can see the green check next to it. Once you see the check, click on the three dots next to your cluster to click on `Connect`.
 2. Click on `Run in Cloud Shell` option and press enter.
 
-### Step3: Deploy via Helm Chart
+#### Step3: Deploy via Helm Chart
 1. Add the helm repo by running below command.
 ```bash
     helm repo add repo-helm-charts https://nfdi4chem.github.io/repo-helm-charts/
@@ -102,14 +110,14 @@ kubectl get services
 5. To access your service you may have to expose it either by setting the type to `Load Balancer` under service in values.yml file or by an Ingress depending upon your requirement.
 To learn more about how to configure Nginx Ingress you can click on the link [here](https://github.com/GoogleCloudPlatform/community/blob/master/archived/nginx-ingress-gke/index.md#deploying-the-nginx-ingress-controller-with-helm).
 
-### Step4: Clean up
+#### Step4: Clean up
 To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete resources by running below command.
 ```bash
 helm delete myrelease
 ```
 
-## Scaling
-In case of performance issue, the CPM application can be scaled accordingly. The Helm chart for CPM comes packaged with Horizontal Pod Autoscaler. Horizontal Pod Autoscaler (HPA) is a Kubernetes feature that automatically adjusts the number of replica pods in a deployment or replica set based on observed CPU utilization or other select metrics. This allows your Kubernetes cluster to dynamically respond to changes in application load, ensuring optimal resource utilization and application availability.
+### Scaling
+In case of performance issue, the CPM application can be scaled automatically using different strategies. The Helm chart for CPM comes packaged with Horizontal Pod Autoscaler. Horizontal Pod Autoscaler (HPA) is a Kubernetes feature that automatically adjusts the number of replica pods in a deployment or replica set based on observed CPU utilization or other select metrics. This allows your Kubernetes cluster to dynamically respond to changes in application load, ensuring optimal resource utilization and application availability.
 You can set the `targetCPUUtilizationPercentage` and `targetMemoryUtilizationPercentage` values in values.yml file  according to your need and demand, which is the deciding factor to trigger the scaling. To learn more about different types of scaling in Kubernetes and GKE follow the official [documentation](https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler) of Google Cloud.
 
 ::: info
@@ -118,7 +126,7 @@ For Docker Compose based deployments follow the documentation here for [scaling]
 
 ::: 
 
-### Contribute or Report an issue
+### Contribute or Report an issue with CPM Helm Chart
 Thank you for your valuable assistance in enhancing our deployment process. If you would like to contribute, kindly create a pull request in our [GitHub](https://github.com/NFDI4Chem/repo-helm-charts) repository. For any issues or bugs you have encountered, please feel free to create an [issue](https://github.com/NFDI4Chem/repo-helm-charts/issues) in the same or write to us at caffeine-devs@uni-jena.de. 
 Your feedback is greatly appreciated.
 

docs/conversions.md

@@ -12,6 +12,6 @@ CONVERT module offers endpoints for converting molecular representations from on
       width="100%"
       height="670"
       style="border:none"
-      src="https://dev.api.naturalproducts.net/v1/docs#/convert">
+      src="https://dev.api.naturalproducts.net/latest/docs#/convert">
   </iframe>
 </div>

docs/depict.md

@@ -10,8 +10,8 @@ Depict module exposes endpoints for 2D and 3D molecular rendering using differen
   <iframe id="inlineFrameExample"
       title="Inline Frame Example"
       width="100%"
-      height="230"
+      height="190"
       style="border:none"
-      src="https://dev.api.naturalproducts.net/v1/docs#/depict">
+      src="https://dev.api.naturalproducts.net/latest/docs#/depict">
   </iframe>
 </div>

docs/docker.md

@@ -23,12 +23,15 @@ docker run -d -p 8080:80 --name [image-name] caffeinejena/cheminfo-microservice:
 
 ```
 
-# Docker Compose
-[Docker Compose](https://docs.docker.com/get-started/08_using_compose/) is a tool that helps you define and share multi-container applications. With Compose, you can create a YAML file to define the services and with a single command, you can spin everything up or tear it all down. 
-The Cheminformatics Python Microservice comes packaged with docker-compose file which you can use to deploy your application in your server. To deploy using Docker compose follow the steps as described below.
+## Docker Compose
+
+[Docker Compose](https://docs.docker.com/get-started/08_using_compose/) is a handy tool that allows you to define and manage multi-container applications. By creating a YAML file to define the services, you can use a simple command to start or stop everything at once.
+Check out https://docs.docker.com/get-started/08_using_compose/ for more information.
+
+The Cheminformatics Python Microservice is readily equipped with a docker-compose file that enables you to effortlessly deploy your application on your server. To deploy your application using Docker compose, simply follow the steps described below.The Cheminformatics Python Microservice comes packaged with a docker-compose file, which you can use to deploy your application on your server. To deploy using Docker compose, follow the steps described below.
 
 ### Installation
-1. Before you run the command make sure you've installed Docker including docker-compose support. If not then follow the link [here](https://docs.docker.com/compose/install/).
+1. Before you run the command make sure you've installed Docker including docker-compose support. More details [here](https://docs.docker.com/compose/install/).
 2. Clone the repository
 ```bash
 git clone https://github.com/Steinbeck-Lab/cheminformatics-python-microservice.git
@@ -41,7 +44,7 @@ docker-compose -f ops/docker-compose-prod.yml up -d
 
 ## Scaling
 
-Scaling in case of performance issues - This docker-compose file supports the builtin scaling. Request are load balanced by [Traefik](https://doc.traefik.io/traefik/). For example to scale upto 3 additional application containers you can simply invoke:
+For better performance you can scale your application using docker-compose builtin scaling support. Requests are load balanced by [Traefik](https://doc.traefik.io/traefik/). For example to scale upto 3 additional application containers you can simply invoke:
 ```bash
 docker-compose -f ops/docker-compose-prod.yml up -d --scale web=3 --no-recreate
 ```

docs/index.rst

@@ -8,7 +8,7 @@ Welcome to Cheminformatics Python Microservice's documentation!
   :width: 500
   :align: center
 
-This set of essential and valuable microservices is designed to be accessed via API calls to support cheminformatics. Generally, it is designed to work with SMILES-based inputs and could be used to translate between different machine-readable representations, get Natural Product (NP) likeliness scores, visualize chemical structures, and generate descriptors. In addition, the microservices also host an instance of STOUT and another instance of DECIMER (two deep learning models for IUPAC name generation and optical chemical structure recognition, respectively).
+This set of essential and valuable microservices is designed to be accessed via API calls to support cheminformatics. Generally, it is designed to work with SMILES-based inputs and could be used to translate between different machine-readable representations, get Natural Product (NP) likeliness scores, visualize chemical structures, and generate descriptors. In addition, the microservice also host an instance of STOUT and another instance of DECIMER (two deep learning models for IUPAC name generation and optical chemical structure recognition, respectively).
 
 How to access
 =============

docs/installation.md

@@ -108,10 +108,10 @@ In any case, you would run it like this:
 $ uvicorn main:app --host 0.0.0.0 --port 8080 --workers 4
 ```
 
-Update the Dockerfile in case you are running via docker-compose and rebuild the image for the changes to reflect.
+Update the Dockerfile to watch for code changes
 
 ```
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--workers", "4"]
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--workers", "4", "--reload"]
 ```
 
 </div>