docs: update pages-docker,cluster-deployment,

contributors & installation

docs/src/deployment/cluster-deployment.md

@@ -2,9 +2,16 @@
 :::
 
 # 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.
+NMR Kit 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.
 
-Please refer to Helm’s [documentation](https://helm.sh/docs/) to get started.
+The chart is packaged with below additional services as subcharts, which can be enabled or disabled via the value.yml file.
+* [minio - v12.6.12](https://artifacthub.io/packages/helm/bitnami/minio)
+* [redis - v17.14.6](https://artifacthub.io/packages/helm/bitnami/redis)
+* [grafana - v8.4.5](https://artifacthub.io/packages/helm/bitnami/grafana)
+* [prometheus - v22.6.5](https://prometheus-community.github.io/helm-charts/)
+* [rdkitcatridgepostgres - v0.1.0](https://nfdi4chem.github.io/repo-helm-charts)
+
+If you are new to Helm, please refer to Helm’s [documentation](https://helm.sh/docs/) to get started.
 
 **Prerequisites:**
 
@@ -22,10 +29,10 @@ If you had already added this repo earlier, run `helm repo update` to retrieve t
 
 * **Deploy the Chart:** To deploy the chart, use the helm install command followed by the chart package name and an optional release name:
 ```bash
-helm install myrelease repo-helm-charts/cheminfo-microservice
+helm install myrelease repo-helm-charts/nmrkit
 ```
 The release name (myrelease in this example) is used to identify the deployment, and it must be unique within the Kubernetes cluster.
-The above command with deploy the service with the default configuration provided in [values.yml](https://github.com/NFDI4Chem/repo-helm-charts/blob/main/charts/cheminfo-microservice/values.yaml) file. To overwrite the default configuration please follow this [link](https://helm.sh/docs/chart_template_guide/values_files/) to learn more.
+The above command with deploy the service with the default configuration provided in [values.yml](https://github.com/NFDI4Chem/repo-helm-charts/blob/main/charts/nmrkit/values.yaml) file. To overwrite the default configuration please follow this [link](https://helm.sh/docs/chart_template_guide/values_files/) to learn more.
 
 * Helm will install the chart and deploy the application to your Kubernetes cluster. You can view the deployed resources using kubectl commands:
 ```bash
@@ -34,7 +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/nmrkit-0.0.2
 ```
 
 * **Uninstalling the Chart:** To remove a deployed chart and associated resources, use the helm uninstall command:
@@ -45,7 +52,7 @@ This will delete all resources created by the chart, including pods, services, a
 
 
 ### Contribute or Report an issue
-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. 
+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) or reach out to us via our [Help Desk](https://helpdesk.nfdi4chem.de/).
 Your feedback is greatly appreciated.
 
 

docs/src/deployment/docker.md

@@ -1,23 +1,25 @@
-:::danger Needs to be updated
-:::
-
 # Docker
-The NMR Kit project utilizes the containerized microservices approach to package chemistry toolkits and deep learning tools. It comes pre-packaged with toolkits [RDKit](https://github.com/rdkit/rdkit), [CDK](https://doi.org/10.1186/s13321-017-0220-4), [OpenBabel](https://github.com/openbabel/openbabel) and deep learning tools ([DECIMER](https://github.com/Kohulan/DECIMER-Image_Transformer), [STOUT](https://github.com/Kohulan/Smiles-TO-iUpac-Translator)) for handling chemical data - OSR, format conversions, and descriptor calculation. This enables efficient handling of large data volumes and improved performance and development of cheminformatics applications that are scalable and interoperable.
-
-It is containerized using Docker and is distributed publicly via the [Docker Hub](https://hub.docker.com/r/caffeinejena/cheminformatics-python-microservice), a cloud-based registry provided by Docker that allows developers to store, share, and distribute Docker images.
+NMRKit is containerized using Docker and is distributed publicly via the [Docker Hub](https://hub.docker.com/r/nfdi4chem/nmrkit), a cloud-based registry provided by Docker that allows developers to store, share, and distribute Docker images.
 
 To use this image:
 
-* Make sure you have Docker installed and configured on your target deployment environment.
-* Pull the image by providing the appropiate tag.
+* Make sure you have [Docker](https://docs.docker.com/get-docker/) installed and configured on your target deployment environment.
+* Pull the NMRKit image by providing the appropiate tag.
 
 ```bash
-docker pull caffeinejena/cheminformatics-python-microservice:[tag]
+docker pull nfdi4chem/nmrkit:[tag]
 
 ```
-* Run the below command to run the image
+* NMRKit uses [rdkit-cartridge-debian](https://hub.docker.com/r/informaticsmatters/rdkit-cartridge-debian) Postgres. Run the below command to spin up the image.
+
+```bash
+docker run -d --name postgres -e POSTGRES_PASSWORD=password -e POSTGRES_USER=nmrkit -p 5432:5432 informaticsmatters/rdkit-cartridge-debian:latest
+
+```
+
+* After the Postgres container is prepared to receive connections, initiate the NMRKit container by executing the following command and providing the Postgres credentials.
 
 ```bash
-docker run -d -p 8080:80 --name [image-name] caffeinejena/cheminfo-microservice:[tag]
+docker run -d -p 8080:80 --name nmrkit -e POSTGRES_PASSWORD=password -e POSTGRES_USER=nmrkit -e POSTGRES_SERVER=postgres -e POSTGRES_DB=nmr_predict nfdi4chem/nmrkit:[tag]
 
 ```

docs/src/development/contributors.md

@@ -1,3 +1,3 @@
 # Contributors
 
-![Alt](https://repobeats.axiom.co/api/embed/f8652b486f670b74258723f278c28c29c7e233d7.svg "Repobeats analytics image")
+![Alt](https://repobeats.axiom.co/api/embed/3830ca170f30ecb4e709a88c4747737874d72b46.svg "Repobeats analytics image")

docs/src/development/installation.md

@@ -9,21 +9,21 @@
 
 4. Navigate to the desired directory: Use `cd` to navigate to the directory where you want to clone the project.
 
-5. Clone the repository: Run the command `git clone https://github.com/Steinbeck-Lab/cheminformatics-python-microservice.git` to clone the project.
+5. Clone the repository: Run the command `git clone https://github.com/NFDI4Chem/nmrkit.git` to clone the project.
 
 6. Use `cd` to navigate into the cloned project directory.
 
 You have successfully cloned the project from GitHub onto your local machine.
 
-Once cloned you can either choose to run the project via Docker (recommended) or locally (need to make sure you have all the dependencies resolved).
+Once cloned you can either choose to run the project via Docker-compose (recommended) or locally (need to make sure you have all the dependencies resolved).
 
 ## Docker
 
-1. Install Docker: Install Docker on your machine by following the instructions for your specific operating system.
+1. Install Docker: Install [Docker](https://img.docker.com/get-docker/) on your machine by following the instructions for your specific operating system.
 
-2. Use `cd` to navigate into the cloned project directory.
+2. Use `cd` to navigate into the cloned project directory and create a .env file which can be copied from .env.template and provide your own values for password and username.
 
-3. You will find a docker-compose.yml file in the project. If you don't have a docker-compose.yaml file uses the following template.
+3. You can use the docker-compose.yml file in the root directory, which is same as below and update accordingly if required.
 
 ```yaml
 version: "3.8"
@@ -33,58 +33,118 @@ services:
     build:
       context: ./
       dockerfile: Dockerfile
-    container_name: cheminformatics-python-microservice
+    container_name: nmrkit-api
     volumes:
       - ./app:/code/app
     ports:
       - "80:80"
     healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:80/latest/chem"]
+      test: ["CMD", "curl", "-f", "http://localhost:80/latest/ping"]
       interval: 1m30s
       timeout: 10s
       retries: 20
       start_period: 60s
-  Prometheus:
-    image: prom/Prometheus
-    container_name: Prometheus
+    env_file:
+      - ./.env
+  prometheus:
+    image: prom/prometheus
+    container_name: nmrkit_prometheus
     ports:
       - 9090:9090
     volumes:
-      - ./Prometheus_data/Prometheus.yml:/etc/Prometheus/Prometheus.yml
+      - ./prometheus_data/prometheus.yml:/etc/prometheus/prometheus.yml
     command:
-      - '--config.file=/etc/Prometheus/Prometheus.yml'
-  Grafana:
-    image: Grafana/Grafana
-    container_name: Grafana
+      - '--config.file=/etc/prometheus/prometheus.yml'
+  grafana:
+    image: grafana/grafana
+    container_name: nmrkit_grafana
     ports:
       - 3000:3000
     volumes:
-      - Grafana_data:/var/lib/Grafana
+      - grafana_data:/var/lib/grafana
+  redis:
+    image: "redis:alpine"
+    ports:
+        - "${FORWARD_REDIS_PORT:-6379}:6379"
+    volumes:
+        - "redis:/data"
+    networks:
+        - default
+    healthcheck:
+        test: ["CMD", "redis-cli", "ping"]
+        retries: 3
+        timeout: 5s
+  pgsql:
+    image: "informaticsmatters/rdkit-cartridge-debian"
+    ports:
+      - "${FORWARD_DB_PORT:-5432}:5432"
+    env_file:
+      - ./.env
+    volumes:
+      - "pgsql:/var/lib/postgresql/data"
+    networks:
+      - default
+    healthcheck:
+      test:
+        [
+            "CMD",
+            "pg_isready",
+            "-q",
+            "-d",
+            "${POSTGRES_DB}",
+            "-U",
+            "${POSTGRES_USER}",
+        ]
+      retries: 3
+      timeout: 5s
+  minio:
+    image: 'minio/minio:latest'
+    ports:
+        - '${FORWARD_MINIO_PORT:-9001}:9001'
+        - '${FORWARD_MINIO_CONSOLE_PORT:-8900}:8900'
+    environment:
+        MINIO_ROOT_USER: 'sail'
+        MINIO_ROOT_PASSWORD: 'password'
+    volumes:
+        - 'minio:/data/minio'
+    networks:
+        - default
+    command: minio server /data/minio --console-address ":8900"
+    healthcheck:
+        test: ["CMD", "curl", "-f", "http://localhost:9001/minio/health/live"]
+        retries: 3
+        timeout: 5s
 volumes:
-  Prometheus_data:
+  prometheus_data:
     driver: local
     driver_opts:
       o: bind
       type: none
-      device: ./Prometheus_data
-  Grafana_data:
+      device: ./prometheus_data
+  grafana_data:
     driver: local
     driver_opts:
       o: bind
       type: none
-      device: ./Grafana_data
+      device: ./grafana_data
+  redis:
+    driver: local
+  minio:
+    driver: local
+  pgsql:
+    driver: local
 networks:
   default: 
-    name: cpm_fastapi
+    name: nmrkit_vpc
 ```
 
-4. Run Docker Compose: Execute the command ```docker-compose up``` to start the containers defined in the Compose file.
+4. Run Docker Compose: Execute the command ```docker-compose up -d``` to start the containers defined in the Compose file.
 
 5. Wait for the containers to start: Docker Compose will start the containers and display their logs in the terminal or command prompt.
 
 Unicorn will start the app and display the server address (usually `http://localhost:80`) and Grafana dashboard can be accessed at `http://localhost:3000`
 
-You may update the docker-compose file to disable or add additional services but by default, the docker-compose file shipped with the project has the web (cheminformatics-python-microservice FAST API app), Prometheus and Grafana (logging and visualisation of metrics) services and associated volumes shared via a network.
+You may update the docker-compose file to disable or add additional services but by default, the docker-compose file shipped with the project has the web (nmrkit FAST API app), [rdkit-cartridge-debian](https://hub.docker.com/r/informaticsmatters/rdkit-cartridge-debian), [Prometheus](https://prometheus.io/img/introduction/overview/) and [Grafana](https://prometheus.io/img/introduction/overview/) (logging and visualisation of metrics), [Minio](https://min.io/img/minio/linux/index.html), [Redis](https://redis.io/img/) services.
 
 ## Standalone
 
@@ -137,7 +197,7 @@ CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--workers"
 
 The following instructions are based on the blog post - https://dev.to/ken_mwaura1/getting-started-monitoring-a-fastapi-app-with-Grafana-and-Prometheus-a-step-by-step-guide-3fbn
 
-To learn more about using Grafana in general, see the official [Prometheus](https://prometheus.io/docs/introduction/overview/) and [Grafana](https://grafana.com/docs/) documentation, or check out our other monitoring tutorials.
+To learn more about using Grafana in general, see the official [Prometheus](https://prometheus.io/img/introduction/overview/) and [Grafana](https://grafana.com/img/) documentation, or check out our other monitoring tutorials.
 
 :::
 
@@ -171,28 +231,28 @@ Grafana login
 Enter the default username and password (admin/admin) and click "Log In". You should be prompted to change the password. Enter a new password and click "Save". You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/grafana_login.jpeg" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana_login.jpeg" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 Grafana home
 
 Click on the "Create your first data source" button. You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/grafana.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 Grafana add the data source
 
 <p align="center">
-  <img align="center" src="/docs/grafana_ds.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana_ds.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 
 Click on the "Prometheus" button. You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/prometheus.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/prometheus.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 Enter the following information:
@@ -211,22 +271,22 @@ TLS CA Certificate: None <br/>
 Click on the "Save & Test" button. You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/grafana_ds_saved.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana_ds_saved.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 Click on the "Dashboards" button. You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/grafana_db.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana_db.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
 Click on the ""New Dashboard" button. You should see the following screen:
 
 <p align="center">
-  <img align="center" src="/docs/grafana_db_new.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
+  <img align="center" src="/img/grafana_db_new.png" alt="Logo" style="filter: drop-shadow(0px 0px 10px rgba(0, 0, 0, 0.5));" width="auto">
 </p>
 
-Download the Cheminformatics Microservice dashboard template (JSON) here - https://github.com/Steinbeck-Lab/cheminformatics-python-microservice/blob/main/cpm-dashboard.json
+Download the NMRKit dashboard template (JSON) here - https://github.com/NFDI4Chem/nmrkit/blob/main/api-dashboard.json
 
 ## Benchmarking / Stress testing
 
@@ -281,7 +341,7 @@ We recommend using flake8 and Black to perform linting and formatting in Python
 2. Linting with flake8: flake8 is a popular Python linter that checks your code for style and potential errors. Run flake8 by executing the following command in your project directory:
 
    ```bash
-   flake8 --ignore E501,W503 $(git ls-files '*.py')
+   flake8 --per-file-ignores="__init__.py:F401" --ignore E402,E501,W503 $(git ls-files '*.py') .
    ```
 
    flake8 will analyze your code and provide feedback on any style violations or issues found.