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MediaCV-NFT is an open-source cloud-native platform for building an NFT Marketplace on top of Algorand blockchain.

Learn more on our official case study.

There are three components involved in the platform. The frontend, the backend, and the smart contracts. The backend and frontend parts of the application have to be deployed to a server. Smart contracts are automatically deployed by the platform when new NFTs are created.

Follow the instructions below to prepare your development environment or to deploy the application to a public server.

To deploy MediaCV-NFT we'll need to create a database, a Kubernetes cluster on the Microsoft Azure, and install several associated tools. This guide assumes that the user has at least some proficiency in using the Microsoft Azure.

• Microsoft Azure SDK
• Docker
• Kubernetes Tools
• Helm
• SQL Database on Microsoft Azure
• Container Registry on Microsoft Azure

1. Initialize your Microsoft Azure SDK by running azure init and following the instructions
2. Go to Kubernetes Engine
3. Click on Create
4. Configure your cluster - for experimenting, we suggest using the Standard cluster with the pre-filled configuration and reduced number of nodes (depending on your budget).

• To reduce the number of nodes go to default-pool, change Number of nodes to 1.

4. Wait for your cluster to be provisioned
5. Click on the Actions button, select Connect and run provided command to connect to your cluster
6. After that you should be able to access your Kubernetes cluster using kubectl command. We suggest reading Overview of kubectl.

The backend folder contains helm folder that contains Helm chart. Helm charts help to manage the complexity of Kubernetes application deployment. Before deploying we'll need to configure our Helm chart and install Kubernetes Nginx Controller

• Inside the values.yaml file, set the host_dns variable to your domain
• Inside the secrets.yaml file, configure:
  • DATABASE_URL - URL to access the database compatible with dj-database-url
  • PURESTAKE_API_KEY - Purestake API Key
  • GOOGLE_CREDENTIALS - Credentials for Google Service Account encoded in base64

1. Connect your Docker to your Container Registry on Microsoft Azure- https://cloud.google.com/container-registry/docs/advanced-authentication
2. Create Kubernetes namespace using kubectl create namespace <insert-namespace-name-here>
3. Switch to that namespace using kubectl config set-context --current --namespace=<insert-namespace-name-here>
4. Run make image && make push && make deploy
5. Check if the containers are running using kubectl get pods
6. Switch to nginx-ingress Kubernetes namespace and get the IP number of the Nginx server using kubectl get services
7. Create a Load Balancer that points to that Nginx server

For deploying the frontend we suggest Vercel.com which can be connected to a Github repository and takes care of the deployment for you.

1. Go to the admin panel in the backend part of the application
2. Click on Users in the API section of the admin panel
3. Click on Add user
4. Enter your Algorand address and select Is Staff
5. Click on Save
6. Visit the frontend part of the application
7. Connect with your wallet
8. Click on the arrow next to your address at the top bar
9. Select Create new NFT
10. Proceed according to the instructions displayed on the screen

By default, the project is configured with an SQLite database, which is embedded into the application and doesn't require any separate installation. We'll only RabbitMQ as a message queue for the background worker. For the application to be fully functional we need both a server and a background worker.

Running RabbitMQ with Docker:

1. Install and run Docker
2. Run docker run -d -p 5672:5672 rabbitmq:3 - this will run RabbitMQ in the background and forward the 5672 port to your computer.

Manual installation:

1. Download, install and run RabbitMQ
2. By default, RabbitMQ will listen on port 5672 on all available interfaces. Refer to https://www.rabbitmq.com/networking.html if you want to customize your configuration.

By default, MediaCV-NFT is configured to connect to RabbitMQ hosted on localhost at port 5672. If you want to change it you can set the CELERY_BROKER_URL variable in your command-line environment or inside the backend/settings_dev.py file.

Example value of CELERY_BROKER_URL: amqp://guest:guest@localhost:5672//

For more information refer to Broker Settings section of Celery documentation.

Alternatively, you can install RabbitMQ yourself and configure it to accept connections on port 5672.

You can set the configuration variables both in your shell environment or backend/settings_dev.py file.

PURESTAKE_API_KEY should to be equal to your Purestake API key. USE_TESTNET should be equal to 0 if you want to use MainNet infrastructure.

1. Install Python 3.9 and Poetry
2. Go to backend folder
3. Run poetry install to install the dependencies and poetry shell to start using a virtual environment which contains those dependencies
4. Migrate the database using python manage.py migrate command
5. Create admin account using python manage.py createsuperuser command, following the instructions on the screen.
6. Run the development server with python manage.py runserver
7. You can access the admin panel at http://localhost:8000/admin/

1. Follow the section above to install the dependencies and run poetry shell inside backend folder.
2. Run DJANGO_SETTINGS_MODULE=nft_market.settings_dev celery -A nft_market.celery worker --loglevel=DEBUG and keep it running alongside the development server to test the application

The frontend configuration can be found in /frontend/src/config/index.js. It contains the following variables:

• ALGORAND_LEDGER - determines the infrastructure that we want to use. Can be MainNet or TestNet.
• USDC_ID - Identifier of Algorand Standard Asset which is going to be used as a stablecoin
• USDC_DECIMAL_POINTS - the amount of decimal points for that asset
• BACKEND_URL - URL of the backend part of the application. By default, it is http://localhost:8000 for the development environment and https://nft-be.ulam.io for the production environment.

It is necessary to run a contract development environment only if you want to introduce changes to it.

• You'll need to download the algorand-builder repository and link the algob and runtime packages. The latest tested commit for algorand-builder is 0cf0f338230521197079e292a4963e814fa574f2.
  • To link the algorand-builder you need to build it using yarn build
  • Issue yarn link command in those folders: packages/algob, packages/runtime
  • Run yarn link "@algorand-builder/algob" and yarn link "@algorand-builder/runtime" in the contract directory
• To install the rest of the dependencies run:
  • poetry install
  • yarn install

Commands should be run inside the poetry shell.

Here are some useful commands:

• yarn test - running tests
• yarn algob compile - contract compilation
• yarn deploy - contract deployment (requires configuring algob.config.js and setting ASA identifiers in scripts/deploy.js)

Algorand has a debugging tool called tealdbg which allows real-time debugging of the contract execution. To debug a transaction you need to supply a teal file with the contract and a dry-run of the transaction:

• tealdbg debug state.teal --dryrun-req tx.dr - tealdbg will provide you with an address that you can enter in your browser to run the debugger

Dry-run can be obtained with the goal command-line tool when issuing a transaction:

• goal app call --app-id {appid} --from {ACCOUNT} --out=dumptx.dr --dryrun-dump

Dry-run can be also extracted from the user interface:

• First, you need to extract the transaction which is sent to the Algorand node by the frontend part of the application
• Then you need to convert it from base64 to binary form and save it to a file
  • You can use base64 -d to convert the base64 text to a binary form in the *nix command-line
• At last, you need to convert the binary form to dry-run using goal clerk dryrun -t tx.bin --dryrun-dump -o tx.dr