A lightning apps directory made for and by the bitcoin community.
To run the project locally, you need to have Node.Js installed on your machine.
1- Either clone the project or download it as Zip from the github repository.
2- Inside the project folder, open the cmd and run npm install to install all the libraries used by the project.
3- You are ready to start !!!
The client app is built in React + TypeScript. To start the client app on your machine, open the CMD in the project root directory, then you will run one of the commands below:
1- npm run client:prod-server
This will run the application and will use the real backend api to get the data.
2- npm run client:mocks
This will spin up a local mocks server with mock data, so you can use the app offline.
3- npm run client:dev-server
This will assume that you have a local api server running on port 8888, and will connect to it.
In all cases, the application will be running on http://localhost:3000
We are using serverless functions to serve our GraphQl endpoint to the client app.
To run the project locally with your own local Postgres DB, you will need to first put a few env variables in an env file that should be created in /envs/server directory, named local.env
The required variables that needs to be put there are:
NODE_ENV = "development"
DATABASE_PROXY_URL = "YOUR DB CONNECTION STRING"
JWT_SECRET = "SOME RANDOM JWT SECRET"
LNURL_AUTH_HOST = "http://localhost:8888/dev/login"
CLOUDFLARE_IMAGE_ACCOUNT_ID = "FOR UPLOADING IMAGES"
CLOUDFLARE_IMAGE_API_KEY = "FOR UPLOADING IMAGES"
CLOUDFLARE_IMAGE_ACCOUNT_HASH = "FOR UPLOADING IMAGES"
For generating the JWT Secret we recommend using: https://www.grc.com/passwords.htm. Then you need to run the migrations against your database. use the command:
Finally, you can start the serverless functions using the command:
And your functions will be served on http://localhost:8888/dev/graphql
prisma studio
prisma studio runs an UI for the DB
prisma migrate dev
Create a migration from the schema.prisma file
prisma migrate deploy
Apply pending migrations to the database
We have integrated Meilisearch to our backend to provide a better search experience for our users. To run Meilisearch locally, go here. To migrate data to Meilisearch, export your Database Tables, User, Stories, Tags, and Categories to JSON files. Many tools exist to do this but we recommend Beekeeper Studio. Export your data to JSON files into the /tools directory. Install the requirements by doing
python3 -m pip install -r requirements.txt
Then add your environment variables to a .env file in the /tools directory. The required variables are:
MEILISEARCH_HOST=
MEILISEARCH_API_KEY=
Then run the migration script with
python3 migrateMeilisearch.py
If the files are large, this process may take awhile.