Companion Cube is a Discord bot built on top of DSharpPlus library. It was primarily designed to replace Abalware™ but has since evolved to fulfill other functions.

Originally the base for Music Turret "fork", it has since received several feature backports, which greatly modernised its codebase.

More information is available on its documentation page.

In order to run the bot you will need to have the following components installed and available on your system:

• .NET Core 3.x runtime or better
• Python 3.6 or better
• Java 8 or better
• PostgreSQL server 9.6 or better
• Lavalink

The bot was designed for UNIX-like environments, and is not guaranteed to work under Windows.

The bot requires that you have .NET Core 3.0 SDK, and preferably Visual Studio 2019 installed and available on your system.

The required NuGet configurations are available in solution's root directory, so no further NuGet configuration should be required. Should that happen to not be the case, however, add the following MyGet feed to your NuGet sources: https://nuget.emzi0767.com/api/v3/index.json

Just open the solution and hit build, then publish. This will create a complete bot distribution in bin/Release/netcoreapp3.0/publish/.

Navigate to where the solution is located. From there you need to restore packages, build, and publish:

• dotnet restore
• dotnet build -c Release
• dotnet publish -c Release -f netcoreapp3.0 -r linux-x64

If you have all the required components installed, you need to properly set your environment up before running the bot.

I strongly recommend using Docker or another isolation/containerization solution to contain your bot.

You will need to log in to your PostgreSQL server, and create both a user and a database for the bot's data. This is typically done via psql utility.

After connecting to your database, you will first need to create a user for the bot to authenticate as: create user companion_cube with nocreatedb nocreaterole encrypted password 'hunter2'; Do not forget to substitute the username and password with your own values.

Next step is to create a database for the database for the bot's data: create database companion_cube with owner='companion_cube'; Of course, don't forget to set your own database name, and set the owner to the username you created.

Finally, you need to input the schema into the database. Exit the psql utility and copy the schema files from Database directory to your server. Next up, open up a shell on your server, navigate to where you dropped the SQL files, and execute the following: find . -iname '*.sql' -exec cat "{}" \; | PGPASSWORD="hunter2" psql -U companion_cube -d companion_cube -h localhost This command will load all schema files to your database. Don't forget to set your password, username, database name, and hostname correctly.

Download and extract Lavalink. Copy the lavalink.sh script from this repo's Scripts directory to Lavalink's, then make it executable via chmod +x lavalink.sh.

Then follow the Lavalink's installation instructions, filling the config with proper values.

Open your browser and go to Google Developer Console. There, create a new project.

Once the project is created, go to its dashboard, and from there to API library. Find YouTube Data API v3, and enable it.

When you enable the API, go to Credentials tab, and press Create Credentials. Select API key as type. Copy the created API key and save it for later.

You can optionally give it a name and restrict its usage.

Go to Discord Developers page and create a new app for the bot. Give it a name and an icon, and press Save Changes. When changes are saved, go to Bot tab, and press Add Bot. Give the bot a username and avatar, and uncheck the Public Bot checkbox, then press Save Changes.

Once changes are saved, press the Copy button under the token. Save the token for later.

Copy all the files from your bot's publish directory to your target directory. Nextup, copy the bot.sh script from the repo's Scripts directory to the same place as your bot, and make it executable via chmod +x bot.sh.

Copy config.json.example from this repository to where the bot files are, and open it in your text editor.

Go to discord section, and paste the Discord API token from step 4 into the token field. You can optionally configure other options here.

Once that's done, go to postgres section. Enter your PostgreSQL server data and database credentials. If your PostgreSQL server runs with SSL/TLS disabled, set encrypt to false.

Next, go to lavalink section, and enter your Lavalink connection details and the password you set when setting up Lavalink.

Finally, go to youtube section, and paste the API key you obtained in step 3.

When all is done, press save.

Download the Unicode database and Unihan database. Extract UnicodeData.txt and Blocks.txt from the first file, and Unihan_Readings.txt from the second. Place the extracted files in Tools directory.

Next up, run the mkjsondata.py script from Tools (it requires Python 3). Once the script is done working, copy the resulting unicode_data.json.gz file to bot's directory.

Using your favourite container software or container multiplexer, start Lavalink by running the autorestart script: ./lavalink.sh. Detach from the multiplexer.

Like above, using a multiplexer or a container, run the bot by doing ./bot.sh. If everything works correctly, congratulations. If not, follow the instructions more carefully.

Lots of effort went into making this bot, and sometimes even related software.

If you feel like I'm doing a good job, or just want to throw money at me, you can do so through any of the following:

• Patreon
• PayPal

If you have other questions or would like to talk in general, feel free to visit my Discord server.