botiana is a bot for slack. She does things.

Follow these directions from slack. Be sure to configure a default icon.

Botiana is intended to run in a container. But, make your own choice, this isn't Soviet Russia. Commits should be emojified using https://gitmoji.carloscuesta.me/

Botiana is currently developed and testing using python 3.7 pip install -r requirements.txt

The settings file has a few defaults you may need to customize.

• You may set your token here, or via the environment
• If you insist, you can change the bot's name, or set it via the environment
• Set your desired level of logs
• Configure the commands you wish to enable from legacy_modules

Several other items can be configured by setting environment variables:

• 'icon_poolball' uri for eight_ball command
• 'icon_wiki' uri for wiki command

more are available, consult legacy_modules.py.

Botiana loads local data from a yaml file: data/data.yaml

If you're running the bot in kubernetes or in docker you can mount your file from a ConfigMap or a volume mount.

docker run -v "/path/to/my/data.yaml":"/usr/local/botiana/data/data.yaml" -e token=$token botiana

Keywords, responses and reactions can occur in specific channels, or all channels. Configure this in the data.yaml file.

Local dictionary entries can be created for lookup. Configure this in the data.yaml file.

If you would like to route spurios statements including the bot name to a service like Wolfram Alpha or Cleverbot, add the following config to your settings.py (following assumes wolfram alpha). Note, the message_processing_module must match the name of the local module you create for this feature.

enable_message_processing = True message_processing_module = 'wolfram'

You will likely also want to add settings for your custom local module that will handle the command parsing / api call to the service

# Wolfram Alpha API token wa_token = os.getenv('wa_token', '')

1. All custom commands must start with a letter, not underscores, as the bot rejects underscore commands.
2. You must define an array local_commands = ['tru', 'lunch'] that defines what commands in locallocal_modules.py are actionable by botiana.

If you're running the bot in kubernetes or in docker you can mount your file from a ConfigMap or a volume mount.

docker run -v "/path/to/my/cool_modules.py":"/usr/local/botiana/local_modules.py" -e token=$token botiana

docker build . -t botiana

Get your token from the slack api and export it as shown and run with docker.

export token="xoxb-11111111111-111111111111-aaa1aAAAAAaaaAAaAAAAaa1a"
docker build . -t botiana;docker run  -e token=$token botiana