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mirror of https://github.com/zokradonh/kopano-docker synced 2025-06-05 23:16:12 +00:00
René Plötz 5617325d8e
Extract spamd-extras into separate extras and add documentation (#482)
Signed-off-by: René Plötz <reneploetz@users.noreply.github.com>
2021-06-22 13:42:55 +02:00
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kopano-spamd extras for kopano-docker

This directory contains a compose file including optional containers to enable learning spam to be used with the SpamAssassin bayes filter.

How to use this compose file?

  1. Add the spamd-extras.yml to the COMPOSE_FILE variable in your .env file.

Example:

COMPOSE_FILE=docker-compose.yml:docker-compose.ports.yml:spamd-extras/spamd-extras.yml
  1. Run docker-compose up -d.

kopano-spamd

After startup there will be a new service kopano-spamd which will persist mails that are moved to Junk to a folder named spam inside the kopanospamd volume. Likewise mails that are moved from the Junk back to Inbox are persisted in ham. Both folders indicate mails that should be trained as either being ham or spam.

The kopano-scheduler container is extended to run the training inside the mail docker container at about 4am with training results being picked up by SpamAssassin automatically. You can check the docker logs of the scheduler for the results of each run.

While already trained files can be deleted immediately after each training run, there is no cleanup provided here. The kopanospamd volume will therefore grow over time.

For the bayes filter to start working you will need to train at least 200 mails of each ham and spam. To create a set of initial data you can use the Kopano WebApp by selecting mails and using the Export as function to create a zip file of those mails and put them into the appropriate folder.

Read more about how to create effective training data here: https://spamassassin.apache.org/full/3.4.x/doc/sa-learn.html#EFFECTIVE-TRAINING