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https://github.com/zokradonh/kopano-docker
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32 lines
1.7 KiB
Markdown
32 lines
1.7 KiB
Markdown
# kopano-spamd extras for kopano-docker
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This directory contains a compose file including optional containers to enable learning spam to be used with the [SpamAssassin](https://spamassassin.apache.org/) bayes filter.
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## How to use this compose file?
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1. Add the `spamd-extras.yml` to the `COMPOSE_FILE` variable in your `.env` file.
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Example:
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```bash
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COMPOSE_FILE=docker-compose.yml:docker-compose.ports.yml:spamd-extras/spamd-extras.yml
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```
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2. Run `docker-compose up -d`.
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## kopano-spamd
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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.
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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.
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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
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automatically. You can check the docker logs of the scheduler for the results of each run.
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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.
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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
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by selecting mails and using the `Export as` function to create a zip file of those mails and put them into the appropriate folder.
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Read more about how to create effective training data here: https://spamassassin.apache.org/full/3.4.x/doc/sa-learn.html#EFFECTIVE-TRAINING
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