It’s been six months since we open sourced Quepid, and it looks like momentum is growing. Since we flipped the switch, we’ve had two minor point releases. We’ve also had our first contributions from non OSC affiliated folks – thank you @moshebla, @cgamesplay, and @synhershko for contributing to the community!
Since July we’ve also had over 200 people sign up on http://app.quepid.com to try their hands at improving their search quality. Many of these have also joined the #quepid channel on Relevance Slack for community support.
Today we released version 6.1.0 of Quepid, the first version that is designed for you to download and install yourself. We decided that we would provide a Docker based deployment process, and there is now an Installation Guide on the project wiki site that walks you through the steps. We’ve even had folks run Quepid on Windows using the Windows Subsystem for Linux + Docker successfully.
If you are upgrading an existing Quepid setup, make sure you migrate your database, so follow the steps in Updating Quepid. Please share your experiences!
There are a number of other release highlights including:
- Improving the documentation via the Quepid Github wiki site, including pages on Community support, Tips for working with Quepid, Troubleshooting tips for Solr and Elasticsearch.
- Now you can embed video and audio files in the search results via
media:, joining the
id:patterns. Makes it easier to build judgment lists for rich media, as your can play the files directly from within the result list.
For the full list you can read about all the changes in the CHANGELOG.
If you’re a Quepid user we’d love to hear about your use case in Relevant Slack – or let us know about features you’d like to see in a future version.
Perhaps you might also like to talk about Quepid or relevance tuning in general – the Call for Papers for our Haystack US conference is still open until February 7th. We expect to start selling tickets in the middle of February.