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* First draft of the Food Discovery demo article * Convert icon to white * Add "Positive and negative feedback" paragraph * Put a note on using cosine distance * Add a picture after the first paragraph * Crop the image * Apply suggestions from code review Co-authored-by: David Myriel <davidmyriel@gmail.com> * Apply changes requested in review * Add architecture diagram * Add CLIP model diagram * Add negated vector * Add recommendation code sample * Add random points image * Change random results image * Add link to Qdrant Cloud * Move recommendation results image to top * Add another link to repo and Discord * Change negated vector image * Adapt cosine distance description * Add link to online demo * Update diagrams * Apply suggestions from code review Co-authored-by: David Myriel <davidmyriel@gmail.com> * Add link to docs about importing a snapshot * Change social preview image * Change social preview image * Adapt weights * Add new food discovery demo to "Use cases" --------- Co-authored-by: David Myriel <davidmyriel@gmail.com>
431 B
431 B
title, weight, icon, sitemapExclude
| title | weight | icon | sitemapExclude |
|---|---|---|---|
| Food Discovery | 20 | search | True |
There are multiple ways to discover things, text search is not the only one. In the case of food, people rely more on appearance than description and ingredients. So why not let people choose their next lunch by its appearance, even if they don't know the name of the dish? We made a demo to showcase this approach.