diff --git a/web/src/views/settings/SearchSettingsView.tsx b/web/src/views/settings/SearchSettingsView.tsx index 904eb980c..ccf3a5629 100644 --- a/web/src/views/settings/SearchSettingsView.tsx +++ b/web/src/views/settings/SearchSettingsView.tsx @@ -125,7 +125,7 @@ export default function SearchSettingsView({ if (changedValue) { addMessage( "search_settings", - `Unsaved search settings changes)`, + `Unsaved search settings changes`, undefined, "search_settings", ); @@ -151,31 +151,37 @@ export default function SearchSettingsView({ Search Settings -
-

- Semantic Search in Frigate allows you to find tracked objects within - your review items using either the image itself, a user-defined text - description, or an automatically generated one. This feature works - by creating embeddings — numerical vector representations — for both - the images and text descriptions of your tracked objects. By - comparing these embeddings, Frigate assesses their similarities to - deliver relevant search results. -

+ + + Semantic Search + +
+
+

+ Semantic Search in Frigate allows you to find tracked objects + within your review items using either the image itself, a + user-defined text description, or an automatically generated one. + This feature works by creating embeddings — numerical vector + representations — for both the images and text descriptions of + your tracked objects. By comparing these embeddings, Frigate + assesses their similarities to deliver relevant search results. +

-
- - Read the documentation - - +
+ + Read the Documentation + + +
- -
+ +
@@ -210,23 +216,24 @@ export default function SearchSettingsView({ />
-
+
-
Model Size
+
Model Size

- Configure the size of the model used for semantic search - embeddings: -

-

- • Configuring the small model employs a quantized - version of the model that uses much less RAM and runs faster - on CPU with a very negligible difference in embedding quality. -

-

- • Configuring the large model employs the full Jina - model and will automatically run on the GPU if applicable. + The size of the model used for semantic search embeddings.

+
    +
  • + Using small employs a quantized version of the + model that uses much less RAM and runs faster on CPU with a + very negligible difference in embedding quality. +
  • +
  • + Using large employs the full Jina model and will + automatically run on the GPU if applicable. +
  • +