search

src/ai.rs

@@ -234,6 +234,7 @@ impl EmbedStore {
         // TODO : fix search
         // + new ranked algorithm
         // + better repr
+        // limit should cover SearchResults not the query -> rework
 
         let results: Vec<DocEmbedding> = sqlx::query_as(
             "SELECT *, 1 / (1 + (embed_mxbai_embed_large <-> $1)) AS similarity FROM doc_embedding ORDER BY embed_mxbai_embed_large <-> $1 LIMIT $2 OFFSET $3",

src/pages/mod.rs

@@ -236,7 +236,7 @@ pub async fn vector_search(
                     EmbedStore::search_vector(&input, limit as i64, offset as i64).await
                 })
             },
-            50,
+            1500,
         )
         .pager(page as u64, vector)
         .await;