Breaking change: remove vector for score details

meilisearch/src/search.rs

@@ -633,10 +633,8 @@ pub fn perform_search(
 
         let mut semantic_score = None;
         for details in &score {
-            if let ScoreDetails::Vector(score_details::Vector {
-                target_vector: _,
-                value_similarity: Some((_matching_vector, similarity)),
-            }) = details
+            if let ScoreDetails::Vector(score_details::Vector { similarity: Some(similarity) }) =
+                details
             {
                 semantic_score = Some(*similarity);
                 break;

milli/src/score_details.rs

@@ -98,9 +98,9 @@ impl ScoreDetails {
             ScoreDetails::ExactWords(e) => RankOrValue::Rank(e.rank()),
             ScoreDetails::Sort(sort) => RankOrValue::Sort(sort),
             ScoreDetails::GeoSort(geosort) => RankOrValue::GeoSort(geosort),
-            ScoreDetails::Vector(vector) => RankOrValue::Score(
-                vector.value_similarity.as_ref().map(|(_, s)| *s as f64).unwrap_or(0.0f64),
-            ),
+            ScoreDetails::Vector(vector) => {
+                RankOrValue::Score(vector.similarity.as_ref().map(|s| *s as f64).unwrap_or(0.0f64))
+            }
             ScoreDetails::Skipped => RankOrValue::Rank(Rank { rank: 0, max_rank: 1 }),
         }
     }
@@ -249,16 +249,13 @@ impl ScoreDetails {
                     order += 1;
                 }
                 ScoreDetails::Vector(s) => {
-                    let vector = format!("vectorSort({:?})", s.target_vector);
-                    let value = s.value_similarity.as_ref().map(|(v, _)| v);
-                    let similarity = s.value_similarity.as_ref().map(|(_, s)| s);
+                    let similarity = s.similarity.as_ref();
 
                     let details = serde_json::json!({
                         "order": order,
-                        "value": value,
                         "similarity": similarity,
                     });
-                    details_map.insert(vector, details);
+                    details_map.insert("vectorSort".into(), details);
                     order += 1;
                 }
                 ScoreDetails::Skipped => {
@@ -494,8 +491,7 @@ impl PartialOrd for GeoSort {
 
 #[derive(Debug, Clone, PartialEq, PartialOrd)]
 pub struct Vector {
-    pub target_vector: Vec<f32>,
-    pub value_similarity: Option<(Vec<f32>, f32)>,
+    pub similarity: Option<f32>,
 }
 
 impl GeoSort {

milli/src/search/new/vector_sort.rs

@@ -12,7 +12,7 @@ pub struct VectorSort<Q: RankingRuleQueryTrait> {
     query: Option<Q>,
     target: Vec<f32>,
     vector_candidates: RoaringBitmap,
-    cached_sorted_docids: std::vec::IntoIter<(DocumentId, f32, Vec<f32>)>,
+    cached_sorted_docids: std::vec::IntoIter<(DocumentId, f32)>,
     limit: usize,
     distribution_shift: Option<DistributionShift>,
     embedder_index: u8,
@@ -70,14 +70,9 @@ impl<Q: RankingRuleQueryTrait> VectorSort<Q> {
         for reader in readers.iter() {
             let nns_by_vector =
                 reader.nns_by_vector(ctx.txn, target, self.limit, None, Some(vector_candidates))?;
-            let vectors: std::result::Result<Vec<_>, _> = nns_by_vector
-                .iter()
-                .map(|(docid, _)| reader.item_vector(ctx.txn, *docid).transpose().unwrap())
-                .collect();
-            let vectors = vectors?;
-            results.extend(nns_by_vector.into_iter().zip(vectors).map(|((x, y), z)| (x, y, z)));
+            results.extend(nns_by_vector.into_iter());
         }
-        results.sort_unstable_by_key(|(_, distance, _)| OrderedFloat(*distance));
+        results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
         self.cached_sorted_docids = results.into_iter();
 
         Ok(())
@@ -118,14 +113,11 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
             return Ok(Some(RankingRuleOutput {
                 query,
                 candidates: universe.clone(),
-                score: ScoreDetails::Vector(score_details::Vector {
-                    target_vector: self.target.clone(),
-                    value_similarity: None,
-                }),
+                score: ScoreDetails::Vector(score_details::Vector { similarity: None }),
             }));
         }
 
-        for (docid, distance, vector) in self.cached_sorted_docids.by_ref() {
+        for (docid, distance) in self.cached_sorted_docids.by_ref() {
             if vector_candidates.contains(docid) {
                 let score = 1.0 - distance;
                 let score = self
@@ -135,10 +127,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
                 return Ok(Some(RankingRuleOutput {
                     query,
                     candidates: RoaringBitmap::from_iter([docid]),
-                    score: ScoreDetails::Vector(score_details::Vector {
-                        target_vector: self.target.clone(),
-                        value_similarity: Some((vector, score)),
-                    }),
+                    score: ScoreDetails::Vector(score_details::Vector { similarity: Some(score) }),
                 }));
             }
         }
@@ -154,10 +143,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
             return Ok(Some(RankingRuleOutput {
                 query,
                 candidates: universe.clone(),
-                score: ScoreDetails::Vector(score_details::Vector {
-                    target_vector: self.target.clone(),
-                    value_similarity: None,
-                }),
+                score: ScoreDetails::Vector(score_details::Vector { similarity: None }),
             }));
         }