TMP: check windows free disk space

.github/workflows/test-suite.yml

@@ -56,6 +56,12 @@ jobs:
       matrix:
         os: [macos-12, windows-2022]
     steps:
+      - name: Check free disk space on C
+        run: |
+          fsutil volume diskfree c:
+      - name: Check free disk space on D
+        run: |
+          fsutil volume diskfree d:
       - uses: actions/checkout@v3
       - name: Cache dependencies
         uses: Swatinem/rust-cache@v2.7.1
@@ -63,11 +69,23 @@ jobs:
         with:
           toolchain: stable
           override: true
+      - name: Check free disk space on C
+        run: |
+          fsutil volume diskfree c:
+      - name: Check free disk space on D
+        run: |
+          fsutil volume diskfree d:
       - name: Run cargo check without any default features
         uses: actions-rs/cargo@v1
         with:
           command: build
           args: --locked --release --no-default-features --all
+      - name: Check free disk space on C
+        run: |
+          fsutil volume diskfree c:
+      - name: Check free disk space on D
+        run: |
+          fsutil volume diskfree d:
       - name: Run cargo test
         uses: actions-rs/cargo@v1
         with:
@@ -116,7 +134,7 @@ jobs:
           override: true
       - name: Run cargo tree without default features and check lindera is not present
         run: |
-          if cargo tree -f '{p} {f}' -e normal --no-default-features | grep -qz lindera; then
+          if cargo tree -f '{p} {f}' -e normal --no-default-features | grep -vqz lindera; then
             echo "lindera has been found in the sources and it shouldn't"
             exit 1
           fi

Cargo.toml

@@ -22,7 +22,7 @@ members = [
 ]
 
 [workspace.package]
-version = "1.9.0"
+version = "1.8.0"
 authors = [
     "Quentin de Quelen <quentin@dequelen.me>",
     "Clément Renault <clement@meilisearch.com>",

README.md

@@ -25,7 +25,7 @@
 
 <p align="center">⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍</p>
 
-[Meilisearch](https://www.meilisearch.com) helps you shape a delightful search experience in a snap, offering features that work out of the box to speed up your workflow.
+Meilisearch helps you shape a delightful search experience in a snap, offering features that work out-of-the-box to speed up your workflow.
 
 <p align="center" name="demo">
   <a href="https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-gif#gh-light-mode-only" target="_blank">
@@ -39,8 +39,8 @@
 🔥 [**Try it!**](https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-link) 🔥
 
 ## ✨ Features
-- **Hybrid search:** Combine the best of both [semantic](https://www.meilisearch.com/docs/learn/experimental/vector_search) & full-text search to get the most relevant results
+
-- **Search-as-you-type:** find & display results in less than 50 milliseconds to provide an intuitive experience
+- **Search-as-you-type:** find search results in less than 50 milliseconds
 - **[Typo tolerance](https://www.meilisearch.com/docs/learn/configuration/typo_tolerance?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** get relevant matches even when queries contain typos and misspellings
 - **[Filtering](https://www.meilisearch.com/docs/learn/fine_tuning_results/filtering?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features) and [faceted search](https://www.meilisearch.com/docs/learn/fine_tuning_results/faceted_search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** enhance your users' search experience with custom filters and build a faceted search interface in a few lines of code
 - **[Sorting](https://www.meilisearch.com/docs/learn/fine_tuning_results/sorting?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** sort results based on price, date, or pretty much anything else your users need
@@ -55,15 +55,15 @@
 
 ## 📖 Documentation
 
-You can consult Meilisearch's documentation at [meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
+You can consult Meilisearch's documentation at [https://www.meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
 
 ## 🚀 Getting started
 
 For basic instructions on how to set up Meilisearch, add documents to an index, and search for documents, take a look at our [Quick Start](https://www.meilisearch.com/docs/learn/getting_started/quick_start?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=get-started) guide.
 
-## 🌍 Supercharge your Meilisearch experience
+## ⚡ Supercharge your Meilisearch experience
 
-Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). Additional features include analytics & monitoring in many regions around the world. No credit card is required.
+Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). No credit card required.
 
 ## 🧰 SDKs & integration tools
 
@@ -85,13 +85,13 @@ Finally, for more in-depth information, refer to our articles explaining fundame
 
 Meilisearch collects **anonymized** data from users to help us improve our product. You can [deactivate this](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) whenever you want.
 
-To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Remember to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
+To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Don't forget to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
 
 If you want to know more about the kind of data we collect and what we use it for, check the [telemetry section](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) of our documentation.
 
 ## 📫 Get in touch!
 
-Meilisearch is a search engine created by [Meili]([https://www.welcometothejungle.com/en/companies/meilisearch](https://www.meilisearch.com/careers)), a software development company headquartered in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
+Meilisearch is a search engine created by [Meili](https://www.welcometothejungle.com/en/companies/meilisearch), a software development company based in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
 
 🗞 [Subscribe to our newsletter](https://meilisearch.us2.list-manage.com/subscribe?u=27870f7b71c908a8b359599fb&id=79582d828e) if you don't want to miss any updates! We promise we won't clutter your mailbox: we only send one edition every two months.
 

dump/src/reader/snapshots/dump__reader__test__import_dump_v6_with_vectors-6.snap

@@ -780,7 +780,7 @@ expression: document
           1.3484878540039063
         ]
       ],
-      "regenerate": true
+      "userProvided": false
     }
   }
 }

dump/src/reader/snapshots/dump__reader__test__import_dump_v6_with_vectors-7.snap

@@ -779,7 +779,7 @@ expression: document
           1.04031240940094
         ]
       ],
-      "regenerate": true
+      "userProvided": false
     }
   }
 }

dump/src/reader/v3/settings.rs

@@ -152,7 +152,6 @@ impl Settings<Unchecked> {
 }
 
 #[derive(Debug, Clone, Deserialize)]
-#[allow(dead_code)] // otherwise rustc complains that the fields go unused
 #[cfg_attr(test, derive(serde::Serialize))]
 #[serde(deny_unknown_fields)]
 #[serde(rename_all = "camelCase")]

dump/src/reader/v4/settings.rs

@@ -182,7 +182,6 @@ impl Settings<Unchecked> {
     }
 }
 
-#[allow(dead_code)] // otherwise rustc complains that the fields go unused
 #[derive(Debug, Clone, Deserialize)]
 #[cfg_attr(test, derive(serde::Serialize))]
 #[serde(deny_unknown_fields)]

dump/src/reader/v5/tasks.rs

@@ -200,7 +200,6 @@ impl std::ops::Deref for IndexUid {
     }
 }
 
-#[allow(dead_code)] // otherwise rustc complains that the fields go unused
 #[derive(Debug)]
 #[cfg_attr(test, derive(serde::Serialize))]
 #[cfg_attr(test, serde(rename_all = "camelCase"))]

index-scheduler/Cargo.toml

@@ -40,9 +40,7 @@ ureq = "2.9.7"
 uuid = { version = "1.6.1", features = ["serde", "v4"] }
 
 [dev-dependencies]
-arroy = "0.4.0"
 big_s = "1.0.2"
 crossbeam = "0.8.4"
 insta = { version = "1.34.0", features = ["json", "redactions"] }
-maplit = "1.0.2"
 meili-snap = { path = "../meili-snap" }

index-scheduler/src/batch.rs

@@ -909,7 +909,6 @@ impl IndexScheduler {
 
                     let fields_ids_map = index.fields_ids_map(&rtxn)?;
                     let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
-                    let embedding_configs = index.embedding_configs(&rtxn)?;
 
                     // 3.1. Dump the documents
                     for ret in index.all_documents(&rtxn)? {
@@ -952,21 +951,16 @@ impl IndexScheduler {
                             };
 
                             for (embedder_name, embeddings) in embeddings {
-                                let user_provided = embedding_configs
+                                // don't change the entry if it already exists, because it was user-provided
-                                    .iter()
+                                vectors.entry(embedder_name).or_insert_with(|| {
-                                    .find(|conf| conf.name == embedder_name)
+                                    let embeddings = ExplicitVectors {
-                                    .is_some_and(|conf| conf.user_provided.contains(id));
+                                        embeddings: VectorOrArrayOfVectors::from_array_of_vectors(
-
+                                            embeddings,
-                                let embeddings = ExplicitVectors {
+                                        ),
-                                    embeddings: Some(
+                                        user_provided: false,
-                                        VectorOrArrayOfVectors::from_array_of_vectors(embeddings),
+                                    };
-                                    ),
+                                    serde_json::to_value(embeddings).unwrap()
-                                    regenerate: !user_provided,
+                                });
-                                };
-                                vectors.insert(
-                                    embedder_name,
-                                    serde_json::to_value(embeddings).unwrap(),
-                                );
                             }
                         }
 

index-scheduler/src/lib.rs

@@ -53,7 +53,6 @@ use meilisearch_types::heed::byteorder::BE;
 use meilisearch_types::heed::types::{SerdeBincode, SerdeJson, Str, I128};
 use meilisearch_types::heed::{self, Database, Env, PutFlags, RoTxn, RwTxn};
 use meilisearch_types::milli::documents::DocumentsBatchBuilder;
-use meilisearch_types::milli::index::IndexEmbeddingConfig;
 use meilisearch_types::milli::update::IndexerConfig;
 use meilisearch_types::milli::vector::{Embedder, EmbedderOptions, EmbeddingConfigs};
 use meilisearch_types::milli::{self, CboRoaringBitmapCodec, Index, RoaringBitmapCodec, BEU32};
@@ -1460,39 +1459,33 @@ impl IndexScheduler {
     // TODO: consider using a type alias or a struct embedder/template
     pub fn embedders(
         &self,
-        embedding_configs: Vec<IndexEmbeddingConfig>,
+        embedding_configs: Vec<(String, milli::vector::EmbeddingConfig)>,
     ) -> Result<EmbeddingConfigs> {
         let res: Result<_> = embedding_configs
             .into_iter()
-            .map(
+            .map(|(name, milli::vector::EmbeddingConfig { embedder_options, prompt })| {
-                |IndexEmbeddingConfig {
+                let prompt =
-                     name,
+                    Arc::new(prompt.try_into().map_err(meilisearch_types::milli::Error::from)?);
-                     config: milli::vector::EmbeddingConfig { embedder_options, prompt },
+                // optimistically return existing embedder
-                     ..
+                {
-                 }| {
+                    let embedders = self.embedders.read().unwrap();
-                    let prompt =
+                    if let Some(embedder) = embedders.get(&embedder_options) {
-                        Arc::new(prompt.try_into().map_err(meilisearch_types::milli::Error::from)?);
+                        return Ok((name, (embedder.clone(), prompt)));
-                    // optimistically return existing embedder
-                    {
-                        let embedders = self.embedders.read().unwrap();
-                        if let Some(embedder) = embedders.get(&embedder_options) {
-                            return Ok((name, (embedder.clone(), prompt)));
-                        }
                     }
+                }
 
-                    // add missing embedder
+                // add missing embedder
-                    let embedder = Arc::new(
+                let embedder = Arc::new(
-                        Embedder::new(embedder_options.clone())
+                    Embedder::new(embedder_options.clone())
-                            .map_err(meilisearch_types::milli::vector::Error::from)
+                        .map_err(meilisearch_types::milli::vector::Error::from)
-                            .map_err(meilisearch_types::milli::Error::from)?,
+                        .map_err(meilisearch_types::milli::Error::from)?,
-                    );
+                );
-                    {
+                {
-                        let mut embedders = self.embedders.write().unwrap();
+                    let mut embedders = self.embedders.write().unwrap();
-                        embedders.insert(embedder_options, embedder.clone());
+                    embedders.insert(embedder_options, embedder.clone());
-                    }
+                }
-                    Ok((name, (embedder, prompt)))
+                Ok((name, (embedder, prompt)))
-                },
+            })
-            )
             .collect();
         res.map(EmbeddingConfigs::new)
     }
@@ -1755,9 +1748,6 @@ mod tests {
     use meilisearch_types::milli::update::IndexDocumentsMethod::{
         ReplaceDocuments, UpdateDocuments,
     };
-    use meilisearch_types::milli::update::Setting;
-    use meilisearch_types::milli::vector::settings::EmbeddingSettings;
-    use meilisearch_types::settings::Unchecked;
     use meilisearch_types::tasks::IndexSwap;
     use meilisearch_types::VERSION_FILE_NAME;
     use tempfile::{NamedTempFile, TempDir};
@@ -1836,7 +1826,6 @@ mod tests {
             assert_eq!(breakpoint, (Init, false));
             let index_scheduler_handle = IndexSchedulerHandle {
                 _tempdir: tempdir,
-                index_scheduler: index_scheduler.private_clone(),
                 test_breakpoint_rcv: receiver,
                 last_breakpoint: breakpoint.0,
             };
@@ -1925,7 +1914,6 @@ mod tests {
 
     pub struct IndexSchedulerHandle {
         _tempdir: TempDir,
-        index_scheduler: IndexScheduler,
         test_breakpoint_rcv: crossbeam::channel::Receiver<(Breakpoint, bool)>,
         last_breakpoint: Breakpoint,
     }
@@ -1943,13 +1931,9 @@ mod tests {
             {
                 Ok(b) => b,
                 Err(RecvTimeoutError::Timeout) => {
-                    let state = snapshot_index_scheduler(&self.index_scheduler);
+                    panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.")
-                    panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.\n{state}")
-                }
-                Err(RecvTimeoutError::Disconnected) => {
-                    let state = snapshot_index_scheduler(&self.index_scheduler);
-                    panic!("The scheduler crashed.\n{state}")
                 }
+                Err(RecvTimeoutError::Disconnected) => panic!("The scheduler crashed."),
             };
             // if we've already encountered a breakpoint we're supposed to be stuck on the false
             // and we expect the same variant with the true to come now.
@@ -1968,13 +1952,9 @@ mod tests {
             {
                 Ok(b) => b,
                 Err(RecvTimeoutError::Timeout) => {
-                    let state = snapshot_index_scheduler(&self.index_scheduler);
+                    panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.")
-                    panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.\n{state}")
-                }
-                Err(RecvTimeoutError::Disconnected) => {
-                    let state = snapshot_index_scheduler(&self.index_scheduler);
-                    panic!("The scheduler crashed.\n{state}")
                 }
+                Err(RecvTimeoutError::Disconnected) => panic!("The scheduler crashed."),
             };
             assert!(!b, "Found the breakpoint handle in a bad state. Check your test suite");
 
@@ -1988,10 +1968,9 @@ mod tests {
         fn advance_till(&mut self, breakpoints: impl IntoIterator<Item = Breakpoint>) {
             for breakpoint in breakpoints {
                 let b = self.advance();
-                let state = snapshot_index_scheduler(&self.index_scheduler);
                 assert_eq!(
                     b, breakpoint,
-                    "Was expecting the breakpoint `{:?}` but instead got `{:?}`.\n{state}",
+                    "Was expecting the breakpoint `{:?}` but instead got `{:?}`.",
                     breakpoint, b
                 );
             }
@@ -2016,7 +1995,6 @@ mod tests {
         // Wait for one successful batch.
         #[track_caller]
         fn advance_one_successful_batch(&mut self) {
-            self.index_scheduler.assert_internally_consistent();
             self.advance_till([Start, BatchCreated]);
             loop {
                 match self.advance() {
@@ -2025,17 +2003,13 @@ mod tests {
                     InsideProcessBatch => (),
                     // the batch went successfully, we can stop the loop and go on with the next states.
                     ProcessBatchSucceeded => break,
-                    AbortedIndexation => panic!("The batch was aborted.\n{}", snapshot_index_scheduler(&self.index_scheduler)),
+                    AbortedIndexation => panic!("The batch was aborted."),
-                    ProcessBatchFailed => {
+                    ProcessBatchFailed => panic!("The batch failed."),
-                        while self.advance() != Start {}
-                        panic!("The batch failed.\n{}", snapshot_index_scheduler(&self.index_scheduler))
-                    },
                     breakpoint => panic!("Encountered an impossible breakpoint `{:?}`, this is probably an issue with the test suite.", breakpoint),
                 }
             }
 
             self.advance_till([AfterProcessing]);
-            self.index_scheduler.assert_internally_consistent();
         }
 
         // Wait for one failed batch.
@@ -2049,8 +2023,8 @@ mod tests {
                     InsideProcessBatch => (),
                     // the batch went failed, we can stop the loop and go on with the next states.
                     ProcessBatchFailed => break,
-                    ProcessBatchSucceeded => panic!("The batch succeeded. (and it wasn't supposed to sorry)\n{}", snapshot_index_scheduler(&self.index_scheduler)),
+                    ProcessBatchSucceeded => panic!("The batch succeeded. (and it wasn't supposed to sorry)"),
-                    AbortedIndexation => panic!("The batch was aborted.\n{}", snapshot_index_scheduler(&self.index_scheduler)),
+                    AbortedIndexation => panic!("The batch was aborted."),
                     breakpoint => panic!("Encountered an impossible breakpoint `{:?}`, this is probably an issue with the test suite.", breakpoint),
                 }
             }
@@ -3078,10 +3052,8 @@ mod tests {
         let rtxn = index.read_txn().unwrap();
 
         let configs = index.embedding_configs(&rtxn).unwrap();
-        let IndexEmbeddingConfig { name, config, user_provided } = configs.first().unwrap();
+        let (_, embedding_config) = configs.first().unwrap();
-        insta::assert_snapshot!(name, @"default");
+        insta::assert_json_snapshot!(embedding_config.embedder_options);
-        insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[]>");
-        insta::assert_json_snapshot!(config.embedder_options);
     }
 
     #[test]
@@ -5017,6 +4989,7 @@ mod tests {
                 false,
             )
             .unwrap();
+        index_scheduler.assert_internally_consistent();
 
         snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after_registering_settings_task_vectors");
 
@@ -5027,7 +5000,7 @@ mod tests {
             insta::assert_json_snapshot!(task.details);
         }
 
-        handle.advance_one_successful_batch();
+        handle.advance_n_successful_batches(1);
         snapshot!(snapshot_index_scheduler(&index_scheduler), name: "settings_update_processed_vectors");
 
         {
@@ -5044,17 +5017,13 @@ mod tests {
             let configs = index.embedding_configs(&rtxn).unwrap();
             // for consistency with the below
             #[allow(clippy::get_first)]
-            let IndexEmbeddingConfig { name, config: fakerest_config, user_provided } =
+            let (name, fakerest_config) = configs.get(0).unwrap();
-                configs.get(0).unwrap();
+            insta::assert_json_snapshot!(name, @r###""A_fakerest""###);
-            insta::assert_snapshot!(name, @"A_fakerest");
-            insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[]>");
             insta::assert_json_snapshot!(fakerest_config.embedder_options);
             let fakerest_name = name.clone();
 
-            let IndexEmbeddingConfig { name, config: simple_hf_config, user_provided } =
+            let (name, simple_hf_config) = configs.get(1).unwrap();
-                configs.get(1).unwrap();
+            insta::assert_json_snapshot!(name, @r###""B_small_hf""###);
-            insta::assert_snapshot!(name, @"B_small_hf");
-            insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[]>");
             insta::assert_json_snapshot!(simple_hf_config.embedder_options);
             let simple_hf_name = name.clone();
 
@@ -5069,25 +5038,25 @@ mod tests {
         // add one doc, specifying vectors
 
         let doc = serde_json::json!(
-            {
+                    {
-                "id": 0,
+                        "id": 0,
-                "doggo": "Intel",
+                        "doggo": "Intel",
-                "breed": "beagle",
+                        "breed": "beagle",
-                "_vectors": {
+                        "_vectors": {
-                    &fakerest_name: {
+                            &fakerest_name: {
-                        // this will never trigger regeneration, which is good because we can't actually generate with
+                                // this will never trigger regeneration, which is good because we can't actually generate with
-                        // this embedder
+                                // this embedder
-                        "regenerate": false,
+                                "userProvided": true,
-                        "embeddings": beagle_embed,
+                                "embeddings": beagle_embed,
-                    },
+                            },
-                    &simple_hf_name: {
+                            &simple_hf_name: {
-                        // this will be regenerated on updates
+                                // this will be regenerated on updates
-                        "regenerate": true,
+                                "userProvided": false,
-                        "embeddings": lab_embed,
+                                "embeddings": lab_embed,
-                    },
+                            },
-                    "noise": [0.1, 0.2, 0.3]
+                            "noise": [0.1, 0.2, 0.3]
-                }
+                        }
-            }
+                    }
         );
 
         let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0u128).unwrap();
@@ -5109,6 +5078,7 @@ mod tests {
                 false,
             )
             .unwrap();
+        index_scheduler.assert_internally_consistent();
 
         snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after adding Intel");
 
@@ -5121,19 +5091,6 @@ mod tests {
             let index = index_scheduler.index("doggos").unwrap();
             let rtxn = index.read_txn().unwrap();
 
-            // Ensure the document have been inserted into the relevant bitamp
-            let configs = index.embedding_configs(&rtxn).unwrap();
-            // for consistency with the below
-            #[allow(clippy::get_first)]
-            let IndexEmbeddingConfig { name, config: _, user_provided: user_defined } =
-                configs.get(0).unwrap();
-            insta::assert_snapshot!(name, @"A_fakerest");
-            insta::assert_debug_snapshot!(user_defined, @"RoaringBitmap<[0]>");
-
-            let IndexEmbeddingConfig { name, config: _, user_provided } = configs.get(1).unwrap();
-            insta::assert_snapshot!(name, @"B_small_hf");
-            insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[]>");
-
             let embeddings = index.embeddings(&rtxn, 0).unwrap();
 
             assert_json_snapshot!(embeddings[&simple_hf_name][0] == lab_embed, @"true");
@@ -5183,6 +5140,7 @@ mod tests {
                 false,
             )
             .unwrap();
+        index_scheduler.assert_internally_consistent();
 
         snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir");
 
@@ -5195,25 +5153,11 @@ mod tests {
                 let index = index_scheduler.index("doggos").unwrap();
                 let rtxn = index.read_txn().unwrap();
 
-                // Ensure the document have been inserted into the relevant bitamp
-                let configs = index.embedding_configs(&rtxn).unwrap();
-                // for consistency with the below
-                #[allow(clippy::get_first)]
-                let IndexEmbeddingConfig { name, config: _, user_provided: user_defined } =
-                    configs.get(0).unwrap();
-                insta::assert_snapshot!(name, @"A_fakerest");
-                insta::assert_debug_snapshot!(user_defined, @"RoaringBitmap<[0]>");
-
-                let IndexEmbeddingConfig { name, config: _, user_provided } =
-                    configs.get(1).unwrap();
-                insta::assert_snapshot!(name, @"B_small_hf");
-                insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[]>");
-
                 let embeddings = index.embeddings(&rtxn, 0).unwrap();
 
-                // automatically changed to patou because set to regenerate
+                // automatically changed to patou
                 assert_json_snapshot!(embeddings[&simple_hf_name][0] == patou_embed, @"true");
-                // remained beagle
+                // remained beagle because set to userProvided
                 assert_json_snapshot!(embeddings[&fakerest_name][0] == beagle_embed, @"true");
 
                 let doc = index.documents(&rtxn, std::iter::once(0)).unwrap()[0].1;
@@ -5232,578 +5176,4 @@ mod tests {
             }
         }
     }
-
-    #[test]
-    fn import_vectors_first_and_embedder_later() {
-        let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
-
-        let content = serde_json::json!(
-            [
-                {
-                    "id": 0,
-                    "doggo": "kefir",
-                },
-                {
-                    "id": 1,
-                    "doggo": "intel",
-                    "_vectors": {
-                        "my_doggo_embedder": vec![1; 384],
-                        "unknown embedder": vec![1, 2, 3],
-                    }
-                },
-                {
-                    "id": 2,
-                    "doggo": "max",
-                    "_vectors": {
-                        "my_doggo_embedder": {
-                            "regenerate": false,
-                            "embeddings": vec![2; 384],
-                        },
-                        "unknown embedder": vec![4, 5],
-                    },
-                },
-                {
-                    "id": 3,
-                    "doggo": "marcel",
-                    "_vectors": {
-                        "my_doggo_embedder": {
-                            "regenerate": true,
-                            "embeddings": vec![3; 384],
-                        },
-                    },
-                },
-                {
-                    "id": 4,
-                    "doggo": "sora",
-                    "_vectors": {
-                        "my_doggo_embedder": {
-                            "regenerate": true,
-                        },
-                    },
-                },
-            ]
-        );
-
-        let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0_u128).unwrap();
-        let documents_count =
-            read_json(serde_json::to_string_pretty(&content).unwrap().as_bytes(), &mut file)
-                .unwrap();
-        snapshot!(documents_count, @"5");
-        file.persist().unwrap();
-
-        index_scheduler
-            .register(
-                KindWithContent::DocumentAdditionOrUpdate {
-                    index_uid: S("doggos"),
-                    primary_key: None,
-                    method: ReplaceDocuments,
-                    content_file: uuid,
-                    documents_count,
-                    allow_index_creation: true,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        let index = index_scheduler.index("doggos").unwrap();
-        let rtxn = index.read_txn().unwrap();
-        let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-        let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-        let documents = index
-            .all_documents(&rtxn)
-            .unwrap()
-            .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-            .collect::<Vec<_>>();
-        snapshot!(serde_json::to_string(&documents).unwrap(), name: "documents after initial push");
-
-        let setting = meilisearch_types::settings::Settings::<Unchecked> {
-            embedders: Setting::Set(maplit::btreemap! {
-                S("my_doggo_embedder") => Setting::Set(EmbeddingSettings {
-                    source: Setting::Set(milli::vector::settings::EmbedderSource::HuggingFace),
-                    model: Setting::Set(S("sentence-transformers/all-MiniLM-L6-v2")),
-                    revision: Setting::Set(S("e4ce9877abf3edfe10b0d82785e83bdcb973e22e")),
-                    document_template: Setting::Set(S("{{doc.doggo}}")),
-                    ..Default::default()
-                })
-            }),
-            ..Default::default()
-        };
-        index_scheduler
-            .register(
-                KindWithContent::SettingsUpdate {
-                    index_uid: S("doggos"),
-                    new_settings: Box::new(setting),
-                    is_deletion: false,
-                    allow_index_creation: false,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        index_scheduler.assert_internally_consistent();
-        handle.advance_one_successful_batch();
-        index_scheduler.assert_internally_consistent();
-
-        let index = index_scheduler.index("doggos").unwrap();
-        let rtxn = index.read_txn().unwrap();
-        let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-        let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-        let documents = index
-            .all_documents(&rtxn)
-            .unwrap()
-            .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-            .collect::<Vec<_>>();
-        // the all the vectors linked to the new specified embedder have been removed
-        // Only the unknown embedders stays in the document DB
-        snapshot!(serde_json::to_string(&documents).unwrap(), @r###"[{"id":0,"doggo":"kefir"},{"id":1,"doggo":"intel","_vectors":{"unknown embedder":[1.0,2.0,3.0]}},{"id":2,"doggo":"max","_vectors":{"unknown embedder":[4.0,5.0]}},{"id":3,"doggo":"marcel"},{"id":4,"doggo":"sora"}]"###);
-        let conf = index.embedding_configs(&rtxn).unwrap();
-        // even though we specified the vector for the ID 3, it shouldn't be marked
-        // as user provided since we explicitely marked it as NOT user provided.
-        snapshot!(format!("{conf:#?}"), @r###"
-        [
-            IndexEmbeddingConfig {
-                name: "my_doggo_embedder",
-                config: EmbeddingConfig {
-                    embedder_options: HuggingFace(
-                        EmbedderOptions {
-                            model: "sentence-transformers/all-MiniLM-L6-v2",
-                            revision: Some(
-                                "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
-                            ),
-                            distribution: None,
-                        },
-                    ),
-                    prompt: PromptData {
-                        template: "{{doc.doggo}}",
-                    },
-                },
-                user_provided: RoaringBitmap<[1, 2]>,
-            },
-        ]
-        "###);
-        let docid = index.external_documents_ids.get(&rtxn, "0").unwrap().unwrap();
-        let embeddings = index.embeddings(&rtxn, docid).unwrap();
-        let embedding = &embeddings["my_doggo_embedder"];
-        assert!(!embedding.is_empty(), "{embedding:?}");
-
-        // the document with the id 3 should keep its original embedding
-        let docid = index.external_documents_ids.get(&rtxn, "3").unwrap().unwrap();
-        let mut embeddings = Vec::new();
-
-        'vectors: for i in 0..=u8::MAX {
-            let reader = arroy::Reader::open(&rtxn, i as u16, index.vector_arroy)
-                .map(Some)
-                .or_else(|e| match e {
-                    arroy::Error::MissingMetadata(_) => Ok(None),
-                    e => Err(e),
-                })
-                .transpose();
-
-            let Some(reader) = reader else {
-                break 'vectors;
-            };
-
-            let embedding = reader.unwrap().item_vector(&rtxn, docid).unwrap();
-            if let Some(embedding) = embedding {
-                embeddings.push(embedding)
-            } else {
-                break 'vectors;
-            }
-        }
-
-        snapshot!(embeddings.len(), @"1");
-        assert!(embeddings[0].iter().all(|i| *i == 3.0), "{:?}", embeddings[0]);
-
-        // If we update marcel it should regenerate its embedding automatically
-
-        let content = serde_json::json!(
-            [
-                {
-                    "id": 3,
-                    "doggo": "marvel",
-                },
-                {
-                    "id": 4,
-                    "doggo": "sorry",
-                },
-            ]
-        );
-
-        let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(1_u128).unwrap();
-        let documents_count =
-            read_json(serde_json::to_string_pretty(&content).unwrap().as_bytes(), &mut file)
-                .unwrap();
-        snapshot!(documents_count, @"2");
-        file.persist().unwrap();
-
-        index_scheduler
-            .register(
-                KindWithContent::DocumentAdditionOrUpdate {
-                    index_uid: S("doggos"),
-                    primary_key: None,
-                    method: UpdateDocuments,
-                    content_file: uuid,
-                    documents_count,
-                    allow_index_creation: true,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        // the document with the id 3 should have its original embedding updated
-        let rtxn = index.read_txn().unwrap();
-        let docid = index.external_documents_ids.get(&rtxn, "3").unwrap().unwrap();
-        let doc = index.documents(&rtxn, Some(docid)).unwrap()[0];
-        let doc = obkv_to_json(&field_ids, &field_ids_map, doc.1).unwrap();
-        snapshot!(json_string!(doc), @r###"
-        {
-          "id": 3,
-          "doggo": "marvel"
-        }
-        "###);
-
-        let embeddings = index.embeddings(&rtxn, docid).unwrap();
-        let embedding = &embeddings["my_doggo_embedder"];
-
-        assert!(!embedding.is_empty());
-        assert!(!embedding[0].iter().all(|i| *i == 3.0), "{:?}", embedding[0]);
-
-        // the document with the id 4 should generate an embedding
-        let docid = index.external_documents_ids.get(&rtxn, "4").unwrap().unwrap();
-        let embeddings = index.embeddings(&rtxn, docid).unwrap();
-        let embedding = &embeddings["my_doggo_embedder"];
-
-        assert!(!embedding.is_empty());
-    }
-
-    #[test]
-    fn delete_document_containing_vector() {
-        // 1. Add an embedder
-        // 2. Push two documents containing a simple vector
-        // 3. Delete the first document
-        // 4. The user defined roaring bitmap shouldn't contains the id of the first document anymore
-        // 5. Clear the index
-        // 6. The user defined roaring bitmap shouldn't contains the id of the second document
-        let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
-
-        let setting = meilisearch_types::settings::Settings::<Unchecked> {
-            embedders: Setting::Set(maplit::btreemap! {
-                S("manual") => Setting::Set(EmbeddingSettings {
-                    source: Setting::Set(milli::vector::settings::EmbedderSource::UserProvided),
-                    dimensions: Setting::Set(3),
-                    ..Default::default()
-                })
-            }),
-            ..Default::default()
-        };
-        index_scheduler
-            .register(
-                KindWithContent::SettingsUpdate {
-                    index_uid: S("doggos"),
-                    new_settings: Box::new(setting),
-                    is_deletion: false,
-                    allow_index_creation: true,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        let content = serde_json::json!(
-            [
-                {
-                    "id": 0,
-                    "doggo": "kefir",
-                    "_vectors": {
-                        "manual": vec![0, 0, 0],
-                    }
-                },
-                {
-                    "id": 1,
-                    "doggo": "intel",
-                    "_vectors": {
-                        "manual": vec![1, 1, 1],
-                    }
-                },
-            ]
-        );
-
-        let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0_u128).unwrap();
-        let documents_count =
-            read_json(serde_json::to_string_pretty(&content).unwrap().as_bytes(), &mut file)
-                .unwrap();
-        snapshot!(documents_count, @"2");
-        file.persist().unwrap();
-
-        index_scheduler
-            .register(
-                KindWithContent::DocumentAdditionOrUpdate {
-                    index_uid: S("doggos"),
-                    primary_key: None,
-                    method: ReplaceDocuments,
-                    content_file: uuid,
-                    documents_count,
-                    allow_index_creation: false,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        index_scheduler
-            .register(
-                KindWithContent::DocumentDeletion {
-                    index_uid: S("doggos"),
-                    documents_ids: vec![S("1")],
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        let index = index_scheduler.index("doggos").unwrap();
-        let rtxn = index.read_txn().unwrap();
-        let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-        let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-        let documents = index
-            .all_documents(&rtxn)
-            .unwrap()
-            .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-            .collect::<Vec<_>>();
-        snapshot!(serde_json::to_string(&documents).unwrap(), @r###"[{"id":0,"doggo":"kefir"}]"###);
-        let conf = index.embedding_configs(&rtxn).unwrap();
-        snapshot!(format!("{conf:#?}"), @r###"
-        [
-            IndexEmbeddingConfig {
-                name: "manual",
-                config: EmbeddingConfig {
-                    embedder_options: UserProvided(
-                        EmbedderOptions {
-                            dimensions: 3,
-                            distribution: None,
-                        },
-                    ),
-                    prompt: PromptData {
-                        template: "{% for field in fields %} {{ field.name }}: {{ field.value }}\n{% endfor %}",
-                    },
-                },
-                user_provided: RoaringBitmap<[0]>,
-            },
-        ]
-        "###);
-        let docid = index.external_documents_ids.get(&rtxn, "0").unwrap().unwrap();
-        let embeddings = index.embeddings(&rtxn, docid).unwrap();
-        let embedding = &embeddings["manual"];
-        assert!(!embedding.is_empty(), "{embedding:?}");
-
-        index_scheduler
-            .register(KindWithContent::DocumentClear { index_uid: S("doggos") }, None, false)
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        let index = index_scheduler.index("doggos").unwrap();
-        let rtxn = index.read_txn().unwrap();
-        let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-        let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-        let documents = index
-            .all_documents(&rtxn)
-            .unwrap()
-            .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-            .collect::<Vec<_>>();
-        snapshot!(serde_json::to_string(&documents).unwrap(), @"[]");
-        let conf = index.embedding_configs(&rtxn).unwrap();
-        snapshot!(format!("{conf:#?}"), @r###"
-        [
-            IndexEmbeddingConfig {
-                name: "manual",
-                config: EmbeddingConfig {
-                    embedder_options: UserProvided(
-                        EmbedderOptions {
-                            dimensions: 3,
-                            distribution: None,
-                        },
-                    ),
-                    prompt: PromptData {
-                        template: "{% for field in fields %} {{ field.name }}: {{ field.value }}\n{% endfor %}",
-                    },
-                },
-                user_provided: RoaringBitmap<[]>,
-            },
-        ]
-        "###);
-    }
-
-    #[test]
-    fn delete_embedder_with_user_provided_vectors() {
-        // 1. Add two embedders
-        // 2. Push two documents containing a simple vector
-        // 3. The documents must not contain the vectors after the update as they are in the vectors db
-        // 3. Delete the embedders
-        // 4. The documents contain the vectors again
-        let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
-
-        let setting = meilisearch_types::settings::Settings::<Unchecked> {
-            embedders: Setting::Set(maplit::btreemap! {
-                S("manual") => Setting::Set(EmbeddingSettings {
-                    source: Setting::Set(milli::vector::settings::EmbedderSource::UserProvided),
-                    dimensions: Setting::Set(3),
-                    ..Default::default()
-                }),
-                S("my_doggo_embedder") => Setting::Set(EmbeddingSettings {
-                    source: Setting::Set(milli::vector::settings::EmbedderSource::HuggingFace),
-                    model: Setting::Set(S("sentence-transformers/all-MiniLM-L6-v2")),
-                    revision: Setting::Set(S("e4ce9877abf3edfe10b0d82785e83bdcb973e22e")),
-                    document_template: Setting::Set(S("{{doc.doggo}}")),
-                    ..Default::default()
-                }),
-            }),
-            ..Default::default()
-        };
-        index_scheduler
-            .register(
-                KindWithContent::SettingsUpdate {
-                    index_uid: S("doggos"),
-                    new_settings: Box::new(setting),
-                    is_deletion: false,
-                    allow_index_creation: true,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        let content = serde_json::json!(
-            [
-                {
-                    "id": 0,
-                    "doggo": "kefir",
-                    "_vectors": {
-                        "manual": vec![0, 0, 0],
-                        "my_doggo_embedder": vec![1; 384],
-                    }
-                },
-                {
-                    "id": 1,
-                    "doggo": "intel",
-                    "_vectors": {
-                        "manual": vec![1, 1, 1],
-                    }
-                },
-            ]
-        );
-
-        let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0_u128).unwrap();
-        let documents_count =
-            read_json(serde_json::to_string_pretty(&content).unwrap().as_bytes(), &mut file)
-                .unwrap();
-        snapshot!(documents_count, @"2");
-        file.persist().unwrap();
-
-        index_scheduler
-            .register(
-                KindWithContent::DocumentAdditionOrUpdate {
-                    index_uid: S("doggos"),
-                    primary_key: None,
-                    method: ReplaceDocuments,
-                    content_file: uuid,
-                    documents_count,
-                    allow_index_creation: false,
-                },
-                None,
-                false,
-            )
-            .unwrap();
-        handle.advance_one_successful_batch();
-
-        {
-            let index = index_scheduler.index("doggos").unwrap();
-            let rtxn = index.read_txn().unwrap();
-            let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-            let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-            let documents = index
-                .all_documents(&rtxn)
-                .unwrap()
-                .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-                .collect::<Vec<_>>();
-            snapshot!(serde_json::to_string(&documents).unwrap(), @r###"[{"id":0,"doggo":"kefir"},{"id":1,"doggo":"intel"}]"###);
-        }
-
-        {
-            let setting = meilisearch_types::settings::Settings::<Unchecked> {
-                embedders: Setting::Set(maplit::btreemap! {
-                    S("manual") => Setting::Reset,
-                }),
-                ..Default::default()
-            };
-            index_scheduler
-                .register(
-                    KindWithContent::SettingsUpdate {
-                        index_uid: S("doggos"),
-                        new_settings: Box::new(setting),
-                        is_deletion: false,
-                        allow_index_creation: true,
-                    },
-                    None,
-                    false,
-                )
-                .unwrap();
-            handle.advance_one_successful_batch();
-        }
-
-        {
-            let index = index_scheduler.index("doggos").unwrap();
-            let rtxn = index.read_txn().unwrap();
-            let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-            let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-            let documents = index
-                .all_documents(&rtxn)
-                .unwrap()
-                .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-                .collect::<Vec<_>>();
-            snapshot!(serde_json::to_string(&documents).unwrap(), @r###"[{"id":0,"doggo":"kefir","_vectors":{"manual":{"embeddings":[[0.0,0.0,0.0]],"regenerate":false}}},{"id":1,"doggo":"intel","_vectors":{"manual":{"embeddings":[[1.0,1.0,1.0]],"regenerate":false}}}]"###);
-        }
-
-        {
-            let setting = meilisearch_types::settings::Settings::<Unchecked> {
-                embedders: Setting::Reset,
-                ..Default::default()
-            };
-            index_scheduler
-                .register(
-                    KindWithContent::SettingsUpdate {
-                        index_uid: S("doggos"),
-                        new_settings: Box::new(setting),
-                        is_deletion: false,
-                        allow_index_creation: true,
-                    },
-                    None,
-                    false,
-                )
-                .unwrap();
-            handle.advance_one_successful_batch();
-        }
-
-        {
-            let index = index_scheduler.index("doggos").unwrap();
-            let rtxn = index.read_txn().unwrap();
-            let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
-            let field_ids = field_ids_map.ids().collect::<Vec<_>>();
-            let documents = index
-                .all_documents(&rtxn)
-                .unwrap()
-                .map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
-                .collect::<Vec<_>>();
-
-            // FIXME: redaction
-            snapshot!(json_string!(serde_json::to_string(&documents).unwrap(), { "[]._vectors.doggo_embedder.embeddings" => "[vector]" }),  @r###""[{\"id\":0,\"doggo\":\"kefir\",\"_vectors\":{\"manual\":{\"embeddings\":[[0.0,0.0,0.0]],\"regenerate\":false},\"my_doggo_embedder\":{\"embeddings\":[[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]],\"regenerate\":false}}},{\"id\":1,\"doggo\":\"intel\",\"_vectors\":{\"manual\":{\"embeddings\":[[1.0,1.0,1.0]],\"regenerate\":false}}}]""###);
-        }
-    }
 }

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-12.snap

@@ -6,6 +6,10 @@ expression: doc
   "doggo": "kefir",
   "breed": "patou",
   "_vectors": {
+    "A_fakerest": {
+      "embeddings": "[vector]",
+      "userProvided": true
+    },
     "noise": [
       0.1,
       0.2,

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-9.snap

@@ -6,6 +6,10 @@ expression: doc
   "doggo": "Intel",
   "breed": "beagle",
   "_vectors": {
+    "A_fakerest": {
+      "embeddings": "[vector]",
+      "userProvided": true
+    },
     "noise": [
       0.1,
       0.2,

meilisearch-types/Cargo.toml

@@ -11,7 +11,7 @@ edition.workspace = true
 license.workspace = true
 
 [dependencies]
-actix-web = { version = "4.6.0", default-features = false }
+actix-web = { version = "4.5.1", default-features = false }
 anyhow = "1.0.79"
 convert_case = "0.6.0"
 csv = "1.3.0"
@@ -30,12 +30,7 @@ serde_json = "1.0.111"
 tar = "0.4.40"
 tempfile = "3.9.0"
 thiserror = "1.0.56"
-time = { version = "0.3.31", features = [
+time = { version = "0.3.31", features = ["serde-well-known", "formatting", "parsing", "macros"] }
-    "serde-well-known",
-    "formatting",
-    "parsing",
-    "macros",
-] }
 tokio = "1.35"
 uuid = { version = "1.6.1", features = ["serde", "v4"] }
 

meilisearch-types/src/deserr/mod.rs

@@ -189,6 +189,4 @@ merge_with_error_impl_take_error_message!(ParseTaskKindError);
 merge_with_error_impl_take_error_message!(ParseTaskStatusError);
 merge_with_error_impl_take_error_message!(IndexUidFormatError);
 merge_with_error_impl_take_error_message!(InvalidSearchSemanticRatio);
-merge_with_error_impl_take_error_message!(InvalidSearchRankingScoreThreshold);
-merge_with_error_impl_take_error_message!(InvalidSimilarRankingScoreThreshold);
 merge_with_error_impl_take_error_message!(InvalidSimilarId);

meilisearch-types/src/error.rs

@@ -222,7 +222,6 @@ InvalidApiKeyUid                      , InvalidRequest       , BAD_REQUEST ;
 InvalidContentType                    , InvalidRequest       , UNSUPPORTED_MEDIA_TYPE ;
 InvalidDocumentCsvDelimiter           , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentFields                 , InvalidRequest       , BAD_REQUEST ;
-InvalidDocumentRetrieveVectors        , InvalidRequest       , BAD_REQUEST ;
 MissingDocumentFilter                 , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentFilter                 , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentGeoField               , InvalidRequest       , BAD_REQUEST ;
@@ -241,11 +240,7 @@ InvalidSearchAttributesToSearchOn     , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchAttributesToCrop         , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchAttributesToHighlight    , InvalidRequest       , BAD_REQUEST ;
 InvalidSimilarAttributesToRetrieve    , InvalidRequest       , BAD_REQUEST ;
-InvalidSimilarRetrieveVectors         , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchAttributesToRetrieve     , InvalidRequest       , BAD_REQUEST ;
-InvalidSearchRankingScoreThreshold    , InvalidRequest       , BAD_REQUEST ;
-InvalidSimilarRankingScoreThreshold   , InvalidRequest       , BAD_REQUEST ;
-InvalidSearchRetrieveVectors          , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchCropLength               , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchCropMarker               , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchFacets                   , InvalidRequest       , BAD_REQUEST ;
@@ -273,14 +268,13 @@ InvalidSimilarShowRankingScore        , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchShowRankingScoreDetails  , InvalidRequest       , BAD_REQUEST ;
 InvalidSimilarShowRankingScoreDetails , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchSort                     , InvalidRequest       , BAD_REQUEST ;
-InvalidSearchDistinct                 , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsDisplayedAttributes    , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsDistinctAttribute      , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsProximityPrecision     , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsFaceting               , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsFilterableAttributes   , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsPagination             , InvalidRequest       , BAD_REQUEST ;
-InvalidSettingsSearchCutoffMs         , InvalidRequest       , BAD_REQUEST ;
+InvalidSettingsSearchCutoffMs           , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsEmbedders              , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsRankingRules           , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsSearchableAttributes   , InvalidRequest       , BAD_REQUEST ;
@@ -385,7 +379,6 @@ impl ErrorCode for milli::Error {
                         Code::IndexPrimaryKeyMultipleCandidatesFound
                     }
                     UserError::PrimaryKeyCannotBeChanged(_) => Code::IndexPrimaryKeyAlreadyExists,
-                    UserError::InvalidDistinctAttribute { .. } => Code::InvalidSearchDistinct,
                     UserError::SortRankingRuleMissing => Code::InvalidSearchSort,
                     UserError::InvalidFacetsDistribution { .. } => Code::InvalidSearchFacets,
                     UserError::InvalidSortableAttribute { .. } => Code::InvalidSearchSort,
@@ -398,8 +391,7 @@ impl ErrorCode for milli::Error {
                     UserError::CriterionError(_) => Code::InvalidSettingsRankingRules,
                     UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
                     UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
-                    UserError::InvalidVectorsMapType { .. }
+                    UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
-                    | UserError::InvalidVectorsEmbedderConf { .. } => Code::InvalidVectorsType,
                     UserError::TooManyVectors(_, _) => Code::TooManyVectors,
                     UserError::SortError(_) => Code::InvalidSearchSort,
                     UserError::InvalidMinTypoWordLenSetting(_, _) => {
@@ -513,21 +505,6 @@ impl fmt::Display for deserr_codes::InvalidSimilarId {
     }
 }
 
-impl fmt::Display for deserr_codes::InvalidSearchRankingScoreThreshold {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        write!(
-            f,
-            "the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`."
-        )
-    }
-}
-
-impl fmt::Display for deserr_codes::InvalidSimilarRankingScoreThreshold {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        deserr_codes::InvalidSearchRankingScoreThreshold.fmt(f)
-    }
-}
-
 #[macro_export]
 macro_rules! internal_error {
     ($target:ty : $($other:path), *) => {

meilisearch-types/src/settings.rs

@@ -8,7 +8,6 @@ use std::str::FromStr;
 
 use deserr::{DeserializeError, Deserr, ErrorKind, MergeWithError, ValuePointerRef};
 use fst::IntoStreamer;
-use milli::index::IndexEmbeddingConfig;
 use milli::proximity::ProximityPrecision;
 use milli::update::Setting;
 use milli::{Criterion, CriterionError, Index, DEFAULT_VALUES_PER_FACET};
@@ -673,7 +672,7 @@ pub fn settings(
     let embedders: BTreeMap<_, _> = index
         .embedding_configs(rtxn)?
         .into_iter()
-        .map(|IndexEmbeddingConfig { name, config, .. }| (name, Setting::Set(config.into())))
+        .map(|(name, config)| (name, Setting::Set(config.into())))
         .collect();
     let embedders = if embedders.is_empty() { Setting::NotSet } else { Setting::Set(embedders) };
 

meilisearch/Cargo.toml

@@ -14,20 +14,20 @@ default-run = "meilisearch"
 
 [dependencies]
 actix-cors = "0.7.0"
-actix-http = { version = "3.7.0", default-features = false, features = [
+actix-http = { version = "3.6.0", default-features = false, features = [
     "compress-brotli",
     "compress-gzip",
     "rustls-0_21",
 ] }
 actix-utils = "3.0.1"
-actix-web = { version = "4.6.0", default-features = false, features = [
+actix-web = { version = "4.5.1", default-features = false, features = [
     "macros",
     "compress-brotli",
     "compress-gzip",
     "cookies",
     "rustls-0_21",
 ] }
-actix-web-static-files = { version = "4.0.1", optional = true }
+actix-web-static-files = { git = "https://github.com/kilork/actix-web-static-files.git", rev = "2d3b6160", optional = true }
 anyhow = { version = "1.0.79", features = ["backtrace"] }
 async-stream = "0.3.5"
 async-trait = "0.1.77"
@@ -105,20 +105,19 @@ url = { version = "2.5.0", features = ["serde"] }
 tracing = "0.1.40"
 tracing-subscriber = { version = "0.3.18", features = ["json"] }
 tracing-trace = { version = "0.1.0", path = "../tracing-trace" }
-tracing-actix-web = "0.7.10"
+tracing-actix-web = "0.7.9"
 build-info = { version = "1.7.0", path = "../build-info" }
 
 [dev-dependencies]
 actix-rt = "2.9.0"
 assert-json-diff = "2.0.2"
-brotli = "6.0.0"
+brotli = "3.4.0"
 insta = "1.34.0"
 manifest-dir-macros = "0.1.18"
 maplit = "1.0.2"
 meili-snap = { path = "../meili-snap" }
 temp-env = "0.3.6"
 urlencoding = "2.1.3"
-wiremock = "0.6.0"
 yaup = "0.2.1"
 
 [build-dependencies]
@@ -159,5 +158,5 @@ vietnamese = ["meilisearch-types/vietnamese"]
 swedish-recomposition = ["meilisearch-types/swedish-recomposition"]
 
 [package.metadata.mini-dashboard]
-assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.14/build.zip"
+assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.13/build.zip"
-sha1 = "592d1b5a3459d621d0aae1dded8fe3154f5c38fe"
+sha1 = "e20cc9b390003c6c844f4b8bcc5c5013191a77ff"

meilisearch/src/analytics/mod.rs

@@ -74,8 +74,8 @@ pub enum DocumentDeletionKind {
 
 #[derive(Copy, Clone, Debug, PartialEq, Eq)]
 pub enum DocumentFetchKind {
-    PerDocumentId { retrieve_vectors: bool },
+    PerDocumentId,
-    Normal { with_filter: bool, limit: usize, offset: usize, retrieve_vectors: bool },
+    Normal { with_filter: bool, limit: usize, offset: usize },
 }
 
 pub trait Analytics: Sync + Send {

meilisearch/src/analytics/segment_analytics.rs

@@ -597,9 +597,6 @@ pub struct SearchAggregator {
     // every time a request has a filter, this field must be incremented by one
     sort_total_number_of_criteria: usize,
 
-    // distinct
-    distinct: bool,
-
     // filter
     filter_with_geo_radius: bool,
     filter_with_geo_bounding_box: bool,
@@ -625,7 +622,6 @@ pub struct SearchAggregator {
     // Whether a non-default embedder was specified
     embedder: bool,
     hybrid: bool,
-    retrieve_vectors: bool,
 
     // every time a search is done, we increment the counter linked to the used settings
     matching_strategy: HashMap<String, usize>,
@@ -652,7 +648,6 @@ pub struct SearchAggregator {
     // scoring
     show_ranking_score: bool,
     show_ranking_score_details: bool,
-    ranking_score_threshold: bool,
 }
 
 impl SearchAggregator {
@@ -666,7 +661,6 @@ impl SearchAggregator {
             page,
             hits_per_page,
             attributes_to_retrieve: _,
-            retrieve_vectors,
             attributes_to_crop: _,
             crop_length,
             attributes_to_highlight: _,
@@ -675,7 +669,6 @@ impl SearchAggregator {
             show_ranking_score_details,
             filter,
             sort,
-            distinct,
             facets: _,
             highlight_pre_tag,
             highlight_post_tag,
@@ -683,7 +676,6 @@ impl SearchAggregator {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
-            ranking_score_threshold,
         } = query;
 
         let mut ret = Self::default();
@@ -698,8 +690,6 @@ impl SearchAggregator {
             ret.sort_sum_of_criteria_terms = sort.len();
         }
 
-        ret.distinct = distinct.is_some();
-
         if let Some(ref filter) = filter {
             static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
             ret.filter_total_number_of_criteria = 1;
@@ -736,7 +726,6 @@ impl SearchAggregator {
         if let Some(ref vector) = vector {
             ret.max_vector_size = vector.len();
         }
-        ret.retrieve_vectors |= retrieve_vectors;
 
         if query.is_finite_pagination() {
             let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
@@ -759,7 +748,6 @@ impl SearchAggregator {
 
         ret.show_ranking_score = *show_ranking_score;
         ret.show_ranking_score_details = *show_ranking_score_details;
-        ret.ranking_score_threshold = ranking_score_threshold.is_some();
 
         if let Some(hybrid) = hybrid {
             ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
@@ -804,7 +792,6 @@ impl SearchAggregator {
             sort_with_geo_point,
             sort_sum_of_criteria_terms,
             sort_total_number_of_criteria,
-            distinct,
             filter_with_geo_radius,
             filter_with_geo_bounding_box,
             filter_sum_of_criteria_terms,
@@ -813,7 +800,6 @@ impl SearchAggregator {
             attributes_to_search_on_total_number_of_uses,
             max_terms_number,
             max_vector_size,
-            retrieve_vectors,
             matching_strategy,
             max_limit,
             max_offset,
@@ -835,7 +821,6 @@ impl SearchAggregator {
             hybrid,
             total_degraded,
             total_used_negative_operator,
-            ranking_score_threshold,
         } = other;
 
         if self.timestamp.is_none() {
@@ -862,9 +847,6 @@ impl SearchAggregator {
         self.sort_total_number_of_criteria =
             self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
 
-        // distinct
-        self.distinct |= distinct;
-
         // filter
         self.filter_with_geo_radius |= filter_with_geo_radius;
         self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
@@ -887,7 +869,6 @@ impl SearchAggregator {
 
         // vector
         self.max_vector_size = self.max_vector_size.max(max_vector_size);
-        self.retrieve_vectors |= retrieve_vectors;
         self.semantic_ratio |= semantic_ratio;
         self.hybrid |= hybrid;
         self.embedder |= embedder;
@@ -923,7 +904,6 @@ impl SearchAggregator {
         // scoring
         self.show_ranking_score |= show_ranking_score;
         self.show_ranking_score_details |= show_ranking_score_details;
-        self.ranking_score_threshold |= ranking_score_threshold;
     }
 
     pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
@@ -936,7 +916,6 @@ impl SearchAggregator {
             sort_with_geo_point,
             sort_sum_of_criteria_terms,
             sort_total_number_of_criteria,
-            distinct,
             filter_with_geo_radius,
             filter_with_geo_bounding_box,
             filter_sum_of_criteria_terms,
@@ -945,7 +924,6 @@ impl SearchAggregator {
             attributes_to_search_on_total_number_of_uses,
             max_terms_number,
             max_vector_size,
-            retrieve_vectors,
             matching_strategy,
             max_limit,
             max_offset,
@@ -967,7 +945,6 @@ impl SearchAggregator {
             hybrid,
             total_degraded,
             total_used_negative_operator,
-            ranking_score_threshold,
         } = self;
 
         if total_received == 0 {
@@ -994,7 +971,6 @@ impl SearchAggregator {
                     "with_geoPoint": sort_with_geo_point,
                     "avg_criteria_number": format!("{:.2}", sort_sum_of_criteria_terms as f64 / sort_total_number_of_criteria as f64),
                 },
-                "distinct": distinct,
                 "filter": {
                    "with_geoRadius": filter_with_geo_radius,
                    "with_geoBoundingBox": filter_with_geo_bounding_box,
@@ -1009,7 +985,6 @@ impl SearchAggregator {
                 },
                 "vector": {
                     "max_vector_size": max_vector_size,
-                    "retrieve_vectors": retrieve_vectors,
                 },
                 "hybrid": {
                     "enabled": hybrid,
@@ -1040,7 +1015,6 @@ impl SearchAggregator {
                 "scoring": {
                     "show_ranking_score": show_ranking_score,
                     "show_ranking_score_details": show_ranking_score_details,
-                    "ranking_score_threshold": ranking_score_threshold,
                 },
             });
 
@@ -1098,7 +1072,6 @@ impl MultiSearchAggregator {
                     page: _,
                     hits_per_page: _,
                     attributes_to_retrieve: _,
-                    retrieve_vectors: _,
                     attributes_to_crop: _,
                     crop_length: _,
                     attributes_to_highlight: _,
@@ -1107,7 +1080,6 @@ impl MultiSearchAggregator {
                     show_matches_position: _,
                     filter: _,
                     sort: _,
-                    distinct: _,
                     facets: _,
                     highlight_pre_tag: _,
                     highlight_post_tag: _,
@@ -1115,7 +1087,6 @@ impl MultiSearchAggregator {
                     matching_strategy: _,
                     attributes_to_search_on: _,
                     hybrid: _,
-                    ranking_score_threshold: _,
                 } = query;
 
                 index_uid.as_str()
@@ -1263,7 +1234,6 @@ impl FacetSearchAggregator {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
-            ranking_score_threshold,
         } = query;
 
         let mut ret = Self::default();
@@ -1278,8 +1248,7 @@ impl FacetSearchAggregator {
             || filter.is_some()
             || *matching_strategy != MatchingStrategy::default()
             || attributes_to_search_on.is_some()
-            || hybrid.is_some()
+            || hybrid.is_some();
-            || ranking_score_threshold.is_some();
 
         ret
     }
@@ -1555,9 +1524,6 @@ pub struct DocumentsFetchAggregator {
     // if a filter was used
     per_filter: bool,
 
-    #[serde(rename = "vector.retrieve_vectors")]
-    retrieve_vectors: bool,
-
     // pagination
     #[serde(rename = "pagination.max_limit")]
     max_limit: usize,
@@ -1567,21 +1533,18 @@ pub struct DocumentsFetchAggregator {
 
 impl DocumentsFetchAggregator {
     pub fn from_query(query: &DocumentFetchKind, request: &HttpRequest) -> Self {
-        let (limit, offset, retrieve_vectors) = match query {
+        let (limit, offset) = match query {
-            DocumentFetchKind::PerDocumentId { retrieve_vectors } => (1, 0, *retrieve_vectors),
+            DocumentFetchKind::PerDocumentId => (1, 0),
-            DocumentFetchKind::Normal { limit, offset, retrieve_vectors, .. } => {
+            DocumentFetchKind::Normal { limit, offset, .. } => (*limit, *offset),
-                (*limit, *offset, *retrieve_vectors)
-            }
         };
         Self {
             timestamp: Some(OffsetDateTime::now_utc()),
             user_agents: extract_user_agents(request).into_iter().collect(),
             total_received: 1,
-            per_document_id: matches!(query, DocumentFetchKind::PerDocumentId { .. }),
+            per_document_id: matches!(query, DocumentFetchKind::PerDocumentId),
             per_filter: matches!(query, DocumentFetchKind::Normal { with_filter, .. } if *with_filter),
             max_limit: limit,
             max_offset: offset,
-            retrieve_vectors,
         }
     }
 
@@ -1595,7 +1558,6 @@ impl DocumentsFetchAggregator {
             per_filter,
             max_limit,
             max_offset,
-            retrieve_vectors,
         } = other;
 
         if self.timestamp.is_none() {
@@ -1611,8 +1573,6 @@ impl DocumentsFetchAggregator {
 
         self.max_limit = self.max_limit.max(max_limit);
         self.max_offset = self.max_offset.max(max_offset);
-
-        self.retrieve_vectors |= retrieve_vectors;
     }
 
     pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
@@ -1653,7 +1613,6 @@ pub struct SimilarAggregator {
 
     // Whether a non-default embedder was specified
     embedder: bool,
-    retrieve_vectors: bool,
 
     // pagination
     max_limit: usize,
@@ -1665,7 +1624,6 @@ pub struct SimilarAggregator {
     // scoring
     show_ranking_score: bool,
     show_ranking_score_details: bool,
-    ranking_score_threshold: bool,
 }
 
 impl SimilarAggregator {
@@ -1677,11 +1635,9 @@ impl SimilarAggregator {
             offset,
             limit,
             attributes_to_retrieve: _,
-            retrieve_vectors,
             show_ranking_score,
             show_ranking_score_details,
             filter,
-            ranking_score_threshold,
         } = query;
 
         let mut ret = Self::default();
@@ -1719,10 +1675,8 @@ impl SimilarAggregator {
 
         ret.show_ranking_score = *show_ranking_score;
         ret.show_ranking_score_details = *show_ranking_score_details;
-        ret.ranking_score_threshold = ranking_score_threshold.is_some();
 
         ret.embedder = embedder.is_some();
-        ret.retrieve_vectors = *retrieve_vectors;
 
         ret
     }
@@ -1754,8 +1708,6 @@ impl SimilarAggregator {
             show_ranking_score,
             show_ranking_score_details,
             embedder,
-            ranking_score_threshold,
-            retrieve_vectors,
         } = other;
 
         if self.timestamp.is_none() {
@@ -1785,7 +1737,6 @@ impl SimilarAggregator {
         }
 
         self.embedder |= embedder;
-        self.retrieve_vectors |= retrieve_vectors;
 
         // pagination
         self.max_limit = self.max_limit.max(max_limit);
@@ -1798,7 +1749,6 @@ impl SimilarAggregator {
         // scoring
         self.show_ranking_score |= show_ranking_score;
         self.show_ranking_score_details |= show_ranking_score_details;
-        self.ranking_score_threshold |= ranking_score_threshold;
     }
 
     pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
@@ -1819,8 +1769,6 @@ impl SimilarAggregator {
             show_ranking_score,
             show_ranking_score_details,
             embedder,
-            ranking_score_threshold,
-            retrieve_vectors,
         } = self;
 
         if total_received == 0 {
@@ -1847,9 +1795,6 @@ impl SimilarAggregator {
                    "avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
                    "most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
                 },
-                "vector": {
-                    "retrieve_vectors": retrieve_vectors,
-                },
                 "hybrid": {
                     "embedder": embedder,
                 },
@@ -1863,7 +1808,6 @@ impl SimilarAggregator {
                 "scoring": {
                     "show_ranking_score": show_ranking_score,
                     "show_ranking_score_details": show_ranking_score_details,
-                    "ranking_score_threshold": ranking_score_threshold,
                 },
             });
 

meilisearch/src/routes/indexes/documents.rs

@@ -16,7 +16,6 @@ use meilisearch_types::error::{Code, ResponseError};
 use meilisearch_types::heed::RoTxn;
 use meilisearch_types::index_uid::IndexUid;
 use meilisearch_types::milli::update::IndexDocumentsMethod;
-use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
 use meilisearch_types::milli::DocumentId;
 use meilisearch_types::star_or::OptionStarOrList;
 use meilisearch_types::tasks::KindWithContent;
@@ -40,7 +39,7 @@ use crate::extractors::sequential_extractor::SeqHandler;
 use crate::routes::{
     get_task_id, is_dry_run, PaginationView, SummarizedTaskView, PAGINATION_DEFAULT_LIMIT,
 };
-use crate::search::{parse_filter, RetrieveVectors};
+use crate::search::parse_filter;
 use crate::Opt;
 
 static ACCEPTED_CONTENT_TYPE: Lazy<Vec<String>> = Lazy::new(|| {
@@ -95,8 +94,6 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
 pub struct GetDocument {
     #[deserr(default, error = DeserrQueryParamError<InvalidDocumentFields>)]
     fields: OptionStarOrList<String>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidDocumentRetrieveVectors>)]
-    retrieve_vectors: Param<bool>,
 }
 
 pub async fn get_document(
@@ -110,20 +107,13 @@ pub async fn get_document(
     debug!(parameters = ?params, "Get document");
     let index_uid = IndexUid::try_from(index_uid)?;
 
-    let GetDocument { fields, retrieve_vectors: param_retrieve_vectors } = params.into_inner();
+    analytics.get_fetch_documents(&DocumentFetchKind::PerDocumentId, &req);
+
+    let GetDocument { fields } = params.into_inner();
     let attributes_to_retrieve = fields.merge_star_and_none();
 
-    let features = index_scheduler.features();
-    let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0, features)?;
-
-    analytics.get_fetch_documents(
-        &DocumentFetchKind::PerDocumentId { retrieve_vectors: param_retrieve_vectors.0 },
-        &req,
-    );
-
     let index = index_scheduler.index(&index_uid)?;
-    let document =
+    let document = retrieve_document(&index, &document_id, attributes_to_retrieve)?;
-        retrieve_document(&index, &document_id, attributes_to_retrieve, retrieve_vectors)?;
     debug!(returns = ?document, "Get document");
     Ok(HttpResponse::Ok().json(document))
 }
@@ -163,8 +153,6 @@ pub struct BrowseQueryGet {
     limit: Param<usize>,
     #[deserr(default, error = DeserrQueryParamError<InvalidDocumentFields>)]
     fields: OptionStarOrList<String>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidDocumentRetrieveVectors>)]
-    retrieve_vectors: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidDocumentFilter>)]
     filter: Option<String>,
 }
@@ -178,8 +166,6 @@ pub struct BrowseQuery {
     limit: usize,
     #[deserr(default, error = DeserrJsonError<InvalidDocumentFields>)]
     fields: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidDocumentRetrieveVectors>)]
-    retrieve_vectors: bool,
     #[deserr(default, error = DeserrJsonError<InvalidDocumentFilter>)]
     filter: Option<Value>,
 }
@@ -199,7 +185,6 @@ pub async fn documents_by_query_post(
             with_filter: body.filter.is_some(),
             limit: body.limit,
             offset: body.offset,
-            retrieve_vectors: body.retrieve_vectors,
         },
         &req,
     );
@@ -216,7 +201,7 @@ pub async fn get_documents(
 ) -> Result<HttpResponse, ResponseError> {
     debug!(parameters = ?params, "Get documents GET");
 
-    let BrowseQueryGet { limit, offset, fields, retrieve_vectors, filter } = params.into_inner();
+    let BrowseQueryGet { limit, offset, fields, filter } = params.into_inner();
 
     let filter = match filter {
         Some(f) => match serde_json::from_str(&f) {
@@ -230,7 +215,6 @@ pub async fn get_documents(
         offset: offset.0,
         limit: limit.0,
         fields: fields.merge_star_and_none(),
-        retrieve_vectors: retrieve_vectors.0,
         filter,
     };
 
@@ -239,7 +223,6 @@ pub async fn get_documents(
             with_filter: query.filter.is_some(),
             limit: query.limit,
             offset: query.offset,
-            retrieve_vectors: query.retrieve_vectors,
         },
         &req,
     );
@@ -253,14 +236,10 @@ fn documents_by_query(
     query: BrowseQuery,
 ) -> Result<HttpResponse, ResponseError> {
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
-    let BrowseQuery { offset, limit, fields, retrieve_vectors, filter } = query;
+    let BrowseQuery { offset, limit, fields, filter } = query;
-
-    let features = index_scheduler.features();
-    let retrieve_vectors = RetrieveVectors::new(retrieve_vectors, features)?;
 
     let index = index_scheduler.index(&index_uid)?;
-    let (total, documents) =
+    let (total, documents) = retrieve_documents(&index, offset, limit, filter, fields)?;
-        retrieve_documents(&index, offset, limit, filter, fields, retrieve_vectors)?;
 
     let ret = PaginationView::new(offset, limit, total as usize, documents);
 
@@ -600,44 +579,13 @@ fn some_documents<'a, 't: 'a>(
     index: &'a Index,
     rtxn: &'t RoTxn,
     doc_ids: impl IntoIterator<Item = DocumentId> + 'a,
-    retrieve_vectors: RetrieveVectors,
 ) -> Result<impl Iterator<Item = Result<Document, ResponseError>> + 'a, ResponseError> {
     let fields_ids_map = index.fields_ids_map(rtxn)?;
     let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
-    let embedding_configs = index.embedding_configs(rtxn)?;
 
     Ok(index.iter_documents(rtxn, doc_ids)?.map(move |ret| {
-        ret.map_err(ResponseError::from).and_then(|(key, document)| -> Result<_, ResponseError> {
+        ret.map_err(ResponseError::from).and_then(|(_key, document)| -> Result<_, ResponseError> {
-            let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
+            Ok(milli::obkv_to_json(&all_fields, &fields_ids_map, document)?)
-            match retrieve_vectors {
-                RetrieveVectors::Ignore => {}
-                RetrieveVectors::Hide => {
-                    document.remove("_vectors");
-                }
-                RetrieveVectors::Retrieve => {
-                    let mut vectors = match document.remove("_vectors") {
-                        Some(Value::Object(map)) => map,
-                        _ => Default::default(),
-                    };
-                    for (name, vector) in index.embeddings(rtxn, key)? {
-                        let user_provided = embedding_configs
-                            .iter()
-                            .find(|conf| conf.name == name)
-                            .is_some_and(|conf| conf.user_provided.contains(key));
-                        let embeddings = ExplicitVectors {
-                            embeddings: Some(vector.into()),
-                            regenerate: !user_provided,
-                        };
-                        vectors.insert(
-                            name,
-                            serde_json::to_value(embeddings).map_err(MeilisearchHttpError::from)?,
-                        );
-                    }
-                    document.insert("_vectors".into(), vectors.into());
-                }
-            }
-
-            Ok(document)
         })
     }))
 }
@@ -648,7 +596,6 @@ fn retrieve_documents<S: AsRef<str>>(
     limit: usize,
     filter: Option<Value>,
     attributes_to_retrieve: Option<Vec<S>>,
-    retrieve_vectors: RetrieveVectors,
 ) -> Result<(u64, Vec<Document>), ResponseError> {
     let rtxn = index.read_txn()?;
     let filter = &filter;
@@ -673,57 +620,53 @@ fn retrieve_documents<S: AsRef<str>>(
     let (it, number_of_documents) = {
         let number_of_documents = candidates.len();
         (
-            some_documents(
+            some_documents(index, &rtxn, candidates.into_iter().skip(offset).take(limit))?,
-                index,
-                &rtxn,
-                candidates.into_iter().skip(offset).take(limit),
-                retrieve_vectors,
-            )?,
             number_of_documents,
         )
     };
 
-    let documents: Vec<_> = it
+    let documents: Result<Vec<_>, ResponseError> = it
         .map(|document| {
             Ok(match &attributes_to_retrieve {
                 Some(attributes_to_retrieve) => permissive_json_pointer::select_values(
                     &document?,
-                    attributes_to_retrieve.iter().map(|s| s.as_ref()).chain(
+                    attributes_to_retrieve.iter().map(|s| s.as_ref()),
-                        (retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors"),
-                    ),
                 ),
                 None => document?,
             })
         })
-        .collect::<Result<_, ResponseError>>()?;
+        .collect();
 
-    Ok((number_of_documents, documents))
+    Ok((number_of_documents, documents?))
 }
 
 fn retrieve_document<S: AsRef<str>>(
     index: &Index,
     doc_id: &str,
     attributes_to_retrieve: Option<Vec<S>>,
-    retrieve_vectors: RetrieveVectors,
 ) -> Result<Document, ResponseError> {
     let txn = index.read_txn()?;
 
+    let fields_ids_map = index.fields_ids_map(&txn)?;
+    let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
+
     let internal_id = index
         .external_documents_ids()
         .get(&txn, doc_id)?
         .ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))?;
 
-    let document = some_documents(index, &txn, Some(internal_id), retrieve_vectors)?
+    let document = index
+        .documents(&txn, std::iter::once(internal_id))?
+        .into_iter()
         .next()
-        .ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))??;
+        .map(|(_, d)| d)
+        .ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))?;
 
+    let document = meilisearch_types::milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
     let document = match &attributes_to_retrieve {
         Some(attributes_to_retrieve) => permissive_json_pointer::select_values(
             &document,
-            attributes_to_retrieve
+            attributes_to_retrieve.iter().map(|s| s.as_ref()),
-                .iter()
-                .map(|s| s.as_ref())
-                .chain((retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors")),
         ),
         None => document,
     };

meilisearch/src/routes/indexes/facet_search.rs

@@ -14,8 +14,8 @@ use crate::extractors::authentication::policies::*;
 use crate::extractors::authentication::GuardedData;
 use crate::routes::indexes::search::search_kind;
 use crate::search::{
-    add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
+    add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, SearchQuery,
-    SearchQuery, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
+    DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
     DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
 };
 use crate::search_queue::SearchQueue;
@@ -46,8 +46,6 @@ pub struct FacetSearchQuery {
     pub matching_strategy: MatchingStrategy,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
     pub attributes_to_search_on: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
-    pub ranking_score_threshold: Option<RankingScoreThreshold>,
 }
 
 pub async fn search(
@@ -105,7 +103,6 @@ impl From<FacetSearchQuery> for SearchQuery {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
-            ranking_score_threshold,
         } = value;
 
         SearchQuery {
@@ -115,7 +112,6 @@ impl From<FacetSearchQuery> for SearchQuery {
             page: None,
             hits_per_page: None,
             attributes_to_retrieve: None,
-            retrieve_vectors: false,
             attributes_to_crop: None,
             crop_length: DEFAULT_CROP_LENGTH(),
             attributes_to_highlight: None,
@@ -124,7 +120,6 @@ impl From<FacetSearchQuery> for SearchQuery {
             show_ranking_score_details: false,
             filter,
             sort: None,
-            distinct: None,
             facets: None,
             highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
             highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
@@ -133,7 +128,6 @@ impl From<FacetSearchQuery> for SearchQuery {
             vector,
             attributes_to_search_on,
             hybrid,
-            ranking_score_threshold,
         }
     }
 }

meilisearch/src/routes/indexes/search.rs

@@ -19,10 +19,9 @@ use crate::extractors::authentication::GuardedData;
 use crate::extractors::sequential_extractor::SeqHandler;
 use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
 use crate::search::{
-    add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
+    add_search_rules, perform_search, HybridQuery, MatchingStrategy, SearchKind, SearchQuery,
-    RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,
+    SemanticRatio, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
+    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
-    DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
 };
 use crate::search_queue::SearchQueue;
 
@@ -51,8 +50,6 @@ pub struct SearchQueryGet {
     hits_per_page: Option<Param<usize>>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToRetrieve>)]
     attributes_to_retrieve: Option<CS<String>>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSearchRetrieveVectors>)]
-    retrieve_vectors: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToCrop>)]
     attributes_to_crop: Option<CS<String>>,
     #[deserr(default = Param(DEFAULT_CROP_LENGTH()), error = DeserrQueryParamError<InvalidSearchCropLength>)]
@@ -63,8 +60,6 @@ pub struct SearchQueryGet {
     filter: Option<String>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchSort>)]
     sort: Option<String>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSearchDistinct>)]
-    distinct: Option<String>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchShowMatchesPosition>)]
     show_matches_position: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchShowRankingScore>)]
@@ -87,21 +82,6 @@ pub struct SearchQueryGet {
     pub hybrid_embedder: Option<String>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchSemanticRatio>)]
     pub hybrid_semantic_ratio: Option<SemanticRatioGet>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSearchRankingScoreThreshold>)]
-    pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, deserr::Deserr)]
-#[deserr(try_from(String) = TryFrom::try_from -> InvalidSearchRankingScoreThreshold)]
-pub struct RankingScoreThresholdGet(RankingScoreThreshold);
-
-impl std::convert::TryFrom<String> for RankingScoreThresholdGet {
-    type Error = InvalidSearchRankingScoreThreshold;
-
-    fn try_from(s: String) -> Result<Self, Self::Error> {
-        let f: f64 = s.parse().map_err(|_| InvalidSearchRankingScoreThreshold)?;
-        Ok(RankingScoreThresholdGet(RankingScoreThreshold::try_from(f)?))
-    }
 }
 
 #[derive(Debug, Clone, Copy, Default, PartialEq, deserr::Deserr)]
@@ -157,13 +137,11 @@ impl From<SearchQueryGet> for SearchQuery {
             page: other.page.as_deref().copied(),
             hits_per_page: other.hits_per_page.as_deref().copied(),
             attributes_to_retrieve: other.attributes_to_retrieve.map(|o| o.into_iter().collect()),
-            retrieve_vectors: other.retrieve_vectors.0,
             attributes_to_crop: other.attributes_to_crop.map(|o| o.into_iter().collect()),
             crop_length: other.crop_length.0,
             attributes_to_highlight: other.attributes_to_highlight.map(|o| o.into_iter().collect()),
             filter,
             sort: other.sort.map(|attr| fix_sort_query_parameters(&attr)),
-            distinct: other.distinct,
             show_matches_position: other.show_matches_position.0,
             show_ranking_score: other.show_ranking_score.0,
             show_ranking_score_details: other.show_ranking_score_details.0,
@@ -174,7 +152,6 @@ impl From<SearchQueryGet> for SearchQuery {
             matching_strategy: other.matching_strategy,
             attributes_to_search_on: other.attributes_to_search_on.map(|o| o.into_iter().collect()),
             hybrid,
-            ranking_score_threshold: other.ranking_score_threshold.map(|o| o.0),
         }
     }
 }
@@ -228,12 +205,10 @@ pub async fn search_with_url_query(
     let features = index_scheduler.features();
 
     let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
-    let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
+
     let _permit = search_queue.try_get_search_permit().await?;
-    let search_result = tokio::task::spawn_blocking(move || {
+    let search_result =
-        perform_search(&index, query, search_kind, retrieve_vector)
+        tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
-    })
-    .await?;
     if let Ok(ref search_result) = search_result {
         aggregate.succeed(search_result);
     }
@@ -270,13 +245,10 @@ pub async fn search_with_post(
     let features = index_scheduler.features();
 
     let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
-    let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
 
     let _permit = search_queue.try_get_search_permit().await?;
-    let search_result = tokio::task::spawn_blocking(move || {
+    let search_result =
-        perform_search(&index, query, search_kind, retrieve_vectors)
+        tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
-    })
-    .await?;
     if let Ok(ref search_result) = search_result {
         aggregate.succeed(search_result);
         if search_result.degraded {
@@ -298,10 +270,11 @@ pub fn search_kind(
     features: RoFeatures,
 ) -> Result<SearchKind, ResponseError> {
     if query.vector.is_some() {
-        features.check_vector("Passing `vector` as a parameter")?;
+        features.check_vector("Passing `vector` as a query parameter")?;
     }
+
     if query.hybrid.is_some() {
-        features.check_vector("Passing `hybrid` as a parameter")?;
+        features.check_vector("Passing `hybrid` as a query parameter")?;
     }
 
     // regardless of anything, always do a keyword search when we don't have a vector and the query is whitespace or missing

meilisearch/src/routes/indexes/similar.rs

@@ -4,7 +4,11 @@ use deserr::actix_web::{AwebJson, AwebQueryParameter};
 use index_scheduler::IndexScheduler;
 use meilisearch_types::deserr::query_params::Param;
 use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
-use meilisearch_types::error::deserr_codes::*;
+use meilisearch_types::error::deserr_codes::{
+    InvalidEmbedder, InvalidSimilarAttributesToRetrieve, InvalidSimilarFilter, InvalidSimilarId,
+    InvalidSimilarLimit, InvalidSimilarOffset, InvalidSimilarShowRankingScore,
+    InvalidSimilarShowRankingScoreDetails,
+};
 use meilisearch_types::error::{ErrorCode as _, ResponseError};
 use meilisearch_types::index_uid::IndexUid;
 use meilisearch_types::keys::actions;
@@ -17,8 +21,8 @@ use crate::analytics::{Analytics, SimilarAggregator};
 use crate::extractors::authentication::GuardedData;
 use crate::extractors::sequential_extractor::SeqHandler;
 use crate::search::{
-    add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, SearchKind,
+    add_search_rules, perform_similar, SearchKind, SimilarQuery, SimilarResult,
-    SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
+    DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
 };
 
 pub fn configure(cfg: &mut web::ServiceConfig) {
@@ -38,7 +42,9 @@ pub async fn similar_get(
 ) -> Result<HttpResponse, ResponseError> {
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
 
-    let query = params.0.try_into()?;
+    let query = params.0.try_into().map_err(|code: InvalidSimilarId| {
+        ResponseError::from_msg(code.to_string(), code.error_code())
+    })?;
 
     let mut aggregate = SimilarAggregator::from_query(&query, &req);
 
@@ -93,8 +99,6 @@ async fn similar(
 
     features.check_vector("Using the similar API")?;
 
-    let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
-
     // Tenant token search_rules.
     if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
         add_search_rules(&mut query.filter, search_rules);
@@ -105,10 +109,8 @@ async fn similar(
     let (embedder_name, embedder) =
         SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
 
-    tokio::task::spawn_blocking(move || {
+    tokio::task::spawn_blocking(move || perform_similar(&index, query, embedder_name, embedder))
-        perform_similar(&index, query, embedder_name, embedder, retrieve_vectors)
+        .await?
-    })
-    .await?
 }
 
 #[derive(Debug, deserr::Deserr)]
@@ -122,35 +124,18 @@ pub struct SimilarQueryGet {
     limit: Param<usize>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSimilarAttributesToRetrieve>)]
     attributes_to_retrieve: Option<CS<String>>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSimilarRetrieveVectors>)]
-    retrieve_vectors: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSimilarFilter>)]
     filter: Option<String>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScore>)]
     show_ranking_score: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScoreDetails>)]
     show_ranking_score_details: Param<bool>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSimilarRankingScoreThreshold>, default)]
-    pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
     #[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
     pub embedder: Option<String>,
 }
 
-#[derive(Debug, Clone, Copy, PartialEq, deserr::Deserr)]
-#[deserr(try_from(String) = TryFrom::try_from -> InvalidSimilarRankingScoreThreshold)]
-pub struct RankingScoreThresholdGet(RankingScoreThresholdSimilar);
-
-impl std::convert::TryFrom<String> for RankingScoreThresholdGet {
-    type Error = InvalidSimilarRankingScoreThreshold;
-
-    fn try_from(s: String) -> Result<Self, Self::Error> {
-        let f: f64 = s.parse().map_err(|_| InvalidSimilarRankingScoreThreshold)?;
-        Ok(RankingScoreThresholdGet(RankingScoreThresholdSimilar::try_from(f)?))
-    }
-}
-
 impl TryFrom<SimilarQueryGet> for SimilarQuery {
-    type Error = ResponseError;
+    type Error = InvalidSimilarId;
 
     fn try_from(
         SimilarQueryGet {
@@ -158,12 +143,10 @@ impl TryFrom<SimilarQueryGet> for SimilarQuery {
             offset,
             limit,
             attributes_to_retrieve,
-            retrieve_vectors,
             filter,
             show_ranking_score,
             show_ranking_score_details,
             embedder,
-            ranking_score_threshold,
         }: SimilarQueryGet,
     ) -> Result<Self, Self::Error> {
         let filter = match filter {
@@ -175,18 +158,14 @@ impl TryFrom<SimilarQueryGet> for SimilarQuery {
         };
 
         Ok(SimilarQuery {
-            id: id.0.try_into().map_err(|code: InvalidSimilarId| {
+            id: id.0.try_into()?,
-                ResponseError::from_msg(code.to_string(), code.error_code())
-            })?,
             offset: offset.0,
             limit: limit.0,
             filter,
             embedder,
             attributes_to_retrieve: attributes_to_retrieve.map(|o| o.into_iter().collect()),
-            retrieve_vectors: retrieve_vectors.0,
             show_ranking_score: show_ranking_score.0,
             show_ranking_score_details: show_ranking_score_details.0,
-            ranking_score_threshold: ranking_score_threshold.map(|x| x.0),
         })
     }
 }

meilisearch/src/routes/multi_search.rs

@@ -15,7 +15,7 @@ use crate::extractors::authentication::{AuthenticationError, GuardedData};
 use crate::extractors::sequential_extractor::SeqHandler;
 use crate::routes::indexes::search::search_kind;
 use crate::search::{
-    add_search_rules, perform_search, RetrieveVectors, SearchQueryWithIndex, SearchResultWithIndex,
+    add_search_rules, perform_search, SearchQueryWithIndex, SearchResultWithIndex,
 };
 use crate::search_queue::SearchQueue;
 
@@ -83,14 +83,11 @@ pub async fn multi_search_with_post(
 
             let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)
                 .with_index(query_index)?;
-            let retrieve_vector =
-                RetrieveVectors::new(query.retrieve_vectors, features).with_index(query_index)?;
 
-            let search_result = tokio::task::spawn_blocking(move || {
+            let search_result =
-                perform_search(&index, query, search_kind, retrieve_vector)
+                tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind))
-            })
+                    .await
-            .await
+                    .with_index(query_index)?;
-            .with_index(query_index)?;
 
             search_results.push(SearchResultWithIndex {
                 index_uid: index_uid.into_inner(),

meilisearch/src/search.rs

@@ -15,7 +15,6 @@ use meilisearch_types::error::{Code, ResponseError};
 use meilisearch_types::heed::RoTxn;
 use meilisearch_types::index_uid::IndexUid;
 use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
-use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
 use meilisearch_types::milli::vector::Embedder;
 use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, TimeBudget};
 use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
@@ -60,8 +59,6 @@ pub struct SearchQuery {
     pub hits_per_page: Option<usize>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToRetrieve>)]
     pub attributes_to_retrieve: Option<BTreeSet<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchRetrieveVectors>)]
-    pub retrieve_vectors: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToCrop>)]
     pub attributes_to_crop: Option<Vec<String>>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchCropLength>, default = DEFAULT_CROP_LENGTH())]
@@ -78,8 +75,6 @@ pub struct SearchQuery {
     pub filter: Option<Value>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchSort>)]
     pub sort: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchDistinct>)]
-    pub distinct: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchFacets>)]
     pub facets: Option<Vec<String>>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchHighlightPreTag>, default = DEFAULT_HIGHLIGHT_PRE_TAG())]
@@ -92,44 +87,6 @@ pub struct SearchQuery {
     pub matching_strategy: MatchingStrategy,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
     pub attributes_to_search_on: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
-    pub ranking_score_threshold: Option<RankingScoreThreshold>,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Deserr)]
-#[deserr(try_from(f64) = TryFrom::try_from -> InvalidSearchRankingScoreThreshold)]
-pub struct RankingScoreThreshold(f64);
-
-impl std::convert::TryFrom<f64> for RankingScoreThreshold {
-    type Error = InvalidSearchRankingScoreThreshold;
-
-    fn try_from(f: f64) -> Result<Self, Self::Error> {
-        // the suggested "fix" is: `!(0.0..=1.0).contains(&f)`` which is allegedly less readable
-        #[allow(clippy::manual_range_contains)]
-        if f > 1.0 || f < 0.0 {
-            Err(InvalidSearchRankingScoreThreshold)
-        } else {
-            Ok(RankingScoreThreshold(f))
-        }
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Deserr)]
-#[deserr(try_from(f64) = TryFrom::try_from -> InvalidSimilarRankingScoreThreshold)]
-pub struct RankingScoreThresholdSimilar(f64);
-
-impl std::convert::TryFrom<f64> for RankingScoreThresholdSimilar {
-    type Error = InvalidSimilarRankingScoreThreshold;
-
-    fn try_from(f: f64) -> Result<Self, Self::Error> {
-        // the suggested "fix" is: `!(0.0..=1.0).contains(&f)`` which is allegedly less readable
-        #[allow(clippy::manual_range_contains)]
-        if f > 1.0 || f < 0.0 {
-            Err(InvalidSimilarRankingScoreThreshold)
-        } else {
-            Ok(Self(f))
-        }
-    }
 }
 
 // Since this structure is logged A LOT we're going to reduce the number of things it logs to the bare minimum.
@@ -146,7 +103,6 @@ impl fmt::Debug for SearchQuery {
             page,
             hits_per_page,
             attributes_to_retrieve,
-            retrieve_vectors,
             attributes_to_crop,
             crop_length,
             attributes_to_highlight,
@@ -155,14 +111,12 @@ impl fmt::Debug for SearchQuery {
             show_ranking_score_details,
             filter,
             sort,
-            distinct,
             facets,
             highlight_pre_tag,
             highlight_post_tag,
             crop_marker,
             matching_strategy,
             attributes_to_search_on,
-            ranking_score_threshold,
         } = self;
 
         let mut debug = f.debug_struct("SearchQuery");
@@ -180,9 +134,6 @@ impl fmt::Debug for SearchQuery {
         if let Some(q) = q {
             debug.field("q", &q);
         }
-        if *retrieve_vectors {
-            debug.field("retrieve_vectors", &retrieve_vectors);
-        }
         if let Some(v) = vector {
             if v.len() < 10 {
                 debug.field("vector", &v);
@@ -205,9 +156,6 @@ impl fmt::Debug for SearchQuery {
         if let Some(sort) = sort {
             debug.field("sort", &sort);
         }
-        if let Some(distinct) = distinct {
-            debug.field("distinct", &distinct);
-        }
         if let Some(facets) = facets {
             debug.field("facets", &facets);
         }
@@ -240,9 +188,6 @@ impl fmt::Debug for SearchQuery {
         debug.field("highlight_pre_tag", &highlight_pre_tag);
         debug.field("highlight_post_tag", &highlight_post_tag);
         debug.field("crop_marker", &crop_marker);
-        if let Some(ranking_score_threshold) = ranking_score_threshold {
-            debug.field("ranking_score_threshold", &ranking_score_threshold);
-        }
 
         debug.finish()
     }
@@ -383,8 +328,6 @@ pub struct SearchQueryWithIndex {
     pub hits_per_page: Option<usize>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToRetrieve>)]
     pub attributes_to_retrieve: Option<BTreeSet<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchRetrieveVectors>)]
-    pub retrieve_vectors: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToCrop>)]
     pub attributes_to_crop: Option<Vec<String>>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchCropLength>, default = DEFAULT_CROP_LENGTH())]
@@ -401,8 +344,6 @@ pub struct SearchQueryWithIndex {
     pub filter: Option<Value>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchSort>)]
     pub sort: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchDistinct>)]
-    pub distinct: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchFacets>)]
     pub facets: Option<Vec<String>>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchHighlightPreTag>, default = DEFAULT_HIGHLIGHT_PRE_TAG())]
@@ -415,8 +356,6 @@ pub struct SearchQueryWithIndex {
     pub matching_strategy: MatchingStrategy,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
     pub attributes_to_search_on: Option<Vec<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
-    pub ranking_score_threshold: Option<RankingScoreThreshold>,
 }
 
 impl SearchQueryWithIndex {
@@ -430,7 +369,6 @@ impl SearchQueryWithIndex {
             page,
             hits_per_page,
             attributes_to_retrieve,
-            retrieve_vectors,
             attributes_to_crop,
             crop_length,
             attributes_to_highlight,
@@ -439,7 +377,6 @@ impl SearchQueryWithIndex {
             show_matches_position,
             filter,
             sort,
-            distinct,
             facets,
             highlight_pre_tag,
             highlight_post_tag,
@@ -447,7 +384,6 @@ impl SearchQueryWithIndex {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
-            ranking_score_threshold,
         } = self;
         (
             index_uid,
@@ -459,7 +395,6 @@ impl SearchQueryWithIndex {
                 page,
                 hits_per_page,
                 attributes_to_retrieve,
-                retrieve_vectors,
                 attributes_to_crop,
                 crop_length,
                 attributes_to_highlight,
@@ -468,7 +403,6 @@ impl SearchQueryWithIndex {
                 show_matches_position,
                 filter,
                 sort,
-                distinct,
                 facets,
                 highlight_pre_tag,
                 highlight_post_tag,
@@ -476,7 +410,6 @@ impl SearchQueryWithIndex {
                 matching_strategy,
                 attributes_to_search_on,
                 hybrid,
-                ranking_score_threshold,
                 // do not use ..Default::default() here,
                 // rather add any missing field from `SearchQuery` to `SearchQueryWithIndex`
             },
@@ -499,14 +432,10 @@ pub struct SimilarQuery {
     pub embedder: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
     pub attributes_to_retrieve: Option<BTreeSet<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSimilarRetrieveVectors>)]
-    pub retrieve_vectors: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScore>, default)]
     pub show_ranking_score: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScoreDetails>, default)]
     pub show_ranking_score_details: bool,
-    #[deserr(default, error = DeserrJsonError<InvalidSimilarRankingScoreThreshold>, default)]
-    pub ranking_score_threshold: Option<RankingScoreThresholdSimilar>,
 }
 
 #[derive(Debug, Clone, PartialEq, Deserr)]
@@ -548,8 +477,6 @@ pub enum MatchingStrategy {
     Last,
     /// All query words are mandatory
     All,
-    /// Remove query words from the most frequent to the least
-    Frequency,
 }
 
 impl Default for MatchingStrategy {
@@ -563,7 +490,6 @@ impl From<MatchingStrategy> for TermsMatchingStrategy {
         match other {
             MatchingStrategy::Last => Self::Last,
             MatchingStrategy::All => Self::All,
-            MatchingStrategy::Frequency => Self::Frequency,
         }
     }
 }
@@ -735,13 +661,6 @@ fn prepare_search<'t>(
 ) -> Result<(milli::Search<'t>, bool, usize, usize), MeilisearchHttpError> {
     let mut search = index.search(rtxn);
     search.time_budget(time_budget);
-    if let Some(ranking_score_threshold) = query.ranking_score_threshold {
-        search.ranking_score_threshold(ranking_score_threshold.0);
-    }
-
-    if let Some(distinct) = &query.distinct {
-        search.distinct(distinct.clone());
-    }
 
     match search_kind {
         SearchKind::KeywordOnly => {
@@ -783,16 +702,11 @@ fn prepare_search<'t>(
         .unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
 
     search.exhaustive_number_hits(is_finite_pagination);
-    search.scoring_strategy(
+    search.scoring_strategy(if query.show_ranking_score || query.show_ranking_score_details {
-        if query.show_ranking_score
+        ScoringStrategy::Detailed
-            || query.show_ranking_score_details
+    } else {
-            || query.ranking_score_threshold.is_some()
+        ScoringStrategy::Skip
-        {
+    });
-            ScoringStrategy::Detailed
-        } else {
-            ScoringStrategy::Skip
-        },
-    );
 
     // compute the offset on the limit depending on the pagination mode.
     let (offset, limit) = if is_finite_pagination {
@@ -837,7 +751,6 @@ pub fn perform_search(
     index: &Index,
     query: SearchQuery,
     search_kind: SearchKind,
-    retrieve_vectors: RetrieveVectors,
 ) -> Result<SearchResult, MeilisearchHttpError> {
     let before_search = Instant::now();
     let rtxn = index.read_txn()?;
@@ -871,37 +784,32 @@ pub fn perform_search(
 
     let SearchQuery {
         q,
+        vector: _,
+        hybrid: _,
+        // already computed from prepare_search
+        offset: _,
         limit,
         page,
         hits_per_page,
         attributes_to_retrieve,
-        // use the enum passed as parameter
-        retrieve_vectors: _,
         attributes_to_crop,
         crop_length,
         attributes_to_highlight,
         show_matches_position,
         show_ranking_score,
         show_ranking_score_details,
+        filter: _,
         sort,
         facets,
         highlight_pre_tag,
         highlight_post_tag,
         crop_marker,
-        // already used in prepare_search
-        vector: _,
-        hybrid: _,
-        offset: _,
-        ranking_score_threshold: _,
         matching_strategy: _,
         attributes_to_search_on: _,
-        filter: _,
-        distinct: _,
     } = query;
 
     let format = AttributesFormat {
         attributes_to_retrieve,
-        retrieve_vectors,
         attributes_to_highlight,
         attributes_to_crop,
         crop_length,
@@ -985,7 +893,6 @@ pub fn perform_search(
 
 struct AttributesFormat {
     attributes_to_retrieve: Option<BTreeSet<String>>,
-    retrieve_vectors: RetrieveVectors,
     attributes_to_highlight: Option<HashSet<String>>,
     attributes_to_crop: Option<Vec<String>>,
     crop_length: usize,
@@ -998,36 +905,6 @@ struct AttributesFormat {
     show_ranking_score_details: bool,
 }
 
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum RetrieveVectors {
-    /// Do not touch the `_vectors` field
-    ///
-    /// this is the behavior when the vectorStore feature is disabled
-    Ignore,
-    /// Remove the `_vectors` field
-    ///
-    /// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `false`
-    Hide,
-    /// Retrieve vectors from the DB and merge them into the `_vectors` field
-    ///
-    /// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `true`
-    Retrieve,
-}
-
-impl RetrieveVectors {
-    pub fn new(
-        retrieve_vector: bool,
-        features: index_scheduler::RoFeatures,
-    ) -> Result<Self, index_scheduler::Error> {
-        match (retrieve_vector, features.check_vector("Passing `retrieveVectors` as a parameter")) {
-            (true, Ok(())) => Ok(Self::Retrieve),
-            (true, Err(error)) => Err(error),
-            (false, Ok(())) => Ok(Self::Hide),
-            (false, Err(_)) => Ok(Self::Ignore),
-        }
-    }
-}
-
 fn make_hits(
     index: &Index,
     rtxn: &RoTxn<'_>,
@@ -1037,32 +914,10 @@ fn make_hits(
     document_scores: Vec<Vec<ScoreDetails>>,
 ) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
     let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
-    let displayed_ids =
+    let displayed_ids = index
-        index.displayed_fields_ids(rtxn)?.map(|fields| fields.into_iter().collect::<BTreeSet<_>>());
+        .displayed_fields_ids(rtxn)?
-
+        .map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
-    let vectors_fid = fields_ids_map.id(milli::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME);
+        .unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
-
-    let vectors_is_hidden = match (&displayed_ids, vectors_fid) {
-        // displayed_ids is a wildcard, so `_vectors` can be displayed regardless of its fid
-        (None, _) => false,
-        // displayed_ids is a finite list, and `_vectors` cannot be part of it because it is not an existing field
-        (Some(_), None) => true,
-        // displayed_ids is a finit list, so hide if `_vectors` is not part of it
-        (Some(map), Some(vectors_fid)) => map.contains(&vectors_fid),
-    };
-
-    let retrieve_vectors = if let RetrieveVectors::Retrieve = format.retrieve_vectors {
-        if vectors_is_hidden {
-            RetrieveVectors::Hide
-        } else {
-            RetrieveVectors::Retrieve
-        }
-    } else {
-        format.retrieve_vectors
-    };
-
-    let displayed_ids =
-        displayed_ids.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
     let fids = |attrs: &BTreeSet<String>| {
         let mut ids = BTreeSet::new();
         for attr in attrs {
@@ -1085,7 +940,6 @@ fn make_hits(
         .intersection(&displayed_ids)
         .cloned()
         .collect();
-
     let attr_to_highlight = format.attributes_to_highlight.unwrap_or_default();
     let attr_to_crop = format.attributes_to_crop.unwrap_or_default();
     let formatted_options = compute_formatted_options(
@@ -1119,48 +973,18 @@ fn make_hits(
     formatter_builder.highlight_prefix(format.highlight_pre_tag);
     formatter_builder.highlight_suffix(format.highlight_post_tag);
     let mut documents = Vec::new();
-    let embedding_configs = index.embedding_configs(rtxn)?;
     let documents_iter = index.documents(rtxn, documents_ids)?;
-    for ((id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
+    for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
         // First generate a document with all the displayed fields
         let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
 
-        let add_vectors_fid =
-            vectors_fid.filter(|_fid| retrieve_vectors == RetrieveVectors::Retrieve);
-
         // select the attributes to retrieve
         let attributes_to_retrieve = to_retrieve_ids
             .iter()
-            // skip the vectors_fid if RetrieveVectors::Hide
-            .filter(|fid| match vectors_fid {
-                Some(vectors_fid) => {
-                    !(retrieve_vectors == RetrieveVectors::Hide && **fid == vectors_fid)
-                }
-                None => true,
-            })
-            // need to retrieve the existing `_vectors` field if the `RetrieveVectors::Retrieve`
-            .chain(add_vectors_fid.iter())
             .map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
         let mut document =
             permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
 
-        if retrieve_vectors == RetrieveVectors::Retrieve {
-            let mut vectors = match document.remove("_vectors") {
-                Some(Value::Object(map)) => map,
-                _ => Default::default(),
-            };
-            for (name, vector) in index.embeddings(rtxn, id)? {
-                let user_provided = embedding_configs
-                    .iter()
-                    .find(|conf| conf.name == name)
-                    .is_some_and(|conf| conf.user_provided.contains(id));
-                let embeddings =
-                    ExplicitVectors { embeddings: Some(vector.into()), regenerate: !user_provided };
-                vectors.insert(name, serde_json::to_value(embeddings)?);
-            }
-            document.insert("_vectors".into(), vectors.into());
-        }
-
         let (matches_position, formatted) = format_fields(
             &displayed_document,
             &fields_ids_map,
@@ -1230,7 +1054,6 @@ pub fn perform_similar(
     query: SimilarQuery,
     embedder_name: String,
     embedder: Arc<Embedder>,
-    retrieve_vectors: RetrieveVectors,
 ) -> Result<SimilarResult, ResponseError> {
     let before_search = Instant::now();
     let rtxn = index.read_txn()?;
@@ -1242,10 +1065,8 @@ pub fn perform_similar(
         filter: _,
         embedder: _,
         attributes_to_retrieve,
-        retrieve_vectors: _,
         show_ranking_score,
         show_ranking_score_details,
-        ranking_score_threshold,
     } = query;
 
     // using let-else rather than `?` so that the borrow checker identifies we're always returning here,
@@ -1269,10 +1090,6 @@ pub fn perform_similar(
         }
     }
 
-    if let Some(ranking_score_threshold) = ranking_score_threshold {
-        similar.ranking_score_threshold(ranking_score_threshold.0);
-    }
-
     let milli::SearchResult {
         documents_ids,
         matching_words: _,
@@ -1289,7 +1106,6 @@ pub fn perform_similar(
 
     let format = AttributesFormat {
         attributes_to_retrieve,
-        retrieve_vectors,
         attributes_to_highlight: None,
         attributes_to_crop: None,
         crop_length: DEFAULT_CROP_LENGTH(),

meilisearch/src/search_queue.rs

@@ -40,9 +40,8 @@ pub struct Permit {
 
 impl Drop for Permit {
     fn drop(&mut self) {
-        let sender = self.sender.clone();
         // if the channel is closed then the whole instance is down
-        std::mem::drop(tokio::spawn(async move { sender.send(()).await }));
+        let _ = futures::executor::block_on(self.sender.send(()));
     }
 }
 

meilisearch/tests/common/index.rs

@@ -182,10 +182,14 @@ impl Index<'_> {
         self.service.get(url).await
     }
 
-    pub async fn get_document(&self, id: u64, options: Option<Value>) -> (Value, StatusCode) {
+    pub async fn get_document(
+        &self,
+        id: u64,
+        options: Option<GetDocumentOptions>,
+    ) -> (Value, StatusCode) {
         let mut url = format!("/indexes/{}/documents/{}", urlencode(self.uid.as_ref()), id);
-        if let Some(options) = options {
+        if let Some(fields) = options.and_then(|o| o.fields) {
-            write!(url, "?{}", yaup::to_string(&options).unwrap()).unwrap();
+            let _ = write!(url, "?fields={}", fields.join(","));
         }
         self.service.get(url).await
     }
@@ -201,11 +205,18 @@ impl Index<'_> {
     }
 
     pub async fn get_all_documents(&self, options: GetAllDocumentsOptions) -> (Value, StatusCode) {
-        let url = format!(
+        let mut url = format!("/indexes/{}/documents?", urlencode(self.uid.as_ref()));
-            "/indexes/{}/documents?{}",
+        if let Some(limit) = options.limit {
-            urlencode(self.uid.as_ref()),
+            let _ = write!(url, "limit={}&", limit);
-            yaup::to_string(&options).unwrap()
+        }
-        );
+
+        if let Some(offset) = options.offset {
+            let _ = write!(url, "offset={}&", offset);
+        }
+
+        if let Some(attributes_to_retrieve) = options.attributes_to_retrieve {
+            let _ = write!(url, "fields={}&", attributes_to_retrieve.join(","));
+        }
 
         self.service.get(url).await
     }
@@ -424,11 +435,13 @@ impl Index<'_> {
     }
 }
 
-#[derive(Debug, Default, serde::Serialize)]
+pub struct GetDocumentOptions {
-#[serde(rename_all = "camelCase")]
+    pub fields: Option<Vec<&'static str>>,
+}
+
+#[derive(Debug, Default)]
 pub struct GetAllDocumentsOptions {
     pub limit: Option<usize>,
     pub offset: Option<usize>,
-    pub retrieve_vectors: bool,
+    pub attributes_to_retrieve: Option<Vec<&'static str>>,
-    pub fields: Option<Vec<&'static str>>,
 }

meilisearch/tests/common/mod.rs

@@ -6,7 +6,7 @@ pub mod service;
 use std::fmt::{self, Display};
 
 #[allow(unused)]
-pub use index::GetAllDocumentsOptions;
+pub use index::{GetAllDocumentsOptions, GetDocumentOptions};
 use meili_snap::json_string;
 use serde::{Deserialize, Serialize};
 #[allow(unused)]
@@ -65,14 +65,7 @@ impl Display for Value {
         write!(
             f,
             "{}",
-            json_string!(self, {
+            json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]" })
-                ".enqueuedAt" => "[date]",
-                ".startedAt" => "[date]",
-                ".finishedAt" => "[date]",
-                ".duration" => "[duration]",
-                ".processingTimeMs" => "[duration]",
-                ".details.embedders.*.url" => "[url]"
-            })
         )
     }
 }

meilisearch/tests/documents/errors.rs

@@ -795,70 +795,3 @@ async fn fetch_document_by_filter() {
     }
     "###);
 }
-
-#[actix_rt::test]
-async fn retrieve_vectors() {
-    let server = Server::new().await;
-    let index = server.index("doggo");
-
-    // GET ALL DOCUMENTS BY QUERY
-    let (response, _code) = index.get_all_documents_raw("?retrieveVectors=tamo").await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `tamo` as a boolean, expected either `true` or `false`",
-      "code": "invalid_document_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
-    }
-    "###);
-    let (response, _code) = index.get_all_documents_raw("?retrieveVectors=true").await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
-      "code": "feature_not_enabled",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
-    }
-    "###);
-
-    // FETCH ALL DOCUMENTS BY POST
-    let (response, _code) =
-        index.get_document_by_filter(json!({ "retrieveVectors": "tamo" })).await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"tamo\"`",
-      "code": "invalid_document_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
-    }
-    "###);
-    let (response, _code) = index.get_document_by_filter(json!({ "retrieveVectors": true })).await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
-      "code": "feature_not_enabled",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
-    }
-    "###);
-
-    // GET A SINGLE DOCUMENT
-    let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": "tamo"}))).await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `tamo` as a boolean, expected either `true` or `false`",
-      "code": "invalid_document_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
-    }
-    "###);
-    let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": true}))).await;
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
-      "code": "feature_not_enabled",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
-    }
-    "###);
-}

meilisearch/tests/documents/get_documents.rs

@@ -4,7 +4,7 @@ use meili_snap::*;
 use urlencoding::encode as urlencode;
 
 use crate::common::encoder::Encoder;
-use crate::common::{GetAllDocumentsOptions, Server, Value};
+use crate::common::{GetAllDocumentsOptions, GetDocumentOptions, Server, Value};
 use crate::json;
 
 // TODO: partial test since we are testing error, amd error is not yet fully implemented in
@@ -59,7 +59,8 @@ async fn get_document() {
         })
     );
 
-    let (response, code) = index.get_document(0, Some(json!({ "fields": ["id"] }))).await;
+    let (response, code) =
+        index.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["id"]) })).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -68,8 +69,9 @@ async fn get_document() {
         })
     );
 
-    let (response, code) =
+    let (response, code) = index
-        index.get_document(0, Some(json!({ "fields": ["nested.content"] }))).await;
+        .get_document(0, Some(GetDocumentOptions { fields: Some(vec!["nested.content"]) }))
+        .await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -209,7 +211,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            fields: Some(vec!["name"]),
+            attributes_to_retrieve: Some(vec!["name"]),
             ..Default::default()
         })
         .await;
@@ -223,19 +225,9 @@ async fn test_get_all_documents_attributes_to_retrieve() {
     assert_eq!(response["limit"], json!(20));
     assert_eq!(response["total"], json!(77));
 
-    let (response, code) = index.get_all_documents_raw("?fields=").await;
-    assert_eq!(code, 200);
-    assert_eq!(response["results"].as_array().unwrap().len(), 20);
-    for results in response["results"].as_array().unwrap() {
-        assert_eq!(results.as_object().unwrap().keys().count(), 0);
-    }
-    assert_eq!(response["offset"], json!(0));
-    assert_eq!(response["limit"], json!(20));
-    assert_eq!(response["total"], json!(77));
-
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            fields: Some(vec!["wrong"]),
+            attributes_to_retrieve: Some(vec![]),
             ..Default::default()
         })
         .await;
@@ -250,7 +242,22 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            fields: Some(vec!["name", "tags"]),
+            attributes_to_retrieve: Some(vec!["wrong"]),
+            ..Default::default()
+        })
+        .await;
+    assert_eq!(code, 200);
+    assert_eq!(response["results"].as_array().unwrap().len(), 20);
+    for results in response["results"].as_array().unwrap() {
+        assert_eq!(results.as_object().unwrap().keys().count(), 0);
+    }
+    assert_eq!(response["offset"], json!(0));
+    assert_eq!(response["limit"], json!(20));
+    assert_eq!(response["total"], json!(77));
+
+    let (response, code) = index
+        .get_all_documents(GetAllDocumentsOptions {
+            attributes_to_retrieve: Some(vec!["name", "tags"]),
             ..Default::default()
         })
         .await;
@@ -263,7 +270,10 @@ async fn test_get_all_documents_attributes_to_retrieve() {
     }
 
     let (response, code) = index
-        .get_all_documents(GetAllDocumentsOptions { fields: Some(vec!["*"]), ..Default::default() })
+        .get_all_documents(GetAllDocumentsOptions {
+            attributes_to_retrieve: Some(vec!["*"]),
+            ..Default::default()
+        })
         .await;
     assert_eq!(code, 200);
     assert_eq!(response["results"].as_array().unwrap().len(), 20);
@@ -273,7 +283,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            fields: Some(vec!["*", "wrong"]),
+            attributes_to_retrieve: Some(vec!["*", "wrong"]),
             ..Default::default()
         })
         .await;
@@ -306,10 +316,12 @@ async fn get_document_s_nested_attributes_to_retrieve() {
     assert_eq!(code, 202);
     index.wait_task(1).await;
 
-    let (response, code) = index.get_document(0, Some(json!({ "fields": ["content"] }))).await;
+    let (response, code) =
+        index.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
     assert_eq!(code, 200);
     assert_eq!(response, json!({}));
-    let (response, code) = index.get_document(1, Some(json!({ "fields": ["content"] }))).await;
+    let (response, code) =
+        index.get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -321,7 +333,9 @@ async fn get_document_s_nested_attributes_to_retrieve() {
         })
     );
 
-    let (response, code) = index.get_document(0, Some(json!({ "fields": ["content.truc"] }))).await;
+    let (response, code) = index
+        .get_document(0, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
+        .await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -329,7 +343,9 @@ async fn get_document_s_nested_attributes_to_retrieve() {
             "content.truc": "foobar",
         })
     );
-    let (response, code) = index.get_document(1, Some(json!({ "fields": ["content.truc"] }))).await;
+    let (response, code) = index
+        .get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
+        .await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -524,207 +540,3 @@ async fn get_document_by_filter() {
     }
     "###);
 }
-
-#[actix_rt::test]
-async fn get_document_with_vectors() {
-    let server = Server::new().await;
-    let index = server.index("doggo");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "manual": {
-                  "source": "userProvided",
-                  "dimensions": 3,
-              }
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
-      {"id": 1, "name": "echo", "_vectors": { "manual": null }},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    // by default you shouldn't see the `_vectors` object
-    let (documents, _code) = index.get_all_documents(Default::default()).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir"
-        },
-        {
-          "id": 1,
-          "name": "echo"
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-    let (documents, _code) = index.get_document(0, None).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "id": 0,
-      "name": "kefir"
-    }
-    "###);
-
-    // if we try to retrieve the vectors with the `fields` parameter they
-    // still shouldn't be displayed
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions {
-            fields: Some(vec!["name", "_vectors"]),
-            ..Default::default()
-        })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "name": "kefir"
-        },
-        {
-          "name": "echo"
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-    let (documents, _code) =
-        index.get_document(0, Some(json!({"fields": ["name", "_vectors"]}))).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "name": "kefir"
-    }
-    "###);
-
-    // If we specify the retrieve vectors boolean and nothing else we should get the vectors
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  0.0,
-                  0.0,
-                  0.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 1,
-          "name": "echo",
-          "_vectors": {}
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-    let (documents, _code) = index.get_document(0, Some(json!({"retrieveVectors": true}))).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "id": 0,
-      "name": "kefir",
-      "_vectors": {
-        "manual": {
-          "embeddings": [
-            [
-              0.0,
-              0.0,
-              0.0
-            ]
-          ],
-          "regenerate": false
-        }
-      }
-    }
-    "###);
-
-    // If we specify the retrieve vectors boolean and exclude vectors form the `fields` we should still get the vectors
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions {
-            retrieve_vectors: true,
-            fields: Some(vec!["name"]),
-            ..Default::default()
-        })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "name": "kefir",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  0.0,
-                  0.0,
-                  0.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "name": "echo",
-          "_vectors": {}
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-    let (documents, _code) =
-        index.get_document(0, Some(json!({"retrieveVectors": true, "fields": ["name"]}))).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "name": "kefir",
-      "_vectors": {
-        "manual": {
-          "embeddings": [
-            [
-              0.0,
-              0.0,
-              0.0
-            ]
-          ],
-          "regenerate": false
-        }
-      }
-    }
-    "###);
-}

meilisearch/tests/dumps/mod.rs

@@ -1938,210 +1938,3 @@ async fn import_dump_v6_containing_experimental_features() {
         })
         .await;
 }
-
-// In this test we must generate the dump ourselves to ensure the
-// `user provided` vectors are well set
-#[actix_rt::test]
-#[cfg_attr(target_os = "windows", ignore)]
-async fn generate_and_import_dump_containing_vectors() {
-    let temp = tempfile::tempdir().unwrap();
-    let mut opt = default_settings(temp.path());
-    let server = Server::new_with_options(opt.clone()).await.unwrap();
-    let (code, _) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-    let index = server.index("pets");
-    let (response, code) = index
-        .update_settings(json!(
-        {
-            "embedders": {
-                "doggo_embedder": {
-                    "source": "huggingFace",
-                    "model": "sentence-transformers/all-MiniLM-L6-v2",
-                    "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
-                    "documentTemplate": "{{doc.doggo}}",
-                }
-            }
-        }
-        ))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(response);
-    let (response, code) = index
-        .add_documents(
-            json!([
-                {"id": 0, "doggo": "kefir", "_vectors": { "doggo_embedder": vec![0; 384] }},
-                {"id": 1, "doggo": "echo", "_vectors": { "doggo_embedder": { "regenerate": false, "embeddings": vec![1; 384] }}},
-                {"id": 2, "doggo": "intel", "_vectors": { "doggo_embedder": { "regenerate": true, "embeddings": vec![2; 384] }}},
-                {"id": 3, "doggo": "bill", "_vectors": { "doggo_embedder": { "regenerate": true }}},
-                {"id": 4, "doggo": "max" },
-            ]),
-            None,
-        )
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(response);
-
-    let (response, code) = server.create_dump().await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(response["status"], @r###""succeeded""###);
-
-    // ========= We made a dump, now we should clear the DB and try to import our dump
-    drop(server);
-    tokio::fs::remove_dir_all(&opt.db_path).await.unwrap();
-    let dump_name = format!("{}.dump", response["details"]["dumpUid"].as_str().unwrap());
-    let dump_path = opt.dump_dir.join(dump_name);
-    assert!(dump_path.exists(), "path: `{}`", dump_path.display());
-
-    opt.import_dump = Some(dump_path);
-    // NOTE: We shouldn't have to change the database path but I lost one hour
-    // because of a « bad path » error and that fixed it.
-    opt.db_path = temp.path().join("data.ms");
-
-    let mut server = Server::new_auth_with_options(opt, temp).await;
-    server.use_api_key("MASTER_KEY");
-
-    let (indexes, code) = server.list_indexes(None, None).await;
-    assert_eq!(code, 200, "{indexes}");
-
-    snapshot!(indexes["results"].as_array().unwrap().len(), @"1");
-    snapshot!(indexes["results"][0]["uid"], @r###""pets""###);
-    snapshot!(indexes["results"][0]["primaryKey"], @r###""id""###);
-
-    let (response, code) = server.get_features().await;
-    meili_snap::snapshot!(code, @"200 OK");
-    meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let index = server.index("pets");
-
-    let (response, code) = index.settings().await;
-    meili_snap::snapshot!(code, @"200 OK");
-    meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
-    {
-      "displayedAttributes": [
-        "*"
-      ],
-      "searchableAttributes": [
-        "*"
-      ],
-      "filterableAttributes": [],
-      "sortableAttributes": [],
-      "rankingRules": [
-        "words",
-        "typo",
-        "proximity",
-        "attribute",
-        "sort",
-        "exactness"
-      ],
-      "stopWords": [],
-      "nonSeparatorTokens": [],
-      "separatorTokens": [],
-      "dictionary": [],
-      "synonyms": {},
-      "distinctAttribute": null,
-      "proximityPrecision": "byWord",
-      "typoTolerance": {
-        "enabled": true,
-        "minWordSizeForTypos": {
-          "oneTypo": 5,
-          "twoTypos": 9
-        },
-        "disableOnWords": [],
-        "disableOnAttributes": []
-      },
-      "faceting": {
-        "maxValuesPerFacet": 100,
-        "sortFacetValuesBy": {
-          "*": "alpha"
-        }
-      },
-      "pagination": {
-        "maxTotalHits": 1000
-      },
-      "embedders": {
-        "doggo_embedder": {
-          "source": "huggingFace",
-          "model": "sentence-transformers/all-MiniLM-L6-v2",
-          "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
-          "documentTemplate": "{{doc.doggo}}"
-        }
-      },
-      "searchCutoffMs": null
-    }
-    "###);
-
-    index
-        .search(json!({"retrieveVectors": true}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(json_string!(response["hits"], { "[]._vectors.doggo_embedder.embeddings" => "[vector]" }), @r###"
-            [
-              {
-                "id": 0,
-                "doggo": "kefir",
-                "_vectors": {
-                  "doggo_embedder": {
-                    "embeddings": "[vector]",
-                    "regenerate": false
-                  }
-                }
-              },
-              {
-                "id": 1,
-                "doggo": "echo",
-                "_vectors": {
-                  "doggo_embedder": {
-                    "embeddings": "[vector]",
-                    "regenerate": false
-                  }
-                }
-              },
-              {
-                "id": 2,
-                "doggo": "intel",
-                "_vectors": {
-                  "doggo_embedder": {
-                    "embeddings": "[vector]",
-                    "regenerate": true
-                  }
-                }
-              },
-              {
-                "id": 3,
-                "doggo": "bill",
-                "_vectors": {
-                  "doggo_embedder": {
-                    "embeddings": "[vector]",
-                    "regenerate": true
-                  }
-                }
-              },
-              {
-                "id": 4,
-                "doggo": "max",
-                "_vectors": {
-                  "doggo_embedder": {
-                    "embeddings": "[vector]",
-                    "regenerate": true
-                  }
-                }
-              }
-            ]
-            "###);
-        })
-        .await;
-}

meilisearch/tests/dumps/snapshots/mod.rs/generate_and_import_dump_containing_vectors/1.snap

@@ -1,25 +0,0 @@
----
-source: meilisearch/tests/dumps/mod.rs
----
-{
-  "uid": 0,
-  "indexUid": "pets",
-  "status": "succeeded",
-  "type": "settingsUpdate",
-  "canceledBy": null,
-  "details": {
-    "embedders": {
-      "doggo_embedder": {
-        "source": "huggingFace",
-        "model": "sentence-transformers/all-MiniLM-L6-v2",
-        "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
-        "documentTemplate": "{{doc.doggo}}"
-      }
-    }
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/dumps/snapshots/mod.rs/generate_and_import_dump_containing_vectors/2.snap

@@ -1,19 +0,0 @@
----
-source: meilisearch/tests/dumps/mod.rs
----
-{
-  "uid": 1,
-  "indexUid": "pets",
-  "status": "succeeded",
-  "type": "documentAdditionOrUpdate",
-  "canceledBy": null,
-  "details": {
-    "receivedDocuments": 5,
-    "indexedDocuments": 5
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/integration.rs

@@ -13,7 +13,6 @@ mod snapshot;
 mod stats;
 mod swap_indexes;
 mod tasks;
-mod vector;
 
 // Tests are isolated by features in different modules to allow better readability, test
 // targetability, and improved incremental compilation times.

meilisearch/tests/search/distinct.rs

@@ -107,39 +107,6 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
     ])
 });
 
-static NESTED_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
-    json!([
-      {
-        "id": 1,
-        "description": "Leather Jacket",
-        "brand": "Lee Jeans",
-        "product_id": "123456",
-        "color": { "main": "Brown", "pattern": "stripped" },
-      },
-      {
-        "id": 2,
-        "description": "Leather Jacket",
-        "brand": "Lee Jeans",
-        "product_id": "123456",
-        "color": { "main": "Black", "pattern": "stripped" },
-      },
-      {
-        "id": 3,
-        "description": "Leather Jacket",
-        "brand": "Lee Jeans",
-        "product_id": "123456",
-        "color": { "main": "Blue", "pattern": "used" },
-      },
-      {
-        "id": 4,
-        "description": "T-Shirt",
-        "brand": "Nike",
-        "product_id": "789012",
-        "color": { "main": "Blue", "pattern": "stripped" },
-      }
-    ])
-});
-
 static DOCUMENT_PRIMARY_KEY: &str = "id";
 static DOCUMENT_DISTINCT_KEY: &str = "product_id";
 
@@ -272,35 +239,3 @@ async fn distinct_search_with_pagination_no_ranking() {
     snapshot!(response["totalPages"], @"2");
     snapshot!(response["totalHits"], @"6");
 }
-
-#[actix_rt::test]
-async fn distinct_at_search_time() {
-    let server = Server::new().await;
-    let index = server.index("tamo");
-
-    let documents = NESTED_DOCUMENTS.clone();
-    index.add_documents(documents, Some(DOCUMENT_PRIMARY_KEY)).await;
-    let (task, _) = index.update_settings_filterable_attributes(json!(["color.main"])).await;
-    let task = index.wait_task(task.uid()).await;
-    snapshot!(task, name: "succeed");
-
-    fn get_hits(response: &Value) -> Vec<String> {
-        let hits_array = response["hits"]
-            .as_array()
-            .unwrap_or_else(|| panic!("{}", &serde_json::to_string_pretty(&response).unwrap()));
-        hits_array
-            .iter()
-            .map(|h| h[DOCUMENT_PRIMARY_KEY].as_number().unwrap().to_string())
-            .collect::<Vec<_>>()
-    }
-
-    let (response, code) =
-        index.search_post(json!({"page": 1, "hitsPerPage": 3, "distinct": "color.main"})).await;
-    let hits = get_hits(&response);
-    snapshot!(code, @"200 OK");
-    snapshot!(hits.len(), @"3");
-    snapshot!(format!("{:?}", hits), @r###"["1", "2", "3"]"###);
-    snapshot!(response["page"], @"1");
-    snapshot!(response["totalPages"], @"1");
-    snapshot!(response["totalHits"], @"3");
-}

meilisearch/tests/search/errors.rs

@@ -167,74 +167,6 @@ async fn search_bad_hits_per_page() {
     "###);
 }
 
-#[actix_rt::test]
-async fn search_bad_attributes_to_retrieve() {
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let (response, code) = index.search_post(json!({"attributesToRetrieve": "doggo"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.attributesToRetrieve`: expected an array, but found a string: `\"doggo\"`",
-      "code": "invalid_search_attributes_to_retrieve",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_retrieve"
-    }
-    "###);
-    // Can't make the `attributes_to_retrieve` fail with a get search since it'll accept anything as an array of strings.
-}
-
-#[actix_rt::test]
-async fn search_bad_retrieve_vectors() {
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let (response, code) = index.search_post(json!({"retrieveVectors": "doggo"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"doggo\"`",
-      "code": "invalid_search_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.search_post(json!({"retrieveVectors": [true]})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found an array: `[true]`",
-      "code": "invalid_search_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.search_get("retrieveVectors=").await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `` as a boolean, expected either `true` or `false`",
-      "code": "invalid_search_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.search_get("retrieveVectors=doggo").await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `doggo` as a boolean, expected either `true` or `false`",
-      "code": "invalid_search_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
-    }
-    "###);
-}
-
 #[actix_rt::test]
 async fn search_bad_attributes_to_crop() {
     let server = Server::new().await;
@@ -389,40 +321,6 @@ async fn search_bad_facets() {
     // Can't make the `attributes_to_highlight` fail with a get search since it'll accept anything as an array of strings.
 }
 
-#[actix_rt::test]
-async fn search_bad_threshold() {
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let (response, code) = index.search_post(json!({"rankingScoreThreshold": "doggo"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.rankingScoreThreshold`: expected a number, but found a string: `\"doggo\"`",
-      "code": "invalid_search_ranking_score_threshold",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_ranking_score_threshold"
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn search_invalid_threshold() {
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let (response, code) = index.search_post(json!({"rankingScoreThreshold": 42})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value at `.rankingScoreThreshold`: the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`.",
-      "code": "invalid_search_ranking_score_threshold",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_ranking_score_threshold"
-    }
-    "###);
-}
-
 #[actix_rt::test]
 async fn search_non_filterable_facets() {
     let server = Server::new().await;
@@ -607,7 +505,7 @@ async fn search_bad_matching_strategy() {
     snapshot!(code, @"400 Bad Request");
     snapshot!(json_string!(response), @r###"
     {
-      "message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`, `frequency`",
+      "message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`",
       "code": "invalid_search_matching_strategy",
       "type": "invalid_request",
       "link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@@ -629,7 +527,7 @@ async fn search_bad_matching_strategy() {
     snapshot!(code, @"400 Bad Request");
     snapshot!(json_string!(response), @r###"
     {
-      "message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`, `frequency`",
+      "message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`",
       "code": "invalid_search_matching_strategy",
       "type": "invalid_request",
       "link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@@ -1140,66 +1038,3 @@ async fn search_on_unknown_field_plus_joker() {
         )
         .await;
 }
-
-#[actix_rt::test]
-async fn distinct_at_search_time() {
-    let server = Server::new().await;
-    let index = server.index("tamo");
-    let (task, _) = index.create(None).await;
-    let task = index.wait_task(task.uid()).await;
-    snapshot!(task, name: "task-succeed");
-
-    let (response, code) =
-        index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
-      "code": "invalid_search_distinct",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
-    }
-    "###);
-
-    let (task, _) = index.update_settings_filterable_attributes(json!(["color", "machin"])).await;
-    index.wait_task(task.uid()).await;
-
-    let (response, code) =
-        index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
-      "code": "invalid_search_distinct",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
-    }
-    "###);
-
-    let (task, _) = index.update_settings_displayed_attributes(json!(["color"])).await;
-    index.wait_task(task.uid()).await;
-
-    let (response, code) =
-        index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
-      "code": "invalid_search_distinct",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
-    }
-    "###);
-
-    let (response, code) =
-        index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": true})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "Invalid value type at `.distinct`: expected a string, but found a boolean: `true`",
-      "code": "invalid_search_distinct",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
-    }
-    "###);
-}

meilisearch/tests/search/geo.rs

@@ -117,69 +117,3 @@ async fn geo_bounding_box_with_string_and_number() {
         )
         .await;
 }
-
-#[actix_rt::test]
-async fn bug_4640() {
-    // https://github.com/meilisearch/meilisearch/issues/4640
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let documents = DOCUMENTS.clone();
-    index.add_documents(documents, None).await;
-    index.update_settings_filterable_attributes(json!(["_geo"])).await;
-    let (ret, _code) = index.update_settings_sortable_attributes(json!(["_geo"])).await;
-    index.wait_task(ret.uid()).await;
-
-    // Sort the document with the second one first
-    index
-        .search(
-            json!({
-                "sort": ["_geoPoint(45.4777599, 9.1967508):asc"],
-            }),
-            |response, code| {
-                assert_eq!(code, 200, "{}", response);
-                snapshot!(json_string!(response, { ".processingTimeMs" => "[time]" }), @r###"
-                {
-                  "hits": [
-                    {
-                      "id": 2,
-                      "name": "La Bella Italia",
-                      "address": "456 Elm Street, Townsville",
-                      "type": "Italian",
-                      "rating": 9,
-                      "_geo": {
-                        "lat": "45.4777599",
-                        "lng": "9.1967508"
-                      }
-                    },
-                    {
-                      "id": 1,
-                      "name": "Taco Truck",
-                      "address": "444 Salsa Street, Burritoville",
-                      "type": "Mexican",
-                      "rating": 9,
-                      "_geo": {
-                        "lat": 34.0522,
-                        "lng": -118.2437
-                      },
-                      "_geoDistance": 9714063
-                    },
-                    {
-                      "id": 3,
-                      "name": "Crêpe Truck",
-                      "address": "2 Billig Avenue, Rouenville",
-                      "type": "French",
-                      "rating": 10
-                    }
-                  ],
-                  "query": "",
-                  "processingTimeMs": "[time]",
-                  "limit": 20,
-                  "offset": 0,
-                  "estimatedTotalHits": 3
-                }
-                "###);
-            },
-        )
-        .await;
-}

meilisearch/tests/search/hybrid.rs

@@ -124,29 +124,29 @@ async fn simple_search() {
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}}),
         )
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}}},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}}}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]}},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]}}]"###);
     snapshot!(response["semanticHitCount"], @"0");
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true, "retrieveVectors": true}),
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true}),
         )
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
     snapshot!(response["semanticHitCount"], @"2");
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true, "retrieveVectors": true}),
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true}),
         )
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
     snapshot!(response["semanticHitCount"], @"3");
 }
 
@@ -204,10 +204,10 @@ async fn distribution_shift() {
     let server = Server::new().await;
     let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
 
-    let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}, "retrieveVectors": true});
+    let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}});
     let (response, code) = index.search_post(search.clone()).await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
 
     let (response, code) = index
         .update_settings(json!({
@@ -228,7 +228,7 @@ async fn distribution_shift() {
 
     let (response, code) = index.search_post(search).await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.19161224365234375},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.1920928955078125e-7},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.1920928955078125e-7}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.19161224365234375},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.1920928955078125e-7},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.1920928955078125e-7}]"###);
 }
 
 #[actix_rt::test]
@@ -239,23 +239,20 @@ async fn highlighter() {
     let (response, code) = index
         .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
             "hybrid": {"semanticRatio": 0.2},
-           "retrieveVectors": true,
+            "attributesToHighlight": [
-           "attributesToHighlight": [
+                     "desc"
-                     "desc",
-                     "_vectors",
                    ],
-           "highlightPreTag": "**BEGIN**",
+                   "highlightPreTag": "**BEGIN**",
-           "highlightPostTag": "**END**",
+                   "highlightPostTag": "**END**"
         }))
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1"}},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2"}}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}}},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}}}]"###);
     snapshot!(response["semanticHitCount"], @"0");
 
     let (response, code) = index
         .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
             "hybrid": {"semanticRatio": 0.8},
-            "retrieveVectors": true,
             "showRankingScore": true,
             "attributesToHighlight": [
                      "desc"
@@ -265,14 +262,13 @@ async fn highlighter() {
         }))
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2"},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1"},"_rankingScore":0.9472135901451112}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}},"_rankingScore":0.9472135901451112}]"###);
     snapshot!(response["semanticHitCount"], @"3");
 
     // no highlighting on full semantic
     let (response, code) = index
         .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
             "hybrid": {"semanticRatio": 1.0},
-            "retrieveVectors": true,
             "showRankingScore": true,
             "attributesToHighlight": [
                      "desc"
@@ -282,7 +278,7 @@ async fn highlighter() {
         }))
         .await;
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},"_rankingScore":0.9472135901451112}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}},"_rankingScore":0.9472135901451112}]"###);
     snapshot!(response["semanticHitCount"], @"3");
 }
 
@@ -365,12 +361,12 @@ async fn single_document() {
 
     let (response, code) = index
     .search_post(
-        json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
+        json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
     )
     .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"][0], @r###"{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0}"###);
+    snapshot!(response["hits"][0], @r###"{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0}"###);
     snapshot!(response["semanticHitCount"], @"1");
 }
 
@@ -381,25 +377,25 @@ async fn query_combination() {
 
     // search without query and vector, but with hybrid => still placeholder
     let (response, code) = index
-        .search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
+        .search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
         .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
     snapshot!(response["semanticHitCount"], @"null");
 
     // same with a different semantic ratio
     let (response, code) = index
-        .search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true, "retrieveVectors": true}))
+        .search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true}))
         .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
     snapshot!(response["semanticHitCount"], @"null");
 
     // wrong vector dimensions
     let (response, code) = index
-    .search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
+    .search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
     .await;
 
     snapshot!(code, @"400 Bad Request");
@@ -414,34 +410,34 @@ async fn query_combination() {
 
     // full vector
     let (response, code) = index
-    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
+    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
     .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.7773500680923462},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.7236068248748779},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.6581138968467712}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.7773500680923462},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.7236068248748779},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.6581138968467712}]"###);
     snapshot!(response["semanticHitCount"], @"3");
 
     // full keyword, without a query
     let (response, code) = index
-    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
+    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true}))
     .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
     snapshot!(response["semanticHitCount"], @"null");
 
     // query + vector, full keyword => keyword
     let (response, code) = index
-    .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
+    .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true}))
     .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9242424242424242}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9242424242424242}]"###);
     snapshot!(response["semanticHitCount"], @"null");
 
     // query + vector, no hybrid keyword =>
     let (response, code) = index
-        .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true, "retrieveVectors": true}))
+        .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true}))
         .await;
 
     snapshot!(code, @"400 Bad Request");
@@ -457,7 +453,7 @@ async fn query_combination() {
     // full vector, without a vector => error
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
+            json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
         )
         .await;
 
@@ -474,93 +470,11 @@ async fn query_combination() {
     // hybrid without a vector => full keyword
     let (response, code) = index
         .search_post(
-            json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true, "retrieveVectors": true}),
+            json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true}),
         )
         .await;
 
     snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.9242424242424242}]"###);
+    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9242424242424242}]"###);
     snapshot!(response["semanticHitCount"], @"0");
 }
-
-#[actix_rt::test]
-async fn retrieve_vectors() {
-    let server = Server::new().await;
-    let index = index_with_documents_hf(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
-
-    let (response, code) = index
-        .search_post(
-            json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
-        )
-        .await;
-    snapshot!(code, @"200 OK");
-    insta::assert_json_snapshot!(response["hits"], {"[]._vectors.default.embeddings" => "[vectors]"},  @r###"
-    [
-      {
-        "title": "Captain Planet",
-        "desc": "He's not part of the Marvel Cinematic Universe",
-        "id": "2",
-        "_vectors": {
-          "default": {
-            "embeddings": "[vectors]",
-            "regenerate": true
-          }
-        }
-      },
-      {
-        "title": "Captain Marvel",
-        "desc": "a Shazam ersatz",
-        "id": "3",
-        "_vectors": {
-          "default": {
-            "embeddings": "[vectors]",
-            "regenerate": true
-          }
-        }
-      },
-      {
-        "title": "Shazam!",
-        "desc": "a Captain Marvel ersatz",
-        "id": "1",
-        "_vectors": {
-          "default": {
-            "embeddings": "[vectors]",
-            "regenerate": true
-          }
-        }
-      }
-    ]
-    "###);
-
-    // remove `_vectors` from displayed attributes
-    let (response, code) =
-        index.update_settings(json!({ "displayedAttributes": ["id", "title", "desc"]} )).await;
-    assert_eq!(202, code, "{:?}", response);
-    index.wait_task(response.uid()).await;
-
-    let (response, code) = index
-        .search_post(
-            json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
-        )
-        .await;
-    snapshot!(code, @"200 OK");
-    insta::assert_json_snapshot!(response["hits"], {"[]._vectors.default.embeddings" => "[vectors]"},  @r###"
-    [
-      {
-        "title": "Captain Planet",
-        "desc": "He's not part of the Marvel Cinematic Universe",
-        "id": "2"
-      },
-      {
-        "title": "Captain Marvel",
-        "desc": "a Shazam ersatz",
-        "id": "3"
-      },
-      {
-        "title": "Shazam!",
-        "desc": "a Captain Marvel ersatz",
-        "id": "1"
-      }
-    ]
-    "###);
-}

meilisearch/tests/search/matching_strategy.rs

@@ -1,128 +0,0 @@
-use meili_snap::snapshot;
-use once_cell::sync::Lazy;
-
-use crate::common::index::Index;
-use crate::common::{Server, Value};
-use crate::json;
-
-async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
-    let index = server.index("test");
-
-    index.add_documents(documents.clone(), None).await;
-    index.wait_task(0).await;
-    index
-}
-
-static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
-    json!([
-    {
-        "title": "Shazam!",
-        "id": "1",
-    },
-    {
-        "title": "Captain Planet",
-        "id": "2",
-    },
-    {
-        "title": "Captain Marvel",
-        "id": "3",
-    },
-    {
-        "title": "a Captain Marvel ersatz",
-        "id": "4"
-    },
-    {
-        "title": "He's not part of the Marvel Cinematic Universe",
-        "id": "5"
-    },
-    {
-        "title": "a Shazam ersatz, but better than Captain Planet",
-        "id": "6"
-    },
-    {
-        "title": "Capitain CAAAAAVEEERNE!!!!",
-        "id": "7"
-    }
-    ])
-});
-
-#[actix_rt::test]
-async fn simple_search() {
-    let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
-
-    index
-        .search(json!({"q": "Captain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"2"},{"id":"6"},{"id":"7"}]"###);
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Captain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Captain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
-        })
-        .await;
-}
-
-#[actix_rt::test]
-async fn search_with_typo() {
-    let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
-
-    index
-        .search(json!({"q": "Capitain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"7"},{"id":"2"},{"id":"6"}]"###);
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Capitain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Capitain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
-        })
-        .await;
-}
-
-#[actix_rt::test]
-async fn search_with_unknown_word() {
-    let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
-
-    index
-        .search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"2"},{"id":"3"},{"id":"4"},{"id":"6"},{"id":"7"}]"###);
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @"[]");
-        })
-        .await;
-
-    index
-        .search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
-            snapshot!(code, @"200 OK");
-            snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
-        })
-        .await;
-}

meilisearch/tests/search/mod.rs

@@ -7,7 +7,6 @@ mod facet_search;
 mod formatted;
 mod geo;
 mod hybrid;
-mod matching_strategy;
 mod multi;
 mod pagination;
 mod restrict_searchable;
@@ -48,31 +47,6 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
     ])
 });
 
-static SCORE_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
-    json!([
-        {
-            "title": "Batman the dark knight returns: Part 1",
-            "id": "A",
-        },
-        {
-            "title": "Batman the dark knight returns: Part 2",
-            "id": "B",
-        },
-        {
-            "title": "Batman Returns",
-            "id": "C",
-        },
-        {
-            "title": "Batman",
-            "id": "D",
-        },
-        {
-            "title": "Badman",
-            "id": "E",
-        }
-    ])
-});
-
 static NESTED_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
     json!([
         {
@@ -301,7 +275,7 @@ async fn negative_special_cases_search() {
     index.add_documents(documents, None).await;
     index.wait_task(0).await;
 
-    index.update_settings(json!({"synonyms": { "escape": ["gläss"] }})).await;
+    index.update_settings(json!({"synonyms": { "escape": ["glass"] }})).await;
     index.wait_task(1).await;
 
     // There is a synonym for escape -> glass but we don't want "escape", only the derivates: glass
@@ -985,213 +959,6 @@ async fn test_score_details() {
         .await;
 }
 
-#[actix_rt::test]
-async fn test_score() {
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let documents = SCORE_DOCUMENTS.clone();
-
-    let res = index.add_documents(json!(documents), None).await;
-    index.wait_task(res.0.uid()).await;
-
-    index
-        .search(
-            json!({
-                "q": "Badman the dark knight returns 1",
-                "showRankingScore": true,
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Batman the dark knight returns: Part 1",
-                    "id": "A",
-                    "_rankingScore": 0.9746605609456898
-                  },
-                  {
-                    "title": "Batman the dark knight returns: Part 2",
-                    "id": "B",
-                    "_rankingScore": 0.8055252965383685
-                  },
-                  {
-                    "title": "Badman",
-                    "id": "E",
-                    "_rankingScore": 0.16666666666666666
-                  },
-                  {
-                    "title": "Batman Returns",
-                    "id": "C",
-                    "_rankingScore": 0.07702020202020202
-                  },
-                  {
-                    "title": "Batman",
-                    "id": "D",
-                    "_rankingScore": 0.07702020202020202
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-}
-
-#[actix_rt::test]
-async fn test_score_threshold() {
-    let query = "Badman dark returns 1";
-    let server = Server::new().await;
-    let index = server.index("test");
-
-    let documents = SCORE_DOCUMENTS.clone();
-
-    let res = index.add_documents(json!(documents), None).await;
-    index.wait_task(res.0.uid()).await;
-
-    index
-        .search(
-            json!({
-                "q": query,
-                "showRankingScore": true,
-                "rankingScoreThreshold": 0.0
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"5");
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Batman the dark knight returns: Part 1",
-                    "id": "A",
-                    "_rankingScore": 0.93430081300813
-                  },
-                  {
-                    "title": "Batman the dark knight returns: Part 2",
-                    "id": "B",
-                    "_rankingScore": 0.6685627880184332
-                  },
-                  {
-                    "title": "Badman",
-                    "id": "E",
-                    "_rankingScore": 0.25
-                  },
-                  {
-                    "title": "Batman Returns",
-                    "id": "C",
-                    "_rankingScore": 0.11553030303030302
-                  },
-                  {
-                    "title": "Batman",
-                    "id": "D",
-                    "_rankingScore": 0.11553030303030302
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .search(
-            json!({
-                "q": query,
-                "showRankingScore": true,
-                "rankingScoreThreshold": 0.2
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"3"###);
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Batman the dark knight returns: Part 1",
-                    "id": "A",
-                    "_rankingScore": 0.93430081300813
-                  },
-                  {
-                    "title": "Batman the dark knight returns: Part 2",
-                    "id": "B",
-                    "_rankingScore": 0.6685627880184332
-                  },
-                  {
-                    "title": "Badman",
-                    "id": "E",
-                    "_rankingScore": 0.25
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .search(
-            json!({
-                "q": query,
-                "showRankingScore": true,
-                "rankingScoreThreshold": 0.5
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"2"###);
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Batman the dark knight returns: Part 1",
-                    "id": "A",
-                    "_rankingScore": 0.93430081300813
-                  },
-                  {
-                    "title": "Batman the dark knight returns: Part 2",
-                    "id": "B",
-                    "_rankingScore": 0.6685627880184332
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .search(
-            json!({
-                "q": query,
-                "showRankingScore": true,
-                "rankingScoreThreshold": 0.8
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"1"###);
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Batman the dark knight returns: Part 1",
-                    "id": "A",
-                    "_rankingScore": 0.93430081300813
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .search(
-            json!({
-                "q": query,
-                "showRankingScore": true,
-                "rankingScoreThreshold": 1.0
-            }),
-            |response, code| {
-                meili_snap::snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"0"###);
-                // nobody is perfect
-                meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @"[]");
-            },
-        )
-        .await;
-}
-
 #[actix_rt::test]
 async fn test_degraded_score_details() {
     let server = Server::new().await;
@@ -1290,38 +1057,21 @@ async fn experimental_feature_vector_store() {
     index.add_documents(json!(documents), None).await;
     index.wait_task(0).await;
 
-    index
+    let (response, code) = index
-        .search(json!({
+        .search_post(json!({
             "vector": [1.0, 2.0, 3.0],
             "showRankingScore": true
-        }), |response, code|{
+        }))
-            meili_snap::snapshot!(code, @"400 Bad Request");
-            meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
-            {
-              "message": "Passing `vector` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
-              "code": "feature_not_enabled",
-              "type": "invalid_request",
-              "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
-            }
-            "###);
-        })
-        .await;
-    index
-        .search(json!({
-            "retrieveVectors": true,
-            "showRankingScore": true
-        }), |response, code|{
-            meili_snap::snapshot!(code, @"400 Bad Request");
-            meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
-            {
-              "message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
-              "code": "feature_not_enabled",
-              "type": "invalid_request",
-              "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
-            }
-            "###);
-        })
         .await;
+    meili_snap::snapshot!(code, @"400 Bad Request");
+    meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
+    {
+      "message": "Passing `vector` as a query parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
+      "code": "feature_not_enabled",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#feature_not_enabled"
+    }
+    "###);
 
     let (response, code) = server.set_features(json!({"vectorStore": true})).await;
     meili_snap::snapshot!(code, @"200 OK");
@@ -1354,7 +1104,6 @@ async fn experimental_feature_vector_store() {
         .search_post(json!({
             "vector": [1.0, 2.0, 3.0],
             "showRankingScore": true,
-            "retrieveVectors": true,
         }))
         .await;
 
@@ -1366,16 +1115,11 @@ async fn experimental_feature_vector_store() {
         "title": "Shazam!",
         "id": "287947",
         "_vectors": {
-          "manual": {
+          "manual": [
-            "embeddings": [
+            1.0,
-              [
+            2.0,
-                1.0,
+            3.0
-                2.0,
+          ]
-                3.0
-              ]
-            ],
-            "regenerate": false
-          }
         },
         "_rankingScore": 1.0
       },
@@ -1383,16 +1127,11 @@ async fn experimental_feature_vector_store() {
         "title": "Captain Marvel",
         "id": "299537",
         "_vectors": {
-          "manual": {
+          "manual": [
-            "embeddings": [
+            1.0,
-              [
+            2.0,
-                1.0,
+            54.0
-                2.0,
+          ]
-                54.0
-              ]
-            ],
-            "regenerate": false
-          }
         },
         "_rankingScore": 0.9129111766815186
       },
@@ -1400,16 +1139,11 @@ async fn experimental_feature_vector_store() {
         "title": "Gläss",
         "id": "450465",
         "_vectors": {
-          "manual": {
+          "manual": [
-            "embeddings": [
+            -100.0,
-              [
+            340.0,
-                -100.0,
+            90.0
-                340.0,
+          ]
-                90.0
-              ]
-            ],
-            "regenerate": false
-          }
         },
         "_rankingScore": 0.8106412887573242
       },
@@ -1417,16 +1151,11 @@ async fn experimental_feature_vector_store() {
         "title": "How to Train Your Dragon: The Hidden World",
         "id": "166428",
         "_vectors": {
-          "manual": {
+          "manual": [
-            "embeddings": [
+            -100.0,
-              [
+            231.0,
-                -100.0,
+            32.0
-                231.0,
+          ]
-                32.0
-              ]
-            ],
-            "regenerate": false
-          }
         },
         "_rankingScore": 0.7412010431289673
       },
@@ -1434,16 +1163,11 @@ async fn experimental_feature_vector_store() {
         "title": "Escape Room",
         "id": "522681",
         "_vectors": {
-          "manual": {
+          "manual": [
-            "embeddings": [
+            10.0,
-              [
+            -23.0,
-                10.0,
+            32.0
-                -23.0,
+          ]
-                32.0
-              ]
-            ],
-            "regenerate": false
-          }
         },
         "_rankingScore": 0.6972063183784485
       }

meilisearch/tests/search/snapshots/distinct.rs/distinct_at_search_time/succeed.snap

@@ -1,20 +0,0 @@
----
-source: meilisearch/tests/search/distinct.rs
----
-{
-  "uid": 1,
-  "indexUid": "tamo",
-  "status": "succeeded",
-  "type": "settingsUpdate",
-  "canceledBy": null,
-  "details": {
-    "filterableAttributes": [
-      "color.main"
-    ]
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/search/snapshots/errors.rs/distinct_at_search_time/task-succeed.snap

@@ -1,18 +0,0 @@
----
-source: meilisearch/tests/search/errors.rs
----
-{
-  "uid": 0,
-  "indexUid": "tamo",
-  "status": "succeeded",
-  "type": "indexCreation",
-  "canceledBy": null,
-  "details": {
-    "primaryKey": null
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/similar/errors.rs

@@ -87,68 +87,6 @@ async fn similar_bad_id() {
     "###);
 }
 
-#[actix_rt::test]
-async fn similar_bad_ranking_score_threshold() {
-    let server = Server::new().await;
-    let index = server.index("test");
-    server.set_features(json!({"vectorStore": true})).await;
-
-    let (response, code) = index
-        .update_settings(json!({
-        "embedders": {
-            "manual": {
-                "source": "userProvided",
-                "dimensions": 3,
-            }
-        },
-        "filterableAttributes": ["title"]}))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let (response, code) = index.similar_post(json!({"rankingScoreThreshold": ["doggo"]})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.rankingScoreThreshold`: expected a number, but found an array: `[\"doggo\"]`",
-      "code": "invalid_similar_ranking_score_threshold",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_ranking_score_threshold"
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn similar_invalid_ranking_score_threshold() {
-    let server = Server::new().await;
-    let index = server.index("test");
-    server.set_features(json!({"vectorStore": true})).await;
-
-    let (response, code) = index
-        .update_settings(json!({
-        "embedders": {
-            "manual": {
-                "source": "userProvided",
-                "dimensions": 3,
-            }
-        },
-        "filterableAttributes": ["title"]}))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let (response, code) = index.similar_post(json!({"rankingScoreThreshold": 42})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value at `.rankingScoreThreshold`: the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`.",
-      "code": "invalid_similar_ranking_score_threshold",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_ranking_score_threshold"
-    }
-    "###);
-}
-
 #[actix_rt::test]
 async fn similar_invalid_id() {
     let server = Server::new().await;
@@ -756,54 +694,3 @@ async fn filter_reserved_geo_point_string() {
         })
         .await;
 }
-
-#[actix_rt::test]
-async fn similar_bad_retrieve_vectors() {
-    let server = Server::new().await;
-    server.set_features(json!({"vectorStore": true})).await;
-    let index = server.index("test");
-
-    let (response, code) = index.similar_post(json!({"retrieveVectors": "doggo"})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"doggo\"`",
-      "code": "invalid_similar_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.similar_post(json!({"retrieveVectors": [true]})).await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found an array: `[true]`",
-      "code": "invalid_similar_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.similar_get("retrieveVectors=").await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `` as a boolean, expected either `true` or `false`",
-      "code": "invalid_similar_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
-    }
-    "###);
-
-    let (response, code) = index.similar_get("retrieveVectors=doggo").await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(json_string!(response), @r###"
-    {
-      "message": "Invalid value in parameter `retrieveVectors`: could not parse `doggo` as a boolean, expected either `true` or `false`",
-      "code": "invalid_similar_retrieve_vectors",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
-    }
-    "###);
-}

meilisearch/tests/similar/mod.rs

@@ -78,7 +78,7 @@ async fn basic() {
     index.wait_task(value.uid()).await;
 
     index
-        .similar(json!({"id": 143, "retrieveVectors": true}), |response, code| {
+        .similar(json!({"id": 143}), |response, code| {
             snapshot!(code, @"200 OK");
             snapshot!(json_string!(response["hits"]), @r###"
             [
@@ -87,16 +87,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "522681",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.1,
-                      [
+                    0.6,
-                        0.10000000149011612,
+                    0.8
-                        0.6000000238418579,
+                  ]
-                        0.800000011920929
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -104,16 +99,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "299537",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.6,
-                      [
+                    0.8,
-                        0.6000000238418579,
+                    -0.2
-                        0.800000011920929,
+                  ]
-                        -0.20000000298023224
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -121,16 +111,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "166428",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.7,
-                      [
+                    0.7,
-                        0.699999988079071,
+                    -0.4
-                        0.699999988079071,
+                  ]
-                        -0.4000000059604645
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -138,16 +123,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "287947",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.8,
-                      [
+                    0.4,
-                        0.800000011920929,
+                    -0.5
-                        0.4000000059604645,
+                  ]
-                        -0.5
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               }
             ]
@@ -156,7 +136,7 @@ async fn basic() {
         .await;
 
     index
-        .similar(json!({"id": "299537", "retrieveVectors": true}), |response, code| {
+        .similar(json!({"id": "299537"}), |response, code| {
             snapshot!(code, @"200 OK");
             snapshot!(json_string!(response["hits"]), @r###"
             [
@@ -165,16 +145,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "166428",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.7,
-                      [
+                    0.7,
-                        0.699999988079071,
+                    -0.4
-                        0.699999988079071,
+                  ]
-                        -0.4000000059604645
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -182,16 +157,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "287947",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.8,
-                      [
+                    0.4,
-                        0.800000011920929,
+                    -0.5
-                        0.4000000059604645,
+                  ]
-                        -0.5
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -199,16 +169,11 @@ async fn basic() {
                 "release_year": 2019,
                 "id": "522681",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.1,
-                      [
+                    0.6,
-                        0.10000000149011612,
+                    0.8
-                        0.6000000238418579,
+                  ]
-                        0.800000011920929
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               },
               {
@@ -216,16 +181,11 @@ async fn basic() {
                 "release_year": 1930,
                 "id": "143",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    -0.5,
-                      [
+                    0.3,
-                        -0.5,
+                    0.85
-                        0.30000001192092896,
+                  ]
-                        0.8500000238418579
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               }
             ]
@@ -234,285 +194,6 @@ async fn basic() {
         .await;
 }
 
-#[actix_rt::test]
-async fn ranking_score_threshold() {
-    let server = Server::new().await;
-    let index = server.index("test");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-        "embedders": {
-            "manual": {
-                "source": "userProvided",
-                "dimensions": 3,
-            }
-        },
-        "filterableAttributes": ["title"]}))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let documents = DOCUMENTS.clone();
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    index
-        .similar(
-            json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0, "retrieveVectors": true}),
-            |response, code| {
-                snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"4");
-                snapshot!(json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Escape Room",
-                    "release_year": 2019,
-                    "id": "522681",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.10000000149011612,
-                            0.6000000238418579,
-                            0.800000011920929
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.890957772731781
-                  },
-                  {
-                    "title": "Captain Marvel",
-                    "release_year": 2019,
-                    "id": "299537",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.6000000238418579,
-                            0.800000011920929,
-                            -0.20000000298023224
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.39060014486312866
-                  },
-                  {
-                    "title": "How to Train Your Dragon: The Hidden World",
-                    "release_year": 2019,
-                    "id": "166428",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.699999988079071,
-                            0.699999988079071,
-                            -0.4000000059604645
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.2819308042526245
-                  },
-                  {
-                    "title": "Shazam!",
-                    "release_year": 2019,
-                    "id": "287947",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.800000011920929,
-                            0.4000000059604645,
-                            -0.5
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.1662663221359253
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .similar(
-            json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.2, "retrieveVectors": true}),
-            |response, code| {
-                snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"3");
-                snapshot!(json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Escape Room",
-                    "release_year": 2019,
-                    "id": "522681",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.10000000149011612,
-                            0.6000000238418579,
-                            0.800000011920929
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.890957772731781
-                  },
-                  {
-                    "title": "Captain Marvel",
-                    "release_year": 2019,
-                    "id": "299537",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.6000000238418579,
-                            0.800000011920929,
-                            -0.20000000298023224
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.39060014486312866
-                  },
-                  {
-                    "title": "How to Train Your Dragon: The Hidden World",
-                    "release_year": 2019,
-                    "id": "166428",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.699999988079071,
-                            0.699999988079071,
-                            -0.4000000059604645
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.2819308042526245
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .similar(
-            json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.3, "retrieveVectors": true}),
-            |response, code| {
-                snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"2");
-                snapshot!(json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Escape Room",
-                    "release_year": 2019,
-                    "id": "522681",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.10000000149011612,
-                            0.6000000238418579,
-                            0.800000011920929
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.890957772731781
-                  },
-                  {
-                    "title": "Captain Marvel",
-                    "release_year": 2019,
-                    "id": "299537",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.6000000238418579,
-                            0.800000011920929,
-                            -0.20000000298023224
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.39060014486312866
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .similar(
-            json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.6, "retrieveVectors": true}),
-            |response, code| {
-                snapshot!(code, @"200 OK");
-                meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"1");
-                snapshot!(json_string!(response["hits"]), @r###"
-                [
-                  {
-                    "title": "Escape Room",
-                    "release_year": 2019,
-                    "id": "522681",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.10000000149011612,
-                            0.6000000238418579,
-                            0.800000011920929
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    },
-                    "_rankingScore": 0.890957772731781
-                  }
-                ]
-                "###);
-            },
-        )
-        .await;
-
-    index
-        .similar(
-            json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.9, "retrieveVectors": true}),
-            |response, code| {
-                snapshot!(code, @"200 OK");
-                snapshot!(json_string!(response["hits"]), @"[]");
-            },
-        )
-        .await;
-}
-
 #[actix_rt::test]
 async fn filter() {
     let server = Server::new().await;
@@ -546,97 +227,71 @@ async fn filter() {
     index.wait_task(value.uid()).await;
 
     index
-        .similar(
+        .similar(json!({"id": 522681, "filter": "release_year = 2019"}), |response, code| {
-            json!({"id": 522681, "filter": "release_year = 2019", "retrieveVectors": true}),
+            snapshot!(code, @"200 OK");
-            |response, code| {
+            snapshot!(json_string!(response["hits"]), @r###"
-                snapshot!(code, @"200 OK");
+            [
-                snapshot!(json_string!(response["hits"]), @r###"
+              {
-                [
+                "title": "Captain Marvel",
-                  {
+                "release_year": 2019,
-                    "title": "Captain Marvel",
+                "id": "299537",
-                    "release_year": 2019,
+                "_vectors": {
-                    "id": "299537",
+                  "manual": [
-                    "_vectors": {
+                    0.6,
-                      "manual": {
+                    0.8,
-                        "embeddings": [
+                    -0.2
-                          [
+                  ]
-                            0.6000000238418579,
+                }
-                            0.800000011920929,
+              },
-                            -0.20000000298023224
+              {
-                          ]
+                "title": "How to Train Your Dragon: The Hidden World",
-                        ],
+                "release_year": 2019,
-                        "regenerate": false
+                "id": "166428",
-                      }
+                "_vectors": {
-                    }
+                  "manual": [
-                  },
+                    0.7,
-                  {
+                    0.7,
-                    "title": "How to Train Your Dragon: The Hidden World",
+                    -0.4
-                    "release_year": 2019,
+                  ]
-                    "id": "166428",
+                }
-                    "_vectors": {
+              },
-                      "manual": {
+              {
-                        "embeddings": [
+                "title": "Shazam!",
-                          [
+                "release_year": 2019,
-                            0.699999988079071,
+                "id": "287947",
-                            0.699999988079071,
+                "_vectors": {
-                            -0.4000000059604645
+                  "manual": [
-                          ]
+                    0.8,
-                        ],
+                    0.4,
-                        "regenerate": false
+                    -0.5
-                      }
+                  ]
-                    }
+                }
-                  },
+              }
-                  {
+            ]
-                    "title": "Shazam!",
+            "###);
-                    "release_year": 2019,
+        })
-                    "id": "287947",
-                    "_vectors": {
-                      "manual": {
-                        "embeddings": [
-                          [
-                            0.800000011920929,
-                            0.4000000059604645,
-                            -0.5
-                          ]
-                        ],
-                        "regenerate": false
-                      }
-                    }
-                  }
-                ]
-                "###);
-            },
-        )
         .await;
 
     index
-        .similar(
+        .similar(json!({"id": 522681, "filter": "release_year < 2000"}), |response, code| {
-            json!({"id": 522681, "filter": "release_year < 2000", "retrieveVectors": true}),
+            snapshot!(code, @"200 OK");
-            |response, code| {
+            snapshot!(json_string!(response["hits"]), @r###"
-                snapshot!(code, @"200 OK");
+            [
-                snapshot!(json_string!(response["hits"]), @r###"
+              {
-                [
+                "title": "All Quiet on the Western Front",
-                  {
+                "release_year": 1930,
-                    "title": "All Quiet on the Western Front",
+                "id": "143",
-                    "release_year": 1930,
+                "_vectors": {
-                    "id": "143",
+                  "manual": [
-                    "_vectors": {
+                    -0.5,
-                      "manual": {
+                    0.3,
-                        "embeddings": [
+                    0.85
-                          [
+                  ]
-                            -0.5,
+                }
-                            0.30000001192092896,
+              }
-                            0.8500000238418579
+            ]
-                          ]
+            "###);
-                        ],
+        })
-                        "regenerate": false
-                      }
-                    }
-                  }
-                ]
-                "###);
-            },
-        )
         .await;
 }
 
@@ -673,7 +328,7 @@ async fn limit_and_offset() {
     index.wait_task(value.uid()).await;
 
     index
-        .similar(json!({"id": 143, "limit": 1, "retrieveVectors": true}), |response, code| {
+        .similar(json!({"id": 143, "limit": 1}), |response, code| {
             snapshot!(code, @"200 OK");
             snapshot!(json_string!(response["hits"]), @r###"
             [
@@ -682,16 +337,11 @@ async fn limit_and_offset() {
                 "release_year": 2019,
                 "id": "522681",
                 "_vectors": {
-                  "manual": {
+                  "manual": [
-                    "embeddings": [
+                    0.1,
-                      [
+                    0.6,
-                        0.10000000149011612,
+                    0.8
-                        0.6000000238418579,
+                  ]
-                        0.800000011920929
-                      ]
-                    ],
-                    "regenerate": false
-                  }
                 }
               }
             ]
@@ -700,32 +350,24 @@ async fn limit_and_offset() {
         .await;
 
     index
-        .similar(
+        .similar(json!({"id": 143, "limit": 1, "offset": 1}), |response, code| {
-            json!({"id": 143, "limit": 1, "offset": 1, "retrieveVectors": true}),
+            snapshot!(code, @"200 OK");
-            |response, code| {
+            snapshot!(json_string!(response["hits"]), @r###"
-                snapshot!(code, @"200 OK");
+            [
-                snapshot!(json_string!(response["hits"]), @r###"
+              {
-                [
+                "title": "Captain Marvel",
-                  {
+                "release_year": 2019,
-                    "title": "Captain Marvel",
+                "id": "299537",
-                    "release_year": 2019,
+                "_vectors": {
-                    "id": "299537",
+                  "manual": [
-                    "_vectors": {
+                    0.6,
-                      "manual": {
+                    0.8,
-                        "embeddings": [
+                    -0.2
-                          [
+                  ]
-                            0.6000000238418579,
+                }
-                            0.800000011920929,
+              }
-                            -0.20000000298023224
+            ]
-                          ]
+            "###);
-                        ],
+        })
-                        "regenerate": false
-                      }
-                    }
-                  }
-                ]
-                "###);
-            },
-        )
         .await;
 }

meilisearch/tests/snapshot/mod.rs

@@ -31,7 +31,6 @@ macro_rules! verify_snapshot {
 }
 
 #[actix_rt::test]
-#[cfg_attr(target_os = "windows", ignore)]
 async fn perform_snapshot() {
     let temp = tempfile::tempdir().unwrap();
     let snapshot_dir = tempfile::tempdir().unwrap();

meilisearch/tests/vector/mod.rs

@@ -1,589 +0,0 @@
-mod rest;
-mod settings;
-
-use meili_snap::{json_string, snapshot};
-
-use crate::common::index::Index;
-use crate::common::{GetAllDocumentsOptions, Server};
-use crate::json;
-
-#[actix_rt::test]
-async fn add_remove_user_provided() {
-    let server = Server::new().await;
-    let index = server.index("doggo");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "manual": {
-                  "source": "userProvided",
-                  "dimensions": 3,
-              }
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
-      {"id": 1, "name": "echo", "_vectors": { "manual": [1, 1, 1] }},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  0.0,
-                  0.0,
-                  0.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 1,
-          "name": "echo",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  1.0,
-                  1.0,
-                  1.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": [10, 10, 10] }},
-      {"id": 1, "name": "echo", "_vectors": { "manual": null }},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  10.0,
-                  10.0,
-                  10.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 1,
-          "name": "echo",
-          "_vectors": {}
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 2
-    }
-    "###);
-
-    let (value, code) = index.delete_document(0).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 1,
-          "name": "echo",
-          "_vectors": {}
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 1
-    }
-    "###);
-}
-
-async fn generate_default_user_provided_documents(server: &Server) -> Index {
-    let index = server.index("doggo");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "manual": {
-                  "source": "userProvided",
-                  "dimensions": 3,
-              }
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
-      {"id": 1, "name": "echo", "_vectors": { "manual": [1, 1, 1] }},
-      {"id": 2, "name": "billou", "_vectors": { "manual": [[2, 2, 2], [2, 2, 3]] }},
-      {"id": 3, "name": "intel", "_vectors": { "manual": { "regenerate": false, "embeddings": [3, 3, 3] }}},
-      {"id": 4, "name": "max", "_vectors": { "manual": { "regenerate": false, "embeddings": [[4, 4, 4], [4, 4, 5]] }}},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    index.wait_task(value.uid()).await;
-
-    index
-}
-
-#[actix_rt::test]
-async fn user_provided_embeddings_error() {
-    let server = Server::new().await;
-    let index = generate_default_user_provided_documents(&server).await;
-
-    // First case, we forget to specify the `regenerate`
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [0, 0, 0] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 2,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    // Second case, we don't specify anything
-    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": {}}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 3,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    // Third case, we specify something wrong in place of regenerate
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": "yes please" }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 4,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": true }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 5,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [true] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 6,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [[true]] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 7,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [23, 0.1, -12], "regenerate": true }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task["status"], @r###""succeeded""###);
-
-    let documents =
-        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task["status"], @r###""succeeded""###);
-
-    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [0.1, [0.2, 0.3]] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 10,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [[0.1, 0.2], 0.3] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 11,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [[0.1, true], 0.3] }}});
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 12,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
-        "code": "invalid_vectors_type",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn clear_documents() {
-    let server = Server::new().await;
-    let index = generate_default_user_provided_documents(&server).await;
-
-    let (value, _code) = index.clear_all_documents().await;
-    index.wait_task(value.uid()).await;
-
-    // Make sure the documents DB has been cleared
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [],
-      "offset": 0,
-      "limit": 20,
-      "total": 0
-    }
-    "###);
-
-    // Make sure the arroy DB has been cleared
-    let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
-    snapshot!(documents, @r###"
-    {
-      "hits": [],
-      "query": "",
-      "processingTimeMs": "[duration]",
-      "limit": 20,
-      "offset": 0,
-      "estimatedTotalHits": 0,
-      "semanticHitCount": 0
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn add_remove_one_vector_4588() {
-    // https://github.com/meilisearch/meilisearch/issues/4588
-    let server = Server::new().await;
-    let index = server.index("doggo");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "manual": {
-                  "source": "userProvided",
-                  "dimensions": 3,
-              }
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, name: "settings-processed");
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, name: "document-added");
-
-    let documents = json!([
-      {"id": 0, "name": "kefir", "_vectors": { "manual": null }},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, name: "document-deleted");
-
-    let (documents, _code) = index.search_post(json!({"vector": [1, 1, 1] })).await;
-    snapshot!(documents, @r###"
-    {
-      "hits": [
-        {
-          "id": 0,
-          "name": "kefir"
-        }
-      ],
-      "query": "",
-      "processingTimeMs": "[duration]",
-      "limit": 20,
-      "offset": 0,
-      "estimatedTotalHits": 1,
-      "semanticHitCount": 1
-    }
-    "###);
-
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir",
-          "_vectors": {}
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 1
-    }
-    "###);
-}

meilisearch/tests/vector/rest.rs

@@ -1,339 +0,0 @@
-use crate::vector::GetAllDocumentsOptions;
-use meili_snap::{json_string, snapshot};
-use std::sync::atomic::{AtomicUsize, Ordering};
-use wiremock::matchers::{method, path};
-use wiremock::{Mock, MockServer, Request, ResponseTemplate};
-
-use crate::common::{Server, Value};
-use crate::json;
-
-static COUNTER: AtomicUsize = AtomicUsize::new(0);
-
-async fn create_mock() -> (MockServer, Value) {
-    let mock_server = MockServer::start().await;
-
-    Mock::given(method("POST"))
-        .and(path("/"))
-        .respond_with(|_req: &Request| {
-            let cpt = COUNTER.fetch_add(1, Ordering::Relaxed);
-            ResponseTemplate::new(200).set_body_json(json!({ "data": vec![cpt; 3] }))
-        })
-        .mount(&mock_server)
-        .await;
-    let url = mock_server.uri();
-
-    let embedder_settings = json!({
-        "source": "rest",
-        "url": url,
-        "dimensions": 3,
-        "query": {},
-    });
-
-    (mock_server, embedder_settings)
-}
-
-#[actix_rt::test]
-async fn dummy_testing_the_mock() {
-    let (mock, _setting) = create_mock().await;
-    let body = reqwest::get(&mock.uri()).await.unwrap().text().await.unwrap();
-    snapshot!(body, @"[0,0,0]");
-    let body = reqwest::get(&mock.uri()).await.unwrap().text().await.unwrap();
-    snapshot!(body, @"[1,1,1]");
-    let body = reqwest::get(&mock.uri()).await.unwrap().text().await.unwrap();
-    snapshot!(body, @"[2,2,2]");
-    let body = reqwest::get(&mock.uri()).await.unwrap().text().await.unwrap();
-    snapshot!(body, @"[3,3,3]");
-    let body = reqwest::get(&mock.uri()).await.unwrap().text().await.unwrap();
-    snapshot!(body, @"[4,4,4]");
-}
-
-async fn get_server_vector() -> Server {
-    let server = Server::new().await;
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-    server
-}
-
-#[actix_rt::test]
-async fn bad_settings() {
-    let (mock, _setting) = create_mock().await;
-
-    let server = get_server_vector().await;
-    let index = server.index("doggo");
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest" }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "`.embedders.rest`: Missing field `url` (note: this field is mandatory for source rest)",
-      "code": "invalid_settings_embedders",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": "kefir" }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"400 Bad Request");
-    snapshot!(response, @r###"
-    {
-      "message": "`.embedders.rest.url`: could not parse `kefir`: relative URL without a base",
-      "code": "invalid_settings_embedders",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": mock.uri() }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 0,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "embedders": {
-          "rest": {
-            "source": "rest",
-            "url": "[url]"
-          }
-        }
-      },
-      "error": {
-        "message": "internal: Error while generating embeddings: runtime error: could not determine model dimensions: test embedding failed with user error: was expected 'input' to be an object in query 'null'.",
-        "code": "internal",
-        "type": "internal",
-        "link": "https://docs.meilisearch.com/errors#internal"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": mock.uri(), "query": {} }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 1,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "embedders": {
-          "rest": {
-            "source": "rest",
-            "url": "[url]",
-            "query": {}
-          }
-        }
-      },
-      "error": {
-        "message": "internal: Error while generating embeddings: runtime error: could not determine model dimensions: test embedding failed with error: component `embedding` not found in path `embedding` in response: `{\n  \"data\": [\n    0,\n    0,\n    0\n  ]\n}`.",
-        "code": "internal",
-        "type": "internal",
-        "link": "https://docs.meilisearch.com/errors#internal"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": mock.uri(), "query": {}, "pathToEmbeddings": ["data"] }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 2,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "embedders": {
-          "rest": {
-            "source": "rest",
-            "url": "[url]",
-            "query": {},
-            "pathToEmbeddings": [
-              "data"
-            ]
-          }
-        }
-      },
-      "error": {
-        "message": "internal: Error while generating embeddings: runtime error: could not determine model dimensions: test embedding failed with error: component `embedding` not found in path `embedding` in response: `{\n  \"data\": [\n    1,\n    1,\n    1\n  ]\n}`.",
-        "code": "internal",
-        "type": "internal",
-        "link": "https://docs.meilisearch.com/errors#internal"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": mock.uri(), "query": {}, "embeddingObject": ["data"] }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 3,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "embedders": {
-          "rest": {
-            "source": "rest",
-            "url": "[url]",
-            "query": {},
-            "embeddingObject": [
-              "data"
-            ]
-          }
-        }
-      },
-      "error": {
-        "message": "internal: Error while generating embeddings: runtime error: could not determine model dimensions: test embedding failed with error: component `data` not found in path `data` in response: `{\n  \"data\": [\n    2,\n    2,\n    2\n  ]\n}`.",
-        "code": "internal",
-        "type": "internal",
-        "link": "https://docs.meilisearch.com/errors#internal"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    // Validate an embedder with a bad dimension of 2 instead of 3
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": json!({ "source": "rest", "url": mock.uri(), "query": {}, "pathToEmbeddings": [], "embeddingObject": ["data"], "dimensions": 2 }),
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task["status"], @r###""succeeded""###);
-
-    let (response, code) = index.add_documents(json!( { "id": 1, "name": "kefir" }), None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task, @r###"
-    {
-      "uid": 5,
-      "indexUid": "doggo",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "An unexpected crash occurred when processing the task.",
-        "code": "internal",
-        "type": "internal",
-        "link": "https://docs.meilisearch.com/errors#internal"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn add_vector_and_user_provided() {
-    let (_mock, setting) = create_mock().await;
-    let server = get_server_vector().await;
-    let index = server.index("doggo");
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "rest": setting,
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    let task = server.wait_task(response.uid()).await;
-    snapshot!(task["status"], @r###""succeeded""###);
-    let documents = json!([
-      {"id": 0, "name": "kefir"},
-      {"id": 1, "name": "echo", "_vectors": { "rest": [1, 1, 1] }},
-      {"id": 2, "name": "intel"},
-    ]);
-    let (value, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let task = index.wait_task(value.uid()).await;
-    snapshot!(task, @"");
-
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [],
-      "offset": 0,
-      "limit": 20,
-      "total": 0
-    }
-    "###);
-}

meilisearch/tests/vector/settings.rs

@@ -1,228 +0,0 @@
-use meili_snap::{json_string, snapshot};
-
-use crate::common::{GetAllDocumentsOptions, Server};
-use crate::json;
-use crate::vector::generate_default_user_provided_documents;
-
-#[actix_rt::test]
-async fn update_embedder() {
-    let server = Server::new().await;
-    let index = server.index("doggo");
-    let (value, code) = server.set_features(json!({"vectorStore": true})).await;
-    snapshot!(code, @"200 OK");
-    snapshot!(value, @r###"
-    {
-      "vectorStore": true,
-      "metrics": false,
-      "logsRoute": false
-    }
-    "###);
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": { "manual": {}},
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    let (response, code) = index
-        .update_settings(json!({
-          "embedders": {
-              "manual": {
-                  "source": "userProvided",
-                  "dimensions": 2,
-              }
-          },
-        }))
-        .await;
-    snapshot!(code, @"202 Accepted");
-
-    let ret = server.wait_task(response.uid()).await;
-    snapshot!(ret, @r###"
-    {
-      "uid": 1,
-      "indexUid": "doggo",
-      "status": "succeeded",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "embedders": {
-          "manual": {
-            "source": "userProvided",
-            "dimensions": 2
-          }
-        }
-      },
-      "error": null,
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-}
-
-#[actix_rt::test]
-async fn reset_embedder_documents() {
-    let server = Server::new().await;
-    let index = generate_default_user_provided_documents(&server).await;
-
-    let (response, code) = index.delete_settings().await;
-    snapshot!(code, @"202 Accepted");
-    server.wait_task(response.uid()).await;
-
-    // Make sure the documents are still present
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions {
-            limit: None,
-            offset: None,
-            retrieve_vectors: false,
-            fields: None,
-        })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir"
-        },
-        {
-          "id": 1,
-          "name": "echo"
-        },
-        {
-          "id": 2,
-          "name": "billou"
-        },
-        {
-          "id": 3,
-          "name": "intel"
-        },
-        {
-          "id": 4,
-          "name": "max"
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 5
-    }
-    "###);
-
-    // Make sure we are still able to retrieve their vectors
-    let (documents, _code) = index
-        .get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
-        .await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "results": [
-        {
-          "id": 0,
-          "name": "kefir",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  0.0,
-                  0.0,
-                  0.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 1,
-          "name": "echo",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  1.0,
-                  1.0,
-                  1.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 2,
-          "name": "billou",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  2.0,
-                  2.0,
-                  2.0
-                ],
-                [
-                  2.0,
-                  2.0,
-                  3.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 3,
-          "name": "intel",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  3.0,
-                  3.0,
-                  3.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        },
-        {
-          "id": 4,
-          "name": "max",
-          "_vectors": {
-            "manual": {
-              "embeddings": [
-                [
-                  4.0,
-                  4.0,
-                  4.0
-                ],
-                [
-                  4.0,
-                  4.0,
-                  5.0
-                ]
-              ],
-              "regenerate": false
-            }
-          }
-        }
-      ],
-      "offset": 0,
-      "limit": 20,
-      "total": 5
-    }
-    "###);
-
-    // Make sure the arroy DB has been cleared
-    let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
-    snapshot!(json_string!(documents), @r###"
-    {
-      "message": "Cannot find embedder with name `default`.",
-      "code": "invalid_embedder",
-      "type": "invalid_request",
-      "link": "https://docs.meilisearch.com/errors#invalid_embedder"
-    }
-    "###);
-}

meilisearch/tests/vector/snapshots/mod.rs/add_remove_one_vector_4588/document-added.snap

@@ -1,19 +0,0 @@
----
-source: meilisearch/tests/vector/mod.rs
----
-{
-  "uid": 1,
-  "indexUid": "doggo",
-  "status": "succeeded",
-  "type": "documentAdditionOrUpdate",
-  "canceledBy": null,
-  "details": {
-    "receivedDocuments": 1,
-    "indexedDocuments": 1
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/vector/snapshots/mod.rs/add_remove_one_vector_4588/document-deleted.snap

@@ -1,19 +0,0 @@
----
-source: meilisearch/tests/vector/mod.rs
----
-{
-  "uid": 2,
-  "indexUid": "doggo",
-  "status": "succeeded",
-  "type": "documentAdditionOrUpdate",
-  "canceledBy": null,
-  "details": {
-    "receivedDocuments": 1,
-    "indexedDocuments": 1
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

meilisearch/tests/vector/snapshots/mod.rs/add_remove_one_vector_4588/settings-processed.snap

@@ -1,23 +0,0 @@
----
-source: meilisearch/tests/vector/mod.rs
----
-{
-  "uid": 0,
-  "indexUid": "doggo",
-  "status": "succeeded",
-  "type": "settingsUpdate",
-  "canceledBy": null,
-  "details": {
-    "embedders": {
-      "manual": {
-        "source": "userProvided",
-        "dimensions": 3
-      }
-    }
-  },
-  "error": null,
-  "duration": "[duration]",
-  "enqueuedAt": "[date]",
-  "startedAt": "[date]",
-  "finishedAt": "[date]"
-}

milli/Cargo.toml

@@ -17,7 +17,7 @@ bincode = "1.3.3"
 bstr = "1.9.0"
 bytemuck = { version = "1.14.0", features = ["extern_crate_alloc"] }
 byteorder = "1.5.0"
-charabia = { version = "0.8.11", default-features = false }
+charabia = { version = "0.8.10", default-features = false }
 concat-arrays = "0.1.2"
 crossbeam-channel = "0.5.11"
 deserr = "0.6.1"
@@ -44,7 +44,7 @@ once_cell = "1.19.0"
 ordered-float = "4.2.0"
 rand_pcg = { version = "0.3.1", features = ["serde1"] }
 rayon = "1.8.0"
-roaring = { version = "0.10.2", features = ["serde"] }
+roaring = "0.10.2"
 rstar = { version = "0.11.0", features = ["serde"] }
 serde = { version = "1.0.195", features = ["derive"] }
 serde_json = { version = "1.0.111", features = ["preserve_order"] }
@@ -71,15 +71,15 @@ csv = "1.3.0"
 candle-core = { version = "0.4.1" }
 candle-transformers = { version = "0.4.1" }
 candle-nn = { version = "0.4.1" }
-tokenizers = { git = "https://github.com/huggingface/tokenizers.git", tag = "v0.15.2", version = "0.15.2", default-features = false, features = [
+tokenizers = { git = "https://github.com/huggingface/tokenizers.git", tag = "v0.15.2", version = "0.15.2", default_features = false, features = [
     "onig",
 ] }
-hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls", default-features = false, features = [
+hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls", default_features = false, features = [
     "online",
 ] }
 tiktoken-rs = "0.5.8"
 liquid = "0.26.4"
-arroy = "0.4.0"
+arroy = "0.3.1"
 rand = "0.8.5"
 tracing = "0.1.40"
 ureq = { version = "2.9.7", features = ["json"] }

milli/examples/search.rs

@@ -59,7 +59,6 @@ fn main() -> Result<(), Box<dyn Error>> {
                 false,
                 universe,
                 &None,
-                &None,
                 GeoSortStrategy::default(),
                 0,
                 20,
@@ -67,7 +66,6 @@ fn main() -> Result<(), Box<dyn Error>> {
                 &mut DefaultSearchLogger,
                 logger,
                 TimeBudget::max(),
-                None,
             )?;
             if let Some((logger, dir)) = detailed_logger {
                 logger.finish(&mut ctx, Path::new(dir))?;

milli/src/error.rs

@@ -119,8 +119,6 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
     InvalidVectorDimensions { expected: usize, found: usize },
     #[error("The `_vectors` field in the document with id: `{document_id}` is not an object. Was expecting an object with a key for each embedder with manually provided vectors, but instead got `{value}`")]
     InvalidVectorsMapType { document_id: String, value: Value },
-    #[error("Bad embedder configuration in the document with id: `{document_id}`. {error}")]
-    InvalidVectorsEmbedderConf { document_id: String, error: deserr::errors::JsonError },
     #[error("{0}")]
     InvalidFilter(String),
     #[error("Invalid type for filter subexpression: expected: {}, found: {1}.", .0.join(", "))]
@@ -136,17 +134,6 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
         }
     )]
     InvalidSortableAttribute { field: String, valid_fields: BTreeSet<String>, hidden_fields: bool },
-    #[error("Attribute `{}` is not filterable and thus, cannot be used as distinct attribute. {}",
-        .field,
-        match .valid_fields.is_empty() {
-            true => "This index does not have configured filterable attributes.".to_string(),
-            false => format!("Available filterable attributes are: `{}{}`.",
-                    valid_fields.iter().map(AsRef::as_ref).collect::<Vec<&str>>().join(", "),
-                    .hidden_fields.then_some(", <..hidden-attributes>").unwrap_or(""),
-                ),
-        }
-    )]
-    InvalidDistinctAttribute { field: String, valid_fields: BTreeSet<String>, hidden_fields: bool },
     #[error("Attribute `{}` is not facet-searchable. {}",
         .field,
         match .valid_fields.is_empty() {
@@ -283,9 +270,8 @@ impl From<arroy::Error> for Error {
             arroy::Error::DatabaseFull
             | arroy::Error::InvalidItemAppend
             | arroy::Error::UnmatchingDistance { .. }
-            | arroy::Error::NeedBuild(_)
+            | arroy::Error::MissingNode
-            | arroy::Error::MissingKey { .. }
+            | arroy::Error::MissingMetadata => {
-            | arroy::Error::MissingMetadata(_) => {
                 Error::InternalError(InternalError::ArroyError(value))
             }
         }

milli/src/fieldids_weights_map.rs

@@ -4,7 +4,6 @@ use std::collections::HashMap;
 
 use serde::{Deserialize, Serialize};
 
-use crate::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME;
 use crate::{FieldId, FieldsIdsMap, Weight};
 
 #[derive(Debug, Default, Serialize, Deserialize)]
@@ -24,13 +23,7 @@ impl FieldidsWeightsMap {
     /// Should only be called in the case there are NO searchable attributes.
     /// All the fields will be inserted in the order of the fields ids map with a weight of 0.
     pub fn from_field_id_map_without_searchable(fid_map: &FieldsIdsMap) -> Self {
-        FieldidsWeightsMap {
+        FieldidsWeightsMap { map: fid_map.ids().map(|fid| (fid, 0)).collect() }
-            map: fid_map
-                .iter()
-                .filter(|(_fid, name)| !crate::is_faceted_by(name, RESERVED_VECTORS_FIELD_NAME))
-                .map(|(fid, _name)| (fid, 0))
-                .collect(),
-        }
     }
 
     /// Removes a field id from the map, returning the associated weight previously in the map.

milli/src/fields_ids_map.rs

@@ -41,16 +41,6 @@ impl FieldsIdsMap {
         }
     }
 
-    /// Get the ids of a field and all its nested fields based on its name.
-    pub fn nested_ids(&self, name: &str) -> Vec<FieldId> {
-        self.names_ids
-            .range(name.to_string()..)
-            .take_while(|(key, _)| key.starts_with(name))
-            .filter(|(key, _)| crate::is_faceted_by(key, name))
-            .map(|(_name, id)| *id)
-            .collect()
-    }
-
     /// Get the id of a field based on its name.
     pub fn id(&self, name: &str) -> Option<FieldId> {
         self.names_ids.get(name).copied()
@@ -136,32 +126,4 @@ mod tests {
         assert_eq!(iter.next(), Some((3, "title")));
         assert_eq!(iter.next(), None);
     }
-
-    #[test]
-    fn nested_fields() {
-        let mut map = FieldsIdsMap::new();
-
-        assert_eq!(map.insert("id"), Some(0));
-        assert_eq!(map.insert("doggo"), Some(1));
-        assert_eq!(map.insert("doggo.name"), Some(2));
-        assert_eq!(map.insert("doggolution"), Some(3));
-        assert_eq!(map.insert("doggo.breed.name"), Some(4));
-        assert_eq!(map.insert("description"), Some(5));
-
-        insta::assert_debug_snapshot!(map.nested_ids("doggo"), @r###"
-        [
-            1,
-            4,
-            2,
-        ]
-        "###);
-
-        insta::assert_debug_snapshot!(map.nested_ids("doggo.breed"), @r###"
-        [
-            4,
-        ]
-        "###);
-
-        insta::assert_debug_snapshot!(map.nested_ids("_vector"), @"[]");
-    }
 }

milli/src/heed_codec/facet/mod.rs

@@ -47,12 +47,6 @@ pub struct FacetGroupValue {
     pub bitmap: RoaringBitmap,
 }
 
-#[derive(Debug)]
-pub struct FacetGroupLazyValue<'b> {
-    pub size: u8,
-    pub bitmap_bytes: &'b [u8],
-}
-
 pub struct FacetGroupKeyCodec<T> {
     _phantom: PhantomData<T>,
 }
@@ -75,7 +69,6 @@ where
         Ok(Cow::Owned(v))
     }
 }
-
 impl<'a, T> heed::BytesDecode<'a> for FacetGroupKeyCodec<T>
 where
     T: BytesDecode<'a>,
@@ -91,7 +84,6 @@ where
 }
 
 pub struct FacetGroupValueCodec;
-
 impl<'a> heed::BytesEncode<'a> for FacetGroupValueCodec {
     type EItem = FacetGroupValue;
 
@@ -101,23 +93,11 @@ impl<'a> heed::BytesEncode<'a> for FacetGroupValueCodec {
         Ok(Cow::Owned(v))
     }
 }
-
 impl<'a> heed::BytesDecode<'a> for FacetGroupValueCodec {
     type DItem = FacetGroupValue;
-
     fn bytes_decode(bytes: &'a [u8]) -> Result<Self::DItem, BoxedError> {
         let size = bytes[0];
         let bitmap = CboRoaringBitmapCodec::deserialize_from(&bytes[1..])?;
         Ok(FacetGroupValue { size, bitmap })
     }
 }
-
-pub struct FacetGroupLazyValueCodec;
-
-impl<'a> heed::BytesDecode<'a> for FacetGroupLazyValueCodec {
-    type DItem = FacetGroupLazyValue<'a>;
-
-    fn bytes_decode(bytes: &'a [u8]) -> Result<Self::DItem, BoxedError> {
-        Ok(FacetGroupLazyValue { size: bytes[0], bitmap_bytes: &bytes[1..] })
-    }
-}

milli/src/heed_codec/roaring_bitmap/cbo_roaring_bitmap_codec.rs

@@ -1,5 +1,5 @@
 use std::borrow::Cow;
-use std::io::{self, Cursor};
+use std::io;
 use std::mem::size_of;
 
 use byteorder::{NativeEndian, ReadBytesExt, WriteBytesExt};
@@ -57,24 +57,6 @@ impl CboRoaringBitmapCodec {
         }
     }
 
-    pub fn intersection_with_serialized(
-        mut bytes: &[u8],
-        other: &RoaringBitmap,
-    ) -> io::Result<RoaringBitmap> {
-        // See above `deserialize_from` method for implementation details.
-        if bytes.len() <= THRESHOLD * size_of::<u32>() {
-            let mut bitmap = RoaringBitmap::new();
-            while let Ok(integer) = bytes.read_u32::<NativeEndian>() {
-                if other.contains(integer) {
-                    bitmap.insert(integer);
-                }
-            }
-            Ok(bitmap)
-        } else {
-            other.intersection_with_serialized_unchecked(Cursor::new(bytes))
-        }
-    }
-
     /// Merge serialized CboRoaringBitmaps in a buffer.
     ///
     /// if the merged values length is under the threshold, values are directly

milli/src/index.rs

@@ -9,7 +9,6 @@ use heed::types::*;
 use heed::{CompactionOption, Database, RoTxn, RwTxn, Unspecified};
 use roaring::RoaringBitmap;
 use rstar::RTree;
-use serde::{Deserialize, Serialize};
 use time::OffsetDateTime;
 
 use crate::documents::PrimaryKey;
@@ -24,7 +23,6 @@ use crate::heed_codec::{
 };
 use crate::order_by_map::OrderByMap;
 use crate::proximity::ProximityPrecision;
-use crate::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME;
 use crate::vector::{Embedding, EmbeddingConfig};
 use crate::{
     default_criteria, CboRoaringBitmapCodec, Criterion, DocumentId, ExternalDocumentsIds,
@@ -646,7 +644,6 @@ impl Index {
         &self,
         wtxn: &mut RwTxn,
         user_fields: &[&str],
-        non_searchable_fields_ids: &[FieldId],
         fields_ids_map: &FieldsIdsMap,
     ) -> Result<()> {
         // We can write the user defined searchable fields as-is.
@@ -665,7 +662,6 @@ impl Index {
             for (weight, user_field) in user_fields.iter().enumerate() {
                 if crate::is_faceted_by(field_from_map, user_field)
                     && !real_fields.contains(&field_from_map)
-                    && !non_searchable_fields_ids.contains(&id)
                 {
                     real_fields.push(field_from_map);
 
@@ -712,7 +708,6 @@ impl Index {
                 Ok(self
                     .fields_ids_map(rtxn)?
                     .names()
-                    .filter(|name| !crate::is_faceted_by(name, RESERVED_VECTORS_FIELD_NAME))
                     .map(|field| Cow::Owned(field.to_string()))
                     .collect())
             })
@@ -1573,16 +1568,12 @@ impl Index {
         Ok(script_language)
     }
 
-    /// Put the embedding configs:
-    /// 1. The name of the embedder
-    /// 2. The configuration option for this embedder
-    /// 3. The list of documents with a user provided embedding
     pub(crate) fn put_embedding_configs(
         &self,
         wtxn: &mut RwTxn<'_>,
-        configs: Vec<IndexEmbeddingConfig>,
+        configs: Vec<(String, EmbeddingConfig)>,
     ) -> heed::Result<()> {
-        self.main.remap_types::<Str, SerdeJson<Vec<IndexEmbeddingConfig>>>().put(
+        self.main.remap_types::<Str, SerdeJson<Vec<(String, EmbeddingConfig)>>>().put(
             wtxn,
             main_key::EMBEDDING_CONFIGS,
             &configs,
@@ -1593,10 +1584,13 @@ impl Index {
         self.main.remap_key_type::<Str>().delete(wtxn, main_key::EMBEDDING_CONFIGS)
     }
 
-    pub fn embedding_configs(&self, rtxn: &RoTxn<'_>) -> Result<Vec<IndexEmbeddingConfig>> {
+    pub fn embedding_configs(
+        &self,
+        rtxn: &RoTxn<'_>,
+    ) -> Result<Vec<(String, crate::vector::EmbeddingConfig)>> {
         Ok(self
             .main
-            .remap_types::<Str, SerdeJson<Vec<IndexEmbeddingConfig>>>()
+            .remap_types::<Str, SerdeJson<Vec<(String, EmbeddingConfig)>>>()
             .get(rtxn, main_key::EMBEDDING_CONFIGS)?
             .unwrap_or_default())
     }
@@ -1610,7 +1604,7 @@ impl Index {
             arroy::Reader::open(rtxn, k, self.vector_arroy)
                 .map(Some)
                 .or_else(|e| match e {
-                    arroy::Error::MissingMetadata(_) => Ok(None),
+                    arroy::Error::MissingMetadata => Ok(None),
                     e => Err(e.into()),
                 })
                 .transpose()
@@ -1643,7 +1637,7 @@ impl Index {
                 let reader = arroy::Reader::open(rtxn, embedder_id | (i as u16), self.vector_arroy)
                     .map(Some)
                     .or_else(|e| match e {
-                        arroy::Error::MissingMetadata(_) => Ok(None),
+                        arroy::Error::MissingMetadata => Ok(None),
                         e => Err(e),
                     })
                     .transpose();
@@ -1668,13 +1662,6 @@ impl Index {
     }
 }
 
-#[derive(Debug, Deserialize, Serialize)]
-pub struct IndexEmbeddingConfig {
-    pub name: String,
-    pub config: EmbeddingConfig,
-    pub user_provided: RoaringBitmap,
-}
-
 #[cfg(test)]
 pub(crate) mod tests {
     use std::collections::HashSet;
@@ -1682,17 +1669,15 @@ pub(crate) mod tests {
 
     use big_s::S;
     use heed::{EnvOpenOptions, RwTxn};
-    use maplit::{btreemap, hashset};
+    use maplit::hashset;
     use tempfile::TempDir;
 
     use crate::documents::DocumentsBatchReader;
     use crate::error::{Error, InternalError};
     use crate::index::{DEFAULT_MIN_WORD_LEN_ONE_TYPO, DEFAULT_MIN_WORD_LEN_TWO_TYPOS};
     use crate::update::{
-        self, IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Setting,
+        self, IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings,
-        Settings,
     };
-    use crate::vector::settings::{EmbedderSource, EmbeddingSettings};
     use crate::{db_snap, obkv_to_json, Filter, Index, Search, SearchResult};
 
     pub(crate) struct TempIndex {
@@ -2798,95 +2783,4 @@ pub(crate) mod tests {
         ]
         "###);
     }
-
-    #[test]
-    fn vectors_are_never_indexed_as_searchable_or_filterable() {
-        let index = TempIndex::new();
-
-        index
-            .add_documents(documents!([
-                { "id": 0, "_vectors": { "doggo": [2345] } },
-                { "id": 1, "_vectors": { "doggo": [6789] } },
-            ]))
-            .unwrap();
-
-        db_snap!(index, fields_ids_map, @r###"
-        0   id               |
-        1   _vectors         |
-        2   _vectors.doggo   |
-        "###);
-        db_snap!(index, searchable_fields, @r###"["id"]"###);
-        db_snap!(index, fieldids_weights_map, @r###"
-        fid weight
-        0   0   |
-        "###);
-
-        let rtxn = index.read_txn().unwrap();
-        let mut search = index.search(&rtxn);
-        let results = search.query("2345").execute().unwrap();
-        assert!(results.candidates.is_empty());
-        drop(rtxn);
-
-        index
-            .update_settings(|settings| {
-                settings.set_searchable_fields(vec![S("_vectors"), S("_vectors.doggo")]);
-                settings.set_filterable_fields(hashset![S("_vectors"), S("_vectors.doggo")]);
-            })
-            .unwrap();
-
-        db_snap!(index, fields_ids_map, @r###"
-        0   id               |
-        1   _vectors         |
-        2   _vectors.doggo   |
-        "###);
-        db_snap!(index, searchable_fields, @"[]");
-        db_snap!(index, fieldids_weights_map, @r###"
-        fid weight
-        "###);
-
-        let rtxn = index.read_txn().unwrap();
-        let mut search = index.search(&rtxn);
-        let results = search.query("2345").execute().unwrap();
-        assert!(results.candidates.is_empty());
-
-        let mut search = index.search(&rtxn);
-        let results = search
-            .filter(Filter::from_str("_vectors.doggo = 6789").unwrap().unwrap())
-            .execute()
-            .unwrap();
-        assert!(results.candidates.is_empty());
-
-        index
-            .update_settings(|settings| {
-                settings.set_embedder_settings(btreemap! {
-                    S("doggo") => Setting::Set(EmbeddingSettings {
-                        dimensions: Setting::Set(1),
-                        source: Setting::Set(EmbedderSource::UserProvided),
-                        ..EmbeddingSettings::default()}),
-                });
-            })
-            .unwrap();
-
-        db_snap!(index, fields_ids_map, @r###"
-        0   id               |
-        1   _vectors         |
-        2   _vectors.doggo   |
-        "###);
-        db_snap!(index, searchable_fields, @"[]");
-        db_snap!(index, fieldids_weights_map, @r###"
-        fid weight
-        "###);
-
-        let rtxn = index.read_txn().unwrap();
-        let mut search = index.search(&rtxn);
-        let results = search.query("2345").execute().unwrap();
-        assert!(results.candidates.is_empty());
-
-        let mut search = index.search(&rtxn);
-        let results = search
-            .filter(Filter::from_str("_vectors.doggo = 6789").unwrap().unwrap())
-            .execute()
-            .unwrap();
-        assert!(results.candidates.is_empty());
-    }
 }

milli/src/search/facet/facet_distribution_iter.rs

@@ -6,11 +6,9 @@ use heed::Result;
 use roaring::RoaringBitmap;
 
 use super::{get_first_facet_value, get_highest_level};
-use crate::heed_codec::facet::{
+use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec};
-    FacetGroupKey, FacetGroupKeyCodec, FacetGroupLazyValueCodec, FacetGroupValueCodec,
-};
 use crate::heed_codec::BytesRefCodec;
-use crate::{CboRoaringBitmapCodec, DocumentId};
+use crate::DocumentId;
 
 /// Call the given closure on the facet distribution of the candidate documents.
 ///
@@ -33,11 +31,14 @@ pub fn lexicographically_iterate_over_facet_distribution<'t, CB>(
 where
     CB: FnMut(&'t [u8], u64, DocumentId) -> Result<ControlFlow<()>>,
 {
-    let db = db.remap_data_type::<FacetGroupLazyValueCodec>();
     let mut fd = LexicographicFacetDistribution { rtxn, db, field_id, callback };
-    let highest_level = get_highest_level(rtxn, db, field_id)?;
+    let highest_level = get_highest_level(
+        rtxn,
+        db.remap_key_type::<FacetGroupKeyCodec<BytesRefCodec>>(),
+        field_id,
+    )?;
 
-    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)? {
+    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec>(rtxn, db, field_id)? {
         fd.iterate(candidates, highest_level, first_bound, usize::MAX)?;
         Ok(())
     } else {
@@ -74,10 +75,13 @@ where
 
     // Represents the list of keys that we must explore.
     let mut heap = BinaryHeap::new();
-    let db = db.remap_data_type::<FacetGroupLazyValueCodec>();
+    let highest_level = get_highest_level(
-    let highest_level = get_highest_level(rtxn, db, field_id)?;
+        rtxn,
+        db.remap_key_type::<FacetGroupKeyCodec<BytesRefCodec>>(),
+        field_id,
+    )?;
 
-    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)? {
+    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec>(rtxn, db, field_id)? {
         // We first fill the heap with values from the highest level
         let starting_key =
             FacetGroupKey { field_id, level: highest_level, left_bound: first_bound };
@@ -88,10 +92,7 @@ where
             if key.field_id != field_id {
                 break;
             }
-            let intersection = CboRoaringBitmapCodec::intersection_with_serialized(
+            let intersection = value.bitmap & candidates;
-                value.bitmap_bytes,
-                candidates,
-            )?;
             let count = intersection.len();
             if count != 0 {
                 heap.push(LevelEntry {
@@ -120,10 +121,7 @@ where
                     if key.field_id != field_id {
                         break;
                     }
-                    let intersection = CboRoaringBitmapCodec::intersection_with_serialized(
+                    let intersection = value.bitmap & candidates;
-                        value.bitmap_bytes,
-                        candidates,
-                    )?;
                     let count = intersection.len();
                     if count != 0 {
                         heap.push(LevelEntry {
@@ -148,7 +146,7 @@ where
     CB: FnMut(&'t [u8], u64, DocumentId) -> Result<ControlFlow<()>>,
 {
     rtxn: &'t heed::RoTxn<'t>,
-    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupLazyValueCodec>,
+    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
     callback: CB,
 }
@@ -173,10 +171,7 @@ where
             if key.field_id != self.field_id {
                 return Ok(ControlFlow::Break(()));
             }
-            let docids_in_common = CboRoaringBitmapCodec::intersection_with_serialized(
+            let docids_in_common = value.bitmap & candidates;
-                value.bitmap_bytes,
-                candidates,
-            )?;
             if !docids_in_common.is_empty() {
                 let any_docid_in_common = docids_in_common.min().unwrap();
                 match (self.callback)(key.left_bound, docids_in_common.len(), any_docid_in_common)?
@@ -210,10 +205,7 @@ where
             if key.field_id != self.field_id {
                 return Ok(ControlFlow::Break(()));
             }
-            let docids_in_common = CboRoaringBitmapCodec::intersection_with_serialized(
+            let docids_in_common = value.bitmap & candidates;
-                value.bitmap_bytes,
-                candidates,
-            )?;
             if !docids_in_common.is_empty() {
                 let cf = self.iterate(
                     &docids_in_common,

milli/src/search/facet/facet_range_search.rs

@@ -4,11 +4,9 @@ use heed::BytesEncode;
 use roaring::RoaringBitmap;
 
 use super::{get_first_facet_value, get_highest_level, get_last_facet_value};
-use crate::heed_codec::facet::{
+use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec};
-    FacetGroupKey, FacetGroupKeyCodec, FacetGroupLazyValueCodec, FacetGroupValueCodec,
-};
 use crate::heed_codec::BytesRefCodec;
-use crate::{CboRoaringBitmapCodec, Result};
+use crate::Result;
 
 /// Find all the document ids for which the given field contains a value contained within
 /// the two bounds.
@@ -18,7 +16,6 @@ pub fn find_docids_of_facet_within_bounds<'t, BoundCodec>(
     field_id: u16,
     left: &'t Bound<<BoundCodec as BytesEncode<'t>>::EItem>,
     right: &'t Bound<<BoundCodec as BytesEncode<'t>>::EItem>,
-    universe: Option<&RoaringBitmap>,
     docids: &mut RoaringBitmap,
 ) -> Result<()>
 where
@@ -49,15 +46,13 @@ where
         }
         Bound::Unbounded => Bound::Unbounded,
     };
-    let db = db.remap_types::<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupLazyValueCodec>();
+    let db = db.remap_key_type::<FacetGroupKeyCodec<BytesRefCodec>>();
-    let mut f = FacetRangeSearch { rtxn, db, field_id, left, right, universe, docids };
+    let mut f = FacetRangeSearch { rtxn, db, field_id, left, right, docids };
     let highest_level = get_highest_level(rtxn, db, field_id)?;
 
-    if let Some(starting_left_bound) =
+    if let Some(starting_left_bound) = get_first_facet_value::<BytesRefCodec>(rtxn, db, field_id)? {
-        get_first_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)?
-    {
         let rightmost_bound =
-            Bound::Included(get_last_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)?.unwrap()); // will not fail because get_first_facet_value succeeded
+            Bound::Included(get_last_facet_value::<BytesRefCodec>(rtxn, db, field_id)?.unwrap()); // will not fail because get_first_facet_value succeeded
         let group_size = usize::MAX;
         f.run(highest_level, starting_left_bound, rightmost_bound, group_size)?;
         Ok(())
@@ -69,16 +64,12 @@ where
 /// Fetch the document ids that have a facet with a value between the two given bounds
 struct FacetRangeSearch<'t, 'b, 'bitmap> {
     rtxn: &'t heed::RoTxn<'t>,
-    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupLazyValueCodec>,
+    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
     left: Bound<&'b [u8]>,
     right: Bound<&'b [u8]>,
-    /// The subset of documents ids that are useful for this search.
-    /// Great performance optimizations can be achieved by only fetching values matching this subset.
-    universe: Option<&'bitmap RoaringBitmap>,
     docids: &'bitmap mut RoaringBitmap,
 }
-
 impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
     fn run_level_0(&mut self, starting_left_bound: &'t [u8], group_size: usize) -> Result<()> {
         let left_key =
@@ -113,13 +104,7 @@ impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
             }
 
             if RangeBounds::<&[u8]>::contains(&(self.left, self.right), &key.left_bound) {
-                *self.docids |= match self.universe {
+                *self.docids |= value.bitmap;
-                    Some(universe) => CboRoaringBitmapCodec::intersection_with_serialized(
-                        value.bitmap_bytes,
-                        universe,
-                    )?,
-                    None => CboRoaringBitmapCodec::deserialize_from(value.bitmap_bytes)?,
-                };
             }
         }
         Ok(())
@@ -210,13 +195,7 @@ impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
                 left_condition && right_condition
             };
             if should_take_whole_group {
-                *self.docids |= match self.universe {
+                *self.docids |= &previous_value.bitmap;
-                    Some(universe) => CboRoaringBitmapCodec::intersection_with_serialized(
-                        previous_value.bitmap_bytes,
-                        universe,
-                    )?,
-                    None => CboRoaringBitmapCodec::deserialize_from(previous_value.bitmap_bytes)?,
-                };
                 previous_key = next_key;
                 previous_value = next_value;
                 continue;
@@ -312,13 +291,7 @@ impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
             left_condition && right_condition
         };
         if should_take_whole_group {
-            *self.docids |= match self.universe {
+            *self.docids |= &previous_value.bitmap;
-                Some(universe) => CboRoaringBitmapCodec::intersection_with_serialized(
-                    previous_value.bitmap_bytes,
-                    universe,
-                )?,
-                None => CboRoaringBitmapCodec::deserialize_from(previous_value.bitmap_bytes)?,
-            };
         } else {
             let level = level - 1;
             let starting_left_bound = previous_key.left_bound;
@@ -392,7 +365,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -412,7 +384,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -447,7 +418,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -469,7 +439,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -505,7 +474,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -531,7 +499,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -570,7 +537,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -590,7 +556,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -606,7 +571,6 @@ mod tests {
                 0,
                 &Bound::Unbounded,
                 &Bound::Unbounded,
-                None,
                 &mut docids,
             )
             .unwrap();
@@ -622,7 +586,6 @@ mod tests {
                 1,
                 &Bound::Unbounded,
                 &Bound::Unbounded,
-                None,
                 &mut docids,
             )
             .unwrap();
@@ -658,7 +621,6 @@ mod tests {
                     0,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();
@@ -672,7 +634,6 @@ mod tests {
                     1,
                     &start,
                     &end,
-                    None,
                     &mut docids,
                 )
                 .unwrap();

milli/src/search/facet/facet_sort_ascending.rs

@@ -36,7 +36,7 @@ pub fn ascending_facet_sort<'t>(
     candidates: RoaringBitmap,
 ) -> Result<impl Iterator<Item = Result<(RoaringBitmap, &'t [u8])>> + 't> {
     let highest_level = get_highest_level(rtxn, db, field_id)?;
-    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)? {
+    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec>(rtxn, db, field_id)? {
         let first_key = FacetGroupKey { field_id, level: highest_level, left_bound: first_bound };
         let iter = db.range(rtxn, &(first_key..)).unwrap().take(usize::MAX);
 

milli/src/search/facet/facet_sort_descending.rs

@@ -19,9 +19,9 @@ pub fn descending_facet_sort<'t>(
     candidates: RoaringBitmap,
 ) -> Result<impl Iterator<Item = Result<(RoaringBitmap, &'t [u8])>> + 't> {
     let highest_level = get_highest_level(rtxn, db, field_id)?;
-    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)? {
+    if let Some(first_bound) = get_first_facet_value::<BytesRefCodec>(rtxn, db, field_id)? {
         let first_key = FacetGroupKey { field_id, level: highest_level, left_bound: first_bound };
-        let last_bound = get_last_facet_value::<BytesRefCodec, _>(rtxn, db, field_id)?.unwrap();
+        let last_bound = get_last_facet_value::<BytesRefCodec>(rtxn, db, field_id)?.unwrap();
         let last_key = FacetGroupKey { field_id, level: highest_level, left_bound: last_bound };
         let iter = db.rev_range(rtxn, &(first_key..=last_key))?.take(usize::MAX);
         Ok(itertools::Either::Left(DescendingFacetSort {

milli/src/search/facet/filter.rs

@@ -4,7 +4,7 @@ use std::ops::Bound::{self, Excluded, Included};
 
 use either::Either;
 pub use filter_parser::{Condition, Error as FPError, FilterCondition, Token};
-use roaring::{MultiOps, RoaringBitmap};
+use roaring::RoaringBitmap;
 use serde_json::Value;
 
 use super::facet_range_search;
@@ -224,14 +224,14 @@ impl<'a> Filter<'a> {
     pub fn evaluate(&self, rtxn: &heed::RoTxn, index: &Index) -> Result<RoaringBitmap> {
         // to avoid doing this for each recursive call we're going to do it ONCE ahead of time
         let filterable_fields = index.filterable_fields(rtxn)?;
-        self.inner_evaluate(rtxn, index, &filterable_fields, None)
+
+        self.inner_evaluate(rtxn, index, &filterable_fields)
     }
 
     fn evaluate_operator(
         rtxn: &heed::RoTxn,
         index: &Index,
         field_id: FieldId,
-        universe: Option<&RoaringBitmap>,
         operator: &Condition<'a>,
     ) -> Result<RoaringBitmap> {
         let numbers_db = index.facet_id_f64_docids;
@@ -291,22 +291,14 @@ impl<'a> Filter<'a> {
             }
             Condition::NotEqual(val) => {
                 let operator = Condition::Equal(val.clone());
-                let docids = Self::evaluate_operator(rtxn, index, field_id, None, &operator)?;
+                let docids = Self::evaluate_operator(rtxn, index, field_id, &operator)?;
                 let all_ids = index.documents_ids(rtxn)?;
                 return Ok(all_ids - docids);
             }
         };
 
         let mut output = RoaringBitmap::new();
-        Self::explore_facet_number_levels(
+        Self::explore_facet_number_levels(rtxn, numbers_db, field_id, left, right, &mut output)?;
-            rtxn,
-            numbers_db,
-            field_id,
-            left,
-            right,
-            universe,
-            &mut output,
-        )?;
         Ok(output)
     }
 
@@ -318,7 +310,6 @@ impl<'a> Filter<'a> {
         field_id: FieldId,
         left: Bound<f64>,
         right: Bound<f64>,
-        universe: Option<&RoaringBitmap>,
         output: &mut RoaringBitmap,
     ) -> Result<()> {
         match (left, right) {
@@ -330,7 +321,7 @@ impl<'a> Filter<'a> {
             (_, _) => (),
         }
         facet_range_search::find_docids_of_facet_within_bounds::<OrderedF64Codec>(
-            rtxn, db, field_id, &left, &right, universe, output,
+            rtxn, db, field_id, &left, &right, output,
         )?;
 
         Ok(())
@@ -341,37 +332,31 @@ impl<'a> Filter<'a> {
         rtxn: &heed::RoTxn,
         index: &Index,
         filterable_fields: &HashSet<String>,
-        universe: Option<&RoaringBitmap>,
     ) -> Result<RoaringBitmap> {
-        if universe.map_or(false, |u| u.is_empty()) {
-            return Ok(RoaringBitmap::new());
-        }
-
         match &self.condition {
             FilterCondition::Not(f) => {
+                let all_ids = index.documents_ids(rtxn)?;
                 let selected = Self::inner_evaluate(
                     &(f.as_ref().clone()).into(),
                     rtxn,
                     index,
                     filterable_fields,
-                    universe,
                 )?;
-                match universe {
+                Ok(all_ids - selected)
-                    Some(universe) => Ok(universe - selected),
-                    None => {
-                        let all_ids = index.documents_ids(rtxn)?;
-                        Ok(all_ids - selected)
-                    }
-                }
             }
             FilterCondition::In { fid, els } => {
                 if crate::is_faceted(fid.value(), filterable_fields) {
                     let field_ids_map = index.fields_ids_map(rtxn)?;
+
                     if let Some(fid) = field_ids_map.id(fid.value()) {
-                        els.iter()
+                        let mut bitmap = RoaringBitmap::new();
-                            .map(|el| Condition::Equal(el.clone()))
+
-                            .map(|op| Self::evaluate_operator(rtxn, index, fid, universe, &op))
+                        for el in els {
-                            .union()
+                            let op = Condition::Equal(el.clone());
+                            let el_bitmap = Self::evaluate_operator(rtxn, index, fid, &op)?;
+                            bitmap |= el_bitmap;
+                        }
+                        Ok(bitmap)
                     } else {
                         Ok(RoaringBitmap::new())
                     }
@@ -386,7 +371,7 @@ impl<'a> Filter<'a> {
                 if crate::is_faceted(fid.value(), filterable_fields) {
                     let field_ids_map = index.fields_ids_map(rtxn)?;
                     if let Some(fid) = field_ids_map.id(fid.value()) {
-                        Self::evaluate_operator(rtxn, index, fid, universe, op)
+                        Self::evaluate_operator(rtxn, index, fid, op)
                     } else {
                         Ok(RoaringBitmap::new())
                     }
@@ -397,11 +382,14 @@ impl<'a> Filter<'a> {
                     }))?
                 }
             }
-            FilterCondition::Or(subfilters) => subfilters
+            FilterCondition::Or(subfilters) => {
-                .iter()
+                let mut bitmap = RoaringBitmap::new();
-                .cloned()
+                for f in subfilters {
-                .map(|f| Self::inner_evaluate(&f.into(), rtxn, index, filterable_fields, universe))
+                    bitmap |=
-                .union(),
+                        Self::inner_evaluate(&(f.clone()).into(), rtxn, index, filterable_fields)?;
+                }
+                Ok(bitmap)
+            }
             FilterCondition::And(subfilters) => {
                 let mut subfilters_iter = subfilters.iter();
                 if let Some(first_subfilter) = subfilters_iter.next() {
@@ -410,21 +398,16 @@ impl<'a> Filter<'a> {
                         rtxn,
                         index,
                         filterable_fields,
-                        universe,
                     )?;
                     for f in subfilters_iter {
                         if bitmap.is_empty() {
                             return Ok(bitmap);
                         }
-                        // TODO We are doing the intersections two times,
-                        //      it could be more efficient
-                        //      Can't I just replace this `&=` by an `=`?
                         bitmap &= Self::inner_evaluate(
                             &(f.clone()).into(),
                             rtxn,
                             index,
                             filterable_fields,
-                            Some(&bitmap),
                         )?;
                     }
                     Ok(bitmap)
@@ -524,7 +507,6 @@ impl<'a> Filter<'a> {
                         rtxn,
                         index,
                         filterable_fields,
-                        universe,
                     )?;
 
                     let geo_lng_token = Token::new(
@@ -557,7 +539,6 @@ impl<'a> Filter<'a> {
                             rtxn,
                             index,
                             filterable_fields,
-                            universe,
                         )?;
 
                         let condition_right = FilterCondition::Condition {
@@ -571,7 +552,6 @@ impl<'a> Filter<'a> {
                             rtxn,
                             index,
                             filterable_fields,
-                            universe,
                         )?;
 
                         left | right
@@ -587,7 +567,6 @@ impl<'a> Filter<'a> {
                             rtxn,
                             index,
                             filterable_fields,
-                            universe,
                         )?
                     };
 

milli/src/search/facet/mod.rs

@@ -7,7 +7,7 @@ use roaring::RoaringBitmap;
 pub use self::facet_distribution::{FacetDistribution, OrderBy, DEFAULT_VALUES_PER_FACET};
 pub use self::filter::{BadGeoError, Filter};
 pub use self::search::{FacetValueHit, SearchForFacetValues};
-use crate::heed_codec::facet::{FacetGroupKeyCodec, OrderedF64Codec};
+use crate::heed_codec::facet::{FacetGroupKeyCodec, FacetGroupValueCodec, OrderedF64Codec};
 use crate::heed_codec::BytesRefCodec;
 use crate::{Index, Result};
 
@@ -54,9 +54,9 @@ pub fn facet_max_value<'t>(
 }
 
 /// Get the first facet value in the facet database
-pub(crate) fn get_first_facet_value<'t, BoundCodec, DC>(
+pub(crate) fn get_first_facet_value<'t, BoundCodec>(
     txn: &'t RoTxn,
-    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, DC>,
+    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
 ) -> heed::Result<Option<BoundCodec::DItem>>
 where
@@ -78,9 +78,9 @@ where
 }
 
 /// Get the last facet value in the facet database
-pub(crate) fn get_last_facet_value<'t, BoundCodec, DC>(
+pub(crate) fn get_last_facet_value<'t, BoundCodec>(
     txn: &'t RoTxn,
-    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, DC>,
+    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
 ) -> heed::Result<Option<BoundCodec::DItem>>
 where
@@ -102,9 +102,9 @@ where
 }
 
 /// Get the height of the highest level in the facet database
-pub(crate) fn get_highest_level<'t, DC>(
+pub(crate) fn get_highest_level<'t>(
     txn: &'t RoTxn<'t>,
-    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, DC>,
+    db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
 ) -> heed::Result<u8> {
     let field_id_prefix = &field_id.to_be_bytes();

milli/src/search/hybrid.rs

@@ -159,7 +159,6 @@ impl<'a> Search<'a> {
             offset: 0,
             limit: self.limit + self.offset,
             sort_criteria: self.sort_criteria.clone(),
-            distinct: self.distinct.clone(),
             searchable_attributes: self.searchable_attributes,
             geo_strategy: self.geo_strategy,
             terms_matching_strategy: self.terms_matching_strategy,
@@ -170,7 +169,6 @@ impl<'a> Search<'a> {
             index: self.index,
             semantic: self.semantic.clone(),
             time_budget: self.time_budget.clone(),
-            ranking_score_threshold: self.ranking_score_threshold,
         };
 
         let semantic = search.semantic.take();

milli/src/search/mod.rs

@@ -11,8 +11,8 @@ use self::new::{execute_vector_search, PartialSearchResult};
 use crate::score_details::{ScoreDetails, ScoringStrategy};
 use crate::vector::Embedder;
 use crate::{
-    execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, Error, Index,
+    execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, Index, Result,
-    Result, SearchContext, TimeBudget, UserError,
+    SearchContext, TimeBudget,
 };
 
 // Building these factories is not free.
@@ -40,7 +40,6 @@ pub struct Search<'a> {
     offset: usize,
     limit: usize,
     sort_criteria: Option<Vec<AscDesc>>,
-    distinct: Option<String>,
     searchable_attributes: Option<&'a [String]>,
     geo_strategy: new::GeoSortStrategy,
     terms_matching_strategy: TermsMatchingStrategy,
@@ -51,7 +50,6 @@ pub struct Search<'a> {
     index: &'a Index,
     semantic: Option<SemanticSearch>,
     time_budget: TimeBudget,
-    ranking_score_threshold: Option<f64>,
 }
 
 impl<'a> Search<'a> {
@@ -62,7 +60,6 @@ impl<'a> Search<'a> {
             offset: 0,
             limit: 20,
             sort_criteria: None,
-            distinct: None,
             searchable_attributes: None,
             geo_strategy: new::GeoSortStrategy::default(),
             terms_matching_strategy: TermsMatchingStrategy::default(),
@@ -73,7 +70,6 @@ impl<'a> Search<'a> {
             index,
             semantic: None,
             time_budget: TimeBudget::max(),
-            ranking_score_threshold: None,
         }
     }
 
@@ -107,11 +103,6 @@ impl<'a> Search<'a> {
         self
     }
 
-    pub fn distinct(&mut self, distinct: String) -> &mut Search<'a> {
-        self.distinct = Some(distinct);
-        self
-    }
-
     pub fn searchable_attributes(&mut self, searchable: &'a [String]) -> &mut Search<'a> {
         self.searchable_attributes = Some(searchable);
         self
@@ -155,11 +146,6 @@ impl<'a> Search<'a> {
         self
     }
 
-    pub fn ranking_score_threshold(&mut self, ranking_score_threshold: f64) -> &mut Search<'a> {
-        self.ranking_score_threshold = Some(ranking_score_threshold);
-        self
-    }
-
     pub fn execute_for_candidates(&self, has_vector_search: bool) -> Result<RoaringBitmap> {
         if has_vector_search {
             let ctx = SearchContext::new(self.index, self.rtxn)?;
@@ -176,19 +162,6 @@ impl<'a> Search<'a> {
             ctx.attributes_to_search_on(searchable_attributes)?;
         }
 
-        if let Some(distinct) = &self.distinct {
-            let filterable_fields = ctx.index.filterable_fields(ctx.txn)?;
-            if !crate::is_faceted(distinct, &filterable_fields) {
-                let (valid_fields, hidden_fields) =
-                    ctx.index.remove_hidden_fields(ctx.txn, filterable_fields)?;
-                return Err(Error::UserError(UserError::InvalidDistinctAttribute {
-                    field: distinct.clone(),
-                    valid_fields,
-                    hidden_fields,
-                }));
-            }
-        }
-
         let universe = filtered_universe(ctx.index, ctx.txn, &self.filter)?;
         let PartialSearchResult {
             located_query_terms,
@@ -205,14 +178,12 @@ impl<'a> Search<'a> {
                     self.scoring_strategy,
                     universe,
                     &self.sort_criteria,
-                    &self.distinct,
                     self.geo_strategy,
                     self.offset,
                     self.limit,
                     embedder_name,
                     embedder,
                     self.time_budget.clone(),
-                    self.ranking_score_threshold,
                 )?
             }
             _ => execute_search(
@@ -223,7 +194,6 @@ impl<'a> Search<'a> {
                 self.exhaustive_number_hits,
                 universe,
                 &self.sort_criteria,
-                &self.distinct,
                 self.geo_strategy,
                 self.offset,
                 self.limit,
@@ -231,7 +201,6 @@ impl<'a> Search<'a> {
                 &mut DefaultSearchLogger,
                 &mut DefaultSearchLogger,
                 self.time_budget.clone(),
-                self.ranking_score_threshold,
             )?,
         };
 
@@ -260,7 +229,6 @@ impl fmt::Debug for Search<'_> {
             offset,
             limit,
             sort_criteria,
-            distinct,
             searchable_attributes,
             geo_strategy: _,
             terms_matching_strategy,
@@ -271,7 +239,6 @@ impl fmt::Debug for Search<'_> {
             index: _,
             semantic,
             time_budget,
-            ranking_score_threshold,
         } = self;
         f.debug_struct("Search")
             .field("query", query)
@@ -280,7 +247,6 @@ impl fmt::Debug for Search<'_> {
             .field("offset", offset)
             .field("limit", limit)
             .field("sort_criteria", sort_criteria)
-            .field("distinct", distinct)
             .field("searchable_attributes", searchable_attributes)
             .field("terms_matching_strategy", terms_matching_strategy)
             .field("scoring_strategy", scoring_strategy)
@@ -291,7 +257,6 @@ impl fmt::Debug for Search<'_> {
                 &semantic.as_ref().map(|semantic| &semantic.embedder_name),
             )
             .field("time_budget", time_budget)
-            .field("ranking_score_threshold", ranking_score_threshold)
             .finish()
     }
 }
@@ -312,8 +277,6 @@ pub enum TermsMatchingStrategy {
     Last,
     // all words are mandatory
     All,
-    // remove more frequent word first
-    Frequency,
 }
 
 impl Default for TermsMatchingStrategy {

milli/src/search/new/bucket_sort.rs

@@ -22,25 +22,18 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
     ctx: &mut SearchContext<'ctx>,
     mut ranking_rules: Vec<BoxRankingRule<'ctx, Q>>,
     query: &Q,
-    distinct: Option<&str>,
     universe: &RoaringBitmap,
     from: usize,
     length: usize,
     scoring_strategy: ScoringStrategy,
     logger: &mut dyn SearchLogger<Q>,
     time_budget: TimeBudget,
-    ranking_score_threshold: Option<f64>,
 ) -> Result<BucketSortOutput> {
     logger.initial_query(query);
     logger.ranking_rules(&ranking_rules);
     logger.initial_universe(universe);
 
-    let distinct_field = match distinct {
+    let distinct_fid = if let Some(field) = ctx.index.distinct_field(ctx.txn)? {
-        Some(distinct) => Some(distinct),
-        None => ctx.index.distinct_field(ctx.txn)?,
-    };
-
-    let distinct_fid = if let Some(field) = distinct_field {
         ctx.index.fields_ids_map(ctx.txn)?.id(field)
     } else {
         None
@@ -171,19 +164,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
             loop {
                 let bucket = std::mem::take(&mut ranking_rule_universes[cur_ranking_rule_index]);
                 ranking_rule_scores.push(ScoreDetails::Skipped);
-
-                // remove candidates from the universe without adding them to result if their score is below the threshold
-                if let Some(ranking_score_threshold) = ranking_score_threshold {
-                    let current_score = ScoreDetails::global_score(ranking_rule_scores.iter());
-                    if current_score < ranking_score_threshold {
-                        all_candidates -= bucket | &ranking_rule_universes[cur_ranking_rule_index];
-                        back!();
-                        continue;
-                    }
-                }
-
                 maybe_add_to_results!(bucket);
-
                 ranking_rule_scores.pop();
 
                 if cur_ranking_rule_index == 0 {
@@ -239,18 +220,6 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
         debug_assert!(
             ranking_rule_universes[cur_ranking_rule_index].is_superset(&next_bucket.candidates)
         );
-
-        // remove candidates from the universe without adding them to result if their score is below the threshold
-        if let Some(ranking_score_threshold) = ranking_score_threshold {
-            let current_score = ScoreDetails::global_score(ranking_rule_scores.iter());
-            if current_score < ranking_score_threshold {
-                all_candidates -=
-                    next_bucket.candidates | &ranking_rule_universes[cur_ranking_rule_index];
-                back!();
-                continue;
-            }
-        }
-
         ranking_rule_universes[cur_ranking_rule_index] -= &next_bucket.candidates;
 
         if cur_ranking_rule_index == ranking_rules_len - 1

milli/src/search/new/graph_based_ranking_rule.rs

@@ -164,21 +164,6 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
                     }
                     costs
                 }
-                TermsMatchingStrategy::Frequency => {
-                    let removal_order =
-                        query_graph.removal_order_for_terms_matching_strategy_frequency(ctx)?;
-                    let mut forbidden_nodes =
-                        SmallBitmap::for_interned_values_in(&query_graph.nodes);
-                    let mut costs = query_graph.nodes.map(|_| None);
-                    // FIXME: this works because only words uses termsmatchingstrategy at the moment.
-                    for ns in removal_order {
-                        for n in ns.iter() {
-                            *costs.get_mut(n) = Some((1, forbidden_nodes.clone()));
-                        }
-                        forbidden_nodes.union(&ns);
-                    }
-                    costs
-                }
                 TermsMatchingStrategy::All => query_graph.nodes.map(|_| None),
             }
         } else {

milli/src/search/new/logger/visual.rs

@@ -22,7 +22,7 @@ pub enum SearchEvents {
     RankingRuleStartIteration { ranking_rule_idx: usize, universe_len: u64 },
     RankingRuleNextBucket { ranking_rule_idx: usize, universe_len: u64, bucket_len: u64 },
     RankingRuleSkipBucket { ranking_rule_idx: usize, bucket_len: u64 },
-    RankingRuleEndIteration { ranking_rule_idx: usize },
+    RankingRuleEndIteration { ranking_rule_idx: usize, universe_len: u64 },
     ExtendResults { new: Vec<u32> },
     ProximityGraph { graph: RankingRuleGraph<ProximityGraph> },
     ProximityPaths { paths: Vec<Vec<Interned<ProximityCondition>>> },
@@ -123,9 +123,12 @@ impl SearchLogger<QueryGraph> for VisualSearchLogger {
         &mut self,
         ranking_rule_idx: usize,
         _ranking_rule: &dyn RankingRule<QueryGraph>,
-        _universe: &RoaringBitmap,
+        universe: &RoaringBitmap,
     ) {
-        self.events.push(SearchEvents::RankingRuleEndIteration { ranking_rule_idx });
+        self.events.push(SearchEvents::RankingRuleEndIteration {
+            ranking_rule_idx,
+            universe_len: universe.len(),
+        });
         self.location.pop();
     }
     fn add_to_results(&mut self, docids: &[u32]) {
@@ -323,7 +326,7 @@ impl<'ctx> DetailedLoggerFinish<'ctx> {
                 assert!(ranking_rule_idx == self.rr_action_counter.len() - 1);
                 self.write_skip_bucket(bucket_len)?;
             }
-            SearchEvents::RankingRuleEndIteration { ranking_rule_idx } => {
+            SearchEvents::RankingRuleEndIteration { ranking_rule_idx, universe_len: _ } => {
                 assert!(ranking_rule_idx == self.rr_action_counter.len() - 1);
                 self.write_end_iteration()?;
             }

milli/src/search/new/matches/mod.rs

@@ -516,7 +516,6 @@ mod tests {
                 false,
                 universe,
                 &None,
-                &None,
                 crate::search::new::GeoSortStrategy::default(),
                 0,
                 100,
@@ -524,7 +523,6 @@ mod tests {
                 &mut crate::DefaultSearchLogger,
                 &mut crate::DefaultSearchLogger,
                 TimeBudget::max(),
-                None,
             )
             .unwrap();
 

milli/src/search/new/mod.rs

@@ -197,11 +197,6 @@ fn resolve_maximally_reduced_query_graph(
             .iter()
             .flat_map(|x| x.iter())
             .collect(),
-        TermsMatchingStrategy::Frequency => query_graph
-            .removal_order_for_terms_matching_strategy_frequency(ctx)?
-            .iter()
-            .flat_map(|x| x.iter())
-            .collect(),
         TermsMatchingStrategy::All => vec![],
     };
     graph.remove_nodes_keep_edges(&nodes_to_remove);
@@ -548,7 +543,6 @@ fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
     Ok(())
 }
 
-#[tracing::instrument(level = "trace", skip_all, target = "search")]
 pub fn filtered_universe(
     index: &Index,
     txn: &RoTxn<'_>,
@@ -568,14 +562,12 @@ pub fn execute_vector_search(
     scoring_strategy: ScoringStrategy,
     universe: RoaringBitmap,
     sort_criteria: &Option<Vec<AscDesc>>,
-    distinct: &Option<String>,
     geo_strategy: geo_sort::Strategy,
     from: usize,
     length: usize,
     embedder_name: &str,
     embedder: &Embedder,
     time_budget: TimeBudget,
-    ranking_score_threshold: Option<f64>,
 ) -> Result<PartialSearchResult> {
     check_sort_criteria(ctx, sort_criteria.as_ref())?;
 
@@ -599,14 +591,12 @@ pub fn execute_vector_search(
         ctx,
         ranking_rules,
         &PlaceholderQuery,
-        distinct.as_deref(),
         &universe,
         from,
         length,
         scoring_strategy,
         placeholder_search_logger,
         time_budget,
-        ranking_score_threshold,
     )?;
 
     Ok(PartialSearchResult {
@@ -629,7 +619,6 @@ pub fn execute_search(
     exhaustive_number_hits: bool,
     mut universe: RoaringBitmap,
     sort_criteria: &Option<Vec<AscDesc>>,
-    distinct: &Option<String>,
     geo_strategy: geo_sort::Strategy,
     from: usize,
     length: usize,
@@ -637,7 +626,6 @@ pub fn execute_search(
     placeholder_search_logger: &mut dyn SearchLogger<PlaceholderQuery>,
     query_graph_logger: &mut dyn SearchLogger<QueryGraph>,
     time_budget: TimeBudget,
-    ranking_score_threshold: Option<f64>,
 ) -> Result<PartialSearchResult> {
     check_sort_criteria(ctx, sort_criteria.as_ref())?;
 
@@ -720,14 +708,12 @@ pub fn execute_search(
             ctx,
             ranking_rules,
             &graph,
-            distinct.as_deref(),
             &universe,
             from,
             length,
             scoring_strategy,
             query_graph_logger,
             time_budget,
-            ranking_score_threshold,
         )?
     } else {
         let ranking_rules =
@@ -736,14 +722,12 @@ pub fn execute_search(
             ctx,
             ranking_rules,
             &PlaceholderQuery,
-            distinct.as_deref(),
             &universe,
             from,
             length,
             scoring_strategy,
             placeholder_search_logger,
             time_budget,
-            ranking_score_threshold,
         )?
     };
 
@@ -753,12 +737,7 @@ pub fn execute_search(
     // The candidates is the universe unless the exhaustive number of hits
     // is requested and a distinct attribute is set.
     if exhaustive_number_hits {
-        let distinct_field = match distinct.as_deref() {
+        if let Some(f) = ctx.index.distinct_field(ctx.txn)? {
-            Some(distinct) => Some(distinct),
-            None => ctx.index.distinct_field(ctx.txn)?,
-        };
-
-        if let Some(f) = distinct_field {
             if let Some(distinct_fid) = fields_ids_map.id(f) {
                 all_candidates = apply_distinct_rule(ctx, distinct_fid, &all_candidates)?.remaining;
             }

milli/src/search/new/query_graph.rs

@@ -1,9 +1,8 @@
-use std::cmp::{Ordering, Reverse};
+use std::cmp::Ordering;
 use std::collections::BTreeMap;
 use std::hash::{Hash, Hasher};
 
 use fxhash::{FxHashMap, FxHasher};
-use roaring::RoaringBitmap;
 
 use super::interner::{FixedSizeInterner, Interned};
 use super::query_term::{
@@ -12,7 +11,6 @@ use super::query_term::{
 use super::small_bitmap::SmallBitmap;
 use super::SearchContext;
 use crate::search::new::interner::Interner;
-use crate::search::new::resolve_query_graph::compute_query_term_subset_docids;
 use crate::Result;
 
 /// A node of the [`QueryGraph`].
@@ -292,49 +290,6 @@ impl QueryGraph {
         }
     }
 
-    pub fn removal_order_for_terms_matching_strategy_frequency(
-        &self,
-        ctx: &mut SearchContext,
-    ) -> Result<Vec<SmallBitmap<QueryNode>>> {
-        // lookup frequency for each term
-        let mut term_with_frequency: Vec<(u8, u64)> = {
-            let mut term_docids: BTreeMap<u8, RoaringBitmap> = Default::default();
-            for (_, node) in self.nodes.iter() {
-                match &node.data {
-                    QueryNodeData::Term(t) => {
-                        let docids = compute_query_term_subset_docids(ctx, &t.term_subset)?;
-                        for id in t.term_ids.clone() {
-                            term_docids
-                                .entry(id)
-                                .and_modify(|curr| *curr |= &docids)
-                                .or_insert_with(|| docids.clone());
-                        }
-                    }
-                    QueryNodeData::Deleted | QueryNodeData::Start | QueryNodeData::End => continue,
-                }
-            }
-            term_docids
-                .into_iter()
-                .map(|(idx, docids)| match docids.len() {
-                    0 => (idx, u64::max_value()),
-                    frequency => (idx, frequency),
-                })
-                .collect()
-        };
-        term_with_frequency.sort_by_key(|(_, frequency)| Reverse(*frequency));
-        let mut term_weight = BTreeMap::new();
-        let mut weight: u16 = 1;
-        let mut peekable = term_with_frequency.into_iter().peekable();
-        while let Some((idx, frequency)) = peekable.next() {
-            term_weight.insert(idx, weight);
-            if peekable.peek().map_or(false, |(_, f)| frequency != *f) {
-                weight += 1;
-            }
-        }
-        let cost_of_term_idx = move |term_idx: u8| *term_weight.get(&term_idx).unwrap();
-        Ok(self.removal_order_for_terms_matching_strategy(ctx, cost_of_term_idx))
-    }
-
     pub fn removal_order_for_terms_matching_strategy_last(
         &self,
         ctx: &SearchContext,
@@ -360,19 +315,10 @@ impl QueryGraph {
         if first_term_idx >= last_term_idx {
             return vec![];
         }
-
         let cost_of_term_idx = |term_idx: u8| {
             let rank = 1 + last_term_idx - term_idx;
             rank as u16
         };
-        self.removal_order_for_terms_matching_strategy(ctx, cost_of_term_idx)
-    }
-
-    pub fn removal_order_for_terms_matching_strategy(
-        &self,
-        ctx: &SearchContext,
-        order: impl Fn(u8) -> u16,
-    ) -> Vec<SmallBitmap<QueryNode>> {
         let mut nodes_to_remove = BTreeMap::<u16, SmallBitmap<QueryNode>>::new();
         let mut at_least_one_mandatory_term = false;
         for (node_id, node) in self.nodes.iter() {
@@ -383,7 +329,7 @@ impl QueryGraph {
             }
             let mut cost = 0;
             for id in t.term_ids.clone() {
-                cost = std::cmp::max(cost, order(id));
+                cost = std::cmp::max(cost, cost_of_term_idx(id));
             }
             nodes_to_remove
                 .entry(cost)

milli/src/search/new/tests/distinct.rs

@@ -205,18 +205,8 @@ fn create_index() -> TempIndex {
     index
 }
 
-fn verify_distinct(
+fn verify_distinct(index: &Index, txn: &RoTxn, docids: &[u32]) -> Vec<String> {
-    index: &Index,
+    let vs = collect_field_values(index, txn, index.distinct_field(txn).unwrap().unwrap(), docids);
-    txn: &RoTxn,
-    distinct: Option<&str>,
-    docids: &[u32],
-) -> Vec<String> {
-    let vs = collect_field_values(
-        index,
-        txn,
-        distinct.or_else(|| index.distinct_field(txn).unwrap()).unwrap(),
-        docids,
-    );
 
     let mut unique = HashSet::new();
     for v in vs.iter() {
@@ -233,49 +223,12 @@ fn verify_distinct(
 fn test_distinct_placeholder_no_ranking_rules() {
     let index = create_index();
 
-    // Set the letter as filterable and unset the distinct attribute.
-    index
-        .update_settings(|s| {
-            s.set_filterable_fields(hashset! { S("letter") });
-            s.reset_distinct_field();
-        })
-        .unwrap();
-
-    let txn = index.read_txn().unwrap();
-
-    let mut s = Search::new(&txn, &index);
-    s.distinct(S("letter"));
-    let SearchResult { documents_ids, .. } = s.execute().unwrap();
-    insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 5, 8, 9, 15, 18, 20, 21, 24, 25, 26]");
-    let distinct_values = verify_distinct(&index, &txn, Some("letter"), &documents_ids);
-    insta::assert_debug_snapshot!(distinct_values, @r###"
-    [
-        "\"A\"",
-        "\"B\"",
-        "\"C\"",
-        "\"D\"",
-        "\"E\"",
-        "\"F\"",
-        "\"G\"",
-        "\"H\"",
-        "\"I\"",
-        "__does_not_exist__",
-        "__does_not_exist__",
-        "__does_not_exist__",
-    ]
-    "###);
-}
-
-#[test]
-fn test_distinct_at_search_placeholder_no_ranking_rules() {
-    let index = create_index();
-
     let txn = index.read_txn().unwrap();
 
     let s = Search::new(&txn, &index);
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 5, 8, 9, 15, 18, 20, 21, 24, 25, 26]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"A\"",
@@ -310,7 +263,7 @@ fn test_distinct_placeholder_sort() {
 
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[14, 26, 4, 7, 17, 23, 1, 19, 25, 8, 20, 24]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"E\"",
@@ -350,7 +303,7 @@ fn test_distinct_placeholder_sort() {
 
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[21, 20, 18, 15, 9, 8, 5, 2, 0, 24, 25, 26]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"I\"",
@@ -393,7 +346,7 @@ fn test_distinct_placeholder_sort() {
 
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[23, 20, 19, 17, 14, 8, 7, 4, 1, 26, 25, 24]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"I\"",
@@ -446,7 +399,7 @@ fn test_distinct_words() {
 
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 2, 26, 5, 8, 9, 15, 18, 20, 21, 25, 24]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"A\"",
@@ -500,7 +453,7 @@ fn test_distinct_sort_words() {
 
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[22, 20, 19, 16, 9, 8, 7, 3, 1, 26, 25, 24]");
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"I\"",
@@ -596,7 +549,7 @@ fn test_distinct_typo() {
     let SearchResult { documents_ids, .. } = s.execute().unwrap();
     insta::assert_snapshot!(format!("{documents_ids:?}"), @"[3, 26, 0, 7, 8, 9, 15, 22, 18, 20, 25, 24]");
 
-    let distinct_values = verify_distinct(&index, &txn, None, &documents_ids);
+    let distinct_values = verify_distinct(&index, &txn, &documents_ids);
     insta::assert_debug_snapshot!(distinct_values, @r###"
     [
         "\"B\"",

milli/src/search/new/tests/snapshots/milli__search__new__tests__attribute_fid__attribute_fid_ngrams.snap

@@ -0,0 +1,244 @@
+---
+source: milli/src/search/new/tests/attribute_fid.rs
+expression: "format!(\"{document_ids_scores:#?}\")"
+---
+[
+    (
+        2,
+        [
+            Fid(
+                Rank {
+                    rank: 19,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 91,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        6,
+        [
+            Fid(
+                Rank {
+                    rank: 15,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 81,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        5,
+        [
+            Fid(
+                Rank {
+                    rank: 14,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 79,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        4,
+        [
+            Fid(
+                Rank {
+                    rank: 13,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 77,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        3,
+        [
+            Fid(
+                Rank {
+                    rank: 12,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 83,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        9,
+        [
+            Fid(
+                Rank {
+                    rank: 11,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 75,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        8,
+        [
+            Fid(
+                Rank {
+                    rank: 10,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 79,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        7,
+        [
+            Fid(
+                Rank {
+                    rank: 10,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 73,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        11,
+        [
+            Fid(
+                Rank {
+                    rank: 7,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 77,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        10,
+        [
+            Fid(
+                Rank {
+                    rank: 6,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 81,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        13,
+        [
+            Fid(
+                Rank {
+                    rank: 6,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 81,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        12,
+        [
+            Fid(
+                Rank {
+                    rank: 6,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 78,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        14,
+        [
+            Fid(
+                Rank {
+                    rank: 5,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 75,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+    (
+        0,
+        [
+            Fid(
+                Rank {
+                    rank: 1,
+                    max_rank: 19,
+                },
+            ),
+            Position(
+                Rank {
+                    rank: 91,
+                    max_rank: 91,
+                },
+            ),
+        ],
+    ),
+]

milli/src/search/new/tests/stop_words.rs

@@ -13,7 +13,7 @@ use std::collections::BTreeSet;
 use std::iter::FromIterator;
 
 use crate::index::tests::TempIndex;
-use crate::{Search, SearchResult, TermsMatchingStrategy};
+use crate::{db_snap, Search, SearchResult, TermsMatchingStrategy};
 
 fn create_index() -> TempIndex {
     let index = TempIndex::new();
@@ -66,10 +66,9 @@ fn create_index() -> TempIndex {
 }
 
 #[test]
-#[cfg(not(feature = "swedish-recomposition"))]
 fn test_stop_words_not_indexed() {
     let index = create_index();
-    crate::db_snap!(index, word_docids, @"6288f9d7db3703b02c57025eb4a69264");
+    db_snap!(index, word_docids, @"6288f9d7db3703b02c57025eb4a69264");
 }
 
 #[test]

milli/src/search/similar.rs

@@ -17,7 +17,6 @@ pub struct Similar<'a> {
     index: &'a Index,
     embedder_name: String,
     embedder: Arc<Embedder>,
-    ranking_score_threshold: Option<f64>,
 }
 
 impl<'a> Similar<'a> {
@@ -30,17 +29,7 @@ impl<'a> Similar<'a> {
         embedder_name: String,
         embedder: Arc<Embedder>,
     ) -> Self {
-        Self {
+        Self { id, filter: None, offset, limit, rtxn, index, embedder_name, embedder }
-            id,
-            filter: None,
-            offset,
-            limit,
-            rtxn,
-            index,
-            embedder_name,
-            embedder,
-            ranking_score_threshold: None,
-        }
     }
 
     pub fn filter(&mut self, filter: Filter<'a>) -> &mut Self {
@@ -48,18 +37,8 @@ impl<'a> Similar<'a> {
         self
     }
 
-    pub fn ranking_score_threshold(&mut self, ranking_score_threshold: f64) -> &mut Self {
-        self.ranking_score_threshold = Some(ranking_score_threshold);
-        self
-    }
-
     pub fn execute(&self) -> Result<SearchResult> {
-        let mut universe = filtered_universe(self.index, self.rtxn, &self.filter)?;
+        let universe = filtered_universe(self.index, self.rtxn, &self.filter)?;
-
-        // we never want to receive the docid
-        universe.remove(self.id);
-
-        let universe = universe;
 
         let embedder_index =
             self.index
@@ -98,8 +77,6 @@ impl<'a> Similar<'a> {
         let mut documents_seen = RoaringBitmap::new();
         documents_seen.insert(self.id);
 
-        let mut candidates = universe;
-
         for (docid, distance) in results
             .into_iter()
             // skip documents we've already seen & mark that we saw the current document
@@ -108,6 +85,8 @@ impl<'a> Similar<'a> {
             // take **after** filter and skip so that we get exactly limit elements if available
             .take(self.limit)
         {
+            documents_ids.push(docid);
+
             let score = 1.0 - distance;
             let score = self
                 .embedder
@@ -115,28 +94,14 @@ impl<'a> Similar<'a> {
                 .map(|distribution| distribution.shift(score))
                 .unwrap_or(score);
 
-            let score_details =
+            let score = ScoreDetails::Vector(score_details::Vector { similarity: Some(score) });
-                vec![ScoreDetails::Vector(score_details::Vector { similarity: Some(score) })];
 
-            let score = ScoreDetails::global_score(score_details.iter());
+            document_scores.push(vec![score]);
-
-            if let Some(ranking_score_threshold) = &self.ranking_score_threshold {
-                if score < *ranking_score_threshold {
-                    // this document is no longer a candidate
-                    candidates.remove(docid);
-                    // any document after this one is no longer a candidate either, so restrict the set to documents already seen.
-                    candidates &= documents_seen;
-                    break;
-                }
-            }
-
-            documents_ids.push(docid);
-            document_scores.push(score_details);
         }
 
         Ok(SearchResult {
             matching_words: Default::default(),
-            candidates,
+            candidates: universe,
             documents_ids,
             document_scores,
             degraded: false,

milli/src/snapshots/index.rs/initial_field_distribution/1/field_distribution.snap

@@ -0,0 +1,7 @@
+---
+source: milli/src/index.rs
+---
+age              1      |
+id               2      |
+name             2      |
+

milli/src/snapshots/index.rs/initial_field_distribution/field_distribution.snap

@@ -0,0 +1,7 @@
+---
+source: milli/src/index.rs
+---
+age              1      |
+id               2      |
+name             2      |
+

milli/src/update/clear_documents.rs

@@ -64,13 +64,6 @@ impl<'t, 'i> ClearDocuments<'t, 'i> {
         self.index.delete_geo_rtree(self.wtxn)?;
         self.index.delete_geo_faceted_documents_ids(self.wtxn)?;
 
-        // Remove all user-provided bits from the configs
-        let mut configs = self.index.embedding_configs(self.wtxn)?;
-        for config in configs.iter_mut() {
-            config.user_provided.clear();
-        }
-        self.index.put_embedding_configs(self.wtxn, configs)?;
-
         // Clear the other databases.
         external_documents_ids.clear(self.wtxn)?;
         word_docids.clear(self.wtxn)?;

milli/src/update/del_add.rs

@@ -40,26 +40,11 @@ pub fn into_del_add_obkv<K: obkv::Key + PartialOrd>(
     operation: DelAddOperation,
     buffer: &mut Vec<u8>,
 ) -> Result<(), std::io::Error> {
-    into_del_add_obkv_conditional_operation(reader, buffer, |_| operation)
-}
-
-/// Akin to the [into_del_add_obkv] function but lets you
-/// conditionally define the `DelAdd` variant based on the obkv key.
-pub fn into_del_add_obkv_conditional_operation<K, F>(
-    reader: obkv::KvReader<K>,
-    buffer: &mut Vec<u8>,
-    operation: F,
-) -> std::io::Result<()>
-where
-    K: obkv::Key + PartialOrd,
-    F: Fn(K) -> DelAddOperation,
-{
     let mut writer = obkv::KvWriter::new(buffer);
     let mut value_buffer = Vec::new();
     for (key, value) in reader.iter() {
         value_buffer.clear();
         let mut value_writer = KvWriterDelAdd::new(&mut value_buffer);
-        let operation = operation(key);
         if matches!(operation, DelAddOperation::Deletion | DelAddOperation::DeletionAndAddition) {
             value_writer.insert(DelAdd::Deletion, value)?;
         }

milli/src/update/index_documents/extract/extract_fid_docid_facet_values.rs

@@ -1,5 +1,5 @@
 use std::borrow::Cow;
-use std::collections::{BTreeMap, BTreeSet};
+use std::collections::BTreeMap;
 use std::convert::TryInto;
 use std::fs::File;
 use std::io::{self, BufReader};
@@ -9,7 +9,7 @@ use std::result::Result as StdResult;
 use bytemuck::bytes_of;
 use grenad::Sorter;
 use heed::BytesEncode;
-use itertools::{merge_join_by, EitherOrBoth};
+use itertools::EitherOrBoth;
 use ordered_float::OrderedFloat;
 use roaring::RoaringBitmap;
 use serde_json::{from_slice, Value};
@@ -18,7 +18,7 @@ use FilterableValues::{Empty, Null, Values};
 use super::helpers::{create_sorter, keep_first, sorter_into_reader, GrenadParameters};
 use crate::error::InternalError;
 use crate::facet::value_encoding::f64_into_bytes;
-use crate::update::del_add::{DelAdd, KvReaderDelAdd, KvWriterDelAdd};
+use crate::update::del_add::{DelAdd, KvWriterDelAdd};
 use crate::update::index_documents::{create_writer, writer_into_reader};
 use crate::update::settings::InnerIndexSettingsDiff;
 use crate::{CboRoaringBitmapCodec, DocumentId, Error, FieldId, Result, MAX_FACET_VALUE_LENGTH};
@@ -45,6 +45,7 @@ pub fn extract_fid_docid_facet_values<R: io::Read + io::Seek>(
     obkv_documents: grenad::Reader<R>,
     indexer: GrenadParameters,
     settings_diff: &InnerIndexSettingsDiff,
+    geo_fields_ids: Option<(FieldId, FieldId)>,
 ) -> Result<ExtractedFacetValues> {
     let max_memory = indexer.max_memory_by_thread();
 
@@ -75,181 +76,143 @@ pub fn extract_fid_docid_facet_values<R: io::Read + io::Seek>(
     let mut numbers_key_buffer = Vec::new();
     let mut strings_key_buffer = Vec::new();
 
-    let old_faceted_fids: BTreeSet<_> =
+    let mut cursor = obkv_documents.into_cursor()?;
-        settings_diff.old.faceted_fields_ids.iter().copied().collect();
+    while let Some((docid_bytes, value)) = cursor.move_on_next()? {
-    let new_faceted_fids: BTreeSet<_> =
+        let obkv = obkv::KvReader::new(value);
-        settings_diff.new.faceted_fields_ids.iter().copied().collect();
 
-    if !settings_diff.settings_update_only || old_faceted_fids != new_faceted_fids {
+        for (field_id, field_bytes) in obkv.iter() {
-        let mut cursor = obkv_documents.into_cursor()?;
+            let delete_faceted = settings_diff.old.faceted_fields_ids.contains(&field_id);
-        while let Some((docid_bytes, value)) = cursor.move_on_next()? {
+            let add_faceted = settings_diff.new.faceted_fields_ids.contains(&field_id);
-            let obkv = obkv::KvReader::new(value);
+            if delete_faceted || add_faceted {
-            let get_document_json_value = move |field_id, side| {
+                numbers_key_buffer.clear();
-                obkv.get(field_id)
+                strings_key_buffer.clear();
-                    .map(KvReaderDelAdd::new)
-                    .and_then(|kv| kv.get(side))
-                    .map(from_slice)
-                    .transpose()
-                    .map_err(InternalError::SerdeJson)
-            };
-            // iterate over the faceted fields instead of over the whole document.
-            for eob in
-                merge_join_by(old_faceted_fids.iter(), new_faceted_fids.iter(), |old, new| {
-                    old.cmp(new)
-                })
-            {
-                let (field_id, del_value, add_value) = match eob {
-                    EitherOrBoth::Left(&field_id) => {
-                        let del_value = get_document_json_value(field_id, DelAdd::Deletion)?;
 
-                        // deletion only
+                // Set key to the field_id
-                        (field_id, del_value, None)
+                // Note: this encoding is consistent with FieldIdCodec
-                    }
+                numbers_key_buffer.extend_from_slice(&field_id.to_be_bytes());
-                    EitherOrBoth::Right(&field_id) => {
+                strings_key_buffer.extend_from_slice(&field_id.to_be_bytes());
-                        let add_value = get_document_json_value(field_id, DelAdd::Addition)?;
 
-                        // addition only
+                let document: [u8; 4] = docid_bytes[..4].try_into().ok().unwrap();
-                        (field_id, None, add_value)
+                let document = DocumentId::from_be_bytes(document);
-                    }
-                    EitherOrBoth::Both(&field_id, _) => {
-                        // during settings update, recompute the changing settings only.
-                        if settings_diff.settings_update_only {
-                            continue;
-                        }
 
-                        let del_value = get_document_json_value(field_id, DelAdd::Deletion)?;
+                // For the other extraction tasks, prefix the key with the field_id and the document_id
-                        let add_value = get_document_json_value(field_id, DelAdd::Addition)?;
+                numbers_key_buffer.extend_from_slice(docid_bytes);
+                strings_key_buffer.extend_from_slice(docid_bytes);
 
-                        (field_id, del_value, add_value)
+                let del_add_obkv = obkv::KvReader::new(field_bytes);
-                    }
+                let del_value = match del_add_obkv.get(DelAdd::Deletion).filter(|_| delete_faceted)
+                {
+                    Some(bytes) => Some(from_slice(bytes).map_err(InternalError::SerdeJson)?),
+                    None => None,
+                };
+                let add_value = match del_add_obkv.get(DelAdd::Addition).filter(|_| add_faceted) {
+                    Some(bytes) => Some(from_slice(bytes).map_err(InternalError::SerdeJson)?),
+                    None => None,
                 };
 
-                if del_value.is_some() || add_value.is_some() {
+                // We insert the document id on the Del and the Add side if the field exists.
-                    numbers_key_buffer.clear();
+                let (ref mut del_exists, ref mut add_exists) =
-                    strings_key_buffer.clear();
+                    facet_exists_docids.entry(field_id).or_default();
+                let (ref mut del_is_null, ref mut add_is_null) =
+                    facet_is_null_docids.entry(field_id).or_default();
+                let (ref mut del_is_empty, ref mut add_is_empty) =
+                    facet_is_empty_docids.entry(field_id).or_default();
 
-                    // Set key to the field_id
+                if del_value.is_some() {
-                    // Note: this encoding is consistent with FieldIdCodec
+                    del_exists.insert(document);
-                    numbers_key_buffer.extend_from_slice(&field_id.to_be_bytes());
+                }
-                    strings_key_buffer.extend_from_slice(&field_id.to_be_bytes());
+                if add_value.is_some() {
+                    add_exists.insert(document);
+                }
 
-                    let document: [u8; 4] = docid_bytes[..4].try_into().ok().unwrap();
+                let geo_support =
-                    let document = DocumentId::from_be_bytes(document);
+                    geo_fields_ids.map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
+                let del_filterable_values =
+                    del_value.map(|value| extract_facet_values(&value, geo_support));
+                let add_filterable_values =
+                    add_value.map(|value| extract_facet_values(&value, geo_support));
 
-                    // For the other extraction tasks, prefix the key with the field_id and the document_id
+                // Those closures are just here to simplify things a bit.
-                    numbers_key_buffer.extend_from_slice(docid_bytes);
+                let mut insert_numbers_diff = |del_numbers, add_numbers| {
-                    strings_key_buffer.extend_from_slice(docid_bytes);
+                    insert_numbers_diff(
+                        &mut fid_docid_facet_numbers_sorter,
+                        &mut numbers_key_buffer,
+                        del_numbers,
+                        add_numbers,
+                    )
+                };
+                let mut insert_strings_diff = |del_strings, add_strings| {
+                    insert_strings_diff(
+                        &mut fid_docid_facet_strings_sorter,
+                        &mut strings_key_buffer,
+                        del_strings,
+                        add_strings,
+                    )
+                };
 
-                    // We insert the document id on the Del and the Add side if the field exists.
+                match (del_filterable_values, add_filterable_values) {
-                    let (ref mut del_exists, ref mut add_exists) =
+                    (None, None) => (),
-                        facet_exists_docids.entry(field_id).or_default();
+                    (Some(del_filterable_values), None) => match del_filterable_values {
-                    let (ref mut del_is_null, ref mut add_is_null) =
+                        Null => {
-                        facet_is_null_docids.entry(field_id).or_default();
+                            del_is_null.insert(document);
-                    let (ref mut del_is_empty, ref mut add_is_empty) =
+                        }
-                        facet_is_empty_docids.entry(field_id).or_default();
+                        Empty => {
-
+                            del_is_empty.insert(document);
-                    if del_value.is_some() {
+                        }
-                        del_exists.insert(document);
+                        Values { numbers, strings } => {
-                    }
+                            insert_numbers_diff(numbers, vec![])?;
-                    if add_value.is_some() {
+                            insert_strings_diff(strings, vec![])?;
-                        add_exists.insert(document);
+                        }
-                    }
+                    },
-
+                    (None, Some(add_filterable_values)) => match add_filterable_values {
-                    let del_geo_support = settings_diff
+                        Null => {
-                        .old
+                            add_is_null.insert(document);
-                        .geo_fields_ids
+                        }
-                        .map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
+                        Empty => {
-                    let add_geo_support = settings_diff
+                            add_is_empty.insert(document);
-                        .new
+                        }
-                        .geo_fields_ids
+                        Values { numbers, strings } => {
-                        .map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
+                            insert_numbers_diff(vec![], numbers)?;
-                    let del_filterable_values =
+                            insert_strings_diff(vec![], strings)?;
-                        del_value.map(|value| extract_facet_values(&value, del_geo_support));
+                        }
-                    let add_filterable_values =
+                    },
-                        add_value.map(|value| extract_facet_values(&value, add_geo_support));
+                    (Some(del_filterable_values), Some(add_filterable_values)) => {
-
+                        match (del_filterable_values, add_filterable_values) {
-                    // Those closures are just here to simplify things a bit.
+                            (Null, Null) | (Empty, Empty) => (),
-                    let mut insert_numbers_diff = |del_numbers, add_numbers| {
+                            (Null, Empty) => {
-                        insert_numbers_diff(
+                                del_is_null.insert(document);
-                            &mut fid_docid_facet_numbers_sorter,
+                                add_is_empty.insert(document);
-                            &mut numbers_key_buffer,
+                            }
-                            del_numbers,
+                            (Empty, Null) => {
-                            add_numbers,
+                                del_is_empty.insert(document);
-                        )
+                                add_is_null.insert(document);
-                    };
+                            }
-                    let mut insert_strings_diff = |del_strings, add_strings| {
+                            (Null, Values { numbers, strings }) => {
-                        insert_strings_diff(
+                                insert_numbers_diff(vec![], numbers)?;
-                            &mut fid_docid_facet_strings_sorter,
+                                insert_strings_diff(vec![], strings)?;
-                            &mut strings_key_buffer,
-                            del_strings,
-                            add_strings,
-                        )
-                    };
-
-                    match (del_filterable_values, add_filterable_values) {
-                        (None, None) => (),
-                        (Some(del_filterable_values), None) => match del_filterable_values {
-                            Null => {
                                 del_is_null.insert(document);
                             }
-                            Empty => {
+                            (Empty, Values { numbers, strings }) => {
+                                insert_numbers_diff(vec![], numbers)?;
+                                insert_strings_diff(vec![], strings)?;
                                 del_is_empty.insert(document);
                             }
-                            Values { numbers, strings } => {
+                            (Values { numbers, strings }, Null) => {
+                                add_is_null.insert(document);
                                 insert_numbers_diff(numbers, vec![])?;
                                 insert_strings_diff(strings, vec![])?;
                             }
-                        },
+                            (Values { numbers, strings }, Empty) => {
-                        (None, Some(add_filterable_values)) => match add_filterable_values {
-                            Null => {
-                                add_is_null.insert(document);
-                            }
-                            Empty => {
                                 add_is_empty.insert(document);
+                                insert_numbers_diff(numbers, vec![])?;
+                                insert_strings_diff(strings, vec![])?;
                             }
-                            Values { numbers, strings } => {
+                            (
-                                insert_numbers_diff(vec![], numbers)?;
+                                Values { numbers: del_numbers, strings: del_strings },
-                                insert_strings_diff(vec![], strings)?;
+                                Values { numbers: add_numbers, strings: add_strings },
-                            }
+                            ) => {
-                        },
+                                insert_numbers_diff(del_numbers, add_numbers)?;
-                        (Some(del_filterable_values), Some(add_filterable_values)) => {
+                                insert_strings_diff(del_strings, add_strings)?;
-                            match (del_filterable_values, add_filterable_values) {
-                                (Null, Null) | (Empty, Empty) => (),
-                                (Null, Empty) => {
-                                    del_is_null.insert(document);
-                                    add_is_empty.insert(document);
-                                }
-                                (Empty, Null) => {
-                                    del_is_empty.insert(document);
-                                    add_is_null.insert(document);
-                                }
-                                (Null, Values { numbers, strings }) => {
-                                    insert_numbers_diff(vec![], numbers)?;
-                                    insert_strings_diff(vec![], strings)?;
-                                    del_is_null.insert(document);
-                                }
-                                (Empty, Values { numbers, strings }) => {
-                                    insert_numbers_diff(vec![], numbers)?;
-                                    insert_strings_diff(vec![], strings)?;
-                                    del_is_empty.insert(document);
-                                }
-                                (Values { numbers, strings }, Null) => {
-                                    add_is_null.insert(document);
-                                    insert_numbers_diff(numbers, vec![])?;
-                                    insert_strings_diff(strings, vec![])?;
-                                }
-                                (Values { numbers, strings }, Empty) => {
-                                    add_is_empty.insert(document);
-                                    insert_numbers_diff(numbers, vec![])?;
-                                    insert_strings_diff(strings, vec![])?;
-                                }
-                                (
-                                    Values { numbers: del_numbers, strings: del_strings },
-                                    Values { numbers: add_numbers, strings: add_strings },
-                                ) => {
-                                    insert_numbers_diff(del_numbers, add_numbers)?;
-                                    insert_strings_diff(del_strings, add_strings)?;
-                                }
                             }
                         }
                     }

milli/src/update/index_documents/extract/extract_geo_points.rs

@@ -8,7 +8,6 @@ use super::helpers::{create_writer, writer_into_reader, GrenadParameters};
 use crate::error::GeoError;
 use crate::update::del_add::{DelAdd, KvReaderDelAdd, KvWriterDelAdd};
 use crate::update::index_documents::extract_finite_float_from_value;
-use crate::update::settings::{InnerIndexSettings, InnerIndexSettingsDiff};
 use crate::{FieldId, InternalError, Result};
 
 /// Extracts the geographical coordinates contained in each document under the `_geo` field.
@@ -19,7 +18,7 @@ pub fn extract_geo_points<R: io::Read + io::Seek>(
     obkv_documents: grenad::Reader<R>,
     indexer: GrenadParameters,
     primary_key_id: FieldId,
-    settings_diff: &InnerIndexSettingsDiff,
+    (lat_fid, lng_fid): (FieldId, FieldId),
 ) -> Result<grenad::Reader<BufReader<File>>> {
     let mut writer = create_writer(
         indexer.chunk_compression_type,
@@ -39,27 +38,47 @@ pub fn extract_geo_points<R: io::Read + io::Seek>(
             serde_json::from_slice(document_id).unwrap()
         };
 
-        // extract old version
+        // first we get the two fields
-        let del_lat_lng =
+        match (obkv.get(lat_fid), obkv.get(lng_fid)) {
-            extract_lat_lng(&obkv, &settings_diff.old, DelAdd::Deletion, document_id)?;
+            (Some(lat), Some(lng)) => {
-        // extract new version
+                let deladd_lat_obkv = KvReaderDelAdd::new(lat);
-        let add_lat_lng =
+                let deladd_lng_obkv = KvReaderDelAdd::new(lng);
-            extract_lat_lng(&obkv, &settings_diff.new, DelAdd::Addition, document_id)?;
 
-        if del_lat_lng != add_lat_lng {
+                // then we extract the values
-            let mut obkv = KvWriterDelAdd::memory();
+                let del_lat_lng = deladd_lat_obkv
-            if let Some([lat, lng]) = del_lat_lng {
+                    .get(DelAdd::Deletion)
-                #[allow(clippy::drop_non_drop)]
+                    .zip(deladd_lng_obkv.get(DelAdd::Deletion))
-                let bytes: [u8; 16] = concat_arrays![lat.to_ne_bytes(), lng.to_ne_bytes()];
+                    .map(|(lat, lng)| extract_lat_lng(lat, lng, document_id))
-                obkv.insert(DelAdd::Deletion, bytes)?;
+                    .transpose()?;
+                let add_lat_lng = deladd_lat_obkv
+                    .get(DelAdd::Addition)
+                    .zip(deladd_lng_obkv.get(DelAdd::Addition))
+                    .map(|(lat, lng)| extract_lat_lng(lat, lng, document_id))
+                    .transpose()?;
+
+                if del_lat_lng != add_lat_lng {
+                    let mut obkv = KvWriterDelAdd::memory();
+                    if let Some([lat, lng]) = del_lat_lng {
+                        #[allow(clippy::drop_non_drop)]
+                        let bytes: [u8; 16] = concat_arrays![lat.to_ne_bytes(), lng.to_ne_bytes()];
+                        obkv.insert(DelAdd::Deletion, bytes)?;
+                    }
+                    if let Some([lat, lng]) = add_lat_lng {
+                        #[allow(clippy::drop_non_drop)]
+                        let bytes: [u8; 16] = concat_arrays![lat.to_ne_bytes(), lng.to_ne_bytes()];
+                        obkv.insert(DelAdd::Addition, bytes)?;
+                    }
+                    let bytes = obkv.into_inner()?;
+                    writer.insert(docid_bytes, bytes)?;
+                }
             }
-            if let Some([lat, lng]) = add_lat_lng {
+            (None, Some(_)) => {
-                #[allow(clippy::drop_non_drop)]
+                return Err(GeoError::MissingLatitude { document_id: document_id() }.into())
-                let bytes: [u8; 16] = concat_arrays![lat.to_ne_bytes(), lng.to_ne_bytes()];
-                obkv.insert(DelAdd::Addition, bytes)?;
             }
-            let bytes = obkv.into_inner()?;
+            (Some(_), None) => {
-            writer.insert(docid_bytes, bytes)?;
+                return Err(GeoError::MissingLongitude { document_id: document_id() }.into())
+            }
+            (None, None) => (),
         }
     }
 
@@ -67,37 +86,16 @@ pub fn extract_geo_points<R: io::Read + io::Seek>(
 }
 
 /// Extract the finite floats lat and lng from two bytes slices.
-fn extract_lat_lng(
+fn extract_lat_lng(lat: &[u8], lng: &[u8], document_id: impl Fn() -> Value) -> Result<[f64; 2]> {
-    document: &obkv::KvReader<FieldId>,
+    let lat = extract_finite_float_from_value(
-    settings: &InnerIndexSettings,
+        serde_json::from_slice(lat).map_err(InternalError::SerdeJson)?,
-    deladd: DelAdd,
+    )
-    document_id: impl Fn() -> Value,
+    .map_err(|lat| GeoError::BadLatitude { document_id: document_id(), value: lat })?;
-) -> Result<Option<[f64; 2]>> {
-    match settings.geo_fields_ids {
-        Some((lat_fid, lng_fid)) => {
-            let lat = document.get(lat_fid).map(KvReaderDelAdd::new).and_then(|r| r.get(deladd));
-            let lng = document.get(lng_fid).map(KvReaderDelAdd::new).and_then(|r| r.get(deladd));
-            let (lat, lng) = match (lat, lng) {
-                (Some(lat), Some(lng)) => (lat, lng),
-                (Some(_), None) => {
-                    return Err(GeoError::MissingLatitude { document_id: document_id() }.into())
-                }
-                (None, Some(_)) => {
-                    return Err(GeoError::MissingLongitude { document_id: document_id() }.into())
-                }
-                (None, None) => return Ok(None),
-            };
-            let lat = extract_finite_float_from_value(
-                serde_json::from_slice(lat).map_err(InternalError::SerdeJson)?,
-            )
-            .map_err(|lat| GeoError::BadLatitude { document_id: document_id(), value: lat })?;
 
-            let lng = extract_finite_float_from_value(
+    let lng = extract_finite_float_from_value(
-                serde_json::from_slice(lng).map_err(InternalError::SerdeJson)?,
+        serde_json::from_slice(lng).map_err(InternalError::SerdeJson)?,
-            )
+    )
-            .map_err(|lng| GeoError::BadLongitude { document_id: document_id(), value: lng })?;
+    .map_err(|lng| GeoError::BadLongitude { document_id: document_id(), value: lng })?;
-            Ok(Some([lat, lng]))
+
-        }
+    Ok([lat, lng])
-        None => Ok(None),
-    }
 }

milli/src/update/index_documents/extract/extract_vector_points.rs

@@ -8,19 +8,18 @@ use std::sync::Arc;
 
 use bytemuck::cast_slice;
 use grenad::Writer;
+use itertools::EitherOrBoth;
 use ordered_float::OrderedFloat;
-use roaring::RoaringBitmap;
 use serde_json::Value;
 
 use super::helpers::{create_writer, writer_into_reader, GrenadParameters};
-use crate::index::IndexEmbeddingConfig;
 use crate::prompt::Prompt;
 use crate::update::del_add::{DelAdd, KvReaderDelAdd, KvWriterDelAdd};
+use crate::update::index_documents::helpers::try_split_at;
 use crate::update::settings::InnerIndexSettingsDiff;
-use crate::vector::parsed_vectors::{ParsedVectorsDiff, VectorState, RESERVED_VECTORS_FIELD_NAME};
+use crate::vector::parsed_vectors::{ParsedVectorsDiff, RESERVED_VECTORS_FIELD_NAME};
-use crate::vector::settings::{EmbedderAction, ReindexAction};
 use crate::vector::Embedder;
-use crate::{try_split_array_at, DocumentId, FieldId, FieldsIdsMap, Result, ThreadPoolNoAbort};
+use crate::{DocumentId, Result, ThreadPoolNoAbort};
 
 /// The length of the elements that are always in the buffer when inserting new values.
 const TRUNCATE_SIZE: usize = size_of::<DocumentId>();
@@ -36,8 +35,6 @@ pub struct ExtractedVectorPoints {
     // embedder
     pub embedder_name: String,
     pub embedder: Arc<Embedder>,
-    pub add_to_user_provided: RoaringBitmap,
-    pub remove_from_user_provided: RoaringBitmap,
 }
 
 enum VectorStateDelta {
@@ -45,7 +42,12 @@ enum VectorStateDelta {
     // Remove all vectors, generated or manual, from this document
     NowRemoved,
 
-    NowManual(Vec<Vec<f32>>),
+    // Add the manually specified vectors, passed in the other grenad
+    // Remove any previously generated vectors
+    // Note: changing the value of the manually specified vector **should not record** this delta
+    WasGeneratedNowManual(Vec<Vec<f32>>),
+
+    ManualDelta(Vec<Vec<f32>>, Vec<Vec<f32>>),
 
     // Add the vector computed from the specified prompt
     // Remove any previous vector
@@ -54,12 +56,14 @@ enum VectorStateDelta {
 }
 
 impl VectorStateDelta {
-    fn into_values(self) -> (bool, String, Vec<Vec<f32>>) {
+    fn into_values(self) -> (bool, String, (Vec<Vec<f32>>, Vec<Vec<f32>>)) {
         match self {
             VectorStateDelta::NoChange => Default::default(),
             VectorStateDelta::NowRemoved => (true, Default::default(), Default::default()),
-            // We always delete the previous vectors
+            VectorStateDelta::WasGeneratedNowManual(add) => {
-            VectorStateDelta::NowManual(add) => (true, Default::default(), add),
+                (true, Default::default(), (Default::default(), add))
+            }
+            VectorStateDelta::ManualDelta(del, add) => (false, Default::default(), (del, add)),
             VectorStateDelta::NowGenerated(prompt) => (true, prompt, Default::default()),
         }
     }
@@ -70,27 +74,12 @@ struct EmbedderVectorExtractor {
     embedder: Arc<Embedder>,
     prompt: Arc<Prompt>,
 
+    // (docid, _index) -> KvWriterDelAdd -> Vector
+    manual_vectors_writer: Writer<BufWriter<File>>,
     // (docid) -> (prompt)
     prompts_writer: Writer<BufWriter<File>>,
     // (docid) -> ()
     remove_vectors_writer: Writer<BufWriter<File>>,
-    // (docid, _index) -> KvWriterDelAdd -> Vector
-    manual_vectors_writer: Writer<BufWriter<File>>,
-    // The docids of the documents that contains a user defined embedding
-    add_to_user_provided: RoaringBitmap,
-
-    action: ExtractionAction,
-}
-
-struct DocumentOperation {
-    // The docids of the documents that contains an auto-generated embedding
-    remove_from_user_provided: RoaringBitmap,
-}
-
-enum ExtractionAction {
-    SettingsFullReindex,
-    SettingsRegeneratePrompts { old_prompt: Arc<Prompt> },
-    DocumentOperation(DocumentOperation),
 }
 
 /// Extracts the embedding vector contained in each document under the `_vectors` field.
@@ -100,7 +89,6 @@ enum ExtractionAction {
 pub fn extract_vector_points<R: io::Read + io::Seek>(
     obkv_documents: grenad::Reader<R>,
     indexer: GrenadParameters,
-    embedders_configs: &[IndexEmbeddingConfig],
     settings_diff: &InnerIndexSettingsDiff,
 ) -> Result<Vec<ExtractedVectorPoints>> {
     let reindex_vectors = settings_diff.reindex_vectors();
@@ -109,207 +97,153 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
     let new_fields_ids_map = &settings_diff.new.fields_ids_map;
     // the vector field id may have changed
     let old_vectors_fid = old_fields_ids_map.id(RESERVED_VECTORS_FIELD_NAME);
+    // filter the old vector fid if the settings has been changed forcing reindexing.
+    let old_vectors_fid = old_vectors_fid.filter(|_| !reindex_vectors);
 
     let new_vectors_fid = new_fields_ids_map.id(RESERVED_VECTORS_FIELD_NAME);
 
     let mut extractors = Vec::new();
+    for (embedder_name, (embedder, prompt)) in
+        settings_diff.new.embedding_configs.clone().into_iter()
+    {
+        // (docid, _index) -> KvWriterDelAdd -> Vector
+        let manual_vectors_writer = create_writer(
+            indexer.chunk_compression_type,
+            indexer.chunk_compression_level,
+            tempfile::tempfile()?,
+        );
 
-    let mut configs = settings_diff.new.embedding_configs.clone().into_inner();
+        // (docid) -> (prompt)
-    let old_configs = &settings_diff.old.embedding_configs;
+        let prompts_writer = create_writer(
+            indexer.chunk_compression_type,
+            indexer.chunk_compression_level,
+            tempfile::tempfile()?,
+        );
 
-    if reindex_vectors {
+        // (docid) -> ()
-        for (name, action) in settings_diff.embedding_config_updates.iter() {
+        let remove_vectors_writer = create_writer(
-            match action {
+            indexer.chunk_compression_type,
-                EmbedderAction::WriteBackToDocuments(_) => continue, // already deleted
+            indexer.chunk_compression_level,
-                EmbedderAction::Reindex(action) => {
+            tempfile::tempfile()?,
-                    let Some((embedder_name, (embedder, prompt))) = configs.remove_entry(name)
+        );
-                    else {
-                        tracing::error!(embedder = name, "Requested embedder config not found");
-                        continue;
-                    };
 
-                    // (docid, _index) -> KvWriterDelAdd -> Vector
+        extractors.push(EmbedderVectorExtractor {
-                    let manual_vectors_writer = create_writer(
+            embedder_name,
-                        indexer.chunk_compression_type,
+            embedder,
-                        indexer.chunk_compression_level,
+            prompt,
-                        tempfile::tempfile()?,
+            manual_vectors_writer,
-                    );
+            prompts_writer,
-
+            remove_vectors_writer,
-                    // (docid) -> (prompt)
+        });
-                    let prompts_writer = create_writer(
-                        indexer.chunk_compression_type,
-                        indexer.chunk_compression_level,
-                        tempfile::tempfile()?,
-                    );
-
-                    // (docid) -> ()
-                    let remove_vectors_writer = create_writer(
-                        indexer.chunk_compression_type,
-                        indexer.chunk_compression_level,
-                        tempfile::tempfile()?,
-                    );
-
-                    let action = match action {
-                        ReindexAction::FullReindex => ExtractionAction::SettingsFullReindex,
-                        ReindexAction::RegeneratePrompts => {
-                            let Some((_, old_prompt)) = old_configs.get(name) else {
-                                tracing::error!(embedder = name, "Old embedder config not found");
-                                continue;
-                            };
-
-                            ExtractionAction::SettingsRegeneratePrompts { old_prompt }
-                        }
-                    };
-
-                    extractors.push(EmbedderVectorExtractor {
-                        embedder_name,
-                        embedder,
-                        prompt,
-                        prompts_writer,
-                        remove_vectors_writer,
-                        manual_vectors_writer,
-                        add_to_user_provided: RoaringBitmap::new(),
-                        action,
-                    });
-                }
-            }
-        }
-    } else {
-        // document operation
-
-        for (embedder_name, (embedder, prompt)) in configs.into_iter() {
-            // (docid, _index) -> KvWriterDelAdd -> Vector
-            let manual_vectors_writer = create_writer(
-                indexer.chunk_compression_type,
-                indexer.chunk_compression_level,
-                tempfile::tempfile()?,
-            );
-
-            // (docid) -> (prompt)
-            let prompts_writer = create_writer(
-                indexer.chunk_compression_type,
-                indexer.chunk_compression_level,
-                tempfile::tempfile()?,
-            );
-
-            // (docid) -> ()
-            let remove_vectors_writer = create_writer(
-                indexer.chunk_compression_type,
-                indexer.chunk_compression_level,
-                tempfile::tempfile()?,
-            );
-
-            extractors.push(EmbedderVectorExtractor {
-                embedder_name,
-                embedder,
-                prompt,
-                prompts_writer,
-                remove_vectors_writer,
-                manual_vectors_writer,
-                add_to_user_provided: RoaringBitmap::new(),
-                action: ExtractionAction::DocumentOperation(DocumentOperation {
-                    remove_from_user_provided: RoaringBitmap::new(),
-                }),
-            });
-        }
     }
 
     let mut key_buffer = Vec::new();
     let mut cursor = obkv_documents.into_cursor()?;
     while let Some((key, value)) = cursor.move_on_next()? {
         // this must always be serialized as (docid, external_docid);
-        const SIZE_OF_DOCUMENTID: usize = std::mem::size_of::<DocumentId>();
         let (docid_bytes, external_id_bytes) =
-            try_split_array_at::<u8, SIZE_OF_DOCUMENTID>(key).unwrap();
+            try_split_at(key, std::mem::size_of::<DocumentId>()).unwrap();
         debug_assert!(from_utf8(external_id_bytes).is_ok());
-        let docid = DocumentId::from_be_bytes(docid_bytes);
 
         let obkv = obkv::KvReader::new(value);
         key_buffer.clear();
-        key_buffer.extend_from_slice(docid_bytes.as_slice());
+        key_buffer.extend_from_slice(docid_bytes);
 
         // since we only need the primary key when we throw an error we create this getter to
         // lazily get it when needed
         let document_id = || -> Value { from_utf8(external_id_bytes).unwrap().into() };
 
-        let mut parsed_vectors = ParsedVectorsDiff::new(
+        let mut parsed_vectors = ParsedVectorsDiff::new(obkv, old_vectors_fid, new_vectors_fid)
-            docid,
+            .map_err(|error| error.to_crate_error(document_id().to_string()))?;
-            embedders_configs,
-            obkv,
-            old_vectors_fid,
-            new_vectors_fid,
-        )
-        .map_err(|error| error.to_crate_error(document_id().to_string()))?;
 
         for EmbedderVectorExtractor {
             embedder_name,
             embedder: _,
             prompt,
+            manual_vectors_writer,
             prompts_writer,
             remove_vectors_writer,
-            manual_vectors_writer,
-            add_to_user_provided,
-            action,
         } in extractors.iter_mut()
         {
-            let (old, new) = parsed_vectors.remove(embedder_name);
+            let delta = match parsed_vectors.remove(embedder_name) {
-            let delta = match action {
+                (Some(old), Some(new)) => {
-                ExtractionAction::SettingsFullReindex => match old {
+                    // no autogeneration
-                    // A full reindex can be triggered either by:
+                    let del_vectors = old.into_array_of_vectors();
-                    // 1. a new embedder
+                    let add_vectors = new.into_array_of_vectors();
-                    // 2. an existing embedder changed so that it must regenerate all generated embeddings.
-                    // For a new embedder, there can be `_vectors.embedder` embeddings to add to the DB
-                    VectorState::Inline(vectors) => {
-                        if !vectors.must_regenerate() {
-                            add_to_user_provided.insert(docid);
-                        }
 
-                        match vectors.into_array_of_vectors() {
+                    if add_vectors.len() > usize::from(u8::MAX) {
-                            Some(add_vectors) => {
+                        return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
-                                if add_vectors.len() > usize::from(u8::MAX) {
+                            document_id().to_string(),
-                                    return Err(crate::Error::UserError(
+                            add_vectors.len(),
-                                        crate::UserError::TooManyVectors(
+                        )));
-                                            document_id().to_string(),
-                                            add_vectors.len(),
-                                        ),
-                                    ));
-                                }
-                                VectorStateDelta::NowManual(add_vectors)
-                            }
-                            None => VectorStateDelta::NoChange,
-                        }
                     }
-                    // this happens only when an existing embedder changed. We cannot regenerate userProvided vectors
+
-                    VectorState::Manual => VectorStateDelta::NoChange,
+                    VectorStateDelta::ManualDelta(del_vectors, add_vectors)
-                    // generated vectors must be regenerated
+                }
-                    VectorState::Generated => regenerate_prompt(obkv, prompt, new_fields_ids_map)?,
+                (Some(_old), None) => {
-                },
+                    // Do we keep this document?
-                // prompt regeneration is only triggered for existing embedders
+                    let document_is_kept = obkv
-                ExtractionAction::SettingsRegeneratePrompts { old_prompt } => {
+                        .iter()
-                    if old.must_regenerate() {
+                        .map(|(_, deladd)| KvReaderDelAdd::new(deladd))
-                        regenerate_if_prompt_changed(
+                        .any(|deladd| deladd.get(DelAdd::Addition).is_some());
+                    if document_is_kept {
+                        // becomes autogenerated
+                        VectorStateDelta::NowGenerated(prompt.render(
                             obkv,
-                            (old_prompt, prompt),
+                            DelAdd::Addition,
-                            (old_fields_ids_map, new_fields_ids_map),
+                            new_fields_ids_map,
-                        )?
+                        )?)
                     } else {
-                        // we can simply ignore user provided vectors as they are not regenerated and are
+                        VectorStateDelta::NowRemoved
-                        // already in the DB since this is an existing embedder
+                    }
-                        VectorStateDelta::NoChange
+                }
+                (None, Some(new)) => {
+                    // was possibly autogenerated, remove all vectors for that document
+                    let add_vectors = new.into_array_of_vectors();
+                    if add_vectors.len() > usize::from(u8::MAX) {
+                        return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
+                            document_id().to_string(),
+                            add_vectors.len(),
+                        )));
+                    }
+
+                    VectorStateDelta::WasGeneratedNowManual(add_vectors)
+                }
+                (None, None) => {
+                    // Do we keep this document?
+                    let document_is_kept = obkv
+                        .iter()
+                        .map(|(_, deladd)| KvReaderDelAdd::new(deladd))
+                        .any(|deladd| deladd.get(DelAdd::Addition).is_some());
+
+                    if document_is_kept {
+                        // Don't give up if the old prompt was failing
+                        let old_prompt = Some(&prompt)
+                            // TODO: this filter works because we erase the vec database when a embedding setting changes.
+                            // When vector pipeline will be optimized, this should be removed.
+                            .filter(|_| !settings_diff.reindex_vectors())
+                            .map(|p| {
+                                p.render(obkv, DelAdd::Deletion, old_fields_ids_map)
+                                    .unwrap_or_default()
+                            });
+                        let new_prompt =
+                            prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
+                        if old_prompt.as_ref() != Some(&new_prompt) {
+                            let old_prompt = old_prompt.unwrap_or_default();
+                            tracing::trace!(
+                                "🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
+                            );
+                            VectorStateDelta::NowGenerated(new_prompt)
+                        } else {
+                            tracing::trace!("⏭️ Prompt unmodified, skipping");
+                            VectorStateDelta::NoChange
+                        }
+                    } else {
+                        VectorStateDelta::NowRemoved
                     }
                 }
-                ExtractionAction::DocumentOperation(DocumentOperation {
-                    remove_from_user_provided,
-                }) => extract_vector_document_diff(
-                    docid,
-                    obkv,
-                    prompt,
-                    (add_to_user_provided, remove_from_user_provided),
-                    (old, new),
-                    (old_fields_ids_map, new_fields_ids_map),
-                    document_id,
-                )?,
             };
+
             // and we finally push the unique vectors into the writer
             push_vectors_diff(
                 remove_vectors_writer,
@@ -317,6 +251,7 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
                 manual_vectors_writer,
                 &mut key_buffer,
                 delta,
+                reindex_vectors,
             )?;
         }
     }
@@ -327,185 +262,43 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
         embedder_name,
         embedder,
         prompt: _,
+        manual_vectors_writer,
         prompts_writer,
         remove_vectors_writer,
-        action,
-        manual_vectors_writer,
-        add_to_user_provided,
     } in extractors
     {
-        let remove_from_user_provided =
-            if let ExtractionAction::DocumentOperation(DocumentOperation {
-                remove_from_user_provided,
-            }) = action
-            {
-                remove_from_user_provided
-            } else {
-                Default::default()
-            };
-
         results.push(ExtractedVectorPoints {
+            // docid, _index -> KvWriterDelAdd -> Vector
             manual_vectors: writer_into_reader(manual_vectors_writer)?,
+            // docid -> ()
             remove_vectors: writer_into_reader(remove_vectors_writer)?,
+            // docid -> prompt
             prompts: writer_into_reader(prompts_writer)?,
+
             embedder,
             embedder_name,
-            add_to_user_provided,
-            remove_from_user_provided,
         })
     }
 
     Ok(results)
 }
 
-fn extract_vector_document_diff(
+/// Computes the diff between both Del and Add numbers and
-    docid: DocumentId,
+/// only inserts the parts that differ in the sorter.
-    obkv: obkv::KvReader<'_, FieldId>,
-    prompt: &Prompt,
-    (add_to_user_provided, remove_from_user_provided): (&mut RoaringBitmap, &mut RoaringBitmap),
-    (old, new): (VectorState, VectorState),
-    (old_fields_ids_map, new_fields_ids_map): (&FieldsIdsMap, &FieldsIdsMap),
-    document_id: impl Fn() -> Value,
-) -> Result<VectorStateDelta> {
-    match (old.must_regenerate(), new.must_regenerate()) {
-        (true, true) | (false, false) => {}
-        (true, false) => {
-            add_to_user_provided.insert(docid);
-        }
-        (false, true) => {
-            remove_from_user_provided.insert(docid);
-        }
-    }
-
-    let delta = match (old, new) {
-        // regardless of the previous state, if a document now contains inline _vectors, they must
-        // be extracted manually
-        (_old, VectorState::Inline(new)) => match new.into_array_of_vectors() {
-            Some(add_vectors) => {
-                if add_vectors.len() > usize::from(u8::MAX) {
-                    return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
-                        document_id().to_string(),
-                        add_vectors.len(),
-                    )));
-                }
-
-                VectorStateDelta::NowManual(add_vectors)
-            }
-            None => VectorStateDelta::NoChange,
-        },
-        // no `_vectors` anywhere, we check for document removal and otherwise we regenerate the prompt if the
-        // document changed
-        (VectorState::Generated, VectorState::Generated) => {
-            // Do we keep this document?
-            let document_is_kept = obkv
-                .iter()
-                .map(|(_, deladd)| KvReaderDelAdd::new(deladd))
-                .any(|deladd| deladd.get(DelAdd::Addition).is_some());
-
-            if document_is_kept {
-                // Don't give up if the old prompt was failing
-                let old_prompt = Some(&prompt).map(|p| {
-                    p.render(obkv, DelAdd::Deletion, old_fields_ids_map).unwrap_or_default()
-                });
-                let new_prompt = prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
-                if old_prompt.as_ref() != Some(&new_prompt) {
-                    let old_prompt = old_prompt.unwrap_or_default();
-                    tracing::trace!(
-                        "🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
-                    );
-                    VectorStateDelta::NowGenerated(new_prompt)
-                } else {
-                    tracing::trace!("⏭️ Prompt unmodified, skipping");
-                    VectorStateDelta::NoChange
-                }
-            } else {
-                VectorStateDelta::NowRemoved
-            }
-        }
-        // inline to the left is not supposed to be possible because the embedder is not new, so `_vectors` was removed from
-        // the previous version of the document.
-        // Manual -> Generated is also not possible without an Inline to the right (which is handled above)
-        // Generated -> Generated is handled above, so not possible
-        // As a result, this code is unreachable
-        (_not_generated, VectorState::Generated) => {
-            // Do we keep this document?
-            let document_is_kept = obkv
-                .iter()
-                .map(|(_, deladd)| KvReaderDelAdd::new(deladd))
-                .any(|deladd| deladd.get(DelAdd::Addition).is_some());
-            if document_is_kept {
-                // becomes autogenerated
-                VectorStateDelta::NowGenerated(prompt.render(
-                    obkv,
-                    DelAdd::Addition,
-                    new_fields_ids_map,
-                )?)
-            } else {
-                // make sure the document is always removed from user provided on removal
-                remove_from_user_provided.insert(docid);
-                VectorStateDelta::NowRemoved
-            }
-        }
-        // inline to the left is not possible because the embedder is not new, and so `_vectors` was removed from the previous
-        // version of the document.
-        // however the Rust type system cannot know that.
-        (_manual, VectorState::Manual) => {
-            // Do we keep this document?
-            let document_is_kept = obkv
-                .iter()
-                .map(|(_, deladd)| KvReaderDelAdd::new(deladd))
-                .any(|deladd| deladd.get(DelAdd::Addition).is_some());
-            if document_is_kept {
-                // if the new version of documents has the vectors in the DB,
-                // then they are user-provided and nothing possibly changed
-                VectorStateDelta::NoChange
-            } else {
-                // make sure the document is always removed from user provided on removal
-                remove_from_user_provided.insert(docid);
-                VectorStateDelta::NowRemoved
-            }
-        }
-    };
-
-    Ok(delta)
-}
-
-fn regenerate_if_prompt_changed(
-    obkv: obkv::KvReader<'_, FieldId>,
-    (old_prompt, new_prompt): (&Prompt, &Prompt),
-    (old_fields_ids_map, new_fields_ids_map): (&FieldsIdsMap, &FieldsIdsMap),
-) -> Result<VectorStateDelta> {
-    let old_prompt =
-        old_prompt.render(obkv, DelAdd::Deletion, old_fields_ids_map).unwrap_or(Default::default());
-    let new_prompt = new_prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
-
-    if new_prompt == old_prompt {
-        return Ok(VectorStateDelta::NoChange);
-    }
-    Ok(VectorStateDelta::NowGenerated(new_prompt))
-}
-
-fn regenerate_prompt(
-    obkv: obkv::KvReader<'_, FieldId>,
-    prompt: &Prompt,
-    new_fields_ids_map: &FieldsIdsMap,
-) -> Result<VectorStateDelta> {
-    let prompt = prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
-
-    Ok(VectorStateDelta::NowGenerated(prompt))
-}
-
-/// We cannot compute the diff between both Del and Add vectors.
-/// We'll push every vector and compute the difference later in TypedChunk.
 fn push_vectors_diff(
     remove_vectors_writer: &mut Writer<BufWriter<File>>,
     prompts_writer: &mut Writer<BufWriter<File>>,
     manual_vectors_writer: &mut Writer<BufWriter<File>>,
     key_buffer: &mut Vec<u8>,
     delta: VectorStateDelta,
+    reindex_vectors: bool,
 ) -> Result<()> {
-    let (must_remove, prompt, mut add_vectors) = delta.into_values();
+    let (must_remove, prompt, (mut del_vectors, mut add_vectors)) = delta.into_values();
-    if must_remove {
+    if must_remove
+    // TODO: the below condition works because we erase the vec database when a embedding setting changes.
+    // When vector pipeline will be optimized, this should be removed.
+    && !reindex_vectors
+    {
         key_buffer.truncate(TRUNCATE_SIZE);
         remove_vectors_writer.insert(&key_buffer, [])?;
     }
@@ -515,22 +308,44 @@ fn push_vectors_diff(
     }
 
     // We sort and dedup the vectors
+    del_vectors.sort_unstable_by(|a, b| compare_vectors(a, b));
     add_vectors.sort_unstable_by(|a, b| compare_vectors(a, b));
+    del_vectors.dedup_by(|a, b| compare_vectors(a, b).is_eq());
     add_vectors.dedup_by(|a, b| compare_vectors(a, b).is_eq());
 
+    let merged_vectors_iter =
+        itertools::merge_join_by(del_vectors, add_vectors, |del, add| compare_vectors(del, add));
+
     // insert vectors into the writer
-    for (i, vector) in add_vectors.into_iter().enumerate().take(u16::MAX as usize) {
+    for (i, eob) in merged_vectors_iter.into_iter().enumerate().take(u16::MAX as usize) {
         // Generate the key by extending the unique index to it.
         key_buffer.truncate(TRUNCATE_SIZE);
         let index = u16::try_from(i).unwrap();
         key_buffer.extend_from_slice(&index.to_be_bytes());
 
-        // We insert only the Add part of the Obkv to inform
+        match eob {
-        // that we only want to remove all those vectors.
+            EitherOrBoth::Both(_, _) => (), // no need to touch anything
-        let mut obkv = KvWriterDelAdd::memory();
+            EitherOrBoth::Left(vector) => {
-        obkv.insert(DelAdd::Addition, cast_slice(&vector))?;
+                // TODO: the below condition works because we erase the vec database when a embedding setting changes.
-        let bytes = obkv.into_inner()?;
+                // When vector pipeline will be optimized, this should be removed.
-        manual_vectors_writer.insert(&key_buffer, bytes)?;
+                if !reindex_vectors {
+                    // We insert only the Del part of the Obkv to inform
+                    // that we only want to remove all those vectors.
+                    let mut obkv = KvWriterDelAdd::memory();
+                    obkv.insert(DelAdd::Deletion, cast_slice(&vector))?;
+                    let bytes = obkv.into_inner()?;
+                    manual_vectors_writer.insert(&key_buffer, bytes)?;
+                }
+            }
+            EitherOrBoth::Right(vector) => {
+                // We insert only the Add part of the Obkv to inform
+                // that we only want to remove all those vectors.
+                let mut obkv = KvWriterDelAdd::memory();
+                obkv.insert(DelAdd::Addition, cast_slice(&vector))?;
+                let bytes = obkv.into_inner()?;
+                manual_vectors_writer.insert(&key_buffer, bytes)?;
+            }
+        }
     }
 
     Ok(())

milli/src/update/index_documents/extract/extract_word_pair_proximity_docids.rs

@@ -26,8 +26,11 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
     indexer: GrenadParameters,
     settings_diff: &InnerIndexSettingsDiff,
 ) -> Result<grenad::Reader<BufReader<File>>> {
+    let any_deletion = settings_diff.old.proximity_precision == ProximityPrecision::ByWord;
+    let any_addition = settings_diff.new.proximity_precision == ProximityPrecision::ByWord;
+
     // early return if the data shouldn't be deleted nor created.
-    if settings_diff.settings_update_only && !settings_diff.reindex_proximities() {
+    if !any_deletion && !any_addition {
         let writer = create_writer(
             indexer.chunk_compression_type,
             indexer.chunk_compression_level,
@@ -36,10 +39,8 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
         return writer_into_reader(writer);
     }
 
-    let any_deletion = settings_diff.old.proximity_precision == ProximityPrecision::ByWord;
-    let any_addition = settings_diff.new.proximity_precision == ProximityPrecision::ByWord;
-
     let max_memory = indexer.max_memory_by_thread();
+
     let mut word_pair_proximity_docids_sorters: Vec<_> = (1..MAX_DISTANCE)
         .map(|_| {
             create_sorter(

milli/src/update/index_documents/extract/mod.rs

@@ -11,7 +11,7 @@ mod extract_word_position_docids;
 
 use std::fs::File;
 use std::io::BufReader;
-use std::sync::{Arc, OnceLock};
+use std::sync::Arc;
 
 use crossbeam_channel::Sender;
 use rayon::prelude::*;
@@ -30,9 +30,8 @@ use self::extract_word_pair_proximity_docids::extract_word_pair_proximity_docids
 use self::extract_word_position_docids::extract_word_position_docids;
 use super::helpers::{as_cloneable_grenad, CursorClonableMmap, GrenadParameters};
 use super::{helpers, TypedChunk};
-use crate::index::IndexEmbeddingConfig;
 use crate::update::settings::InnerIndexSettingsDiff;
-use crate::{FieldId, Result, ThreadPoolNoAbort, ThreadPoolNoAbortBuilder};
+use crate::{FieldId, Result, ThreadPoolNoAbortBuilder};
 
 /// Extract data for each databases from obkv documents in parallel.
 /// Send data in grenad file over provided Sender.
@@ -44,7 +43,7 @@ pub(crate) fn data_from_obkv_documents(
     indexer: GrenadParameters,
     lmdb_writer_sx: Sender<Result<TypedChunk>>,
     primary_key_id: FieldId,
-    embedders_configs: Arc<Vec<IndexEmbeddingConfig>>,
+    geo_fields_ids: Option<(FieldId, FieldId)>,
     settings_diff: Arc<InnerIndexSettingsDiff>,
     max_positions_per_attributes: Option<u32>,
 ) -> Result<()> {
@@ -57,7 +56,6 @@ pub(crate) fn data_from_obkv_documents(
                         original_documents_chunk,
                         indexer,
                         lmdb_writer_sx.clone(),
-                        embedders_configs.clone(),
                         settings_diff.clone(),
                     )
                 })
@@ -72,6 +70,7 @@ pub(crate) fn data_from_obkv_documents(
                         indexer,
                         lmdb_writer_sx.clone(),
                         primary_key_id,
+                        geo_fields_ids,
                         settings_diff.clone(),
                         max_positions_per_attributes,
                     )
@@ -207,47 +206,33 @@ fn run_extraction_task<FE, FS, M>(
     })
 }
 
-fn request_threads() -> &'static ThreadPoolNoAbort {
-    static REQUEST_THREADS: OnceLock<ThreadPoolNoAbort> = OnceLock::new();
-
-    REQUEST_THREADS.get_or_init(|| {
-        ThreadPoolNoAbortBuilder::new()
-            .num_threads(crate::vector::REQUEST_PARALLELISM)
-            .thread_name(|index| format!("embedding-request-{index}"))
-            .build()
-            .unwrap()
-    })
-}
-
 /// Extract chunked data and send it into lmdb_writer_sx sender:
 /// - documents
 fn send_original_documents_data(
     original_documents_chunk: Result<grenad::Reader<BufReader<File>>>,
     indexer: GrenadParameters,
     lmdb_writer_sx: Sender<Result<TypedChunk>>,
-    embedders_configs: Arc<Vec<IndexEmbeddingConfig>>,
     settings_diff: Arc<InnerIndexSettingsDiff>,
 ) -> Result<()> {
     let original_documents_chunk =
         original_documents_chunk.and_then(|c| unsafe { as_cloneable_grenad(&c) })?;
 
+    let request_threads = ThreadPoolNoAbortBuilder::new()
+        .num_threads(crate::vector::REQUEST_PARALLELISM)
+        .thread_name(|index| format!("embedding-request-{index}"))
+        .build()?;
+
     let index_vectors = (settings_diff.reindex_vectors() || !settings_diff.settings_update_only())
         // no point in indexing vectors without embedders
         && (!settings_diff.new.embedding_configs.inner_as_ref().is_empty());
 
     if index_vectors {
         let settings_diff = settings_diff.clone();
-        let embedders_configs = embedders_configs.clone();
 
         let original_documents_chunk = original_documents_chunk.clone();
         let lmdb_writer_sx = lmdb_writer_sx.clone();
         rayon::spawn(move || {
-            match extract_vector_points(
+            match extract_vector_points(original_documents_chunk.clone(), indexer, &settings_diff) {
-                original_documents_chunk.clone(),
-                indexer,
-                &embedders_configs,
-                &settings_diff,
-            ) {
                 Ok(extracted_vectors) => {
                     for ExtractedVectorPoints {
                         manual_vectors,
@@ -255,15 +240,13 @@ fn send_original_documents_data(
                         prompts,
                         embedder_name,
                         embedder,
-                        add_to_user_provided,
-                        remove_from_user_provided,
                     } in extracted_vectors
                     {
                         let embeddings = match extract_embeddings(
                             prompts,
                             indexer,
                             embedder.clone(),
-                            request_threads(),
+                            &request_threads,
                         ) {
                             Ok(results) => Some(results),
                             Err(error) => {
@@ -281,8 +264,6 @@ fn send_original_documents_data(
                                 expected_dimension: embedder.dimensions(),
                                 manual_vectors,
                                 embedder_name,
-                                add_to_user_provided,
-                                remove_from_user_provided,
                             }));
                         }
                     }
@@ -312,6 +293,7 @@ fn send_and_extract_flattened_documents_data(
     indexer: GrenadParameters,
     lmdb_writer_sx: Sender<Result<TypedChunk>>,
     primary_key_id: FieldId,
+    geo_fields_ids: Option<(FieldId, FieldId)>,
     settings_diff: Arc<InnerIndexSettingsDiff>,
     max_positions_per_attributes: Option<u32>,
 ) -> Result<(
@@ -321,13 +303,12 @@ fn send_and_extract_flattened_documents_data(
     let flattened_documents_chunk =
         flattened_documents_chunk.and_then(|c| unsafe { as_cloneable_grenad(&c) })?;
 
-    if settings_diff.run_geo_indexing() {
+    if let Some(geo_fields_ids) = geo_fields_ids {
         let documents_chunk_cloned = flattened_documents_chunk.clone();
         let lmdb_writer_sx_cloned = lmdb_writer_sx.clone();
-        let settings_diff = settings_diff.clone();
         rayon::spawn(move || {
             let result =
-                extract_geo_points(documents_chunk_cloned, indexer, primary_key_id, &settings_diff);
+                extract_geo_points(documents_chunk_cloned, indexer, primary_key_id, geo_fields_ids);
             let _ = match result {
                 Ok(geo_points) => lmdb_writer_sx_cloned.send(Ok(TypedChunk::GeoPoints(geo_points))),
                 Err(error) => lmdb_writer_sx_cloned.send(Err(error)),
@@ -366,6 +347,7 @@ fn send_and_extract_flattened_documents_data(
                     flattened_documents_chunk.clone(),
                     indexer,
                     &settings_diff,
+                    geo_fields_ids,
                 )?;
 
                 // send fid_docid_facet_numbers_chunk to DB writer

milli/src/update/index_documents/mod.rs

@@ -286,7 +286,6 @@ where
         settings_diff.new.recompute_searchables(self.wtxn, self.index)?;
 
         let settings_diff = Arc::new(settings_diff);
-        let embedders_configs = Arc::new(self.index.embedding_configs(self.wtxn)?);
 
         let backup_pool;
         let pool = match self.indexer_config.thread_pool {
@@ -316,6 +315,28 @@ where
         // get the primary key field id
         let primary_key_id = settings_diff.new.fields_ids_map.id(&primary_key).unwrap();
 
+        // get the fid of the `_geo.lat` and `_geo.lng` fields.
+        let mut field_id_map = self.index.fields_ids_map(self.wtxn)?;
+
+        // self.index.fields_ids_map($a)? ==>> field_id_map
+        let geo_fields_ids = match field_id_map.id("_geo") {
+            Some(gfid) => {
+                let is_sortable = self.index.sortable_fields_ids(self.wtxn)?.contains(&gfid);
+                let is_filterable = self.index.filterable_fields_ids(self.wtxn)?.contains(&gfid);
+                // if `_geo` is faceted then we get the `lat` and `lng`
+                if is_sortable || is_filterable {
+                    let field_ids = field_id_map
+                        .insert("_geo.lat")
+                        .zip(field_id_map.insert("_geo.lng"))
+                        .ok_or(UserError::AttributeLimitReached)?;
+                    Some(field_ids)
+                } else {
+                    None
+                }
+            }
+            None => None,
+        };
+
         let pool_params = GrenadParameters {
             chunk_compression_type: self.indexer_config.chunk_compression_type,
             chunk_compression_level: self.indexer_config.chunk_compression_level,
@@ -370,7 +391,6 @@ where
 
         // Run extraction pipeline in parallel.
         pool.install(|| {
-            let settings_diff_cloned = settings_diff.clone();
             rayon::spawn(move || {
                 let child_span = tracing::trace_span!(target: "indexing::details", parent: &current_span, "extract_and_send_grenad_chunks");
                 let _enter = child_span.enter();
@@ -400,8 +420,8 @@ where
                         pool_params,
                         lmdb_writer_sx.clone(),
                         primary_key_id,
-                        embedders_configs.clone(),
+                        geo_fields_ids,
-                        settings_diff_cloned,
+                        settings_diff.clone(),
                         max_positions_per_attributes,
                     )
                 });
@@ -428,7 +448,7 @@ where
                     Err(status) => {
                         if let Some(typed_chunks) = chunk_accumulator.pop_longest() {
                             let (docids, is_merged_database) =
-                                write_typed_chunk_into_index(self.wtxn, self.index, &settings_diff, typed_chunks)?;
+                                write_typed_chunk_into_index(typed_chunks, self.index, self.wtxn)?;
                             if !docids.is_empty() {
                                 final_documents_ids |= docids;
                                 let documents_seen_count = final_documents_ids.len();
@@ -503,8 +523,6 @@ where
                                 embeddings,
                                 manual_vectors,
                                 embedder_name,
-                                add_to_user_provided,
-                                remove_from_user_provided,
                             } => {
                                 dimension.insert(embedder_name.clone(), expected_dimension);
                                 TypedChunk::VectorPoints {
@@ -513,8 +531,6 @@ where
                                     expected_dimension,
                                     manual_vectors,
                                     embedder_name,
-                                    add_to_user_provided,
-                                    remove_from_user_provided,
                                 }
                             }
                             otherwise => otherwise,
@@ -547,11 +563,10 @@ where
             pool.install(|| {
                 for k in crate::vector::arroy_db_range_for_embedder(embedder_index) {
                     let writer = arroy::Writer::new(vector_arroy, k, dimension);
-                    if writer.need_build(wtxn)? {
+                    if writer.is_empty(wtxn)? {
-                        writer.build(wtxn, &mut rng, None)?;
-                    } else if writer.is_empty(wtxn)? {
                         break;
                     }
+                    writer.build(wtxn, &mut rng, None)?;
                 }
                 Result::Ok(())
             })
@@ -788,7 +803,6 @@ mod tests {
     use super::*;
     use crate::documents::documents_batch_reader_from_objects;
     use crate::index::tests::TempIndex;
-    use crate::index::IndexEmbeddingConfig;
     use crate::search::TermsMatchingStrategy;
     use crate::update::Setting;
     use crate::{db_snap, Filter, Search};
@@ -2624,12 +2638,10 @@ mod tests {
 
         let rtxn = index.read_txn().unwrap();
         let mut embedding_configs = index.embedding_configs(&rtxn).unwrap();
-        let IndexEmbeddingConfig { name: embedder_name, config: embedder, user_provided } =
+        let (embedder_name, embedder) = embedding_configs.pop().unwrap();
-            embedding_configs.pop().unwrap();
-        insta::assert_snapshot!(embedder_name, @"manual");
-        insta::assert_debug_snapshot!(user_provided, @"RoaringBitmap<[0, 1, 2]>");
         let embedder =
             std::sync::Arc::new(crate::vector::Embedder::new(embedder.embedder_options).unwrap());
+        assert_eq!("manual", embedder_name);
         let res = index
             .search(&rtxn)
             .semantic(embedder_name, embedder, Some([0.0, 1.0, 2.0].to_vec()))

milli/src/update/index_documents/transform.rs

@@ -1,7 +1,7 @@
 use std::borrow::Cow;
 use std::collections::btree_map::Entry as BEntry;
 use std::collections::hash_map::Entry as HEntry;
-use std::collections::{BTreeMap, HashMap, HashSet};
+use std::collections::{HashMap, HashSet};
 use std::fs::File;
 use std::io::{Read, Seek};
 
@@ -20,15 +20,10 @@ use super::{IndexDocumentsMethod, IndexerConfig};
 use crate::documents::{DocumentsBatchIndex, EnrichedDocument, EnrichedDocumentsBatchReader};
 use crate::error::{Error, InternalError, UserError};
 use crate::index::{db_name, main_key};
-use crate::update::del_add::{
+use crate::update::del_add::{into_del_add_obkv, DelAdd, DelAddOperation, KvReaderDelAdd};
-    into_del_add_obkv, into_del_add_obkv_conditional_operation, DelAdd, DelAddOperation,
-    KvReaderDelAdd,
-};
 use crate::update::index_documents::GrenadParameters;
 use crate::update::settings::{InnerIndexSettings, InnerIndexSettingsDiff};
 use crate::update::{AvailableDocumentsIds, UpdateIndexingStep};
-use crate::vector::parsed_vectors::{ExplicitVectors, VectorOrArrayOfVectors};
-use crate::vector::settings::{EmbedderAction, WriteBackToDocuments};
 use crate::{
     is_faceted_by, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldsIdsMap, Index, Result,
 };
@@ -53,6 +48,7 @@ pub struct Transform<'a, 'i> {
     fields_ids_map: FieldsIdsMap,
 
     indexer_settings: &'a IndexerConfig,
+    pub autogenerate_docids: bool,
     pub index_documents_method: IndexDocumentsMethod,
     available_documents_ids: AvailableDocumentsIds,
 
@@ -106,7 +102,7 @@ impl<'a, 'i> Transform<'a, 'i> {
         index: &'i Index,
         indexer_settings: &'a IndexerConfig,
         index_documents_method: IndexDocumentsMethod,
-        _autogenerate_docids: bool,
+        autogenerate_docids: bool,
     ) -> Result<Self> {
         // We must choose the appropriate merge function for when two or more documents
         // with the same user id must be merged or fully replaced in the same batch.
@@ -140,6 +136,7 @@ impl<'a, 'i> Transform<'a, 'i> {
             index,
             fields_ids_map: index.fields_ids_map(wtxn)?,
             indexer_settings,
+            autogenerate_docids,
             available_documents_ids: AvailableDocumentsIds::from_documents_ids(&documents_ids),
             original_sorter,
             flattened_sorter,
@@ -808,15 +805,13 @@ impl<'a, 'i> Transform<'a, 'i> {
         let mut new_inner_settings = old_inner_settings.clone();
         new_inner_settings.fields_ids_map = fields_ids_map;
 
-        let embedding_config_updates = Default::default();
+        let settings_diff = InnerIndexSettingsDiff {
-        let settings_update_only = false;
+            old: old_inner_settings,
-        let settings_diff = InnerIndexSettingsDiff::new(
+            new: new_inner_settings,
-            old_inner_settings,
-            new_inner_settings,
             primary_key_id,
-            embedding_config_updates,
+            embedding_configs_updated: false,
-            settings_update_only,
+            settings_update_only: false,
-        );
+        };
 
         Ok(TransformOutput {
             primary_key,
@@ -835,19 +830,24 @@ impl<'a, 'i> Transform<'a, 'i> {
     /// Rebind the field_ids of the provided document to their values
     /// based on the field_ids_maps difference between the old and the new settings,
     /// then fill the provided buffers with delta documents using KvWritterDelAdd.
-    #[allow(clippy::too_many_arguments)] // need the vectors + fid, feel free to create a struct xo xo
     fn rebind_existing_document(
         old_obkv: KvReader<FieldId>,
         settings_diff: &InnerIndexSettingsDiff,
         modified_faceted_fields: &HashSet<String>,
-        mut injected_vectors: serde_json::Map<String, serde_json::Value>,
-        old_vectors_fid: Option<FieldId>,
         original_obkv_buffer: Option<&mut Vec<u8>>,
         flattened_obkv_buffer: Option<&mut Vec<u8>>,
     ) -> Result<()> {
         // Always keep the primary key.
         let is_primary_key = |id: FieldId| -> bool { settings_diff.primary_key_id == Some(id) };
 
+        // If only the `searchableAttributes` has been changed, keep only the searchable fields.
+        let must_reindex_searchables = settings_diff.reindex_searchable();
+        let necessary_searchable_field = |id: FieldId| -> bool {
+            must_reindex_searchables
+                && (settings_diff.old.searchable_fields_ids.contains(&id)
+                    || settings_diff.new.searchable_fields_ids.contains(&id))
+        };
+
         // If only a faceted field has been added, keep only this field.
         let must_reindex_facets = settings_diff.reindex_facets();
         let necessary_faceted_field = |id: FieldId| -> bool {
@@ -862,68 +862,16 @@ impl<'a, 'i> Transform<'a, 'i> {
         // we need the fields for the prompt/templating.
         let reindex_vectors = settings_diff.reindex_vectors();
 
-        // The operations that we must perform on the different fields.
-        let mut operations = HashMap::new();
-        let mut error_seen = false;
-
         let mut obkv_writer = KvWriter::<_, FieldId>::memory();
-        'write_fid: for (id, val) in old_obkv.iter() {
+        for (id, val) in old_obkv.iter() {
-            if !injected_vectors.is_empty() {
+            if is_primary_key(id)
-                'inject_vectors: {
+                || necessary_searchable_field(id)
-                    let Some(vectors_fid) = old_vectors_fid else { break 'inject_vectors };
+                || necessary_faceted_field(id)
-
+                || reindex_vectors
-                    if id < vectors_fid {
+            {
-                        break 'inject_vectors;
-                    }
-
-                    let mut existing_vectors = if id == vectors_fid {
-                        let existing_vectors: std::result::Result<
-                            serde_json::Map<String, serde_json::Value>,
-                            serde_json::Error,
-                        > = serde_json::from_slice(val);
-
-                        match existing_vectors {
-                            Ok(existing_vectors) => existing_vectors,
-                            Err(error) => {
-                                if !error_seen {
-                                    tracing::error!(%error, "Unexpected `_vectors` field that is not a map. Treating as an empty map");
-                                    error_seen = true;
-                                }
-                                Default::default()
-                            }
-                        }
-                    } else {
-                        Default::default()
-                    };
-
-                    existing_vectors.append(&mut injected_vectors);
-
-                    operations.insert(vectors_fid, DelAddOperation::DeletionAndAddition);
-                    obkv_writer
-                        .insert(vectors_fid, serde_json::to_vec(&existing_vectors).unwrap())?;
-                    if id == vectors_fid {
-                        continue 'write_fid;
-                    }
-                }
-            }
-
-            if is_primary_key(id) || necessary_faceted_field(id) || reindex_vectors {
-                operations.insert(id, DelAddOperation::DeletionAndAddition);
-                obkv_writer.insert(id, val)?;
-            } else if let Some(operation) = settings_diff.reindex_searchable_id(id) {
-                operations.insert(id, operation);
                 obkv_writer.insert(id, val)?;
             }
         }
-        if !injected_vectors.is_empty() {
-            'inject_vectors: {
-                let Some(vectors_fid) = old_vectors_fid else { break 'inject_vectors };
-
-                operations.insert(vectors_fid, DelAddOperation::DeletionAndAddition);
-                obkv_writer.insert(vectors_fid, serde_json::to_vec(&injected_vectors).unwrap())?;
-            }
-        }
-
         let data = obkv_writer.into_inner()?;
         let obkv = KvReader::<FieldId>::new(&data);
 
@@ -939,9 +887,11 @@ impl<'a, 'i> Transform<'a, 'i> {
             let flattened = flattened.as_deref().map_or(obkv, KvReader::new);
 
             flattened_obkv_buffer.clear();
-            into_del_add_obkv_conditional_operation(flattened, flattened_obkv_buffer, |id| {
+            into_del_add_obkv(
-                operations.get(&id).copied().unwrap_or(DelAddOperation::DeletionAndAddition)
+                flattened,
-            })?;
+                DelAddOperation::DeletionAndAddition,
+                flattened_obkv_buffer,
+            )?;
         }
 
         Ok(())
@@ -951,11 +901,6 @@ impl<'a, 'i> Transform<'a, 'i> {
     /// of the index with the attributes reordered accordingly to the `FieldsIdsMap` given as argument.
     ///
     // TODO this can be done in parallel by using the rayon `ThreadPool`.
-    #[tracing::instrument(
-        level = "trace"
-        skip(self, wtxn, settings_diff),
-        target = "indexing::documents"
-    )]
     pub fn prepare_for_documents_reindexing(
         self,
         wtxn: &mut heed::RwTxn<'i>,
@@ -989,35 +934,6 @@ impl<'a, 'i> Transform<'a, 'i> {
             None
         };
 
-        let readers: Result<
-            BTreeMap<&str, (Vec<arroy::Reader<arroy::distances::Angular>>, &RoaringBitmap)>,
-        > = settings_diff
-            .embedding_config_updates
-            .iter()
-            .filter_map(|(name, action)| {
-                if let EmbedderAction::WriteBackToDocuments(WriteBackToDocuments {
-                    embedder_id,
-                    user_provided,
-                }) = action
-                {
-                    let readers: Result<Vec<_>> =
-                        self.index.arroy_readers(wtxn, *embedder_id).collect();
-                    match readers {
-                        Ok(readers) => Some(Ok((name.as_str(), (readers, user_provided)))),
-                        Err(error) => Some(Err(error)),
-                    }
-                } else {
-                    None
-                }
-            })
-            .collect();
-        let readers = readers?;
-
-        let old_vectors_fid = settings_diff
-            .old
-            .fields_ids_map
-            .id(crate::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME);
-
         // We initialize the sorter with the user indexing settings.
         let mut flattened_sorter =
             if settings_diff.reindex_searchable() || settings_diff.reindex_facets() {
@@ -1044,50 +960,10 @@ impl<'a, 'i> Transform<'a, 'i> {
                     InternalError::DatabaseMissingEntry { db_name: db_name::DOCUMENTS, key: None },
                 )?;
 
-                let injected_vectors: std::result::Result<
-                    serde_json::Map<String, serde_json::Value>,
-                    arroy::Error,
-                > = readers
-                    .iter()
-                    .filter_map(|(name, (readers, user_provided))| {
-                        if !user_provided.contains(docid) {
-                            return None;
-                        }
-                        let mut vectors = Vec::new();
-                        for reader in readers {
-                            let Some(vector) = reader.item_vector(wtxn, docid).transpose() else {
-                                break;
-                            };
-
-                            match vector {
-                                Ok(vector) => vectors.push(vector),
-                                Err(error) => return Some(Err(error)),
-                            }
-                        }
-                        if vectors.is_empty() {
-                            return None;
-                        }
-                        Some(Ok((
-                            name.to_string(),
-                            serde_json::to_value(ExplicitVectors {
-                                embeddings: Some(VectorOrArrayOfVectors::from_array_of_vectors(
-                                    vectors,
-                                )),
-                                regenerate: false,
-                            })
-                            .unwrap(),
-                        )))
-                    })
-                    .collect();
-
-                let injected_vectors = injected_vectors?;
-
                 Self::rebind_existing_document(
                     old_obkv,
                     &settings_diff,
                     &modified_faceted_fields,
-                    injected_vectors,
-                    old_vectors_fid,
                     Some(&mut original_obkv_buffer).filter(|_| original_sorter.is_some()),
                     Some(&mut flattened_obkv_buffer).filter(|_| flattened_sorter.is_some()),
                 )?;
@@ -1104,23 +980,6 @@ impl<'a, 'i> Transform<'a, 'i> {
             }
         }
 
-        let mut writers = Vec::new();
-
-        // delete all vectors from the embedders that need removal
-        for (_, (readers, _)) in readers {
-            for reader in readers {
-                let dimensions = reader.dimensions();
-                let arroy_index = reader.index();
-                drop(reader);
-                let writer = arroy::Writer::new(self.index.vector_arroy, arroy_index, dimensions);
-                writers.push(writer);
-            }
-        }
-
-        for writer in writers {
-            writer.clear(wtxn)?;
-        }
-
         let grenad_params = GrenadParameters {
             chunk_compression_type: self.indexer_settings.chunk_compression_type,
             chunk_compression_level: self.indexer_settings.chunk_compression_level,

milli/src/update/index_documents/typed_chunk.rs

@@ -7,7 +7,7 @@ use bytemuck::allocation::pod_collect_to_vec;
 use charabia::{Language, Script};
 use grenad::{Merger, MergerBuilder};
 use heed::types::Bytes;
-use heed::{BytesDecode, RwTxn};
+use heed::RwTxn;
 use obkv::{KvReader, KvWriter};
 use roaring::RoaringBitmap;
 
@@ -20,17 +20,13 @@ use super::MergeFn;
 use crate::external_documents_ids::{DocumentOperation, DocumentOperationKind};
 use crate::facet::FacetType;
 use crate::index::db_name::DOCUMENTS;
-use crate::index::IndexEmbeddingConfig;
-use crate::proximity::MAX_DISTANCE;
 use crate::update::del_add::{deladd_serialize_add_side, DelAdd, KvReaderDelAdd};
 use crate::update::facet::FacetsUpdate;
 use crate::update::index_documents::helpers::{
     as_cloneable_grenad, keep_latest_obkv, try_split_array_at,
 };
-use crate::update::settings::InnerIndexSettingsDiff;
 use crate::{
-    lat_lng_to_xyz, CboRoaringBitmapCodec, DocumentId, FieldId, GeoPoint, Index, InternalError,
+    lat_lng_to_xyz, DocumentId, FieldId, GeoPoint, Index, InternalError, Result, SerializationError,
-    Result, SerializationError, U8StrStrCodec,
 };
 
 /// This struct accumulates and group the TypedChunks
@@ -91,8 +87,6 @@ pub(crate) enum TypedChunk {
         expected_dimension: usize,
         manual_vectors: grenad::Reader<BufReader<File>>,
         embedder_name: String,
-        add_to_user_provided: RoaringBitmap,
-        remove_from_user_provided: RoaringBitmap,
     },
     ScriptLanguageDocids(HashMap<(Script, Language), (RoaringBitmap, RoaringBitmap)>),
 }
@@ -128,10 +122,9 @@ impl TypedChunk {
 /// Return new documents seen.
 #[tracing::instrument(level = "trace", skip_all, target = "indexing::write_db")]
 pub(crate) fn write_typed_chunk_into_index(
-    wtxn: &mut RwTxn,
-    index: &Index,
-    settings_diff: &InnerIndexSettingsDiff,
     typed_chunks: Vec<TypedChunk>,
+    index: &Index,
+    wtxn: &mut RwTxn,
 ) -> Result<(RoaringBitmap, bool)> {
     let mut is_merged_database = false;
     match typed_chunks[0] {
@@ -157,11 +150,8 @@ pub(crate) fn write_typed_chunk_into_index(
             let mut docids = index.documents_ids(wtxn)?;
             let mut iter = merger.into_stream_merger_iter()?;
 
-            let embedders: BTreeSet<_> = index
+            let embedders: BTreeSet<_> =
-                .embedding_configs(wtxn)?
+                index.embedding_configs(wtxn)?.into_iter().map(|(k, _v)| k).collect();
-                .into_iter()
-                .map(|IndexEmbeddingConfig { name, .. }| name)
-                .collect();
             let mut vectors_buffer = Vec::new();
             while let Some((key, reader)) = iter.next()? {
                 let mut writer: KvWriter<_, FieldId> = KvWriter::memory();
@@ -187,7 +177,7 @@ pub(crate) fn write_typed_chunk_into_index(
                                     // if the `_vectors` field cannot be parsed as map of vectors, just write it as-is
                                     break 'vectors Some(addition);
                                 };
-                                vectors.retain_not_embedded_vectors(&embedders);
+                                vectors.retain_user_provided_vectors(&embedders);
                                 let crate::vector::parsed_vectors::ParsedVectors(vectors) = vectors;
                                 if vectors.is_empty() {
                                     // skip writing empty `_vectors` map
@@ -495,22 +485,13 @@ pub(crate) fn write_typed_chunk_into_index(
             }
             let merger = builder.build();
 
-            if settings_diff.only_additional_fields.is_some() {
+            write_entries_into_database(
-                write_proximity_entries_into_database_additional_searchables(
+                merger,
-                    merger,
+                &index.word_pair_proximity_docids,
-                    &index.word_pair_proximity_docids,
+                wtxn,
-                    wtxn,
+                deladd_serialize_add_side,
-                )?;
+                merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
-            } else {
+            )?;
-                write_entries_into_database(
-                    merger,
-                    &index.word_pair_proximity_docids,
-                    wtxn,
-                    deladd_serialize_add_side,
-                    merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
-                )?;
-            }
-
             is_merged_database = true;
         }
         TypedChunk::FieldIdDocidFacetNumbers(_) => {
@@ -625,8 +606,6 @@ pub(crate) fn write_typed_chunk_into_index(
             let mut remove_vectors_builder = MergerBuilder::new(keep_first as MergeFn);
             let mut manual_vectors_builder = MergerBuilder::new(keep_first as MergeFn);
             let mut embeddings_builder = MergerBuilder::new(keep_first as MergeFn);
-            let mut add_to_user_provided = RoaringBitmap::new();
-            let mut remove_from_user_provided = RoaringBitmap::new();
             let mut params = None;
             for typed_chunk in typed_chunks {
                 let TypedChunk::VectorPoints {
@@ -635,8 +614,6 @@ pub(crate) fn write_typed_chunk_into_index(
                     embeddings,
                     expected_dimension,
                     embedder_name,
-                    add_to_user_provided: aud,
-                    remove_from_user_provided: rud,
                 } = typed_chunk
                 else {
                     unreachable!();
@@ -649,23 +626,11 @@ pub(crate) fn write_typed_chunk_into_index(
                 if let Some(embeddings) = embeddings {
                     embeddings_builder.push(embeddings.into_cursor()?);
                 }
-                add_to_user_provided |= aud;
-                remove_from_user_provided |= rud;
             }
 
             // typed chunks has always at least 1 chunk.
             let Some((expected_dimension, embedder_name)) = params else { unreachable!() };
 
-            let mut embedding_configs = index.embedding_configs(wtxn)?;
-            let index_embedder_config = embedding_configs
-                .iter_mut()
-                .find(|IndexEmbeddingConfig { name, .. }| name == &embedder_name)
-                .unwrap();
-            index_embedder_config.user_provided -= remove_from_user_provided;
-            index_embedder_config.user_provided |= add_to_user_provided;
-
-            index.put_embedding_configs(wtxn, embedding_configs)?;
-
             let embedder_index = index.embedder_category_id.get(wtxn, &embedder_name)?.ok_or(
                 InternalError::DatabaseMissingEntry { db_name: "embedder_category_id", key: None },
             )?;
@@ -865,51 +830,3 @@ where
     }
     Ok(())
 }
-
-/// Akin to the `write_entries_into_database` function but specialized
-/// for the case when we only index additional searchable fields only.
-#[tracing::instrument(level = "trace", skip_all, target = "indexing::write_db")]
-fn write_proximity_entries_into_database_additional_searchables<R>(
-    merger: Merger<R, MergeFn>,
-    database: &heed::Database<U8StrStrCodec, CboRoaringBitmapCodec>,
-    wtxn: &mut RwTxn,
-) -> Result<()>
-where
-    R: io::Read + io::Seek,
-{
-    let mut iter = merger.into_stream_merger_iter()?;
-    while let Some((key, value)) = iter.next()? {
-        if valid_lmdb_key(key) {
-            let (proximity_to_insert, word1, word2) =
-                U8StrStrCodec::bytes_decode(key).map_err(heed::Error::Decoding)?;
-            let data_to_insert = match KvReaderDelAdd::new(value).get(DelAdd::Addition) {
-                Some(value) => {
-                    CboRoaringBitmapCodec::bytes_decode(value).map_err(heed::Error::Decoding)?
-                }
-                None => continue,
-            };
-
-            let mut data_to_remove = RoaringBitmap::new();
-            for prox in 1..(MAX_DISTANCE as u8) {
-                let key = (prox, word1, word2);
-                let database_value = database.get(wtxn, &key)?.unwrap_or_default();
-                let value = if prox == proximity_to_insert {
-                    // Proximity that should be changed.
-                    // Union values and remove lower proximity data
-                    (&database_value | &data_to_insert) - &data_to_remove
-                } else {
-                    // Remove lower proximity data
-                    &database_value - &data_to_remove
-                };
-
-                // add the current data in data_to_remove for the next proximities
-                data_to_remove |= &value;
-
-                if database_value != value {
-                    database.put(wtxn, &key, &value)?;
-                }
-            }
-        }
-    }
-    Ok(())
-}

milli/src/update/settings.rs

@@ -6,27 +6,19 @@ use std::sync::Arc;
 use charabia::{Normalize, Tokenizer, TokenizerBuilder};
 use deserr::{DeserializeError, Deserr};
 use itertools::{EitherOrBoth, Itertools};
-use roaring::RoaringBitmap;
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 use time::OffsetDateTime;
 
-use super::del_add::DelAddOperation;
 use super::index_documents::{IndexDocumentsConfig, Transform};
 use super::IndexerConfig;
 use crate::criterion::Criterion;
 use crate::error::UserError;
-use crate::index::{
+use crate::index::{DEFAULT_MIN_WORD_LEN_ONE_TYPO, DEFAULT_MIN_WORD_LEN_TWO_TYPOS};
-    IndexEmbeddingConfig, DEFAULT_MIN_WORD_LEN_ONE_TYPO, DEFAULT_MIN_WORD_LEN_TWO_TYPOS,
-};
 use crate::order_by_map::OrderByMap;
 use crate::proximity::ProximityPrecision;
 use crate::update::index_documents::IndexDocumentsMethod;
 use crate::update::{IndexDocuments, UpdateIndexingStep};
-use crate::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME;
+use crate::vector::settings::{check_set, check_unset, EmbedderSource, EmbeddingSettings};
-use crate::vector::settings::{
-    check_set, check_unset, EmbedderAction, EmbedderSource, EmbeddingSettings, ReindexAction,
-    WriteBackToDocuments,
-};
 use crate::vector::{Embedder, EmbeddingConfig, EmbeddingConfigs};
 use crate::{FieldId, FieldsIdsMap, Index, Result};
 
@@ -497,7 +489,6 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
                 self.index.put_all_searchable_fields_from_fields_ids_map(
                     self.wtxn,
                     &names,
-                    &fields_ids_map.nested_ids(RESERVED_VECTORS_FIELD_NAME),
                     &fields_ids_map,
                 )?;
                 self.index.put_fields_ids_map(self.wtxn, &fields_ids_map)?;
@@ -927,177 +918,92 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
         Ok(changed)
     }
 
-    fn update_embedding_configs(&mut self) -> Result<BTreeMap<String, EmbedderAction>> {
+    fn update_embedding_configs(&mut self) -> Result<bool> {
-        match std::mem::take(&mut self.embedder_settings) {
+        let update = match std::mem::take(&mut self.embedder_settings) {
-            Setting::Set(configs) => self.update_embedding_configs_set(configs),
+            Setting::Set(configs) => {
-            Setting::Reset => {
+                let mut changed = false;
-                // all vectors should be written back to documents
                 let old_configs = self.index.embedding_configs(self.wtxn)?;
-                let remove_all: Result<BTreeMap<String, EmbedderAction>> = old_configs
+                let old_configs: BTreeMap<String, Setting<EmbeddingSettings>> =
+                    old_configs.into_iter().map(|(k, v)| (k, Setting::Set(v.into()))).collect();
+
+                let mut new_configs = BTreeMap::new();
+                for joined in old_configs
                     .into_iter()
-                    .map(|IndexEmbeddingConfig { name, config: _, user_provided }| -> Result<_> {
+                    .merge_join_by(configs.into_iter(), |(left, _), (right, _)| left.cmp(right))
-                        let embedder_id =
+                {
-                            self.index.embedder_category_id.get(self.wtxn, &name)?.ok_or(
+                    match joined {
-                                crate::InternalError::DatabaseMissingEntry {
+                        // updated config
-                                    db_name: crate::index::db_name::VECTOR_EMBEDDER_CATEGORY_ID,
+                        EitherOrBoth::Both((name, mut old), (_, new)) => {
-                                    key: None,
+                            changed |= EmbeddingSettings::apply_and_need_reindex(&mut old, new);
-                                },
+                            if changed {
-                            )?;
+                                tracing::debug!(embedder = name, "need reindex");
-                        Ok((
+                            } else {
-                            name,
+                                tracing::debug!(embedder = name, "skip reindex");
-                            EmbedderAction::WriteBackToDocuments(WriteBackToDocuments {
+                            }
-                                embedder_id,
+                            let new = validate_embedding_settings(old, &name)?;
-                                user_provided,
+                            new_configs.insert(name, new);
-                            }),
+                        }
-                        ))
+                        // unchanged config
+                        EitherOrBoth::Left((name, setting)) => {
+                            new_configs.insert(name, setting);
+                        }
+                        // new config
+                        EitherOrBoth::Right((name, mut setting)) => {
+                            // apply the default source in case the source was not set so that it gets validated
+                            crate::vector::settings::EmbeddingSettings::apply_default_source(
+                                &mut setting,
+                            );
+                            crate::vector::settings::EmbeddingSettings::apply_default_openai_model(
+                                &mut setting,
+                            );
+                            let setting = validate_embedding_settings(setting, &name)?;
+                            changed = true;
+                            new_configs.insert(name, setting);
+                        }
+                    }
+                }
+                let new_configs: Vec<(String, EmbeddingConfig)> = new_configs
+                    .into_iter()
+                    .filter_map(|(name, setting)| match setting {
+                        Setting::Set(value) => Some((name, value.into())),
+                        Setting::Reset => None,
+                        Setting::NotSet => Some((name, EmbeddingSettings::default().into())),
                     })
                     .collect();
 
-                let remove_all = remove_all?;
-
                 self.index.embedder_category_id.clear(self.wtxn)?;
+                for (index, (embedder_name, _)) in new_configs.iter().enumerate() {
+                    self.index.embedder_category_id.put_with_flags(
+                        self.wtxn,
+                        heed::PutFlags::APPEND,
+                        embedder_name,
+                        &index
+                            .try_into()
+                            .map_err(|_| UserError::TooManyEmbedders(new_configs.len()))?,
+                    )?;
+                }
+
+                if new_configs.is_empty() {
+                    self.index.delete_embedding_configs(self.wtxn)?;
+                } else {
+                    self.index.put_embedding_configs(self.wtxn, new_configs)?;
+                }
+                changed
+            }
+            Setting::Reset => {
                 self.index.delete_embedding_configs(self.wtxn)?;
-                Ok(remove_all)
+                true
             }
-            Setting::NotSet => Ok(Default::default()),
+            Setting::NotSet => false,
-        }
+        };
-    }
 
-    fn update_embedding_configs_set(
+        // if any changes force a reindexing
-        &mut self,
+        // clear the vector database.
-        configs: BTreeMap<String, Setting<EmbeddingSettings>>,
+        if update {
-    ) -> Result<BTreeMap<String, EmbedderAction>> {
+            self.index.vector_arroy.clear(self.wtxn)?;
-        use crate::vector::settings::SettingsDiff;
+        }
 
-        let old_configs = self.index.embedding_configs(self.wtxn)?;
+        Ok(update)
-        let old_configs: BTreeMap<String, (EmbeddingSettings, RoaringBitmap)> = old_configs
-            .into_iter()
-            .map(|IndexEmbeddingConfig { name, config, user_provided }| {
-                (name, (config.into(), user_provided))
-            })
-            .collect();
-        let mut updated_configs = BTreeMap::new();
-        let mut embedder_actions = BTreeMap::new();
-        for joined in old_configs
-            .into_iter()
-            .merge_join_by(configs.into_iter(), |(left, _), (right, _)| left.cmp(right))
-        {
-            match joined {
-                // updated config
-                EitherOrBoth::Both((name, (old, user_provided)), (_, new)) => {
-                    let settings_diff = SettingsDiff::from_settings(old, new);
-                    match settings_diff {
-                        SettingsDiff::Remove => {
-                            tracing::debug!(
-                                embedder = name,
-                                user_provided = user_provided.len(),
-                                "removing embedder"
-                            );
-                            let embedder_id =
-                                self.index.embedder_category_id.get(self.wtxn, &name)?.ok_or(
-                                    crate::InternalError::DatabaseMissingEntry {
-                                        db_name: crate::index::db_name::VECTOR_EMBEDDER_CATEGORY_ID,
-                                        key: None,
-                                    },
-                                )?;
-                            // free id immediately
-                            self.index.embedder_category_id.delete(self.wtxn, &name)?;
-                            embedder_actions.insert(
-                                name,
-                                EmbedderAction::WriteBackToDocuments(WriteBackToDocuments {
-                                    embedder_id,
-                                    user_provided,
-                                }),
-                            );
-                        }
-                        SettingsDiff::Reindex { action, updated_settings } => {
-                            tracing::debug!(
-                                embedder = name,
-                                user_provided = user_provided.len(),
-                                ?action,
-                                "reindex embedder"
-                            );
-                            embedder_actions.insert(name.clone(), EmbedderAction::Reindex(action));
-                            let new =
-                                validate_embedding_settings(Setting::Set(updated_settings), &name)?;
-                            updated_configs.insert(name, (new, user_provided));
-                        }
-                        SettingsDiff::UpdateWithoutReindex { updated_settings } => {
-                            tracing::debug!(
-                                embedder = name,
-                                user_provided = user_provided.len(),
-                                "update without reindex embedder"
-                            );
-                            let new =
-                                validate_embedding_settings(Setting::Set(updated_settings), &name)?;
-                            updated_configs.insert(name, (new, user_provided));
-                        }
-                    }
-                }
-                // unchanged config
-                EitherOrBoth::Left((name, (setting, user_provided))) => {
-                    tracing::debug!(embedder = name, "unchanged embedder");
-                    updated_configs.insert(name, (Setting::Set(setting), user_provided));
-                }
-                // new config
-                EitherOrBoth::Right((name, mut setting)) => {
-                    tracing::debug!(embedder = name, "new embedder");
-                    // apply the default source in case the source was not set so that it gets validated
-                    crate::vector::settings::EmbeddingSettings::apply_default_source(&mut setting);
-                    crate::vector::settings::EmbeddingSettings::apply_default_openai_model(
-                        &mut setting,
-                    );
-                    let setting = validate_embedding_settings(setting, &name)?;
-                    embedder_actions
-                        .insert(name.clone(), EmbedderAction::Reindex(ReindexAction::FullReindex));
-                    updated_configs.insert(name, (setting, RoaringBitmap::new()));
-                }
-            }
-        }
-        let mut free_indices: [bool; u8::MAX as usize] = [true; u8::MAX as usize];
-        for res in self.index.embedder_category_id.iter(self.wtxn)? {
-            let (_name, id) = res?;
-            free_indices[id as usize] = false;
-        }
-        let mut free_indices = free_indices.iter_mut().enumerate();
-        let mut find_free_index =
-            move || free_indices.find(|(_, free)| **free).map(|(index, _)| index as u8);
-        for (name, action) in embedder_actions.iter() {
-            match action {
-                EmbedderAction::Reindex(ReindexAction::RegeneratePrompts) => {
-                    /* cannot be a new embedder, so has to have an id already */
-                }
-                EmbedderAction::Reindex(ReindexAction::FullReindex) => {
-                    if self.index.embedder_category_id.get(self.wtxn, name)?.is_none() {
-                        let id = find_free_index()
-                            .ok_or(UserError::TooManyEmbedders(updated_configs.len()))?;
-                        tracing::debug!(embedder = name, id, "assigning free id to new embedder");
-                        self.index.embedder_category_id.put(self.wtxn, name, &id)?;
-                    }
-                }
-                EmbedderAction::WriteBackToDocuments(_) => { /* already removed */ }
-            }
-        }
-        let updated_configs: Vec<IndexEmbeddingConfig> = updated_configs
-            .into_iter()
-            .filter_map(|(name, (config, user_provided))| match config {
-                Setting::Set(config) => {
-                    Some(IndexEmbeddingConfig { name, config: config.into(), user_provided })
-                }
-                Setting::Reset => None,
-                Setting::NotSet => Some(IndexEmbeddingConfig {
-                    name,
-                    config: EmbeddingSettings::default().into(),
-                    user_provided,
-                }),
-            })
-            .collect();
-        if updated_configs.is_empty() {
-            self.index.delete_embedding_configs(self.wtxn)?;
-        } else {
-            self.index.put_embedding_configs(self.wtxn, updated_configs)?;
-        }
-        Ok(embedder_actions)
     }
 
     fn update_search_cutoff(&mut self) -> Result<bool> {
@@ -1151,8 +1057,13 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
         self.update_searchable()?;
         self.update_exact_attributes()?;
         self.update_proximity_precision()?;
-
+        // TODO: very rough approximation of the needs for reindexing where any change will result in
-        let embedding_config_updates = self.update_embedding_configs()?;
+        // a full reindexing.
+        // What can be done instead:
+        // 1. Only change the distance on a distance change
+        // 2. Only change the name -> embedder mapping on a name change
+        // 3. Keep the old vectors but reattempt indexing on a prompt change: only actually changed prompt will need embedding + storage
+        let embedding_configs_updated = self.update_embedding_configs()?;
 
         let mut new_inner_settings = InnerIndexSettings::from_index(self.index, self.wtxn)?;
         new_inner_settings.recompute_facets(self.wtxn, self.index)?;
@@ -1161,14 +1072,13 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
             .index
             .primary_key(self.wtxn)?
             .and_then(|name| new_inner_settings.fields_ids_map.id(name));
-        let settings_update_only = true;
+        let inner_settings_diff = InnerIndexSettingsDiff {
-        let inner_settings_diff = InnerIndexSettingsDiff::new(
+            old: old_inner_settings,
-            old_inner_settings,
+            new: new_inner_settings,
-            new_inner_settings,
             primary_key_id,
-            embedding_config_updates,
+            embedding_configs_updated,
-            settings_update_only,
+            settings_update_only: true,
-        );
+        };
 
         if inner_settings_diff.any_reindexing_needed() {
             self.reindex(&progress_callback, &should_abort, inner_settings_diff)?;
@@ -1182,106 +1092,24 @@ pub struct InnerIndexSettingsDiff {
     pub(crate) old: InnerIndexSettings,
     pub(crate) new: InnerIndexSettings,
     pub(crate) primary_key_id: Option<FieldId>,
-    pub(crate) embedding_config_updates: BTreeMap<String, EmbedderAction>,
+    // TODO: compare directly the embedders.
+    pub(crate) embedding_configs_updated: bool,
     pub(crate) settings_update_only: bool,
-    /// The set of only the additional searchable fields.
-    /// If any other searchable field has been modified, is set to None.
-    pub(crate) only_additional_fields: Option<HashSet<String>>,
-
-    // Cache the check to see if all the stop_words, allowed_separators, dictionary,
-    // exact_attributes, proximity_precision are different.
-    pub(crate) cache_reindex_searchable_without_user_defined: bool,
-    // Cache the check to see if the user_defined_searchables are different.
-    pub(crate) cache_user_defined_searchables: bool,
-    // Cache the check to see if the exact_attributes are different.
-    pub(crate) cache_exact_attributes: bool,
 }
 
 impl InnerIndexSettingsDiff {
-    #[tracing::instrument(level = "trace", skip_all, target = "indexing::settings")]
-    pub(crate) fn new(
-        old_settings: InnerIndexSettings,
-        new_settings: InnerIndexSettings,
-        primary_key_id: Option<FieldId>,
-        embedding_config_updates: BTreeMap<String, EmbedderAction>,
-        settings_update_only: bool,
-    ) -> Self {
-        let only_additional_fields = match (
-            &old_settings.user_defined_searchable_fields,
-            &new_settings.user_defined_searchable_fields,
-        ) {
-            (None, None) | (Some(_), None) | (None, Some(_)) => None, // None means *
-            (Some(old), Some(new)) => {
-                let old: HashSet<_> = old.iter().cloned().collect();
-                let new: HashSet<_> = new.iter().cloned().collect();
-                if old.difference(&new).next().is_none() {
-                    // if no field has been removed return only the additional ones
-                    Some(&new - &old).filter(|x| !x.is_empty())
-                } else {
-                    None
-                }
-            }
-        };
-
-        let cache_reindex_searchable_without_user_defined = {
-            old_settings.stop_words.as_ref().map(|set| set.as_fst().as_bytes())
-                != new_settings.stop_words.as_ref().map(|set| set.as_fst().as_bytes())
-                || old_settings.allowed_separators != new_settings.allowed_separators
-                || old_settings.dictionary != new_settings.dictionary
-                || old_settings.proximity_precision != new_settings.proximity_precision
-        };
-
-        let cache_exact_attributes = old_settings.exact_attributes != new_settings.exact_attributes;
-
-        let cache_user_defined_searchables = old_settings.user_defined_searchable_fields
-            != new_settings.user_defined_searchable_fields;
-
-        InnerIndexSettingsDiff {
-            old: old_settings,
-            new: new_settings,
-            primary_key_id,
-            embedding_config_updates,
-            settings_update_only,
-            only_additional_fields,
-            cache_reindex_searchable_without_user_defined,
-            cache_user_defined_searchables,
-            cache_exact_attributes,
-        }
-    }
-
     pub fn any_reindexing_needed(&self) -> bool {
         self.reindex_searchable() || self.reindex_facets() || self.reindex_vectors()
     }
 
     pub fn reindex_searchable(&self) -> bool {
-        self.cache_reindex_searchable_without_user_defined
+        self.old.stop_words.as_ref().map(|set| set.as_fst().as_bytes())
-            || self.cache_exact_attributes
+            != self.new.stop_words.as_ref().map(|set| set.as_fst().as_bytes())
-            || self.cache_user_defined_searchables
+            || self.old.allowed_separators != self.new.allowed_separators
-    }
+            || self.old.dictionary != self.new.dictionary
-
+            || self.old.user_defined_searchable_fields != self.new.user_defined_searchable_fields
-    pub fn reindex_proximities(&self) -> bool {
+            || self.old.exact_attributes != self.new.exact_attributes
-        // if any searchable settings force the reindexing
+            || self.old.proximity_precision != self.new.proximity_precision
-        (self.cache_reindex_searchable_without_user_defined || self.cache_user_defined_searchables)
-        // and if any settings needs the proximity database created
-            && (self.old.proximity_precision == ProximityPrecision::ByAttribute
-                || self.new.proximity_precision == ProximityPrecision::ByAttribute)
-    }
-
-    pub fn reindex_searchable_id(&self, id: FieldId) -> Option<DelAddOperation> {
-        if self.cache_reindex_searchable_without_user_defined || self.cache_exact_attributes {
-            Some(DelAddOperation::DeletionAndAddition)
-        } else if let Some(only_additional_fields) = &self.only_additional_fields {
-            let additional_field = self.new.fields_ids_map.name(id).unwrap();
-            if only_additional_fields.contains(additional_field) {
-                Some(DelAddOperation::Addition)
-            } else {
-                None
-            }
-        } else if self.cache_user_defined_searchables {
-            Some(DelAddOperation::DeletionAndAddition)
-        } else {
-            None
-        }
     }
 
     pub fn reindex_facets(&self) -> bool {
@@ -1307,18 +1135,13 @@ impl InnerIndexSettingsDiff {
     }
 
     pub fn reindex_vectors(&self) -> bool {
-        !self.embedding_config_updates.is_empty()
+        self.embedding_configs_updated
     }
 
     pub fn settings_update_only(&self) -> bool {
         self.settings_update_only
     }
 
-    pub fn run_geo_indexing(&self) -> bool {
-        self.old.geo_fields_ids != self.new.geo_fields_ids
-            || (!self.settings_update_only && self.new.geo_fields_ids.is_some())
-    }
-
     pub fn modified_faceted_fields(&self) -> HashSet<String> {
         &self.old.user_defined_faceted_fields ^ &self.new.user_defined_faceted_fields
     }
@@ -1338,9 +1161,6 @@ pub(crate) struct InnerIndexSettings {
     pub proximity_precision: ProximityPrecision,
     pub embedding_configs: EmbeddingConfigs,
     pub existing_fields: HashSet<String>,
-    pub geo_fields_ids: Option<(FieldId, FieldId)>,
-    pub non_searchable_fields_ids: Vec<FieldId>,
-    pub non_faceted_fields_ids: Vec<FieldId>,
 }
 
 impl InnerIndexSettings {
@@ -1349,13 +1169,13 @@ impl InnerIndexSettings {
         let stop_words = stop_words.map(|sw| sw.map_data(Vec::from).unwrap());
         let allowed_separators = index.allowed_separators(rtxn)?;
         let dictionary = index.dictionary(rtxn)?;
-        let mut fields_ids_map = index.fields_ids_map(rtxn)?;
+        let fields_ids_map = index.fields_ids_map(rtxn)?;
         let user_defined_searchable_fields = index.user_defined_searchable_fields(rtxn)?;
         let user_defined_searchable_fields =
             user_defined_searchable_fields.map(|sf| sf.into_iter().map(String::from).collect());
         let user_defined_faceted_fields = index.user_defined_faceted_fields(rtxn)?;
-        let mut searchable_fields_ids = index.searchable_fields_ids(rtxn)?;
+        let searchable_fields_ids = index.searchable_fields_ids(rtxn)?;
-        let mut faceted_fields_ids = index.faceted_fields_ids(rtxn)?;
+        let faceted_fields_ids = index.faceted_fields_ids(rtxn)?;
         let exact_attributes = index.exact_attributes_ids(rtxn)?;
         let proximity_precision = index.proximity_precision(rtxn)?.unwrap_or_default();
         let embedding_configs = embedders(index.embedding_configs(rtxn)?)?;
@@ -1364,28 +1184,6 @@ impl InnerIndexSettings {
             .into_iter()
             .filter_map(|(field, count)| (count != 0).then_some(field))
             .collect();
-        // index.fields_ids_map($a)? ==>> fields_ids_map
-        let geo_fields_ids = match fields_ids_map.id("_geo") {
-            Some(gfid) => {
-                let is_sortable = index.sortable_fields_ids(rtxn)?.contains(&gfid);
-                let is_filterable = index.filterable_fields_ids(rtxn)?.contains(&gfid);
-                // if `_geo` is faceted then we get the `lat` and `lng`
-                if is_sortable || is_filterable {
-                    let field_ids = fields_ids_map
-                        .insert("_geo.lat")
-                        .zip(fields_ids_map.insert("_geo.lng"))
-                        .ok_or(UserError::AttributeLimitReached)?;
-                    Some(field_ids)
-                } else {
-                    None
-                }
-            }
-            None => None,
-        };
-
-        let vectors_fids = fields_ids_map.nested_ids(RESERVED_VECTORS_FIELD_NAME);
-        searchable_fields_ids.retain(|id| !vectors_fids.contains(id));
-        faceted_fields_ids.retain(|id| !vectors_fids.contains(id));
 
         Ok(Self {
             stop_words,
@@ -1400,9 +1198,6 @@ impl InnerIndexSettings {
             proximity_precision,
             embedding_configs,
             existing_fields,
-            geo_fields_ids,
-            non_searchable_fields_ids: vectors_fids.clone(),
-            non_faceted_fields_ids: vectors_fids.clone(),
         })
     }
 
@@ -1410,10 +1205,9 @@ impl InnerIndexSettings {
     pub fn recompute_facets(&mut self, wtxn: &mut heed::RwTxn, index: &Index) -> Result<()> {
         let new_facets = self
             .fields_ids_map
-            .iter()
+            .names()
-            .filter(|(fid, _field)| !self.non_faceted_fields_ids.contains(fid))
+            .filter(|&field| crate::is_faceted(field, &self.user_defined_faceted_fields))
-            .filter(|(_fid, field)| crate::is_faceted(field, &self.user_defined_faceted_fields))
+            .map(|field| field.to_string())
-            .map(|(_fid, field)| field.to_string())
             .collect();
         index.put_faceted_fields(wtxn, &new_facets)?;
 
@@ -1433,7 +1227,6 @@ impl InnerIndexSettings {
             index.put_all_searchable_fields_from_fields_ids_map(
                 wtxn,
                 &searchable_fields,
-                &self.non_searchable_fields_ids,
                 &self.fields_ids_map,
             )?;
         }
@@ -1444,25 +1237,19 @@ impl InnerIndexSettings {
     }
 }
 
-fn embedders(embedding_configs: Vec<IndexEmbeddingConfig>) -> Result<EmbeddingConfigs> {
+fn embedders(embedding_configs: Vec<(String, EmbeddingConfig)>) -> Result<EmbeddingConfigs> {
     let res: Result<_> = embedding_configs
         .into_iter()
-        .map(
+        .map(|(name, EmbeddingConfig { embedder_options, prompt })| {
-            |IndexEmbeddingConfig {
+            let prompt = Arc::new(prompt.try_into().map_err(crate::Error::from)?);
-                 name,
-                 config: EmbeddingConfig { embedder_options, prompt },
-                 ..
-             }| {
-                let prompt = Arc::new(prompt.try_into().map_err(crate::Error::from)?);
 
-                let embedder = Arc::new(
+            let embedder = Arc::new(
-                    Embedder::new(embedder_options.clone())
+                Embedder::new(embedder_options.clone())
-                        .map_err(crate::vector::Error::from)
+                    .map_err(crate::vector::Error::from)
-                        .map_err(crate::Error::from)?,
+                    .map_err(crate::Error::from)?,
-                );
+            );
-                Ok((name, (embedder, prompt)))
+            Ok((name, (embedder, prompt)))
-            },
+        })
-        )
         .collect();
     res.map(EmbeddingConfigs::new)
 }
@@ -1768,7 +1555,7 @@ mod tests {
         // When we search for something that is not in
         // the searchable fields it must not return any document.
         let result = index.search(&rtxn).query("23").execute().unwrap();
-        assert_eq!(result.documents_ids, Vec::<u32>::new());
+        assert!(result.documents_ids.is_empty());
 
         // When we search for something that is in the searchable fields
         // we must find the appropriate document.

milli/src/vector/mod.rs

@@ -152,10 +152,6 @@ impl EmbeddingConfigs {
         &self.0
     }
 
-    pub fn into_inner(self) -> HashMap<String, (Arc<Embedder>, Arc<Prompt>)> {
-        self.0
-    }
-
     /// Get the name of the default embedder configuration.
     ///
     /// The default embedder is determined as follows:

milli/src/vector/parsed_vectors.rs

@@ -1,119 +1,51 @@
 use std::collections::{BTreeMap, BTreeSet};
 
-use deserr::{take_cf_content, DeserializeError, Deserr, Sequence};
 use obkv::KvReader;
 use serde_json::{from_slice, Value};
 
 use super::Embedding;
-use crate::index::IndexEmbeddingConfig;
 use crate::update::del_add::{DelAdd, KvReaderDelAdd};
-use crate::{DocumentId, FieldId, InternalError, UserError};
+use crate::{FieldId, InternalError, UserError};
 
 pub const RESERVED_VECTORS_FIELD_NAME: &str = "_vectors";
 
-#[derive(serde::Serialize, Debug)]
+#[derive(serde::Serialize, serde::Deserialize, Debug)]
 #[serde(untagged)]
 pub enum Vectors {
     ImplicitlyUserProvided(VectorOrArrayOfVectors),
     Explicit(ExplicitVectors),
 }
 
-impl<E: DeserializeError> Deserr<E> for Vectors {
-    fn deserialize_from_value<V: deserr::IntoValue>(
-        value: deserr::Value<V>,
-        location: deserr::ValuePointerRef,
-    ) -> Result<Self, E> {
-        match value {
-            deserr::Value::Sequence(_) | deserr::Value::Null => {
-                Ok(Vectors::ImplicitlyUserProvided(VectorOrArrayOfVectors::deserialize_from_value(
-                    value, location,
-                )?))
-            }
-            deserr::Value::Map(_) => {
-                Ok(Vectors::Explicit(ExplicitVectors::deserialize_from_value(value, location)?))
-            }
-
-            value => Err(take_cf_content(E::error(
-                None,
-                deserr::ErrorKind::IncorrectValueKind {
-                    actual: value,
-                    accepted: &[
-                        deserr::ValueKind::Sequence,
-                        deserr::ValueKind::Map,
-                        deserr::ValueKind::Null,
-                    ],
-                },
-                location,
-            ))),
-        }
-    }
-}
-
 impl Vectors {
-    pub fn must_regenerate(&self) -> bool {
+    pub fn into_array_of_vectors(self) -> Vec<Embedding> {
         match self {
-            Vectors::ImplicitlyUserProvided(_) => false,
+            Vectors::ImplicitlyUserProvided(embeddings)
-            Vectors::Explicit(ExplicitVectors { regenerate, .. }) => *regenerate,
+            | Vectors::Explicit(ExplicitVectors { embeddings, user_provided: _ }) => {
-        }
+                embeddings.into_array_of_vectors().unwrap_or_default()
-    }
-
-    pub fn into_array_of_vectors(self) -> Option<Vec<Embedding>> {
-        match self {
-            Vectors::ImplicitlyUserProvided(embeddings) => {
-                Some(embeddings.into_array_of_vectors().unwrap_or_default())
-            }
-            Vectors::Explicit(ExplicitVectors { embeddings, regenerate: _ }) => {
-                embeddings.map(|embeddings| embeddings.into_array_of_vectors().unwrap_or_default())
             }
         }
     }
 }
 
-#[derive(serde::Serialize, Deserr, Debug)]
+#[derive(serde::Serialize, serde::Deserialize, Debug)]
 #[serde(rename_all = "camelCase")]
 pub struct ExplicitVectors {
-    #[serde(default)]
+    pub embeddings: VectorOrArrayOfVectors,
-    #[deserr(default)]
+    pub user_provided: bool,
-    pub embeddings: Option<VectorOrArrayOfVectors>,
-    pub regenerate: bool,
-}
-
-pub enum VectorState {
-    Inline(Vectors),
-    Manual,
-    Generated,
-}
-
-impl VectorState {
-    pub fn must_regenerate(&self) -> bool {
-        match self {
-            VectorState::Inline(vectors) => vectors.must_regenerate(),
-            VectorState::Manual => false,
-            VectorState::Generated => true,
-        }
-    }
-}
-
-pub enum VectorsState {
-    NoVectorsFid,
-    NoVectorsFieldInDocument,
-    Vectors(BTreeMap<String, Vectors>),
 }
 
 pub struct ParsedVectorsDiff {
-    old: BTreeMap<String, VectorState>,
+    pub old: Option<BTreeMap<String, Vectors>>,
-    new: VectorsState,
+    pub new: Option<BTreeMap<String, Vectors>>,
 }
 
 impl ParsedVectorsDiff {
     pub fn new(
-        docid: DocumentId,
-        embedders_configs: &[IndexEmbeddingConfig],
         documents_diff: KvReader<'_, FieldId>,
         old_vectors_fid: Option<FieldId>,
         new_vectors_fid: Option<FieldId>,
     ) -> Result<Self, Error> {
-        let mut old = match old_vectors_fid
+        let old = match old_vectors_fid
             .and_then(|vectors_fid| documents_diff.get(vectors_fid))
             .map(KvReaderDelAdd::new)
             .map(|obkv| to_vector_map(obkv, DelAdd::Deletion))
@@ -129,84 +61,48 @@ impl ParsedVectorsDiff {
                 return Err(error);
             }
         }
-        .flatten().map_or(BTreeMap::default(), |del| del.into_iter().map(|(name, vec)| (name, VectorState::Inline(vec))).collect());
+        .flatten();
-        for embedding_config in embedders_configs {
+        let new = new_vectors_fid
-            if embedding_config.user_provided.contains(docid) {
+            .and_then(|vectors_fid| documents_diff.get(vectors_fid))
-                old.entry(embedding_config.name.to_string()).or_insert(VectorState::Manual);
+            .map(KvReaderDelAdd::new)
-            }
+            .map(|obkv| to_vector_map(obkv, DelAdd::Addition))
-        }
+            .transpose()?
-
+            .flatten();
-        let new = 'new: {
-            let Some(new_vectors_fid) = new_vectors_fid else {
-                break 'new VectorsState::NoVectorsFid;
-            };
-            let Some(bytes) = documents_diff.get(new_vectors_fid) else {
-                break 'new VectorsState::NoVectorsFieldInDocument;
-            };
-            let obkv = KvReaderDelAdd::new(bytes);
-            match to_vector_map(obkv, DelAdd::Addition)? {
-                Some(new) => VectorsState::Vectors(new),
-                None => VectorsState::NoVectorsFieldInDocument,
-            }
-        };
-
         Ok(Self { old, new })
     }
 
-    pub fn remove(&mut self, embedder_name: &str) -> (VectorState, VectorState) {
+    pub fn remove(&mut self, embedder_name: &str) -> (Option<Vectors>, Option<Vectors>) {
-        let old = self.old.remove(embedder_name).unwrap_or(VectorState::Generated);
+        let old = self.old.as_mut().and_then(|old| old.remove(embedder_name));
-        let state_from_old = match old {
+        let new = self.new.as_mut().and_then(|new| new.remove(embedder_name));
-            // assume a userProvided is still userProvided
-            VectorState::Manual => VectorState::Manual,
-            // generated is still generated
-            VectorState::Generated => VectorState::Generated,
-            // weird case that shouldn't happen were the previous docs version is inline,
-            // but it was removed in the new version
-            // Since it is not in the new version, we switch to generated
-            VectorState::Inline(_) => VectorState::Generated,
-        };
-        let new = match &mut self.new {
-            VectorsState::Vectors(new) => {
-                new.remove(embedder_name).map(VectorState::Inline).unwrap_or(state_from_old)
-            }
-            _ =>
-            // if no `_vectors` field is present in the new document,
-            // the state depends on the previous version of the document
-            {
-                state_from_old
-            }
-        };
-
         (old, new)
     }
 }
 
 pub struct ParsedVectors(pub BTreeMap<String, Vectors>);
 
-impl<E: DeserializeError> Deserr<E> for ParsedVectors {
-    fn deserialize_from_value<V: deserr::IntoValue>(
-        value: deserr::Value<V>,
-        location: deserr::ValuePointerRef,
-    ) -> Result<Self, E> {
-        let value = <BTreeMap<String, Vectors>>::deserialize_from_value(value, location)?;
-        Ok(ParsedVectors(value))
-    }
-}
-
 impl ParsedVectors {
     pub fn from_bytes(value: &[u8]) -> Result<Self, Error> {
-        let value: serde_json::Value = from_slice(value).map_err(Error::InternalSerdeJson)?;
+        let Ok(value) = from_slice(value) else {
-        deserr::deserialize(value).map_err(|error| Error::InvalidEmbedderConf { error })
+            let value = from_slice(value).map_err(Error::InternalSerdeJson)?;
+            return Err(Error::InvalidMap(value));
+        };
+        Ok(ParsedVectors(value))
     }
 
-    pub fn retain_not_embedded_vectors(&mut self, embedders: &BTreeSet<String>) {
+    pub fn retain_user_provided_vectors(&mut self, embedders: &BTreeSet<String>) {
-        self.0.retain(|k, _v| !embedders.contains(k))
+        self.0.retain(|k, v| match v {
+            Vectors::ImplicitlyUserProvided(_) => true,
+            Vectors::Explicit(ExplicitVectors { embeddings: _, user_provided }) => {
+                *user_provided
+                // if the embedder is not in the config, then never touch it
+                || !embedders.contains(k)
+            }
+        });
     }
 }
 
 pub enum Error {
     InvalidMap(Value),
-    InvalidEmbedderConf { error: deserr::errors::JsonError },
     InternalSerdeJson(serde_json::Error),
 }
 
@@ -216,12 +112,6 @@ impl Error {
             Error::InvalidMap(value) => {
                 crate::Error::UserError(UserError::InvalidVectorsMapType { document_id, value })
             }
-            Error::InvalidEmbedderConf { error } => {
-                crate::Error::UserError(UserError::InvalidVectorsEmbedderConf {
-                    document_id,
-                    error,
-                })
-            }
             Error::InternalSerdeJson(error) => {
                 crate::Error::InternalError(InternalError::SerdeJson(error))
             }
@@ -242,84 +132,13 @@ fn to_vector_map(
 }
 
 /// Represents either a vector or an array of multiple vectors.
-#[derive(serde::Serialize, Debug)]
+#[derive(serde::Serialize, serde::Deserialize, Debug)]
 #[serde(transparent)]
 pub struct VectorOrArrayOfVectors {
     #[serde(with = "either::serde_untagged_optional")]
     inner: Option<either::Either<Vec<Embedding>, Embedding>>,
 }
 
-impl<E: DeserializeError> Deserr<E> for VectorOrArrayOfVectors {
-    fn deserialize_from_value<V: deserr::IntoValue>(
-        value: deserr::Value<V>,
-        location: deserr::ValuePointerRef,
-    ) -> Result<Self, E> {
-        match value {
-            deserr::Value::Null => Ok(VectorOrArrayOfVectors { inner: None }),
-            deserr::Value::Sequence(seq) => {
-                let mut iter = seq.into_iter();
-                match iter.next().map(|v| v.into_value()) {
-                    None => {
-                        // With the strange way serde serialize the `Either`, we must send the left part
-                        // otherwise it'll consider we returned [[]]
-                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Left(Vec::new())) })
-                    }
-                    Some(val @ deserr::Value::Sequence(_)) => {
-                        let first = Embedding::deserialize_from_value(val, location.push_index(0))?;
-                        let mut collect = vec![first];
-                        let mut tail = iter
-                            .enumerate()
-                            .map(|(i, v)| {
-                                Embedding::deserialize_from_value(
-                                    v.into_value(),
-                                    location.push_index(i + 1),
-                                )
-                            })
-                            .collect::<Result<Vec<_>, _>>()?;
-                        collect.append(&mut tail);
-
-                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Left(collect)) })
-                    }
-                    Some(
-                        val @ deserr::Value::Integer(_)
-                        | val @ deserr::Value::NegativeInteger(_)
-                        | val @ deserr::Value::Float(_),
-                    ) => {
-                        let first = <f32>::deserialize_from_value(val, location.push_index(0))?;
-                        let mut embedding = iter
-                            .enumerate()
-                            .map(|(i, v)| {
-                                <f32>::deserialize_from_value(
-                                    v.into_value(),
-                                    location.push_index(i + 1),
-                                )
-                            })
-                            .collect::<Result<Vec<_>, _>>()?;
-                        embedding.insert(0, first);
-                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Right(embedding)) })
-                    }
-                    Some(value) => Err(take_cf_content(E::error(
-                        None,
-                        deserr::ErrorKind::IncorrectValueKind {
-                            actual: value,
-                            accepted: &[deserr::ValueKind::Sequence, deserr::ValueKind::Float],
-                        },
-                        location.push_index(0),
-                    ))),
-                }
-            }
-            value => Err(take_cf_content(E::error(
-                None,
-                deserr::ErrorKind::IncorrectValueKind {
-                    actual: value,
-                    accepted: &[deserr::ValueKind::Sequence, deserr::ValueKind::Null],
-                },
-                location,
-            ))),
-        }
-    }
-}
-
 impl VectorOrArrayOfVectors {
     pub fn into_array_of_vectors(self) -> Option<Vec<Embedding>> {
         match self.inner? {
@@ -331,41 +150,21 @@ impl VectorOrArrayOfVectors {
     pub fn from_array_of_vectors(array_of_vec: Vec<Embedding>) -> Self {
         Self { inner: Some(either::Either::Left(array_of_vec)) }
     }
-
-    pub fn from_vector(vec: Embedding) -> Self {
-        Self { inner: Some(either::Either::Right(vec)) }
-    }
-}
-
-impl From<Embedding> for VectorOrArrayOfVectors {
-    fn from(vec: Embedding) -> Self {
-        Self::from_vector(vec)
-    }
-}
-
-impl From<Vec<Embedding>> for VectorOrArrayOfVectors {
-    fn from(vec: Vec<Embedding>) -> Self {
-        Self::from_array_of_vectors(vec)
-    }
 }
 
 #[cfg(test)]
 mod test {
     use super::VectorOrArrayOfVectors;
 
-    fn embedding_from_str(s: &str) -> Result<VectorOrArrayOfVectors, deserr::errors::JsonError> {
-        let value: serde_json::Value = serde_json::from_str(s).unwrap();
-        deserr::deserialize(value)
-    }
-
     #[test]
     fn array_of_vectors() {
-        let null = embedding_from_str("null").unwrap();
+        let null: VectorOrArrayOfVectors = serde_json::from_str("null").unwrap();
-        let empty = embedding_from_str("[]").unwrap();
+        let empty: VectorOrArrayOfVectors = serde_json::from_str("[]").unwrap();
-        let one = embedding_from_str("[0.1]").unwrap();
+        let one: VectorOrArrayOfVectors = serde_json::from_str("[0.1]").unwrap();
-        let two = embedding_from_str("[0.1, 0.2]").unwrap();
+        let two: VectorOrArrayOfVectors = serde_json::from_str("[0.1, 0.2]").unwrap();
-        let one_vec = embedding_from_str("[[0.1, 0.2]]").unwrap();
+        let one_vec: VectorOrArrayOfVectors = serde_json::from_str("[[0.1, 0.2]]").unwrap();
-        let two_vecs = embedding_from_str("[[0.1, 0.2], [0.3, 0.4]]").unwrap();
+        let two_vecs: VectorOrArrayOfVectors =
+            serde_json::from_str("[[0.1, 0.2], [0.3, 0.4]]").unwrap();
 
         insta::assert_json_snapshot!(null.into_array_of_vectors(), @"null");
         insta::assert_json_snapshot!(empty.into_array_of_vectors(), @"[]");

milli/src/vector/settings.rs

@@ -1,5 +1,4 @@
 use deserr::Deserr;
-use roaring::RoaringBitmap;
 use serde::{Deserialize, Serialize};
 
 use super::rest::InputType;
@@ -73,238 +72,6 @@ pub fn check_unset<T>(
     }
 }
 
-/// Indicates what action should take place during a reindexing operation for an embedder
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
-pub enum ReindexAction {
-    /// An indexing operation should take place for this embedder, keeping existing vectors
-    /// and checking whether the document template changed or not
-    RegeneratePrompts,
-    /// An indexing operation should take place for all documents for this embedder, removing existing vectors
-    /// (except userProvided ones)
-    FullReindex,
-}
-
-pub enum SettingsDiff {
-    Remove,
-    Reindex { action: ReindexAction, updated_settings: EmbeddingSettings },
-    UpdateWithoutReindex { updated_settings: EmbeddingSettings },
-}
-
-pub enum EmbedderAction {
-    WriteBackToDocuments(WriteBackToDocuments),
-    Reindex(ReindexAction),
-}
-
-pub struct WriteBackToDocuments {
-    pub embedder_id: u8,
-    pub user_provided: RoaringBitmap,
-}
-
-impl SettingsDiff {
-    pub fn from_settings(old: EmbeddingSettings, new: Setting<EmbeddingSettings>) -> Self {
-        match new {
-            Setting::Set(new) => {
-                let EmbeddingSettings {
-                    mut source,
-                    mut model,
-                    mut revision,
-                    mut api_key,
-                    mut dimensions,
-                    mut document_template,
-                    mut url,
-                    mut query,
-                    mut input_field,
-                    mut path_to_embeddings,
-                    mut embedding_object,
-                    mut input_type,
-                    mut distribution,
-                } = old;
-
-                let EmbeddingSettings {
-                    source: new_source,
-                    model: new_model,
-                    revision: new_revision,
-                    api_key: new_api_key,
-                    dimensions: new_dimensions,
-                    document_template: new_document_template,
-                    url: new_url,
-                    query: new_query,
-                    input_field: new_input_field,
-                    path_to_embeddings: new_path_to_embeddings,
-                    embedding_object: new_embedding_object,
-                    input_type: new_input_type,
-                    distribution: new_distribution,
-                } = new;
-
-                let mut reindex_action = None;
-
-                // **Warning**: do not use short-circuiting || here, we want all these operations applied
-                if source.apply(new_source) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                    // when the source changes, we need to reapply the default settings for the new source
-                    apply_default_for_source(
-                        &source,
-                        &mut model,
-                        &mut revision,
-                        &mut dimensions,
-                        &mut url,
-                        &mut query,
-                        &mut input_field,
-                        &mut path_to_embeddings,
-                        &mut embedding_object,
-                        &mut input_type,
-                        &mut document_template,
-                    )
-                }
-                if model.apply(new_model) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if revision.apply(new_revision) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if dimensions.apply(new_dimensions) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if url.apply(new_url) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if query.apply(new_query) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if input_field.apply(new_input_field) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if path_to_embeddings.apply(new_path_to_embeddings) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if embedding_object.apply(new_embedding_object) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if input_type.apply(new_input_type) {
-                    ReindexAction::push_action(&mut reindex_action, ReindexAction::FullReindex);
-                }
-                if document_template.apply(new_document_template) {
-                    ReindexAction::push_action(
-                        &mut reindex_action,
-                        ReindexAction::RegeneratePrompts,
-                    );
-                }
-
-                distribution.apply(new_distribution);
-                api_key.apply(new_api_key);
-
-                let updated_settings = EmbeddingSettings {
-                    source,
-                    model,
-                    revision,
-                    api_key,
-                    dimensions,
-                    document_template,
-                    url,
-                    query,
-                    input_field,
-                    path_to_embeddings,
-                    embedding_object,
-                    input_type,
-                    distribution,
-                };
-
-                match reindex_action {
-                    Some(action) => Self::Reindex { action, updated_settings },
-                    None => Self::UpdateWithoutReindex { updated_settings },
-                }
-            }
-            Setting::Reset => Self::Remove,
-            Setting::NotSet => Self::UpdateWithoutReindex { updated_settings: old },
-        }
-    }
-}
-
-impl ReindexAction {
-    fn push_action(this: &mut Option<Self>, other: Self) {
-        *this = match (*this, other) {
-            (_, ReindexAction::FullReindex) => Some(ReindexAction::FullReindex),
-            (Some(ReindexAction::FullReindex), _) => Some(ReindexAction::FullReindex),
-            (_, ReindexAction::RegeneratePrompts) => Some(ReindexAction::RegeneratePrompts),
-        }
-    }
-}
-
-#[allow(clippy::too_many_arguments)] // private function
-fn apply_default_for_source(
-    source: &Setting<EmbedderSource>,
-    model: &mut Setting<String>,
-    revision: &mut Setting<String>,
-    dimensions: &mut Setting<usize>,
-    url: &mut Setting<String>,
-    query: &mut Setting<serde_json::Value>,
-    input_field: &mut Setting<Vec<String>>,
-    path_to_embeddings: &mut Setting<Vec<String>>,
-    embedding_object: &mut Setting<Vec<String>>,
-    input_type: &mut Setting<InputType>,
-    document_template: &mut Setting<String>,
-) {
-    match source {
-        Setting::Set(EmbedderSource::HuggingFace) => {
-            *model = Setting::Reset;
-            *revision = Setting::Reset;
-            *dimensions = Setting::NotSet;
-            *url = Setting::NotSet;
-            *query = Setting::NotSet;
-            *input_field = Setting::NotSet;
-            *path_to_embeddings = Setting::NotSet;
-            *embedding_object = Setting::NotSet;
-            *input_type = Setting::NotSet;
-        }
-        Setting::Set(EmbedderSource::Ollama) => {
-            *model = Setting::Reset;
-            *revision = Setting::NotSet;
-            *dimensions = Setting::Reset;
-            *url = Setting::NotSet;
-            *query = Setting::NotSet;
-            *input_field = Setting::NotSet;
-            *path_to_embeddings = Setting::NotSet;
-            *embedding_object = Setting::NotSet;
-            *input_type = Setting::NotSet;
-        }
-        Setting::Set(EmbedderSource::OpenAi) | Setting::Reset => {
-            *model = Setting::Reset;
-            *revision = Setting::NotSet;
-            *dimensions = Setting::NotSet;
-            *url = Setting::NotSet;
-            *query = Setting::NotSet;
-            *input_field = Setting::NotSet;
-            *path_to_embeddings = Setting::NotSet;
-            *embedding_object = Setting::NotSet;
-            *input_type = Setting::NotSet;
-        }
-        Setting::Set(EmbedderSource::Rest) => {
-            *model = Setting::NotSet;
-            *revision = Setting::NotSet;
-            *dimensions = Setting::Reset;
-            *url = Setting::Reset;
-            *query = Setting::Reset;
-            *input_field = Setting::Reset;
-            *path_to_embeddings = Setting::Reset;
-            *embedding_object = Setting::Reset;
-            *input_type = Setting::Reset;
-        }
-        Setting::Set(EmbedderSource::UserProvided) => {
-            *model = Setting::NotSet;
-            *revision = Setting::NotSet;
-            *dimensions = Setting::Reset;
-            *url = Setting::NotSet;
-            *query = Setting::NotSet;
-            *input_field = Setting::NotSet;
-            *path_to_embeddings = Setting::NotSet;
-            *embedding_object = Setting::NotSet;
-            *input_type = Setting::NotSet;
-            *document_template = Setting::NotSet;
-        }
-        Setting::NotSet => {}
-    }
-}
-
 pub fn check_set<T>(
     key: &Setting<T>,
     field: &'static str,
@@ -443,6 +210,66 @@ impl EmbeddingSettings {
             *model = Setting::Set(openai::EmbeddingModel::default().name().to_owned())
         }
     }
+
+    pub(crate) fn apply_and_need_reindex(
+        old: &mut Setting<EmbeddingSettings>,
+        new: Setting<EmbeddingSettings>,
+    ) -> bool {
+        match (old, new) {
+            (
+                Setting::Set(EmbeddingSettings {
+                    source: old_source,
+                    model: old_model,
+                    revision: old_revision,
+                    api_key: old_api_key,
+                    dimensions: old_dimensions,
+                    document_template: old_document_template,
+                    url: old_url,
+                    query: old_query,
+                    input_field: old_input_field,
+                    path_to_embeddings: old_path_to_embeddings,
+                    embedding_object: old_embedding_object,
+                    input_type: old_input_type,
+                    distribution: old_distribution,
+                }),
+                Setting::Set(EmbeddingSettings {
+                    source: new_source,
+                    model: new_model,
+                    revision: new_revision,
+                    api_key: new_api_key,
+                    dimensions: new_dimensions,
+                    document_template: new_document_template,
+                    url: new_url,
+                    query: new_query,
+                    input_field: new_input_field,
+                    path_to_embeddings: new_path_to_embeddings,
+                    embedding_object: new_embedding_object,
+                    input_type: new_input_type,
+                    distribution: new_distribution,
+                }),
+            ) => {
+                let mut needs_reindex = false;
+
+                needs_reindex |= old_source.apply(new_source);
+                needs_reindex |= old_model.apply(new_model);
+                needs_reindex |= old_revision.apply(new_revision);
+                needs_reindex |= old_dimensions.apply(new_dimensions);
+                needs_reindex |= old_document_template.apply(new_document_template);
+                needs_reindex |= old_url.apply(new_url);
+                needs_reindex |= old_query.apply(new_query);
+                needs_reindex |= old_input_field.apply(new_input_field);
+                needs_reindex |= old_path_to_embeddings.apply(new_path_to_embeddings);
+                needs_reindex |= old_embedding_object.apply(new_embedding_object);
+                needs_reindex |= old_input_type.apply(new_input_type);
+
+                old_distribution.apply(new_distribution);
+                old_api_key.apply(new_api_key);
+                needs_reindex
+            }
+            (Setting::Reset, Setting::Reset) | (_, Setting::NotSet) => false,
+            _ => true,
+        }
+    }
 }
 
 #[derive(Debug, Clone, Copy, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]