Make the CI happy about the never type

4891: Update version for the next release (v1.9.1) in Cargo.toml r=dureuill a=meili-bot

⚠️ This PR is automatically generated. Check the new version is the expected one and Cargo.lock has been updated before merging.

Co-authored-by: dureuill <dureuill@users.noreply.github.com>

.github/workflows/bench-pr.yml

@@ -43,4 +43,11 @@ jobs:
 
         - name: Run benchmarks on PR ${{ github.event.issue.id }}
           run: |
-            cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" --dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" --reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" -- ${{ steps.command.outputs.command-arguments }}
+            cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" \
+               --dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" \
+               --reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" \
+               -- ${{ steps.command.outputs.command-arguments }} > benchlinks.txt
+
+        - name: Send comment in PR
+          run: |
+            gh pr comment ${{github.event.issue.number}} --body-file benchlinks.txt

.github/workflows/flaky-tests.yml

@@ -1,4 +1,6 @@
 name: Look for flaky tests
+env:
+  ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
 on:
   workflow_dispatch:
   schedule:

.github/workflows/fuzzer-indexing.yml

@@ -1,5 +1,6 @@
 name: Run the indexing fuzzer
-
+env:
+  ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
 on:
   push:
     branches:

.github/workflows/publish-apt-brew-pkg.yml

@@ -15,6 +15,8 @@ jobs:
 
   debian:
     name: Publish debian packagge
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     runs-on: ubuntu-latest
     needs: check-version
     container:

.github/workflows/publish-binaries.yml

@@ -35,6 +35,8 @@ jobs:
   publish-linux:
     name: Publish binary for Linux
     runs-on: ubuntu-latest
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     needs: check-version
     container:
       # Use ubuntu-18.04 to compile with glibc 2.27
@@ -132,6 +134,8 @@ jobs:
     name: Publish binary for aarch64
     runs-on: ubuntu-latest
     needs: check-version
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     container:
       # Use ubuntu-18.04 to compile with glibc 2.27
       image: ubuntu:18.04

.github/workflows/test-suite.yml

@@ -21,6 +21,8 @@ jobs:
   test-linux:
     name: Tests on ubuntu-18.04
     runs-on: ubuntu-latest
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     container:
       # Use ubuntu-18.04 to compile with glibc 2.27, which are the production expectations
       image: ubuntu:18.04
@@ -77,6 +79,8 @@ jobs:
   test-all-features:
     name: Tests almost all features
     runs-on: ubuntu-latest
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     container:
       # Use ubuntu-18.04 to compile with glibc 2.27, which are the production expectations
       image: ubuntu:18.04
@@ -100,6 +104,8 @@ jobs:
 
   test-disabled-tokenization:
     name: Test disabled tokenization
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     runs-on: ubuntu-latest
     container:
       image: ubuntu:18.04
@@ -116,7 +122,7 @@ 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 -vqz lindera; then
+          if cargo tree -f '{p} {f}' -e normal --no-default-features | grep -qz lindera; then
             echo "lindera has been found in the sources and it shouldn't"
             exit 1
           fi
@@ -127,6 +133,8 @@ jobs:
   # We run tests in debug also, to make sure that the debug_assertions are hit
   test-debug:
     name: Run tests in debug
+    env:
+      ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true
     runs-on: ubuntu-latest
     container:
       # Use ubuntu-18.04 to compile with glibc 2.27, which are the production expectations

BENCHMARKS.md

@@ -187,8 +187,8 @@ They are JSON files with the following structure (comments are not actually supp
   },
   // Core of the workload.
   // A list of commands to run sequentially.
-  // A command is a request to the Meilisearch instance that is executed while the profiling runs.
-  "commands": [
+  // Optional: A precommand is a request to the Meilisearch instance that is executed before the profiling runs.
+  "precommands": [
     {
       // Meilisearch route to call. `http://localhost:7700/` will be prepended.
       "route": "indexes/movies/settings",
@@ -224,8 +224,11 @@ They are JSON files with the following structure (comments are not actually supp
       // - DontWait: run the next command without waiting the response to this one.
       // - WaitForResponse: run the next command as soon as the response from the server is received.
       // - WaitForTask: run the next command once **all** the Meilisearch tasks created up to now have finished processing.
-      "synchronous": "DontWait"
-    },
+      "synchronous": "WaitForTask"
+    }
+  ],
+  // A command is a request to the Meilisearch instance that is executed while the profiling runs.
+  "commands": [
     {
       "route": "indexes/movies/documents",
       "method": "POST",

Cargo.toml

@@ -17,11 +17,12 @@ members = [
     "benchmarks",
     "fuzzers",
     "tracing-trace",
-    "xtask", "build-info",
+    "xtask",
+    "build-info",
 ]
 
 [workspace.package]
-version = "1.8.0"
+version = "1.9.1"
 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 helps you shape a delightful search experience in a snap, offering features that work out-of-the-box to speed up your workflow.
+[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.
 
 <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 @@ Meilisearch helps you shape a delightful search experience in a snap, offering f
 🔥 [**Try it!**](https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-link) 🔥
 
 ## ✨ Features
-
-- **Search-as-you-type:** find search results in less than 50 milliseconds
+- **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
 - **[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 @@ Meilisearch helps you shape a delightful search experience in a snap, offering f
 
 ## 📖 Documentation
 
-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).
+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).
 
 ## 🚀 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). No credit card 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). Additional features include analytics & monitoring in many regions around the world. No credit card is 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). Don't forget 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). Remember 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), 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)
+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)
 
 🗞 [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/lib.rs

@@ -256,8 +256,8 @@ pub(crate) mod test {
 
     pub fn create_test_settings() -> Settings<Checked> {
         let settings = Settings {
-            displayed_attributes: Setting::Set(vec![S("race"), S("name")]),
-            searchable_attributes: Setting::Set(vec![S("name"), S("race")]),
+            displayed_attributes: Setting::Set(vec![S("race"), S("name")]).into(),
+            searchable_attributes: Setting::Set(vec![S("name"), S("race")]).into(),
             filterable_attributes: Setting::Set(btreeset! { S("race"), S("age") }),
             sortable_attributes: Setting::Set(btreeset! { S("age") }),
             ranking_rules: Setting::NotSet,

dump/src/reader/compat/v5_to_v6.rs

@@ -315,8 +315,8 @@ impl From<v5::ResponseError> for v6::ResponseError {
 impl<T> From<v5::Settings<T>> for v6::Settings<v6::Unchecked> {
     fn from(settings: v5::Settings<T>) -> Self {
         v6::Settings {
-            displayed_attributes: settings.displayed_attributes.into(),
-            searchable_attributes: settings.searchable_attributes.into(),
+            displayed_attributes: v6::Setting::from(settings.displayed_attributes).into(),
+            searchable_attributes: v6::Setting::from(settings.searchable_attributes).into(),
             filterable_attributes: settings.filterable_attributes.into(),
             sortable_attributes: settings.sortable_attributes.into(),
             ranking_rules: {

dump/src/reader/mod.rs

@@ -197,6 +197,140 @@ pub(crate) mod test {
     use super::*;
     use crate::reader::v6::RuntimeTogglableFeatures;
 
+    #[test]
+    fn import_dump_v6_with_vectors() {
+        // dump containing two indexes
+        //
+        // "vector", configured with an embedder
+        // contains:
+        // - one document with an overriden vector,
+        // - one document with a natural vector
+        // - one document with a _vectors map containing one additional embedder name and a natural vector
+        // - one document with a _vectors map containing one additional embedder name and an overriden vector
+        //
+        // "novector", no embedder
+        // contains:
+        // - a document without vector
+        // - a document with a random _vectors field
+        let dump = File::open("tests/assets/v6-with-vectors.dump").unwrap();
+        let mut dump = DumpReader::open(dump).unwrap();
+
+        // top level infos
+        insta::assert_display_snapshot!(dump.date().unwrap(), @"2024-05-16 15:51:34.151044 +00:00:00");
+        insta::assert_debug_snapshot!(dump.instance_uid().unwrap(), @"None");
+
+        // tasks
+        let tasks = dump.tasks().unwrap().collect::<Result<Vec<_>>>().unwrap();
+        let (tasks, update_files): (Vec<_>, Vec<_>) = tasks.into_iter().unzip();
+        meili_snap::snapshot_hash!(meili_snap::json_string!(tasks), @"278f63325ef06ca04d01df98d8207b94");
+        assert_eq!(update_files.len(), 10);
+        assert!(update_files[0].is_none()); // the dump creation
+        assert!(update_files[1].is_none());
+        assert!(update_files[2].is_none());
+        assert!(update_files[3].is_none());
+        assert!(update_files[4].is_none());
+        assert!(update_files[5].is_none());
+        assert!(update_files[6].is_none());
+        assert!(update_files[7].is_none());
+        assert!(update_files[8].is_none());
+        assert!(update_files[9].is_none());
+
+        // indexes
+        let mut indexes = dump.indexes().unwrap().collect::<Result<Vec<_>>>().unwrap();
+        // the index are not ordered in any way by default
+        indexes.sort_by_key(|index| index.metadata().uid.to_string());
+
+        let mut vector_index = indexes.pop().unwrap();
+        let mut novector_index = indexes.pop().unwrap();
+        assert!(indexes.is_empty());
+
+        // vector
+
+        insta::assert_json_snapshot!(vector_index.metadata(), @r###"
+        {
+          "uid": "vector",
+          "primaryKey": "id",
+          "createdAt": "2024-05-16T15:33:17.240962Z",
+          "updatedAt": "2024-05-16T15:40:55.723052Z"
+        }
+        "###);
+
+        {
+            let documents: Result<Vec<_>> = vector_index.documents().unwrap().collect();
+            let mut documents = documents.unwrap();
+            assert_eq!(documents.len(), 4);
+
+            documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document);
+            }
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document);
+            }
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document);
+            }
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document);
+            }
+        }
+
+        // novector
+
+        insta::assert_json_snapshot!(novector_index.metadata(), @r###"
+        {
+          "uid": "novector",
+          "primaryKey": "id",
+          "createdAt": "2024-05-16T15:33:03.568055Z",
+          "updatedAt": "2024-05-16T15:33:07.530217Z"
+        }
+        "###);
+
+        insta::assert_json_snapshot!(novector_index.settings().unwrap().embedders, @"null");
+
+        {
+            let documents: Result<Vec<_>> = novector_index.documents().unwrap().collect();
+            let mut documents = documents.unwrap();
+            assert_eq!(documents.len(), 2);
+
+            documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document, @r###"
+                {
+                  "id": "e1",
+                  "other": "random1",
+                  "_vectors": "toto"
+                }
+                "###);
+            }
+
+            {
+                let document = documents.pop().unwrap();
+                insta::assert_json_snapshot!(document, @r###"
+                {
+                  "id": "e0",
+                  "other": "random0"
+                }
+                "###);
+            }
+        }
+
+        assert_eq!(
+            dump.features().unwrap().unwrap(),
+            RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
+        );
+    }
+
     #[test]
     fn import_dump_v6_experimental() {
         let dump = File::open("tests/assets/v6-with-experimental.dump").unwrap();

dump/src/reader/snapshots/dump__reader__test__import_dump_v6_with_vectors-5.snap

@@ -0,0 +1,783 @@
+---
+source: dump/src/reader/mod.rs
+expression: document
+---
+{
+  "id": "e3",
+  "desc": "overriden vector + map",
+  "_vectors": {
+    "default": [
+      0.2,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
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+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
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@@ -0,0 +1,786 @@
+---
+source: dump/src/reader/mod.rs
+expression: document
+---
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dump/src/reader/snapshots/dump__reader__test__import_dump_v6_with_vectors-7.snap

@@ -0,0 +1,785 @@
+---
+source: dump/src/reader/mod.rs
+expression: document
+---
+{
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dump/src/reader/snapshots/dump__reader__test__import_dump_v6_with_vectors-8.snap

@@ -0,0 +1,780 @@
+---
+source: dump/src/reader/mod.rs
+expression: document
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+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1,
+      0.1
+    ]
+  }
+}

dump/src/reader/v3/settings.rs

@@ -152,6 +152,7 @@ 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

@@ -182,6 +182,7 @@ 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

@@ -200,6 +200,7 @@ 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"))]

filter-parser/src/lib.rs

@@ -568,7 +568,7 @@ pub mod tests {
         insta::assert_display_snapshot!(p(r"title = 'foo\\\\'"), @r#"{title} = {foo\\}"#);
         insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\'"), @r#"{title} = {foo\\\}"#);
         insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\\\'"), @r#"{title} = {foo\\\\}"#);
-        // but it also works with other sequencies
+        // but it also works with other sequences
         insta::assert_display_snapshot!(p(r#"title = 'foo\x20\n\t\"\'"'"#), @"{title} = {foo \n\t\"\'\"}");
     }
 

index-scheduler/Cargo.toml

@@ -22,7 +22,6 @@ flate2 = "1.0.28"
 meilisearch-auth = { path = "../meilisearch-auth" }
 meilisearch-types = { path = "../meilisearch-types" }
 page_size = "0.5.0"
-puffin = { version = "0.16.0", features = ["serialization"] }
 rayon = "1.8.1"
 roaring = { version = "0.10.2", features = ["serde"] }
 serde = { version = "1.0.195", features = ["derive"] }
@@ -37,11 +36,13 @@ time = { version = "0.3.31", features = [
     "macros",
 ] }
 tracing = "0.1.40"
-ureq = "2.9.1"
+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

@@ -13,7 +13,7 @@ We can combine the two tasks in a single batch:
 1. import documents X and Y
 
 Processing this batch is functionally equivalent to processing the two
-tasks individally, but should be much faster since we are only performing
+tasks individually, but should be much faster since we are only performing
 one indexing operation.
 */
 
@@ -31,6 +31,9 @@ use meilisearch_types::milli::heed::CompactionOption;
 use meilisearch_types::milli::update::{
     IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings as MilliSettings,
 };
+use meilisearch_types::milli::vector::parsed_vectors::{
+    ExplicitVectors, VectorOrArrayOfVectors, RESERVED_VECTORS_FIELD_NAME,
+};
 use meilisearch_types::milli::{self, Filter};
 use meilisearch_types::settings::{apply_settings_to_builder, Settings, Unchecked};
 use meilisearch_types::tasks::{Details, IndexSwap, Kind, KindWithContent, Status, Task};
@@ -526,8 +529,6 @@ impl IndexScheduler {
         #[cfg(test)]
         self.maybe_fail(crate::tests::FailureLocation::InsideCreateBatch)?;
 
-        puffin::profile_function!();
-
         let enqueued = &self.get_status(rtxn, Status::Enqueued)?;
         let to_cancel = self.get_kind(rtxn, Kind::TaskCancelation)? & enqueued;
 
@@ -636,8 +637,6 @@ impl IndexScheduler {
             self.breakpoint(crate::Breakpoint::InsideProcessBatch);
         }
 
-        puffin::profile_function!(batch.to_string());
-
         match batch {
             Batch::TaskCancelation { mut task, previous_started_at, previous_processing_tasks } => {
                 // 1. Retrieve the tasks that matched the query at enqueue-time.
@@ -785,10 +784,12 @@ impl IndexScheduler {
                 let dst = temp_snapshot_dir.path().join("auth");
                 fs::create_dir_all(&dst)?;
                 // TODO We can't use the open_auth_store_env function here but we should
-                let auth = milli::heed::EnvOpenOptions::new()
-                    .map_size(1024 * 1024 * 1024) // 1 GiB
-                    .max_dbs(2)
-                    .open(&self.auth_path)?;
+                let auth = unsafe {
+                    milli::heed::EnvOpenOptions::new()
+                        .map_size(1024 * 1024 * 1024) // 1 GiB
+                        .max_dbs(2)
+                        .open(&self.auth_path)
+                }?;
                 auth.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)?;
 
                 // 5. Copy and tarball the flat snapshot
@@ -896,38 +897,95 @@ impl IndexScheduler {
                 dump_tasks.flush()?;
 
                 // 3. Dump the indexes
-                self.index_mapper.try_for_each_index(&rtxn, |uid, index| -> Result<()> {
-                    let rtxn = index.read_txn()?;
-                    let metadata = IndexMetadata {
-                        uid: uid.to_owned(),
-                        primary_key: index.primary_key(&rtxn)?.map(String::from),
-                        created_at: index.created_at(&rtxn)?,
-                        updated_at: index.updated_at(&rtxn)?,
-                    };
-                    let mut index_dumper = dump.create_index(uid, &metadata)?;
+                let () =
+                    self.index_mapper.try_for_each_index(&rtxn, |uid, index| -> Result<()> {
+                        let rtxn = index.read_txn()?;
+                        let metadata = IndexMetadata {
+                            uid: uid.to_owned(),
+                            primary_key: index.primary_key(&rtxn)?.map(String::from),
+                            created_at: index.created_at(&rtxn)?,
+                            updated_at: index.updated_at(&rtxn)?,
+                        };
+                        let mut index_dumper = dump.create_index(uid, &metadata)?;
 
-                    let fields_ids_map = index.fields_ids_map(&rtxn)?;
-                    let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
+                        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)? {
-                        if self.must_stop_processing.get() {
-                            return Err(Error::AbortedTask);
+                        // 3.1. Dump the documents
+                        for ret in index.all_documents(&rtxn)? {
+                            if self.must_stop_processing.get() {
+                                return Err(Error::AbortedTask);
+                            }
+
+                            let (id, doc) = ret?;
+
+                            let mut document =
+                                milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
+
+                            'inject_vectors: {
+                                let embeddings = index.embeddings(&rtxn, id)?;
+
+                                if embeddings.is_empty() {
+                                    break 'inject_vectors;
+                                }
+
+                                let vectors = document
+                                    .entry(RESERVED_VECTORS_FIELD_NAME.to_owned())
+                                    .or_insert(serde_json::Value::Object(Default::default()));
+
+                                let serde_json::Value::Object(vectors) = vectors else {
+                                    return Err(milli::Error::UserError(
+                                        milli::UserError::InvalidVectorsMapType {
+                                            document_id: {
+                                                if let Ok(Some(Ok(index))) = index
+                                                    .external_id_of(&rtxn, std::iter::once(id))
+                                                    .map(|it| it.into_iter().next())
+                                                {
+                                                    index
+                                                } else {
+                                                    format!("internal docid={id}")
+                                                }
+                                            },
+                                            value: vectors.clone(),
+                                        },
+                                    )
+                                    .into());
+                                };
+
+                                for (embedder_name, embeddings) in embeddings {
+                                    let user_provided = embedding_configs
+                                        .iter()
+                                        .find(|conf| conf.name == embedder_name)
+                                        .is_some_and(|conf| conf.user_provided.contains(id));
+
+                                    let embeddings = ExplicitVectors {
+                                        embeddings: Some(
+                                            VectorOrArrayOfVectors::from_array_of_vectors(
+                                                embeddings,
+                                            ),
+                                        ),
+                                        regenerate: !user_provided,
+                                    };
+                                    vectors.insert(
+                                        embedder_name,
+                                        serde_json::to_value(embeddings).unwrap(),
+                                    );
+                                }
+                            }
+
+                            index_dumper.push_document(&document)?;
                         }
-                        let (_id, doc) = ret?;
-                        let document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
-                        index_dumper.push_document(&document)?;
-                    }
 
-                    // 3.2. Dump the settings
-                    let settings = meilisearch_types::settings::settings(
-                        index,
-                        &rtxn,
-                        meilisearch_types::settings::SecretPolicy::RevealSecrets,
-                    )?;
-                    index_dumper.settings(&settings)?;
-                    Ok(())
-                })?;
+                        // 3.2. Dump the settings
+                        let settings = meilisearch_types::settings::settings(
+                            index,
+                            &rtxn,
+                            meilisearch_types::settings::SecretPolicy::RevealSecrets,
+                        )?;
+                        index_dumper.settings(&settings)?;
+                        Ok(())
+                    })?;
 
                 // 4. Dump experimental feature settings
                 let features = self.features().runtime_features();
@@ -1174,8 +1232,6 @@ impl IndexScheduler {
         index: &'i Index,
         operation: IndexOperation,
     ) -> Result<Vec<Task>> {
-        puffin::profile_function!();
-
         match operation {
             IndexOperation::DocumentClear { mut tasks, .. } => {
                 let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()?;
@@ -1236,7 +1292,11 @@ impl IndexScheduler {
                     }
                 }
 
-                let config = IndexDocumentsConfig { update_method: method, ..Default::default() };
+                let config = IndexDocumentsConfig {
+                    update_method: method,
+                    compute_prefix_databases: self.compute_prefix_databases,
+                    ..Default::default()
+                };
 
                 let embedder_configs = index.embedding_configs(index_wtxn)?;
                 // TODO: consider Arc'ing the map too (we only need read access + we'll be cloning it multiple times, so really makes sense)
@@ -1346,6 +1406,7 @@ impl IndexScheduler {
                 let deleted_documents = delete_document_by_filter(
                     index_wtxn,
                     filter,
+                    self.compute_prefix_databases,
                     self.index_mapper.indexer_config(),
                     self.must_stop_processing.clone(),
                     index,
@@ -1586,6 +1647,7 @@ impl IndexScheduler {
 fn delete_document_by_filter<'a>(
     wtxn: &mut RwTxn<'a>,
     filter: &serde_json::Value,
+    compute_prefix_databases: bool,
     indexer_config: &IndexerConfig,
     must_stop_processing: MustStopProcessing,
     index: &'a Index,
@@ -1601,6 +1663,7 @@ fn delete_document_by_filter<'a>(
 
         let config = IndexDocumentsConfig {
             update_method: IndexDocumentsMethod::ReplaceDocuments,
+            compute_prefix_databases,
             ..Default::default()
         };
 

index-scheduler/src/features.rs

@@ -68,19 +68,6 @@ impl RoFeatures {
             .into())
         }
     }
-
-    pub fn check_puffin(&self) -> Result<()> {
-        if self.runtime.export_puffin_reports {
-            Ok(())
-        } else {
-            Err(FeatureNotEnabledError {
-                disabled_action: "Outputting Puffin reports to disk",
-                feature: "export puffin reports",
-                issue_link: "https://github.com/meilisearch/product/discussions/693",
-            }
-            .into())
-        }
-    }
 }
 
 impl FeatureData {

index-scheduler/src/insta_snapshot.rs

@@ -32,7 +32,7 @@ pub fn snapshot_index_scheduler(scheduler: &IndexScheduler) -> String {
         features: _,
         max_number_of_tasks: _,
         max_number_of_batched_tasks: _,
-        puffin_frame: _,
+        compute_prefix_databases: _,
         wake_up: _,
         dumps_path: _,
         snapshots_path: _,

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-15.snap

@@ -0,0 +1,15 @@
+---
+source: index-scheduler/src/lib.rs
+expression: doc
+---
+{
+  "doggo": "Intel",
+  "breed": "beagle",
+  "_vectors": {
+    "noise": [
+      0.1,
+      0.2,
+      0.3
+    ]
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-2.snap

@@ -0,0 +1,20 @@
+---
+source: index-scheduler/src/lib.rs
+expression: task.details
+---
+{
+  "embedders": {
+    "A_fakerest": {
+      "source": "rest",
+      "apiKey": "MyXXXX...",
+      "dimensions": 384,
+      "url": "http://localhost:7777"
+    },
+    "B_small_hf": {
+      "source": "huggingFace",
+      "model": "sentence-transformers/all-MiniLM-L6-v2",
+      "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
+      "documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
+    }
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-22.snap

@@ -0,0 +1,15 @@
+---
+source: index-scheduler/src/lib.rs
+expression: doc
+---
+{
+  "doggo": "kefir",
+  "breed": "patou",
+  "_vectors": {
+    "noise": [
+      0.1,
+      0.2,
+      0.3
+    ]
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-5.snap

@@ -0,0 +1,23 @@
+---
+source: index-scheduler/src/lib.rs
+expression: fakerest_config.embedder_options
+---
+{
+  "Rest": {
+    "api_key": "My super secret",
+    "distribution": null,
+    "dimensions": 384,
+    "url": "http://localhost:7777",
+    "query": null,
+    "input_field": [
+      "input"
+    ],
+    "path_to_embeddings": [
+      "data"
+    ],
+    "embedding_object": [
+      "embedding"
+    ],
+    "input_type": "text"
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors-8.snap

@@ -0,0 +1,11 @@
+---
+source: index-scheduler/src/lib.rs
+expression: simple_hf_config.embedder_options
+---
+{
+  "HuggingFace": {
+    "model": "sentence-transformers/all-MiniLM-L6-v2",
+    "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
+    "distribution": null
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__import_vectors.snap

@@ -0,0 +1,20 @@
+---
+source: index-scheduler/src/lib.rs
+expression: task.details
+---
+{
+  "embedders": {
+    "A_fakerest": {
+      "source": "rest",
+      "apiKey": "MyXXXX...",
+      "dimensions": 384,
+      "url": "http://localhost:7777"
+    },
+    "B_small_hf": {
+      "source": "huggingFace",
+      "model": "sentence-transformers/all-MiniLM-L6-v2",
+      "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
+      "documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
+    }
+  }
+}

index-scheduler/src/snapshots/index_scheduler__tests__settings_update-2.snap

@@ -7,6 +7,7 @@ expression: task.details
     "default": {
       "source": "rest",
       "apiKey": "MyXXXX...",
+      "dimensions": 4,
       "url": "http://localhost:7777"
     }
   }

index-scheduler/src/snapshots/index_scheduler__tests__settings_update-5.snap

@@ -6,7 +6,7 @@ expression: embedding_config.embedder_options
   "Rest": {
     "api_key": "My super secret",
     "distribution": null,
-    "dimensions": null,
+    "dimensions": 4,
     "url": "http://localhost:7777",
     "query": null,
     "input_field": [

index-scheduler/src/snapshots/index_scheduler__tests__settings_update.snap

@@ -7,6 +7,7 @@ expression: task.details
     "default": {
       "source": "rest",
       "apiKey": "MyXXXX...",
+      "dimensions": 4,
       "url": "http://localhost:7777"
     }
   }

index-scheduler/src/snapshots/lib.rs/import_vectors/Intel to kefir succeeds.snap

@@ -0,0 +1,49 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
+2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued []
+succeeded [0,1,2,]
+----------------------------------------------------------------------
+### Kind:
+"documentAdditionOrUpdate" [1,2,]
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,1,2,]
+----------------------------------------------------------------------
+### Index Mapper:
+doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+[timestamp] [1,]
+[timestamp] [2,]
+----------------------------------------------------------------------
+### Started At:
+[timestamp] [0,]
+[timestamp] [1,]
+[timestamp] [2,]
+----------------------------------------------------------------------
+### Finished At:
+[timestamp] [0,]
+[timestamp] [1,]
+[timestamp] [2,]
+----------------------------------------------------------------------
+### File Store:
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/import_vectors/Intel to kefir.snap

@@ -0,0 +1,48 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
+2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued [2,]
+succeeded [0,1,]
+----------------------------------------------------------------------
+### Kind:
+"documentAdditionOrUpdate" [1,2,]
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,1,2,]
+----------------------------------------------------------------------
+### Index Mapper:
+doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+[timestamp] [1,]
+[timestamp] [2,]
+----------------------------------------------------------------------
+### Started At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### Finished At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### File Store:
+00000000-0000-0000-0000-000000000001
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/import_vectors/adding Intel succeeds.snap

@@ -0,0 +1,45 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued []
+succeeded [0,1,]
+----------------------------------------------------------------------
+### Kind:
+"documentAdditionOrUpdate" [1,]
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,1,]
+----------------------------------------------------------------------
+### Index Mapper:
+doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### Started At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### Finished At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### File Store:
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/import_vectors/after adding Intel.snap

@@ -0,0 +1,44 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+1 {uid: 1, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued [1,]
+succeeded [0,]
+----------------------------------------------------------------------
+### Kind:
+"documentAdditionOrUpdate" [1,]
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,1,]
+----------------------------------------------------------------------
+### Index Mapper:
+doggos: { number_of_documents: 0, field_distribution: {} }
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+[timestamp] [1,]
+----------------------------------------------------------------------
+### Started At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### Finished At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### File Store:
+00000000-0000-0000-0000-000000000000
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/import_vectors/after_registering_settings_task_vectors.snap

@@ -0,0 +1,36 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: enqueued, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued [0,]
+----------------------------------------------------------------------
+### Kind:
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,]
+----------------------------------------------------------------------
+### Index Mapper:
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### Started At:
+----------------------------------------------------------------------
+### Finished At:
+----------------------------------------------------------------------
+### File Store:
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/import_vectors/settings_update_processed_vectors.snap

@@ -0,0 +1,40 @@
+---
+source: index-scheduler/src/lib.rs
+---
+### Autobatching Enabled = true
+### Processing Tasks:
+[]
+----------------------------------------------------------------------
+### All Tasks:
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+----------------------------------------------------------------------
+### Status:
+enqueued []
+succeeded [0,]
+----------------------------------------------------------------------
+### Kind:
+"settingsUpdate" [0,]
+----------------------------------------------------------------------
+### Index Tasks:
+doggos [0,]
+----------------------------------------------------------------------
+### Index Mapper:
+doggos: { number_of_documents: 0, field_distribution: {} }
+
+----------------------------------------------------------------------
+### Canceled By:
+
+----------------------------------------------------------------------
+### Enqueued At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### Started At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### Finished At:
+[timestamp] [0,]
+----------------------------------------------------------------------
+### File Store:
+
+----------------------------------------------------------------------
+

index-scheduler/src/snapshots/lib.rs/test_settings_update/after_registering_settings_task.snap

@@ -6,7 +6,7 @@ source: index-scheduler/src/lib.rs
 []
 ----------------------------------------------------------------------
 ### All Tasks:
-0 {uid: 0, status: enqueued, details: { settings: Settings { displayed_attributes: NotSet, searchable_attributes: NotSet, filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: NotSet, document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: NotSet, searchable_attributes: NotSet, filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: NotSet, document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+0 {uid: 0, status: enqueued, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(4), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(4), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
 ----------------------------------------------------------------------
 ### Status:
 enqueued [0,]

index-scheduler/src/snapshots/lib.rs/test_settings_update/settings_update_processed.snap

@@ -6,7 +6,7 @@ source: index-scheduler/src/lib.rs
 []
 ----------------------------------------------------------------------
 ### All Tasks:
-0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: NotSet, searchable_attributes: NotSet, filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: NotSet, document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: NotSet, searchable_attributes: NotSet, filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: NotSet, document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
+0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(4), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"default": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(4), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
 ----------------------------------------------------------------------
 ### Status:
 enqueued []

index-scheduler/src/utils.rs

@@ -272,9 +272,9 @@ pub fn swap_index_uid_in_task(task: &mut Task, swap: (&str, &str)) {
     }
     for index_uid in index_uids {
         if index_uid == swap.0 {
-            *index_uid = swap.1.to_owned();
+            swap.1.clone_into(index_uid);
         } else if index_uid == swap.1 {
-            *index_uid = swap.0.to_owned();
+            swap.0.clone_into(index_uid);
         }
     }
 }

meilisearch-auth/src/store.rs

@@ -49,7 +49,7 @@ pub fn open_auth_store_env(path: &Path) -> milli::heed::Result<milli::heed::Env>
     let mut options = EnvOpenOptions::new();
     options.map_size(AUTH_STORE_SIZE); // 1GB
     options.max_dbs(2);
-    options.open(path)
+    unsafe { options.open(path) }
 }
 
 impl HeedAuthStore {

meilisearch-types/Cargo.toml

@@ -11,7 +11,7 @@ edition.workspace = true
 license.workspace = true
 
 [dependencies]
-actix-web = { version = "4.5.1", default-features = false }
+actix-web = { version = "4.6.0", default-features = false }
 anyhow = "1.0.79"
 convert_case = "0.6.0"
 csv = "1.3.0"
@@ -30,7 +30,12 @@ serde_json = "1.0.111"
 tar = "0.4.40"
 tempfile = "3.9.0"
 thiserror = "1.0.56"
-time = { version = "0.3.31", features = ["serde-well-known", "formatting", "parsing", "macros"] }
+time = { version = "0.3.31", features = [
+    "serde-well-known",
+    "formatting",
+    "parsing",
+    "macros",
+] }
 tokio = "1.35"
 uuid = { version = "1.6.1", features = ["serde", "v4"] }
 
@@ -44,6 +49,7 @@ all-tokenizations = ["milli/all-tokenizations"]
 
 # chinese specialized tokenization
 chinese = ["milli/chinese"]
+chinese-pinyin = ["milli/chinese-pinyin"]
 # hebrew specialized tokenization
 hebrew = ["milli/hebrew"]
 # japanese specialized tokenization
@@ -56,3 +62,5 @@ greek = ["milli/greek"]
 khmer = ["milli/khmer"]
 # allow vietnamese specialized tokenization
 vietnamese = ["milli/vietnamese"]
+# force swedish character recomposition
+swedish-recomposition = ["milli/swedish-recomposition"]

meilisearch-types/src/deserr/mod.rs

@@ -26,7 +26,7 @@ pub type DeserrQueryParamError<C = BadRequest> = DeserrError<DeserrQueryParam, C
 
 /// A request deserialization error.
 ///
-/// The first generic paramater is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
+/// The first generic parameter is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
 /// The second generic parameter is the default error code for the deserialization error, in case it is not given.
 pub struct DeserrError<Format, C: Default + ErrorCode> {
     pub msg: String,
@@ -189,3 +189,6 @@ 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

@@ -222,6 +222,7 @@ 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 ;
@@ -239,18 +240,27 @@ InvalidIndexUid                       , InvalidRequest       , BAD_REQUEST ;
 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 ;
 InvalidSearchSemanticRatio            , InvalidRequest       , BAD_REQUEST ;
 InvalidFacetSearchFacetName           , InvalidRequest       , BAD_REQUEST ;
+InvalidSimilarId                      , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchFilter                   , InvalidRequest       , BAD_REQUEST ;
+InvalidSimilarFilter                  , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchHighlightPostTag         , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchHighlightPreTag          , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchHitsPerPage              , InvalidRequest       , BAD_REQUEST ;
+InvalidSimilarLimit                   , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchLimit                    , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchMatchingStrategy         , InvalidRequest       , BAD_REQUEST ;
+InvalidSimilarOffset                  , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchOffset                   , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchPage                     , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchQ                        , InvalidRequest       , BAD_REQUEST ;
@@ -259,15 +269,18 @@ InvalidFacetSearchName                , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchVector                   , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchShowMatchesPosition      , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchShowRankingScore         , InvalidRequest       , BAD_REQUEST ;
+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 ;
@@ -322,7 +335,8 @@ UnretrievableErrorCode                , InvalidRequest       , BAD_REQUEST ;
 UnsupportedMediaType                  , InvalidRequest       , UNSUPPORTED_MEDIA_TYPE ;
 
 // Experimental features
-VectorEmbeddingError                  , InvalidRequest       , BAD_REQUEST
+VectorEmbeddingError                  , InvalidRequest       , BAD_REQUEST ;
+NotFoundSimilarId                     , InvalidRequest       , BAD_REQUEST
 }
 
 impl ErrorCode for JoinError {
@@ -371,6 +385,7 @@ 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,
@@ -383,8 +398,8 @@ impl ErrorCode for milli::Error {
                     UserError::CriterionError(_) => Code::InvalidSettingsRankingRules,
                     UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
                     UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
-                    UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
-                    UserError::InvalidVectorsType { .. } => Code::InvalidVectorsType,
+                    UserError::InvalidVectorsMapType { .. }
+                    | UserError::InvalidVectorsEmbedderConf { .. } => Code::InvalidVectorsType,
                     UserError::TooManyVectors(_, _) => Code::TooManyVectors,
                     UserError::SortError(_) => Code::InvalidSearchSort,
                     UserError::InvalidMinTypoWordLenSetting(_, _) => {
@@ -423,7 +438,6 @@ impl ErrorCode for HeedError {
             HeedError::Mdb(_)
             | HeedError::Encoding(_)
             | HeedError::Decoding(_)
-            | HeedError::InvalidDatabaseTyping
             | HeedError::DatabaseClosing
             | HeedError::BadOpenOptions { .. } => Code::Internal,
         }
@@ -488,6 +502,32 @@ impl fmt::Display for deserr_codes::InvalidSearchSemanticRatio {
     }
 }
 
+impl fmt::Display for deserr_codes::InvalidSimilarId {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        write!(
+            f,
+            "the value of `id` is invalid. \
+            A document identifier can be of type integer or string, \
+            only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_)."
+        )
+    }
+}
+
+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/features.rs

@@ -6,7 +6,6 @@ pub struct RuntimeTogglableFeatures {
     pub vector_store: bool,
     pub metrics: bool,
     pub logs_route: bool,
-    pub export_puffin_reports: bool,
 }
 
 #[derive(Default, Debug, Clone, Copy)]

meilisearch-types/src/settings.rs

@@ -3,11 +3,12 @@ use std::convert::Infallible;
 use std::fmt;
 use std::marker::PhantomData;
 use std::num::NonZeroUsize;
-use std::ops::ControlFlow;
+use std::ops::{ControlFlow, Deref};
 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};
@@ -143,21 +144,13 @@ impl MergeWithError<milli::CriterionError> for DeserrJsonError<InvalidSettingsRa
 )]
 #[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
 pub struct Settings<T> {
-    #[serde(
-        default,
-        serialize_with = "serialize_with_wildcard",
-        skip_serializing_if = "Setting::is_not_set"
-    )]
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
     #[deserr(default, error = DeserrJsonError<InvalidSettingsDisplayedAttributes>)]
-    pub displayed_attributes: Setting<Vec<String>>,
+    pub displayed_attributes: WildcardSetting,
 
-    #[serde(
-        default,
-        serialize_with = "serialize_with_wildcard",
-        skip_serializing_if = "Setting::is_not_set"
-    )]
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
     #[deserr(default, error = DeserrJsonError<InvalidSettingsSearchableAttributes>)]
-    pub searchable_attributes: Setting<Vec<String>>,
+    pub searchable_attributes: WildcardSetting,
 
     #[serde(default, skip_serializing_if = "Setting::is_not_set")]
     #[deserr(default, error = DeserrJsonError<InvalidSettingsFilterableAttributes>)]
@@ -251,8 +244,8 @@ impl<T> Settings<T> {
 impl Settings<Checked> {
     pub fn cleared() -> Settings<Checked> {
         Settings {
-            displayed_attributes: Setting::Reset,
-            searchable_attributes: Setting::Reset,
+            displayed_attributes: Setting::Reset.into(),
+            searchable_attributes: Setting::Reset.into(),
             filterable_attributes: Setting::Reset,
             sortable_attributes: Setting::Reset,
             ranking_rules: Setting::Reset,
@@ -319,7 +312,7 @@ impl Settings<Checked> {
 
 impl Settings<Unchecked> {
     pub fn check(self) -> Settings<Checked> {
-        let displayed_attributes = match self.displayed_attributes {
+        let displayed_attributes = match self.displayed_attributes.0 {
             Setting::Set(fields) => {
                 if fields.iter().any(|f| f == "*") {
                     Setting::Reset
@@ -330,7 +323,7 @@ impl Settings<Unchecked> {
             otherwise => otherwise,
         };
 
-        let searchable_attributes = match self.searchable_attributes {
+        let searchable_attributes = match self.searchable_attributes.0 {
             Setting::Set(fields) => {
                 if fields.iter().any(|f| f == "*") {
                     Setting::Reset
@@ -342,8 +335,8 @@ impl Settings<Unchecked> {
         };
 
         Settings {
-            displayed_attributes,
-            searchable_attributes,
+            displayed_attributes: displayed_attributes.into(),
+            searchable_attributes: searchable_attributes.into(),
             filterable_attributes: self.filterable_attributes,
             sortable_attributes: self.sortable_attributes,
             ranking_rules: self.ranking_rules,
@@ -412,13 +405,13 @@ pub fn apply_settings_to_builder(
         _kind,
     } = settings;
 
-    match searchable_attributes {
+    match searchable_attributes.deref() {
         Setting::Set(ref names) => builder.set_searchable_fields(names.clone()),
         Setting::Reset => builder.reset_searchable_fields(),
         Setting::NotSet => (),
     }
 
-    match displayed_attributes {
+    match displayed_attributes.deref() {
         Setting::Set(ref names) => builder.set_displayed_fields(names.clone()),
         Setting::Reset => builder.reset_displayed_fields(),
         Setting::NotSet => (),
@@ -680,7 +673,7 @@ pub fn settings(
     let embedders: BTreeMap<_, _> = index
         .embedding_configs(rtxn)?
         .into_iter()
-        .map(|(name, config)| (name, Setting::Set(config.into())))
+        .map(|IndexEmbeddingConfig { name, config, .. }| (name, Setting::Set(config.into())))
         .collect();
     let embedders = if embedders.is_empty() { Setting::NotSet } else { Setting::Set(embedders) };
 
@@ -690,11 +683,13 @@ pub fn settings(
         displayed_attributes: match displayed_attributes {
             Some(attrs) => Setting::Set(attrs),
             None => Setting::Reset,
-        },
+        }
+        .into(),
         searchable_attributes: match searchable_attributes {
             Some(attrs) => Setting::Set(attrs),
             None => Setting::Reset,
-        },
+        }
+        .into(),
         filterable_attributes: Setting::Set(filterable_attributes),
         sortable_attributes: Setting::Set(sortable_attributes),
         ranking_rules: Setting::Set(criteria.iter().map(|c| c.clone().into()).collect()),
@@ -848,6 +843,41 @@ impl From<ProximityPrecisionView> for ProximityPrecision {
     }
 }
 
+#[derive(Debug, Clone, Default, Deserialize, PartialEq, Eq)]
+pub struct WildcardSetting(Setting<Vec<String>>);
+
+impl From<Setting<Vec<String>>> for WildcardSetting {
+    fn from(setting: Setting<Vec<String>>) -> Self {
+        Self(setting)
+    }
+}
+
+impl Serialize for WildcardSetting {
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        serialize_with_wildcard(&self.0, serializer)
+    }
+}
+
+impl<E: deserr::DeserializeError> Deserr<E> for WildcardSetting {
+    fn deserialize_from_value<V: deserr::IntoValue>(
+        value: deserr::Value<V>,
+        location: ValuePointerRef<'_>,
+    ) -> Result<Self, E> {
+        Ok(Self(Setting::deserialize_from_value(value, location)?))
+    }
+}
+
+impl std::ops::Deref for WildcardSetting {
+    type Target = Setting<Vec<String>>;
+
+    fn deref(&self) -> &Self::Target {
+        &self.0
+    }
+}
+
 #[cfg(test)]
 pub(crate) mod test {
     use super::*;
@@ -856,8 +886,8 @@ pub(crate) mod test {
     fn test_setting_check() {
         // test no changes
         let settings = Settings {
-            displayed_attributes: Setting::Set(vec![String::from("hello")]),
-            searchable_attributes: Setting::Set(vec![String::from("hello")]),
+            displayed_attributes: Setting::Set(vec![String::from("hello")]).into(),
+            searchable_attributes: Setting::Set(vec![String::from("hello")]).into(),
             filterable_attributes: Setting::NotSet,
             sortable_attributes: Setting::NotSet,
             ranking_rules: Setting::NotSet,
@@ -883,8 +913,9 @@ pub(crate) mod test {
         // test wildcard
         // test no changes
         let settings = Settings {
-            displayed_attributes: Setting::Set(vec![String::from("*")]),
-            searchable_attributes: Setting::Set(vec![String::from("hello"), String::from("*")]),
+            displayed_attributes: Setting::Set(vec![String::from("*")]).into(),
+            searchable_attributes: Setting::Set(vec![String::from("hello"), String::from("*")])
+                .into(),
             filterable_attributes: Setting::NotSet,
             sortable_attributes: Setting::NotSet,
             ranking_rules: Setting::NotSet,
@@ -904,7 +935,7 @@ pub(crate) mod test {
         };
 
         let checked = settings.check();
-        assert_eq!(checked.displayed_attributes, Setting::Reset);
-        assert_eq!(checked.searchable_attributes, Setting::Reset);
+        assert_eq!(checked.displayed_attributes, Setting::Reset.into());
+        assert_eq!(checked.searchable_attributes, Setting::Reset.into());
     }
 }

meilisearch/Cargo.toml

@@ -14,20 +14,20 @@ default-run = "meilisearch"
 
 [dependencies]
 actix-cors = "0.7.0"
-actix-http = { version = "3.6.0", default-features = false, features = [
+actix-http = { version = "3.7.0", default-features = false, features = [
     "compress-brotli",
     "compress-gzip",
     "rustls-0_21",
 ] }
 actix-utils = "3.0.1"
-actix-web = { version = "4.5.1", default-features = false, features = [
+actix-web = { version = "4.6.0", default-features = false, features = [
     "macros",
     "compress-brotli",
     "compress-gzip",
     "cookies",
     "rustls-0_21",
 ] }
-actix-web-static-files = { git = "https://github.com/kilork/actix-web-static-files.git", rev = "2d3b6160", optional = true }
+actix-web-static-files = { version = "4.0.1", optional = true }
 anyhow = { version = "1.0.79", features = ["backtrace"] }
 async-stream = "0.3.5"
 async-trait = "0.1.77"
@@ -67,7 +67,6 @@ permissive-json-pointer = { path = "../permissive-json-pointer" }
 pin-project-lite = "0.2.13"
 platform-dirs = "0.3.0"
 prometheus = { version = "0.13.3", features = ["process"] }
-puffin = { version = "0.16.0", features = ["serialization"] }
 rand = "0.8.5"
 rayon = "1.8.0"
 regex = "1.10.2"
@@ -75,7 +74,7 @@ reqwest = { version = "0.11.23", features = [
     "rustls-tls",
     "json",
 ], default-features = false }
-rustls = "0.21.6"
+rustls = "0.21.12"
 rustls-pemfile = "1.0.2"
 segment = { version = "0.2.3", optional = true }
 serde = { version = "1.0.195", features = ["derive"] }
@@ -106,13 +105,13 @@ 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 = "0.7.9"
+tracing-actix-web = "0.7.10"
 build-info = { version = "1.7.0", path = "../build-info" }
 
 [dev-dependencies]
 actix-rt = "2.9.0"
 assert-json-diff = "2.0.2"
-brotli = "3.4.0"
+brotli = "6.0.0"
 insta = "1.34.0"
 manifest-dir-macros = "0.1.18"
 maplit = "1.0.2"
@@ -149,13 +148,15 @@ mini-dashboard = [
     "zip",
 ]
 chinese = ["meilisearch-types/chinese"]
+chinese-pinyin = ["meilisearch-types/chinese-pinyin"]
 hebrew = ["meilisearch-types/hebrew"]
 japanese = ["meilisearch-types/japanese"]
 thai = ["meilisearch-types/thai"]
 greek = ["meilisearch-types/greek"]
 khmer = ["meilisearch-types/khmer"]
 vietnamese = ["meilisearch-types/vietnamese"]
+swedish-recomposition = ["meilisearch-types/swedish-recomposition"]
 
 [package.metadata.mini-dashboard]
-assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.13/build.zip"
-sha1 = "e20cc9b390003c6c844f4b8bcc5c5013191a77ff"
+assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.14/build.zip"
+sha1 = "592d1b5a3459d621d0aae1dded8fe3154f5c38fe"

meilisearch/src/analytics/mock_analytics.rs

@@ -7,7 +7,6 @@ use serde_json::Value;
 
 use super::{find_user_id, Analytics, DocumentDeletionKind, DocumentFetchKind};
 use crate::routes::indexes::documents::UpdateDocumentsQuery;
-use crate::routes::tasks::TasksFilterQuery;
 use crate::Opt;
 
 pub struct MockAnalytics {
@@ -26,6 +25,18 @@ impl SearchAggregator {
     pub fn succeed(&mut self, _: &dyn Any) {}
 }
 
+#[derive(Default)]
+pub struct SimilarAggregator;
+
+#[allow(dead_code)]
+impl SimilarAggregator {
+    pub fn from_query(_: &dyn Any, _: &dyn Any) -> Self {
+        Self
+    }
+
+    pub fn succeed(&mut self, _: &dyn Any) {}
+}
+
 #[derive(Default)]
 pub struct MultiSearchAggregator;
 
@@ -67,6 +78,8 @@ impl Analytics for MockAnalytics {
     fn publish(&self, _event_name: String, _send: Value, _request: Option<&HttpRequest>) {}
     fn get_search(&self, _aggregate: super::SearchAggregator) {}
     fn post_search(&self, _aggregate: super::SearchAggregator) {}
+    fn get_similar(&self, _aggregate: super::SimilarAggregator) {}
+    fn post_similar(&self, _aggregate: super::SimilarAggregator) {}
     fn post_multi_search(&self, _aggregate: super::MultiSearchAggregator) {}
     fn post_facet_search(&self, _aggregate: super::FacetSearchAggregator) {}
     fn add_documents(
@@ -86,6 +99,4 @@ impl Analytics for MockAnalytics {
     }
     fn get_fetch_documents(&self, _documents_query: &DocumentFetchKind, _request: &HttpRequest) {}
     fn post_fetch_documents(&self, _documents_query: &DocumentFetchKind, _request: &HttpRequest) {}
-    fn get_tasks(&self, _query: &TasksFilterQuery, _request: &HttpRequest) {}
-    fn health_seen(&self, _request: &HttpRequest) {}
 }

meilisearch/src/analytics/mod.rs

@@ -14,7 +14,6 @@ use platform_dirs::AppDirs;
 use serde_json::Value;
 
 use crate::routes::indexes::documents::UpdateDocumentsQuery;
-use crate::routes::tasks::TasksFilterQuery;
 
 // if the analytics feature is disabled
 // the `SegmentAnalytics` point to the mock instead of the real analytics
@@ -23,6 +22,8 @@ pub type SegmentAnalytics = mock_analytics::MockAnalytics;
 #[cfg(not(feature = "analytics"))]
 pub type SearchAggregator = mock_analytics::SearchAggregator;
 #[cfg(not(feature = "analytics"))]
+pub type SimilarAggregator = mock_analytics::SimilarAggregator;
+#[cfg(not(feature = "analytics"))]
 pub type MultiSearchAggregator = mock_analytics::MultiSearchAggregator;
 #[cfg(not(feature = "analytics"))]
 pub type FacetSearchAggregator = mock_analytics::FacetSearchAggregator;
@@ -33,6 +34,8 @@ pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
 #[cfg(feature = "analytics")]
 pub type SearchAggregator = segment_analytics::SearchAggregator;
 #[cfg(feature = "analytics")]
+pub type SimilarAggregator = segment_analytics::SimilarAggregator;
+#[cfg(feature = "analytics")]
 pub type MultiSearchAggregator = segment_analytics::MultiSearchAggregator;
 #[cfg(feature = "analytics")]
 pub type FacetSearchAggregator = segment_analytics::FacetSearchAggregator;
@@ -71,8 +74,8 @@ pub enum DocumentDeletionKind {
 
 #[derive(Copy, Clone, Debug, PartialEq, Eq)]
 pub enum DocumentFetchKind {
-    PerDocumentId,
-    Normal { with_filter: bool, limit: usize, offset: usize },
+    PerDocumentId { retrieve_vectors: bool },
+    Normal { with_filter: bool, limit: usize, offset: usize, retrieve_vectors: bool },
 }
 
 pub trait Analytics: Sync + Send {
@@ -87,6 +90,12 @@ pub trait Analytics: Sync + Send {
     /// This method should be called to aggregate a post search
     fn post_search(&self, aggregate: SearchAggregator);
 
+    /// This method should be called to aggregate a get similar request
+    fn get_similar(&self, aggregate: SimilarAggregator);
+
+    /// This method should be called to aggregate a post similar request
+    fn post_similar(&self, aggregate: SimilarAggregator);
+
     /// This method should be called to aggregate a post array of searches
     fn post_multi_search(&self, aggregate: MultiSearchAggregator);
 
@@ -117,10 +126,4 @@ pub trait Analytics: Sync + Send {
         index_creation: bool,
         request: &HttpRequest,
     );
-
-    // this method should be called to aggregate the get tasks requests.
-    fn get_tasks(&self, query: &TasksFilterQuery, request: &HttpRequest);
-
-    // this method should be called to aggregate a add documents request
-    fn health_seen(&self, request: &HttpRequest);
 }

meilisearch/src/analytics/segment_analytics.rs

@@ -33,12 +33,12 @@ use crate::option::{
 };
 use crate::routes::indexes::documents::UpdateDocumentsQuery;
 use crate::routes::indexes::facet_search::FacetSearchQuery;
-use crate::routes::tasks::TasksFilterQuery;
 use crate::routes::{create_all_stats, Stats};
 use crate::search::{
     FacetSearchResult, MatchingStrategy, SearchQuery, SearchQueryWithIndex, SearchResult,
-    DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
+    SimilarQuery, SimilarResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
+    DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
+    DEFAULT_SEMANTIC_RATIO,
 };
 use crate::Opt;
 
@@ -74,6 +74,8 @@ pub enum AnalyticsMsg {
     BatchMessage(Track),
     AggregateGetSearch(SearchAggregator),
     AggregatePostSearch(SearchAggregator),
+    AggregateGetSimilar(SimilarAggregator),
+    AggregatePostSimilar(SimilarAggregator),
     AggregatePostMultiSearch(MultiSearchAggregator),
     AggregatePostFacetSearch(FacetSearchAggregator),
     AggregateAddDocuments(DocumentsAggregator),
@@ -81,8 +83,6 @@ pub enum AnalyticsMsg {
     AggregateUpdateDocuments(DocumentsAggregator),
     AggregateGetFetchDocuments(DocumentsFetchAggregator),
     AggregatePostFetchDocuments(DocumentsFetchAggregator),
-    AggregateTasks(TasksAggregator),
-    AggregateHealth(HealthAggregator),
 }
 
 pub struct SegmentAnalytics {
@@ -152,8 +152,8 @@ impl SegmentAnalytics {
             update_documents_aggregator: DocumentsAggregator::default(),
             get_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
             post_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
-            get_tasks_aggregator: TasksAggregator::default(),
-            health_aggregator: HealthAggregator::default(),
+            get_similar_aggregator: SimilarAggregator::default(),
+            post_similar_aggregator: SimilarAggregator::default(),
         });
         tokio::spawn(segment.run(index_scheduler.clone(), auth_controller.clone()));
 
@@ -189,6 +189,14 @@ impl super::Analytics for SegmentAnalytics {
         let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSearch(aggregate));
     }
 
+    fn get_similar(&self, aggregate: SimilarAggregator) {
+        let _ = self.sender.try_send(AnalyticsMsg::AggregateGetSimilar(aggregate));
+    }
+
+    fn post_similar(&self, aggregate: SimilarAggregator) {
+        let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSimilar(aggregate));
+    }
+
     fn post_facet_search(&self, aggregate: FacetSearchAggregator) {
         let _ = self.sender.try_send(AnalyticsMsg::AggregatePostFacetSearch(aggregate));
     }
@@ -231,16 +239,6 @@ impl super::Analytics for SegmentAnalytics {
         let aggregate = DocumentsFetchAggregator::from_query(documents_query, request);
         let _ = self.sender.try_send(AnalyticsMsg::AggregatePostFetchDocuments(aggregate));
     }
-
-    fn get_tasks(&self, query: &TasksFilterQuery, request: &HttpRequest) {
-        let aggregate = TasksAggregator::from_query(query, request);
-        let _ = self.sender.try_send(AnalyticsMsg::AggregateTasks(aggregate));
-    }
-
-    fn health_seen(&self, request: &HttpRequest) {
-        let aggregate = HealthAggregator::from_query(request);
-        let _ = self.sender.try_send(AnalyticsMsg::AggregateHealth(aggregate));
-    }
 }
 
 /// This structure represent the `infos` field we send in the analytics.
@@ -258,6 +256,7 @@ struct Infos {
     experimental_enable_logs_route: bool,
     experimental_reduce_indexing_memory_usage: bool,
     experimental_max_number_of_batched_tasks: usize,
+    experimental_disable_prefix_db: bool,
     gpu_enabled: bool,
     db_path: bool,
     import_dump: bool,
@@ -300,6 +299,7 @@ impl From<Opt> for Infos {
             experimental_enable_logs_route,
             experimental_reduce_indexing_memory_usage,
             experimental_max_number_of_batched_tasks,
+            experimental_disable_prefix_db,
             http_addr,
             master_key: _,
             env,
@@ -349,6 +349,7 @@ impl From<Opt> for Infos {
             experimental_replication_parameters,
             experimental_enable_logs_route,
             experimental_reduce_indexing_memory_usage,
+            experimental_disable_prefix_db,
             gpu_enabled: meilisearch_types::milli::vector::is_cuda_enabled(),
             db_path: db_path != PathBuf::from("./data.ms"),
             import_dump: import_dump.is_some(),
@@ -394,8 +395,8 @@ pub struct Segment {
     update_documents_aggregator: DocumentsAggregator,
     get_fetch_documents_aggregator: DocumentsFetchAggregator,
     post_fetch_documents_aggregator: DocumentsFetchAggregator,
-    get_tasks_aggregator: TasksAggregator,
-    health_aggregator: HealthAggregator,
+    get_similar_aggregator: SimilarAggregator,
+    post_similar_aggregator: SimilarAggregator,
 }
 
 impl Segment {
@@ -458,8 +459,8 @@ impl Segment {
                         Some(AnalyticsMsg::AggregateUpdateDocuments(agreg)) => self.update_documents_aggregator.aggregate(agreg),
                         Some(AnalyticsMsg::AggregateGetFetchDocuments(agreg)) => self.get_fetch_documents_aggregator.aggregate(agreg),
                         Some(AnalyticsMsg::AggregatePostFetchDocuments(agreg)) => self.post_fetch_documents_aggregator.aggregate(agreg),
-                        Some(AnalyticsMsg::AggregateTasks(agreg)) => self.get_tasks_aggregator.aggregate(agreg),
-                        Some(AnalyticsMsg::AggregateHealth(agreg)) => self.health_aggregator.aggregate(agreg),
+                        Some(AnalyticsMsg::AggregateGetSimilar(agreg)) => self.get_similar_aggregator.aggregate(agreg),
+                        Some(AnalyticsMsg::AggregatePostSimilar(agreg)) => self.post_similar_aggregator.aggregate(agreg),
                         None => (),
                     }
                 }
@@ -513,8 +514,8 @@ impl Segment {
             update_documents_aggregator,
             get_fetch_documents_aggregator,
             post_fetch_documents_aggregator,
-            get_tasks_aggregator,
-            health_aggregator,
+            get_similar_aggregator,
+            post_similar_aggregator,
         } = self;
 
         if let Some(get_search) =
@@ -562,11 +563,17 @@ impl Segment {
         {
             let _ = self.batcher.push(post_fetch_documents).await;
         }
-        if let Some(get_tasks) = take(get_tasks_aggregator).into_event(user, "Tasks Seen") {
-            let _ = self.batcher.push(get_tasks).await;
+
+        if let Some(get_similar_documents) =
+            take(get_similar_aggregator).into_event(user, "Similar GET")
+        {
+            let _ = self.batcher.push(get_similar_documents).await;
         }
-        if let Some(health) = take(health_aggregator).into_event(user, "Health Seen") {
-            let _ = self.batcher.push(health).await;
+
+        if let Some(post_similar_documents) =
+            take(post_similar_aggregator).into_event(user, "Similar POST")
+        {
+            let _ = self.batcher.push(post_similar_documents).await;
         }
         let _ = self.batcher.flush().await;
     }
@@ -593,6 +600,9 @@ 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,
@@ -618,6 +628,7 @@ 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>,
@@ -644,6 +655,7 @@ pub struct SearchAggregator {
     // scoring
     show_ranking_score: bool,
     show_ranking_score_details: bool,
+    ranking_score_threshold: bool,
 }
 
 impl SearchAggregator {
@@ -657,6 +669,7 @@ impl SearchAggregator {
             page,
             hits_per_page,
             attributes_to_retrieve: _,
+            retrieve_vectors,
             attributes_to_crop: _,
             crop_length,
             attributes_to_highlight: _,
@@ -665,6 +678,7 @@ impl SearchAggregator {
             show_ranking_score_details,
             filter,
             sort,
+            distinct,
             facets: _,
             highlight_pre_tag,
             highlight_post_tag,
@@ -672,6 +686,7 @@ impl SearchAggregator {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
+            ranking_score_threshold,
         } = query;
 
         let mut ret = Self::default();
@@ -686,6 +701,8 @@ 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;
@@ -722,6 +739,7 @@ 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);
@@ -744,6 +762,7 @@ 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();
@@ -788,6 +807,7 @@ 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,
@@ -796,6 +816,7 @@ impl SearchAggregator {
             attributes_to_search_on_total_number_of_uses,
             max_terms_number,
             max_vector_size,
+            retrieve_vectors,
             matching_strategy,
             max_limit,
             max_offset,
@@ -817,6 +838,7 @@ impl SearchAggregator {
             hybrid,
             total_degraded,
             total_used_negative_operator,
+            ranking_score_threshold,
         } = other;
 
         if self.timestamp.is_none() {
@@ -843,6 +865,9 @@ 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;
@@ -865,6 +890,7 @@ 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;
@@ -900,6 +926,7 @@ 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> {
@@ -912,6 +939,7 @@ 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,
@@ -920,6 +948,7 @@ impl SearchAggregator {
             attributes_to_search_on_total_number_of_uses,
             max_terms_number,
             max_vector_size,
+            retrieve_vectors,
             matching_strategy,
             max_limit,
             max_offset,
@@ -941,6 +970,7 @@ impl SearchAggregator {
             hybrid,
             total_degraded,
             total_used_negative_operator,
+            ranking_score_threshold,
         } = self;
 
         if total_received == 0 {
@@ -967,6 +997,7 @@ 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,
@@ -981,6 +1012,7 @@ impl SearchAggregator {
                 },
                 "vector": {
                     "max_vector_size": max_vector_size,
+                    "retrieve_vectors": retrieve_vectors,
                 },
                 "hybrid": {
                     "enabled": hybrid,
@@ -1011,6 +1043,7 @@ impl SearchAggregator {
                 "scoring": {
                     "show_ranking_score": show_ranking_score,
                     "show_ranking_score_details": show_ranking_score_details,
+                    "ranking_score_threshold": ranking_score_threshold,
                 },
             });
 
@@ -1068,6 +1101,7 @@ impl MultiSearchAggregator {
                     page: _,
                     hits_per_page: _,
                     attributes_to_retrieve: _,
+                    retrieve_vectors: _,
                     attributes_to_crop: _,
                     crop_length: _,
                     attributes_to_highlight: _,
@@ -1076,6 +1110,7 @@ impl MultiSearchAggregator {
                     show_matches_position: _,
                     filter: _,
                     sort: _,
+                    distinct: _,
                     facets: _,
                     highlight_pre_tag: _,
                     highlight_post_tag: _,
@@ -1083,6 +1118,7 @@ impl MultiSearchAggregator {
                     matching_strategy: _,
                     attributes_to_search_on: _,
                     hybrid: _,
+                    ranking_score_threshold: _,
                 } = query;
 
                 index_uid.as_str()
@@ -1230,6 +1266,7 @@ impl FacetSearchAggregator {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
+            ranking_score_threshold,
         } = query;
 
         let mut ret = Self::default();
@@ -1244,7 +1281,8 @@ 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
     }
@@ -1503,176 +1541,6 @@ impl DocumentsDeletionAggregator {
     }
 }
 
-#[derive(Default, Serialize)]
-pub struct TasksAggregator {
-    #[serde(skip)]
-    timestamp: Option<OffsetDateTime>,
-
-    // context
-    #[serde(rename = "user-agent")]
-    user_agents: HashSet<String>,
-
-    filtered_by_uid: bool,
-    filtered_by_index_uid: bool,
-    filtered_by_type: bool,
-    filtered_by_status: bool,
-    filtered_by_canceled_by: bool,
-    filtered_by_before_enqueued_at: bool,
-    filtered_by_after_enqueued_at: bool,
-    filtered_by_before_started_at: bool,
-    filtered_by_after_started_at: bool,
-    filtered_by_before_finished_at: bool,
-    filtered_by_after_finished_at: bool,
-    total_received: usize,
-}
-
-impl TasksAggregator {
-    pub fn from_query(query: &TasksFilterQuery, request: &HttpRequest) -> Self {
-        let TasksFilterQuery {
-            limit: _,
-            from: _,
-            uids,
-            index_uids,
-            types,
-            statuses,
-            canceled_by,
-            before_enqueued_at,
-            after_enqueued_at,
-            before_started_at,
-            after_started_at,
-            before_finished_at,
-            after_finished_at,
-        } = query;
-
-        Self {
-            timestamp: Some(OffsetDateTime::now_utc()),
-            user_agents: extract_user_agents(request).into_iter().collect(),
-            filtered_by_uid: uids.is_some(),
-            filtered_by_index_uid: index_uids.is_some(),
-            filtered_by_type: types.is_some(),
-            filtered_by_status: statuses.is_some(),
-            filtered_by_canceled_by: canceled_by.is_some(),
-            filtered_by_before_enqueued_at: before_enqueued_at.is_some(),
-            filtered_by_after_enqueued_at: after_enqueued_at.is_some(),
-            filtered_by_before_started_at: before_started_at.is_some(),
-            filtered_by_after_started_at: after_started_at.is_some(),
-            filtered_by_before_finished_at: before_finished_at.is_some(),
-            filtered_by_after_finished_at: after_finished_at.is_some(),
-            total_received: 1,
-        }
-    }
-
-    /// Aggregate one [TasksAggregator] into another.
-    pub fn aggregate(&mut self, other: Self) {
-        let Self {
-            timestamp,
-            user_agents,
-            total_received,
-            filtered_by_uid,
-            filtered_by_index_uid,
-            filtered_by_type,
-            filtered_by_status,
-            filtered_by_canceled_by,
-            filtered_by_before_enqueued_at,
-            filtered_by_after_enqueued_at,
-            filtered_by_before_started_at,
-            filtered_by_after_started_at,
-            filtered_by_before_finished_at,
-            filtered_by_after_finished_at,
-        } = other;
-
-        if self.timestamp.is_none() {
-            self.timestamp = timestamp;
-        }
-
-        // we can't create a union because there is no `into_union` method
-        for user_agent in user_agents {
-            self.user_agents.insert(user_agent);
-        }
-
-        self.filtered_by_uid |= filtered_by_uid;
-        self.filtered_by_index_uid |= filtered_by_index_uid;
-        self.filtered_by_type |= filtered_by_type;
-        self.filtered_by_status |= filtered_by_status;
-        self.filtered_by_canceled_by |= filtered_by_canceled_by;
-        self.filtered_by_before_enqueued_at |= filtered_by_before_enqueued_at;
-        self.filtered_by_after_enqueued_at |= filtered_by_after_enqueued_at;
-        self.filtered_by_before_started_at |= filtered_by_before_started_at;
-        self.filtered_by_after_started_at |= filtered_by_after_started_at;
-        self.filtered_by_before_finished_at |= filtered_by_before_finished_at;
-        self.filtered_by_after_finished_at |= filtered_by_after_finished_at;
-        self.filtered_by_after_finished_at |= filtered_by_after_finished_at;
-
-        self.total_received = self.total_received.saturating_add(total_received);
-    }
-
-    pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
-        // if we had no timestamp it means we never encountered any events and
-        // thus we don't need to send this event.
-        let timestamp = self.timestamp?;
-
-        Some(Track {
-            timestamp: Some(timestamp),
-            user: user.clone(),
-            event: event_name.to_string(),
-            properties: serde_json::to_value(self).ok()?,
-            ..Default::default()
-        })
-    }
-}
-
-#[derive(Default, Serialize)]
-pub struct HealthAggregator {
-    #[serde(skip)]
-    timestamp: Option<OffsetDateTime>,
-
-    // context
-    #[serde(rename = "user-agent")]
-    user_agents: HashSet<String>,
-
-    #[serde(rename = "requests.total_received")]
-    total_received: usize,
-}
-
-impl HealthAggregator {
-    pub fn from_query(request: &HttpRequest) -> Self {
-        Self {
-            timestamp: Some(OffsetDateTime::now_utc()),
-            user_agents: extract_user_agents(request).into_iter().collect(),
-            total_received: 1,
-        }
-    }
-
-    /// Aggregate one [HealthAggregator] into another.
-    pub fn aggregate(&mut self, other: Self) {
-        let Self { timestamp, user_agents, total_received } = other;
-
-        if self.timestamp.is_none() {
-            self.timestamp = timestamp;
-        }
-
-        // we can't create a union because there is no `into_union` method
-        for user_agent in user_agents {
-            self.user_agents.insert(user_agent);
-        }
-        self.total_received = self.total_received.saturating_add(total_received);
-    }
-
-    pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
-        // if we had no timestamp it means we never encountered any events and
-        // thus we don't need to send this event.
-        let timestamp = self.timestamp?;
-
-        Some(Track {
-            timestamp: Some(timestamp),
-            user: user.clone(),
-            event: event_name.to_string(),
-            properties: serde_json::to_value(self).ok()?,
-            ..Default::default()
-        })
-    }
-}
-
 #[derive(Default, Serialize)]
 pub struct DocumentsFetchAggregator {
     #[serde(skip)]
@@ -1690,6 +1558,9 @@ 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,
@@ -1699,18 +1570,21 @@ pub struct DocumentsFetchAggregator {
 
 impl DocumentsFetchAggregator {
     pub fn from_query(query: &DocumentFetchKind, request: &HttpRequest) -> Self {
-        let (limit, offset) = match query {
-            DocumentFetchKind::PerDocumentId => (1, 0),
-            DocumentFetchKind::Normal { limit, offset, .. } => (*limit, *offset),
+        let (limit, offset, retrieve_vectors) = match query {
+            DocumentFetchKind::PerDocumentId { retrieve_vectors } => (1, 0, *retrieve_vectors),
+            DocumentFetchKind::Normal { limit, offset, retrieve_vectors, .. } => {
+                (*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,
         }
     }
 
@@ -1724,6 +1598,7 @@ impl DocumentsFetchAggregator {
             per_filter,
             max_limit,
             max_offset,
+            retrieve_vectors,
         } = other;
 
         if self.timestamp.is_none() {
@@ -1739,6 +1614,8 @@ 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> {
@@ -1755,3 +1632,251 @@ impl DocumentsFetchAggregator {
         })
     }
 }
+
+#[derive(Default)]
+pub struct SimilarAggregator {
+    timestamp: Option<OffsetDateTime>,
+
+    // context
+    user_agents: HashSet<String>,
+
+    // requests
+    total_received: usize,
+    total_succeeded: usize,
+    time_spent: BinaryHeap<usize>,
+
+    // filter
+    filter_with_geo_radius: bool,
+    filter_with_geo_bounding_box: bool,
+    // every time a request has a filter, this field must be incremented by the number of terms it contains
+    filter_sum_of_criteria_terms: usize,
+    // every time a request has a filter, this field must be incremented by one
+    filter_total_number_of_criteria: usize,
+    used_syntax: HashMap<String, usize>,
+
+    // Whether a non-default embedder was specified
+    embedder: bool,
+    retrieve_vectors: bool,
+
+    // pagination
+    max_limit: usize,
+    max_offset: usize,
+
+    // formatting
+    max_attributes_to_retrieve: usize,
+
+    // scoring
+    show_ranking_score: bool,
+    show_ranking_score_details: bool,
+    ranking_score_threshold: bool,
+}
+
+impl SimilarAggregator {
+    #[allow(clippy::field_reassign_with_default)]
+    pub fn from_query(query: &SimilarQuery, request: &HttpRequest) -> Self {
+        let SimilarQuery {
+            id: _,
+            embedder,
+            offset,
+            limit,
+            attributes_to_retrieve: _,
+            retrieve_vectors,
+            show_ranking_score,
+            show_ranking_score_details,
+            filter,
+            ranking_score_threshold,
+        } = query;
+
+        let mut ret = Self::default();
+        ret.timestamp = Some(OffsetDateTime::now_utc());
+
+        ret.total_received = 1;
+        ret.user_agents = extract_user_agents(request).into_iter().collect();
+
+        if let Some(ref filter) = filter {
+            static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
+            ret.filter_total_number_of_criteria = 1;
+
+            let syntax = match filter {
+                Value::String(_) => "string".to_string(),
+                Value::Array(values) => {
+                    if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
+                        "mixed".to_string()
+                    } else {
+                        "array".to_string()
+                    }
+                }
+                _ => "none".to_string(),
+            };
+            // convert the string to a HashMap
+            ret.used_syntax.insert(syntax, 1);
+
+            let stringified_filters = filter.to_string();
+            ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
+            ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
+            ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
+        }
+
+        ret.max_limit = *limit;
+        ret.max_offset = *offset;
+
+        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
+    }
+
+    pub fn succeed(&mut self, result: &SimilarResult) {
+        let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
+
+        self.total_succeeded = self.total_succeeded.saturating_add(1);
+
+        self.time_spent.push(*processing_time_ms as usize);
+    }
+
+    /// Aggregate one [SimilarAggregator] into another.
+    pub fn aggregate(&mut self, mut other: Self) {
+        let Self {
+            timestamp,
+            user_agents,
+            total_received,
+            total_succeeded,
+            ref mut time_spent,
+            filter_with_geo_radius,
+            filter_with_geo_bounding_box,
+            filter_sum_of_criteria_terms,
+            filter_total_number_of_criteria,
+            used_syntax,
+            max_limit,
+            max_offset,
+            max_attributes_to_retrieve,
+            show_ranking_score,
+            show_ranking_score_details,
+            embedder,
+            ranking_score_threshold,
+            retrieve_vectors,
+        } = other;
+
+        if self.timestamp.is_none() {
+            self.timestamp = timestamp;
+        }
+
+        // context
+        for user_agent in user_agents.into_iter() {
+            self.user_agents.insert(user_agent);
+        }
+
+        // request
+        self.total_received = self.total_received.saturating_add(total_received);
+        self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
+        self.time_spent.append(time_spent);
+
+        // filter
+        self.filter_with_geo_radius |= filter_with_geo_radius;
+        self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
+        self.filter_sum_of_criteria_terms =
+            self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
+        self.filter_total_number_of_criteria =
+            self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
+        for (key, value) in used_syntax.into_iter() {
+            let used_syntax = self.used_syntax.entry(key).or_insert(0);
+            *used_syntax = used_syntax.saturating_add(value);
+        }
+
+        self.embedder |= embedder;
+        self.retrieve_vectors |= retrieve_vectors;
+
+        // pagination
+        self.max_limit = self.max_limit.max(max_limit);
+        self.max_offset = self.max_offset.max(max_offset);
+
+        // formatting
+        self.max_attributes_to_retrieve =
+            self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
+
+        // 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> {
+        let Self {
+            timestamp,
+            user_agents,
+            total_received,
+            total_succeeded,
+            time_spent,
+            filter_with_geo_radius,
+            filter_with_geo_bounding_box,
+            filter_sum_of_criteria_terms,
+            filter_total_number_of_criteria,
+            used_syntax,
+            max_limit,
+            max_offset,
+            max_attributes_to_retrieve,
+            show_ranking_score,
+            show_ranking_score_details,
+            embedder,
+            ranking_score_threshold,
+            retrieve_vectors,
+        } = self;
+
+        if total_received == 0 {
+            None
+        } else {
+            // we get all the values in a sorted manner
+            let time_spent = time_spent.into_sorted_vec();
+            // the index of the 99th percentage of value
+            let percentile_99th = time_spent.len() * 99 / 100;
+            // We are only interested by the slowest value of the 99th fastest results
+            let time_spent = time_spent.get(percentile_99th);
+
+            let properties = json!({
+                "user-agent": user_agents,
+                "requests": {
+                    "99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
+                    "total_succeeded": total_succeeded,
+                    "total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
+                    "total_received": total_received,
+                },
+                "filter": {
+                   "with_geoRadius": filter_with_geo_radius,
+                   "with_geoBoundingBox": filter_with_geo_bounding_box,
+                   "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,
+                },
+                "pagination": {
+                   "max_limit": max_limit,
+                   "max_offset": max_offset,
+                },
+                "formatting": {
+                    "max_attributes_to_retrieve": max_attributes_to_retrieve,
+                },
+                "scoring": {
+                    "show_ranking_score": show_ranking_score,
+                    "show_ranking_score_details": show_ranking_score_details,
+                    "ranking_score_threshold": ranking_score_threshold,
+                },
+            });
+
+            Some(Track {
+                timestamp,
+                user: user.clone(),
+                event: event_name.to_string(),
+                properties,
+                ..Default::default()
+            })
+        }
+    }
+}

meilisearch/src/lib.rs

@@ -311,6 +311,7 @@ fn open_or_create_database_unchecked(
             index_growth_amount: byte_unit::Byte::from_str("10GiB").unwrap().get_bytes() as usize,
             index_count: DEFAULT_INDEX_COUNT,
             instance_features,
+            compute_prefix_databases: !opt.experimental_disable_prefix_db,
         })?)
     };
 

meilisearch/src/middleware.rs

@@ -59,10 +59,12 @@ where
             let request_path = req.path();
             let is_registered_resource = req.resource_map().has_resource(request_path);
             if is_registered_resource {
+                let request_pattern = req.match_pattern();
+                let metric_path = request_pattern.as_ref().map_or(request_path, String::as_str);
                 let request_method = req.method().to_string();
                 histogram_timer = Some(
                     crate::metrics::MEILISEARCH_HTTP_RESPONSE_TIME_SECONDS
-                        .with_label_values(&[&request_method, request_path])
+                        .with_label_values(&[&request_method, metric_path])
                         .start_timer(),
                 );
             }

meilisearch/src/option.rs

@@ -13,6 +13,7 @@ use byte_unit::{Byte, ByteError};
 use clap::Parser;
 use meilisearch_types::features::InstanceTogglableFeatures;
 use meilisearch_types::milli::update::IndexerConfig;
+use meilisearch_types::milli::ThreadPoolNoAbortBuilder;
 use rustls::server::{
     AllowAnyAnonymousOrAuthenticatedClient, AllowAnyAuthenticatedClient, ServerSessionMemoryCache,
 };
@@ -59,6 +60,7 @@ const MEILI_EXPERIMENTAL_REDUCE_INDEXING_MEMORY_USAGE: &str =
     "MEILI_EXPERIMENTAL_REDUCE_INDEXING_MEMORY_USAGE";
 const MEILI_EXPERIMENTAL_MAX_NUMBER_OF_BATCHED_TASKS: &str =
     "MEILI_EXPERIMENTAL_MAX_NUMBER_OF_BATCHED_TASKS";
+const MEILI_EXPERIMENTAL_DISABLE_PREFIX_DB: &str = "MEILI_EXPERIMENTAL_DISABLE_PREFIXDB";
 
 const DEFAULT_CONFIG_FILE_PATH: &str = "./config.toml";
 const DEFAULT_DB_PATH: &str = "./data.ms";
@@ -388,6 +390,11 @@ pub struct Opt {
     #[serde(default = "default_limit_batched_tasks")]
     pub experimental_max_number_of_batched_tasks: usize,
 
+    /// Experimentally disable the prefix database, see: <https://github.com/orgs/meilisearch/discussions>
+    #[clap(long, env = MEILI_EXPERIMENTAL_DISABLE_PREFIX_DB)]
+    #[serde(default)]
+    pub experimental_disable_prefix_db: bool,
+
     #[serde(flatten)]
     #[clap(flatten)]
     pub indexer_options: IndexerOpts,
@@ -488,6 +495,7 @@ impl Opt {
             experimental_enable_logs_route,
             experimental_replication_parameters,
             experimental_reduce_indexing_memory_usage,
+            experimental_disable_prefix_db,
         } = self;
         export_to_env_if_not_present(MEILI_DB_PATH, db_path);
         export_to_env_if_not_present(MEILI_HTTP_ADDR, http_addr);
@@ -517,6 +525,10 @@ impl Opt {
             MEILI_EXPERIMENTAL_MAX_NUMBER_OF_BATCHED_TASKS,
             experimental_max_number_of_batched_tasks.to_string(),
         );
+        export_to_env_if_not_present(
+            MEILI_EXPERIMENTAL_DISABLE_PREFIX_DB,
+            experimental_disable_prefix_db.to_string(),
+        );
         if let Some(ssl_cert_path) = ssl_cert_path {
             export_to_env_if_not_present(MEILI_SSL_CERT_PATH, ssl_cert_path);
         }
@@ -666,7 +678,7 @@ impl TryFrom<&IndexerOpts> for IndexerConfig {
     type Error = anyhow::Error;
 
     fn try_from(other: &IndexerOpts) -> Result<Self, Self::Error> {
-        let thread_pool = rayon::ThreadPoolBuilder::new()
+        let thread_pool = ThreadPoolNoAbortBuilder::new()
             .thread_name(|index| format!("indexing-thread:{index}"))
             .num_threads(*other.max_indexing_threads)
             .build()?;

meilisearch/src/routes/features.rs

@@ -47,8 +47,6 @@ pub struct RuntimeTogglableFeatures {
     pub metrics: Option<bool>,
     #[deserr(default)]
     pub logs_route: Option<bool>,
-    #[deserr(default)]
-    pub export_puffin_reports: Option<bool>,
 }
 
 async fn patch_features(
@@ -68,21 +66,13 @@ async fn patch_features(
         vector_store: new_features.0.vector_store.unwrap_or(old_features.vector_store),
         metrics: new_features.0.metrics.unwrap_or(old_features.metrics),
         logs_route: new_features.0.logs_route.unwrap_or(old_features.logs_route),
-        export_puffin_reports: new_features
-            .0
-            .export_puffin_reports
-            .unwrap_or(old_features.export_puffin_reports),
     };
 
     // explicitly destructure for analytics rather than using the `Serialize` implementation, because
     // the it renames to camelCase, which we don't want for analytics.
     // **Do not** ignore fields with `..` or `_` here, because we want to add them in the future.
-    let meilisearch_types::features::RuntimeTogglableFeatures {
-        vector_store,
-        metrics,
-        logs_route,
-        export_puffin_reports,
-    } = new_features;
+    let meilisearch_types::features::RuntimeTogglableFeatures { vector_store, metrics, logs_route } =
+        new_features;
 
     analytics.publish(
         "Experimental features Updated".to_string(),
@@ -90,7 +80,6 @@ async fn patch_features(
             "vector_store": vector_store,
             "metrics": metrics,
             "logs_route": logs_route,
-            "export_puffin_reports": export_puffin_reports,
         }),
         Some(&req),
     );

meilisearch/src/routes/indexes/documents.rs

@@ -16,6 +16,7 @@ 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;
@@ -39,7 +40,7 @@ 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;
+use crate::search::{parse_filter, RetrieveVectors};
 use crate::Opt;
 
 static ACCEPTED_CONTENT_TYPE: Lazy<Vec<String>> = Lazy::new(|| {
@@ -94,6 +95,8 @@ 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(
@@ -107,13 +110,20 @@ pub async fn get_document(
     debug!(parameters = ?params, "Get document");
     let index_uid = IndexUid::try_from(index_uid)?;
 
-    analytics.get_fetch_documents(&DocumentFetchKind::PerDocumentId, &req);
-
-    let GetDocument { fields } = params.into_inner();
+    let GetDocument { fields, retrieve_vectors: param_retrieve_vectors } = 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 = retrieve_document(&index, &document_id, attributes_to_retrieve)?;
+    let document =
+        retrieve_document(&index, &document_id, attributes_to_retrieve, retrieve_vectors)?;
     debug!(returns = ?document, "Get document");
     Ok(HttpResponse::Ok().json(document))
 }
@@ -153,6 +163,8 @@ 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>,
 }
@@ -166,6 +178,8 @@ 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>,
 }
@@ -185,6 +199,7 @@ 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,
     );
@@ -201,7 +216,7 @@ pub async fn get_documents(
 ) -> Result<HttpResponse, ResponseError> {
     debug!(parameters = ?params, "Get documents GET");
 
-    let BrowseQueryGet { limit, offset, fields, filter } = params.into_inner();
+    let BrowseQueryGet { limit, offset, fields, retrieve_vectors, filter } = params.into_inner();
 
     let filter = match filter {
         Some(f) => match serde_json::from_str(&f) {
@@ -215,6 +230,7 @@ pub async fn get_documents(
         offset: offset.0,
         limit: limit.0,
         fields: fields.merge_star_and_none(),
+        retrieve_vectors: retrieve_vectors.0,
         filter,
     };
 
@@ -223,6 +239,7 @@ pub async fn get_documents(
             with_filter: query.filter.is_some(),
             limit: query.limit,
             offset: query.offset,
+            retrieve_vectors: query.retrieve_vectors,
         },
         &req,
     );
@@ -236,10 +253,14 @@ fn documents_by_query(
     query: BrowseQuery,
 ) -> Result<HttpResponse, ResponseError> {
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
-    let BrowseQuery { offset, limit, fields, filter } = query;
+    let BrowseQuery { offset, limit, fields, retrieve_vectors, 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) = retrieve_documents(&index, offset, limit, filter, fields)?;
+    let (total, documents) =
+        retrieve_documents(&index, offset, limit, filter, fields, retrieve_vectors)?;
 
     let ret = PaginationView::new(offset, limit, total as usize, documents);
 
@@ -579,13 +600,44 @@ 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> {
-            Ok(milli::obkv_to_json(&all_fields, &fields_ids_map, document)?)
+        ret.map_err(ResponseError::from).and_then(|(key, document)| -> Result<_, ResponseError> {
+            let mut document = 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)
         })
     }))
 }
@@ -596,6 +648,7 @@ 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;
@@ -620,53 +673,57 @@ fn retrieve_documents<S: AsRef<str>>(
     let (it, number_of_documents) = {
         let number_of_documents = candidates.len();
         (
-            some_documents(index, &rtxn, candidates.into_iter().skip(offset).take(limit))?,
+            some_documents(
+                index,
+                &rtxn,
+                candidates.into_iter().skip(offset).take(limit),
+                retrieve_vectors,
+            )?,
             number_of_documents,
         )
     };
 
-    let documents: Result<Vec<_>, ResponseError> = it
+    let documents: Vec<_> = 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()),
+                    attributes_to_retrieve.iter().map(|s| s.as_ref()).chain(
+                        (retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors"),
+                    ),
                 ),
                 None => document?,
             })
         })
-        .collect();
+        .collect::<Result<_, ResponseError>>()?;
 
-    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 = index
-        .documents(&txn, std::iter::once(internal_id))?
-        .into_iter()
+    let document = some_documents(index, &txn, Some(internal_id), retrieve_vectors)?
         .next()
-        .map(|(_, d)| d)
-        .ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))?;
+        .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.iter().map(|s| s.as_ref()),
+            attributes_to_retrieve
+                .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, SearchQuery,
-    DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
+    add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
+    SearchQuery, 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;
@@ -46,6 +46,8 @@ 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(
@@ -69,7 +71,7 @@ pub async fn search(
 
     // Tenant token search_rules.
     if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
-        add_search_rules(&mut search_query, search_rules);
+        add_search_rules(&mut search_query.filter, search_rules);
     }
 
     let index = index_scheduler.index(&index_uid)?;
@@ -103,6 +105,7 @@ impl From<FacetSearchQuery> for SearchQuery {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
+            ranking_score_threshold,
         } = value;
 
         SearchQuery {
@@ -112,6 +115,7 @@ 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,
@@ -120,6 +124,7 @@ 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(),
@@ -128,6 +133,7 @@ impl From<FacetSearchQuery> for SearchQuery {
             vector,
             attributes_to_search_on,
             hybrid,
+            ranking_score_threshold,
         }
     }
 }

meilisearch/src/routes/indexes/mod.rs

@@ -29,6 +29,7 @@ pub mod documents;
 pub mod facet_search;
 pub mod search;
 pub mod settings;
+pub mod similar;
 
 pub fn configure(cfg: &mut web::ServiceConfig) {
     cfg.service(
@@ -48,6 +49,7 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
             .service(web::scope("/documents").configure(documents::configure))
             .service(web::scope("/search").configure(search::configure))
             .service(web::scope("/facet-search").configure(facet_search::configure))
+            .service(web::scope("/similar").configure(similar::configure))
             .service(web::scope("/settings").configure(settings::configure)),
     );
 }
@@ -269,12 +271,8 @@ impl From<index_scheduler::IndexStats> for IndexStats {
 pub async fn get_index_stats(
     index_scheduler: GuardedData<ActionPolicy<{ actions::STATS_GET }>, Data<IndexScheduler>>,
     index_uid: web::Path<String>,
-    req: HttpRequest,
-    analytics: web::Data<dyn Analytics>,
 ) -> Result<HttpResponse, ResponseError> {
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
-    analytics.publish("Stats Seen".to_string(), json!({ "per_index_uid": true }), Some(&req));
-
     let stats = IndexStats::from(index_scheduler.index_stats(&index_uid)?);
 
     debug!(returns = ?stats, "Get index stats");

meilisearch/src/routes/indexes/search.rs

@@ -19,9 +19,10 @@ 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, SearchKind, SearchQuery,
-    SemanticRatio, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
+    add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
+    RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,
+    DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
+    DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
 };
 use crate::search_queue::SearchQueue;
 
@@ -50,6 +51,8 @@ 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>)]
@@ -60,6 +63,8 @@ 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>)]
@@ -82,6 +87,21 @@ 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)]
@@ -137,11 +157,13 @@ 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,
@@ -152,6 +174,7 @@ 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),
         }
     }
 }
@@ -196,7 +219,7 @@ pub async fn search_with_url_query(
 
     // Tenant token search_rules.
     if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
-        add_search_rules(&mut query, search_rules);
+        add_search_rules(&mut query.filter, search_rules);
     }
 
     let mut aggregate = SearchAggregator::from_query(&query, &req);
@@ -205,10 +228,12 @@ 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 || perform_search(&index, query, search_kind)).await?;
+    let search_result = tokio::task::spawn_blocking(move || {
+        perform_search(&index, query, search_kind, retrieve_vector)
+    })
+    .await?;
     if let Ok(ref search_result) = search_result {
         aggregate.succeed(search_result);
     }
@@ -235,7 +260,7 @@ pub async fn search_with_post(
 
     // Tenant token search_rules.
     if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
-        add_search_rules(&mut query, search_rules);
+        add_search_rules(&mut query.filter, search_rules);
     }
 
     let mut aggregate = SearchAggregator::from_query(&query, &req);
@@ -245,10 +270,13 @@ 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 || perform_search(&index, query, search_kind)).await?;
+    let search_result = tokio::task::spawn_blocking(move || {
+        perform_search(&index, query, search_kind, retrieve_vectors)
+    })
+    .await?;
     if let Ok(ref search_result) = search_result {
         aggregate.succeed(search_result);
         if search_result.degraded {
@@ -270,11 +298,10 @@ pub fn search_kind(
     features: RoFeatures,
 ) -> Result<SearchKind, ResponseError> {
     if query.vector.is_some() {
-        features.check_vector("Passing `vector` as a query parameter")?;
+        features.check_vector("Passing `vector` as a parameter")?;
     }
-
     if query.hybrid.is_some() {
-        features.check_vector("Passing `hybrid` as a query parameter")?;
+        features.check_vector("Passing `hybrid` as a 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/settings.rs

@@ -137,10 +137,8 @@ macro_rules! make_setting_route {
                 let settings = settings(&index, &rtxn, meilisearch_types::settings::SecretPolicy::HideSecrets)?;
 
                 debug!(returns = ?settings, "Update settings");
-                let mut json = serde_json::json!(&settings);
-                let val = json[$camelcase_attr].take();
 
-                Ok(HttpResponse::Ok().json(val))
+                Ok(HttpResponse::Ok().json(settings.$attr))
             }
 
             pub fn resources() -> Resource {

meilisearch/src/routes/indexes/similar.rs

@@ -0,0 +1,192 @@
+use actix_web::web::{self, Data};
+use actix_web::{HttpRequest, HttpResponse};
+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::{ErrorCode as _, ResponseError};
+use meilisearch_types::index_uid::IndexUid;
+use meilisearch_types::keys::actions;
+use meilisearch_types::serde_cs::vec::CS;
+use serde_json::Value;
+use tracing::debug;
+
+use super::ActionPolicy;
+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,
+    SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
+};
+
+pub fn configure(cfg: &mut web::ServiceConfig) {
+    cfg.service(
+        web::resource("")
+            .route(web::get().to(SeqHandler(similar_get)))
+            .route(web::post().to(SeqHandler(similar_post))),
+    );
+}
+
+pub async fn similar_get(
+    index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
+    index_uid: web::Path<String>,
+    params: AwebQueryParameter<SimilarQueryGet, DeserrQueryParamError>,
+    req: HttpRequest,
+    analytics: web::Data<dyn Analytics>,
+) -> Result<HttpResponse, ResponseError> {
+    let index_uid = IndexUid::try_from(index_uid.into_inner())?;
+
+    let query = params.0.try_into()?;
+
+    let mut aggregate = SimilarAggregator::from_query(&query, &req);
+
+    debug!(parameters = ?query, "Similar get");
+
+    let similar = similar(index_scheduler, index_uid, query).await;
+
+    if let Ok(similar) = &similar {
+        aggregate.succeed(similar);
+    }
+    analytics.get_similar(aggregate);
+
+    let similar = similar?;
+
+    debug!(returns = ?similar, "Similar get");
+    Ok(HttpResponse::Ok().json(similar))
+}
+
+pub async fn similar_post(
+    index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
+    index_uid: web::Path<String>,
+    params: AwebJson<SimilarQuery, DeserrJsonError>,
+    req: HttpRequest,
+    analytics: web::Data<dyn Analytics>,
+) -> Result<HttpResponse, ResponseError> {
+    let index_uid = IndexUid::try_from(index_uid.into_inner())?;
+
+    let query = params.into_inner();
+    debug!(parameters = ?query, "Similar post");
+
+    let mut aggregate = SimilarAggregator::from_query(&query, &req);
+
+    let similar = similar(index_scheduler, index_uid, query).await;
+
+    if let Ok(similar) = &similar {
+        aggregate.succeed(similar);
+    }
+    analytics.post_similar(aggregate);
+
+    let similar = similar?;
+
+    debug!(returns = ?similar, "Similar post");
+    Ok(HttpResponse::Ok().json(similar))
+}
+
+async fn similar(
+    index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
+    index_uid: IndexUid,
+    mut query: SimilarQuery,
+) -> Result<SimilarResult, ResponseError> {
+    let features = index_scheduler.features();
+
+    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);
+    }
+
+    let index = index_scheduler.index(&index_uid)?;
+
+    let (embedder_name, embedder) =
+        SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
+
+    tokio::task::spawn_blocking(move || {
+        perform_similar(&index, query, embedder_name, embedder, retrieve_vectors)
+    })
+    .await?
+}
+
+#[derive(Debug, deserr::Deserr)]
+#[deserr(error = DeserrQueryParamError, rename_all = camelCase, deny_unknown_fields)]
+pub struct SimilarQueryGet {
+    #[deserr(error = DeserrQueryParamError<InvalidSimilarId>)]
+    id: Param<String>,
+    #[deserr(default = Param(DEFAULT_SEARCH_OFFSET()), error = DeserrQueryParamError<InvalidSimilarOffset>)]
+    offset: Param<usize>,
+    #[deserr(default = Param(DEFAULT_SEARCH_LIMIT()), error = DeserrQueryParamError<InvalidSimilarLimit>)]
+    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;
+
+    fn try_from(
+        SimilarQueryGet {
+            id,
+            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 {
+            Some(f) => match serde_json::from_str(&f) {
+                Ok(v) => Some(v),
+                _ => Some(Value::String(f)),
+            },
+            None => None,
+        };
+
+        Ok(SimilarQuery {
+            id: id.0.try_into().map_err(|code: InvalidSimilarId| {
+                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/mod.rs

@@ -8,11 +8,9 @@ use meilisearch_types::error::{Code, ResponseError};
 use meilisearch_types::settings::{Settings, Unchecked};
 use meilisearch_types::tasks::{Kind, Status, Task, TaskId};
 use serde::{Deserialize, Serialize};
-use serde_json::json;
 use time::OffsetDateTime;
 use tracing::debug;
 
-use crate::analytics::Analytics;
 use crate::extractors::authentication::policies::*;
 use crate::extractors::authentication::GuardedData;
 use crate::search_queue::SearchQueue;
@@ -296,10 +294,7 @@ pub struct Stats {
 async fn get_stats(
     index_scheduler: GuardedData<ActionPolicy<{ actions::STATS_GET }>, Data<IndexScheduler>>,
     auth_controller: GuardedData<ActionPolicy<{ actions::STATS_GET }>, Data<AuthController>>,
-    req: HttpRequest,
-    analytics: web::Data<dyn Analytics>,
 ) -> Result<HttpResponse, ResponseError> {
-    analytics.publish("Stats Seen".to_string(), json!({ "per_index_uid": false }), Some(&req));
     let filters = index_scheduler.filters();
 
     let stats = create_all_stats((*index_scheduler).clone(), (*auth_controller).clone(), filters)?;
@@ -355,11 +350,7 @@ struct VersionResponse {
 
 async fn get_version(
     _index_scheduler: GuardedData<ActionPolicy<{ actions::VERSION }>, Data<IndexScheduler>>,
-    req: HttpRequest,
-    analytics: web::Data<dyn Analytics>,
 ) -> HttpResponse {
-    analytics.publish("Version Seen".to_string(), json!(null), Some(&req));
-
     let build_info = build_info::BuildInfo::from_build();
 
     HttpResponse::Ok().json(VersionResponse {
@@ -376,21 +367,11 @@ async fn get_version(
     })
 }
 
-#[derive(Serialize)]
-struct KeysResponse {
-    private: Option<String>,
-    public: Option<String>,
-}
-
 pub async fn get_health(
-    req: HttpRequest,
     index_scheduler: Data<IndexScheduler>,
     auth_controller: Data<AuthController>,
     search_queue: Data<SearchQueue>,
-    analytics: web::Data<dyn Analytics>,
 ) -> Result<HttpResponse, ResponseError> {
-    analytics.health_seen(&req);
-
     search_queue.health().unwrap();
     index_scheduler.health().unwrap();
     auth_controller.health().unwrap();

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, SearchQueryWithIndex, SearchResultWithIndex,
+    add_search_rules, perform_search, RetrieveVectors, SearchQueryWithIndex, SearchResultWithIndex,
 };
 use crate::search_queue::SearchQueue;
 
@@ -67,7 +67,7 @@ pub async fn multi_search_with_post(
             // Apply search rules from tenant token
             if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid)
             {
-                add_search_rules(&mut query, search_rules);
+                add_search_rules(&mut query.filter, search_rules);
             }
 
             let index = index_scheduler
@@ -83,11 +83,14 @@ 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 || perform_search(&index, query, search_kind))
-                    .await
-                    .with_index(query_index)?;
+            let search_result = tokio::task::spawn_blocking(move || {
+                perform_search(&index, query, search_kind, retrieve_vector)
+            })
+            .await
+            .with_index(query_index)?;
 
             search_results.push(SearchResultWithIndex {
                 index_uid: index_uid.into_inner(),

meilisearch/src/routes/tasks.rs

@@ -270,12 +270,8 @@ pub struct AllTasks {
 async fn get_tasks(
     index_scheduler: GuardedData<ActionPolicy<{ actions::TASKS_GET }>, Data<IndexScheduler>>,
     params: AwebQueryParameter<TasksFilterQuery, DeserrQueryParamError>,
-    req: HttpRequest,
-    analytics: web::Data<dyn Analytics>,
 ) -> Result<HttpResponse, ResponseError> {
     let mut params = params.into_inner();
-    analytics.get_tasks(&params, &req);
-
     // We +1 just to know if there is more after this "page" or not.
     params.limit.0 = params.limit.0.saturating_add(1);
     let limit = params.limit.0;
@@ -298,8 +294,6 @@ async fn get_tasks(
 async fn get_task(
     index_scheduler: GuardedData<ActionPolicy<{ actions::TASKS_GET }>, Data<IndexScheduler>>,
     task_uid: web::Path<String>,
-    req: HttpRequest,
-    analytics: web::Data<dyn Analytics>,
 ) -> Result<HttpResponse, ResponseError> {
     let task_uid_string = task_uid.into_inner();
 
@@ -310,8 +304,6 @@ async fn get_task(
         }
     };
 
-    analytics.publish("Tasks Seen".to_string(), json!({ "per_task_uid": true }), Some(&req));
-
     let query = index_scheduler::Query { uids: Some(vec![task_uid]), ..Query::default() };
     let filters = index_scheduler.filters();
     let (tasks, _) = index_scheduler.get_tasks_from_authorized_indexes(query, filters)?;

meilisearch/src/search.rs

@@ -1,3 +1,4 @@
+use core::fmt;
 use std::cmp::min;
 use std::collections::{BTreeMap, BTreeSet, HashSet};
 use std::str::FromStr;
@@ -10,10 +11,11 @@ use indexmap::IndexMap;
 use meilisearch_auth::IndexSearchRules;
 use meilisearch_types::deserr::DeserrJsonError;
 use meilisearch_types::error::deserr_codes::*;
-use meilisearch_types::error::ResponseError;
+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;
@@ -39,7 +41,7 @@ pub const DEFAULT_HIGHLIGHT_PRE_TAG: fn() -> String = || "<em>".to_string();
 pub const DEFAULT_HIGHLIGHT_POST_TAG: fn() -> String = || "</em>".to_string();
 pub const DEFAULT_SEMANTIC_RATIO: fn() -> SemanticRatio = || SemanticRatio(0.5);
 
-#[derive(Debug, Clone, Default, PartialEq, Deserr)]
+#[derive(Clone, Default, PartialEq, Deserr)]
 #[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
 pub struct SearchQuery {
     #[deserr(default, error = DeserrJsonError<InvalidSearchQ>)]
@@ -58,6 +60,8 @@ 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())]
@@ -74,6 +78,8 @@ 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())]
@@ -86,6 +92,160 @@ 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.
+// - Only what IS used, we know everything else is set to None so there is no need to print it
+// - Re-order the most important field to debug first
+impl fmt::Debug for SearchQuery {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        let Self {
+            q,
+            vector,
+            hybrid,
+            offset,
+            limit,
+            page,
+            hits_per_page,
+            attributes_to_retrieve,
+            retrieve_vectors,
+            attributes_to_crop,
+            crop_length,
+            attributes_to_highlight,
+            show_matches_position,
+            show_ranking_score,
+            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");
+
+        // First, everything related to the number of documents to retrieve
+        debug.field("limit", &limit).field("offset", &offset);
+        if let Some(page) = page {
+            debug.field("page", &page);
+        }
+        if let Some(hits_per_page) = hits_per_page {
+            debug.field("hits_per_page", &hits_per_page);
+        }
+
+        // Then, everything related to the queries
+        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);
+            } else {
+                debug.field(
+                    "vector",
+                    &format!("[{}, {}, {}, ... {} dimensions]", v[0], v[1], v[2], v.len()),
+                );
+            }
+        }
+        if let Some(hybrid) = hybrid {
+            debug.field("hybrid", &hybrid);
+        }
+        if let Some(attributes_to_search_on) = attributes_to_search_on {
+            debug.field("attributes_to_search_on", &attributes_to_search_on);
+        }
+        if let Some(filter) = filter {
+            debug.field("filter", &filter);
+        }
+        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);
+        }
+        debug.field("matching_strategy", &matching_strategy);
+
+        // Then everything related to the formatting
+        debug.field("crop_length", &crop_length);
+        if *show_matches_position {
+            debug.field("show_matches_position", show_matches_position);
+        }
+        if *show_ranking_score {
+            debug.field("show_ranking_score", show_ranking_score);
+        }
+        if *show_ranking_score_details {
+            debug.field("self.show_ranking_score_details", show_ranking_score_details);
+        }
+        debug.field("crop_length", &crop_length);
+        if let Some(facets) = facets {
+            debug.field("facets", &facets);
+        }
+        if let Some(attributes_to_retrieve) = attributes_to_retrieve {
+            debug.field("attributes_to_retrieve", &attributes_to_retrieve);
+        }
+        if let Some(attributes_to_crop) = attributes_to_crop {
+            debug.field("attributes_to_crop", &attributes_to_crop);
+        }
+        if let Some(attributes_to_highlight) = attributes_to_highlight {
+            debug.field("attributes_to_highlight", &attributes_to_highlight);
+        }
+        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()
+    }
 }
 
 #[derive(Debug, Clone, Default, PartialEq, Deserr)]
@@ -126,7 +286,7 @@ impl SearchKind {
         Ok(Self::Hybrid { embedder_name, embedder, semantic_ratio })
     }
 
-    fn embedder(
+    pub(crate) fn embedder(
         index_scheduler: &index_scheduler::IndexScheduler,
         index: &Index,
         embedder_name: Option<&str>,
@@ -223,6 +383,8 @@ 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())]
@@ -239,6 +401,8 @@ 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())]
@@ -251,6 +415,8 @@ 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 {
@@ -264,6 +430,7 @@ impl SearchQueryWithIndex {
             page,
             hits_per_page,
             attributes_to_retrieve,
+            retrieve_vectors,
             attributes_to_crop,
             crop_length,
             attributes_to_highlight,
@@ -272,6 +439,7 @@ impl SearchQueryWithIndex {
             show_matches_position,
             filter,
             sort,
+            distinct,
             facets,
             highlight_pre_tag,
             highlight_post_tag,
@@ -279,6 +447,7 @@ impl SearchQueryWithIndex {
             matching_strategy,
             attributes_to_search_on,
             hybrid,
+            ranking_score_threshold,
         } = self;
         (
             index_uid,
@@ -290,6 +459,7 @@ impl SearchQueryWithIndex {
                 page,
                 hits_per_page,
                 attributes_to_retrieve,
+                retrieve_vectors,
                 attributes_to_crop,
                 crop_length,
                 attributes_to_highlight,
@@ -298,6 +468,7 @@ impl SearchQueryWithIndex {
                 show_matches_position,
                 filter,
                 sort,
+                distinct,
                 facets,
                 highlight_pre_tag,
                 highlight_post_tag,
@@ -305,6 +476,7 @@ 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`
             },
@@ -312,6 +484,63 @@ impl SearchQueryWithIndex {
     }
 }
 
+#[derive(Debug, Clone, PartialEq, Deserr)]
+#[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
+pub struct SimilarQuery {
+    #[deserr(error = DeserrJsonError<InvalidSimilarId>)]
+    pub id: ExternalDocumentId,
+    #[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSimilarOffset>)]
+    pub offset: usize,
+    #[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSimilarLimit>)]
+    pub limit: usize,
+    #[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
+    pub filter: Option<Value>,
+    #[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
+    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)]
+#[deserr(try_from(Value) = TryFrom::try_from -> InvalidSimilarId)]
+pub struct ExternalDocumentId(String);
+
+impl AsRef<str> for ExternalDocumentId {
+    fn as_ref(&self) -> &str {
+        &self.0
+    }
+}
+
+impl ExternalDocumentId {
+    pub fn into_inner(self) -> String {
+        self.0
+    }
+}
+
+impl TryFrom<String> for ExternalDocumentId {
+    type Error = InvalidSimilarId;
+
+    fn try_from(value: String) -> Result<Self, Self::Error> {
+        serde_json::Value::String(value).try_into()
+    }
+}
+
+impl TryFrom<Value> for ExternalDocumentId {
+    type Error = InvalidSimilarId;
+
+    fn try_from(value: Value) -> Result<Self, Self::Error> {
+        Ok(Self(milli::documents::validate_document_id_value(value).map_err(|_| InvalidSimilarId)?))
+    }
+}
+
 #[derive(Debug, Copy, Clone, PartialEq, Eq, Deserr)]
 #[deserr(rename_all = camelCase)]
 pub enum MatchingStrategy {
@@ -319,6 +548,8 @@ 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 {
@@ -332,6 +563,7 @@ impl From<MatchingStrategy> for TermsMatchingStrategy {
         match other {
             MatchingStrategy::Last => Self::Last,
             MatchingStrategy::All => Self::All,
+            MatchingStrategy::Frequency => Self::Frequency,
         }
     }
 }
@@ -370,7 +602,7 @@ pub struct SearchHit {
     pub ranking_score_details: Option<serde_json::Map<String, serde_json::Value>>,
 }
 
-#[derive(Serialize, Debug, Clone, PartialEq)]
+#[derive(Serialize, Clone, PartialEq)]
 #[serde(rename_all = "camelCase")]
 pub struct SearchResult {
     pub hits: Vec<SearchHit>,
@@ -393,6 +625,56 @@ pub struct SearchResult {
     pub used_negative_operator: bool,
 }
 
+impl fmt::Debug for SearchResult {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        let SearchResult {
+            hits,
+            query,
+            processing_time_ms,
+            hits_info,
+            facet_distribution,
+            facet_stats,
+            semantic_hit_count,
+            degraded,
+            used_negative_operator,
+        } = self;
+
+        let mut debug = f.debug_struct("SearchResult");
+        // The most important thing when looking at a search result is the time it took to process
+        debug.field("processing_time_ms", &processing_time_ms);
+        debug.field("hits", &format!("[{} hits returned]", hits.len()));
+        debug.field("query", &query);
+        debug.field("hits_info", &hits_info);
+        if *used_negative_operator {
+            debug.field("used_negative_operator", used_negative_operator);
+        }
+        if *degraded {
+            debug.field("degraded", degraded);
+        }
+        if let Some(facet_distribution) = facet_distribution {
+            debug.field("facet_distribution", &facet_distribution);
+        }
+        if let Some(facet_stats) = facet_stats {
+            debug.field("facet_stats", &facet_stats);
+        }
+        if let Some(semantic_hit_count) = semantic_hit_count {
+            debug.field("semantic_hit_count", &semantic_hit_count);
+        }
+
+        debug.finish()
+    }
+}
+
+#[derive(Serialize, Debug, Clone, PartialEq)]
+#[serde(rename_all = "camelCase")]
+pub struct SimilarResult {
+    pub hits: Vec<SearchHit>,
+    pub id: String,
+    pub processing_time_ms: u128,
+    #[serde(flatten)]
+    pub hits_info: HitsInfo,
+}
+
 #[derive(Serialize, Debug, Clone, PartialEq)]
 #[serde(rename_all = "camelCase")]
 pub struct SearchResultWithIndex {
@@ -425,8 +707,8 @@ pub struct FacetSearchResult {
 }
 
 /// Incorporate search rules in search query
-pub fn add_search_rules(query: &mut SearchQuery, rules: IndexSearchRules) {
-    query.filter = match (query.filter.take(), rules.filter) {
+pub fn add_search_rules(filter: &mut Option<Value>, rules: IndexSearchRules) {
+    *filter = match (filter.take(), rules.filter) {
         (None, rules_filter) => rules_filter,
         (filter, None) => filter,
         (Some(filter), Some(rules_filter)) => {
@@ -453,6 +735,13 @@ 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 => {
@@ -494,11 +783,16 @@ fn prepare_search<'t>(
         .unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
 
     search.exhaustive_number_hits(is_finite_pagination);
-    search.scoring_strategy(if query.show_ranking_score || query.show_ranking_score_details {
-        ScoringStrategy::Detailed
-    } else {
-        ScoringStrategy::Skip
-    });
+    search.scoring_strategy(
+        if query.show_ranking_score
+            || query.show_ranking_score_details
+            || query.ranking_score_threshold.is_some()
+        {
+            ScoringStrategy::Detailed
+        } else {
+            ScoringStrategy::Skip
+        },
+    );
 
     // compute the offset on the limit depending on the pagination mode.
     let (offset, limit) = if is_finite_pagination {
@@ -543,6 +837,7 @@ 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()?;
@@ -574,131 +869,57 @@ pub fn perform_search(
         SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
     };
 
-    let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
+    let SearchQuery {
+        q,
+        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,
+        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 displayed_ids = index
-        .displayed_fields_ids(&rtxn)?
-        .map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
-        .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 {
-            if attr == "*" {
-                ids = displayed_ids.clone();
-                break;
-            }
-
-            if let Some(id) = fields_ids_map.id(attr) {
-                ids.insert(id);
-            }
-        }
-        ids
+    let format = AttributesFormat {
+        attributes_to_retrieve,
+        retrieve_vectors,
+        attributes_to_highlight,
+        attributes_to_crop,
+        crop_length,
+        crop_marker,
+        highlight_pre_tag,
+        highlight_post_tag,
+        show_matches_position,
+        sort,
+        show_ranking_score,
+        show_ranking_score_details,
     };
 
-    // The attributes to retrieve are the ones explicitly marked as to retrieve (all by default),
-    // but these attributes must be also be present
-    // - in the fields_ids_map
-    // - in the displayed attributes
-    let to_retrieve_ids: BTreeSet<_> = query
-        .attributes_to_retrieve
-        .as_ref()
-        .map(fids)
-        .unwrap_or_else(|| displayed_ids.clone())
-        .intersection(&displayed_ids)
-        .cloned()
-        .collect();
-
-    let attr_to_highlight = query.attributes_to_highlight.unwrap_or_default();
-
-    let attr_to_crop = query.attributes_to_crop.unwrap_or_default();
-
-    // Attributes in `formatted_options` correspond to the attributes that will be in `_formatted`
-    // These attributes are:
-    // - the attributes asked to be highlighted or cropped (with `attributesToCrop` or `attributesToHighlight`)
-    // - the attributes asked to be retrieved: these attributes will not be highlighted/cropped
-    // But these attributes must be also present in displayed attributes
-    let formatted_options = compute_formatted_options(
-        &attr_to_highlight,
-        &attr_to_crop,
-        query.crop_length,
-        &to_retrieve_ids,
-        &fields_ids_map,
-        &displayed_ids,
-    );
-
-    let mut tokenizer_builder = TokenizerBuilder::default();
-    tokenizer_builder.create_char_map(true);
-
-    let script_lang_map = index.script_language(&rtxn)?;
-    if !script_lang_map.is_empty() {
-        tokenizer_builder.allow_list(&script_lang_map);
-    }
-
-    let separators = index.allowed_separators(&rtxn)?;
-    let separators: Option<Vec<_>> =
-        separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
-    if let Some(ref separators) = separators {
-        tokenizer_builder.separators(separators);
-    }
-
-    let dictionary = index.dictionary(&rtxn)?;
-    let dictionary: Option<Vec<_>> =
-        dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
-    if let Some(ref dictionary) = dictionary {
-        tokenizer_builder.words_dict(dictionary);
-    }
-
-    let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
-    formatter_builder.crop_marker(query.crop_marker);
-    formatter_builder.highlight_prefix(query.highlight_pre_tag);
-    formatter_builder.highlight_suffix(query.highlight_post_tag);
-
-    let mut documents = Vec::new();
-    let documents_iter = index.documents(&rtxn, documents_ids)?;
-
-    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)?;
-
-        // select the attributes to retrieve
-        let attributes_to_retrieve = to_retrieve_ids
-            .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);
-
-        let (matches_position, formatted) = format_fields(
-            &displayed_document,
-            &fields_ids_map,
-            &formatter_builder,
-            &formatted_options,
-            query.show_matches_position,
-            &displayed_ids,
-        )?;
-
-        if let Some(sort) = query.sort.as_ref() {
-            insert_geo_distance(sort, &mut document);
-        }
-
-        let ranking_score =
-            query.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
-        let ranking_score_details =
-            query.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
-
-        let hit = SearchHit {
-            document,
-            formatted,
-            matches_position,
-            ranking_score_details,
-            ranking_score,
-        };
-        documents.push(hit);
-    }
+    let documents =
+        make_hits(index, &rtxn, format, matching_words, documents_ids, document_scores)?;
 
     let number_of_hits = min(candidates.len() as usize, max_total_hits);
     let hits_info = if is_finite_pagination {
-        let hits_per_page = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
+        let hits_per_page = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
         // If hit_per_page is 0, then pages can't be computed and so we respond 0.
         let total_pages = (number_of_hits + hits_per_page.saturating_sub(1))
             .checked_div(hits_per_page)
@@ -706,15 +927,15 @@ pub fn perform_search(
 
         HitsInfo::Pagination {
             hits_per_page,
-            page: query.page.unwrap_or(1),
+            page: page.unwrap_or(1),
             total_pages,
             total_hits: number_of_hits,
         }
     } else {
-        HitsInfo::OffsetLimit { limit: query.limit, offset, estimated_total_hits: number_of_hits }
+        HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits }
     };
 
-    let (facet_distribution, facet_stats) = match query.facets {
+    let (facet_distribution, facet_stats) = match facets {
         Some(ref fields) => {
             let mut facet_distribution = index.facets_distribution(&rtxn);
 
@@ -751,7 +972,7 @@ pub fn perform_search(
     let result = SearchResult {
         hits: documents,
         hits_info,
-        query: query.q.unwrap_or_default(),
+        query: q.unwrap_or_default(),
         processing_time_ms: before_search.elapsed().as_millis(),
         facet_distribution,
         facet_stats,
@@ -762,6 +983,214 @@ pub fn perform_search(
     Ok(result)
 }
 
+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,
+    crop_marker: String,
+    highlight_pre_tag: String,
+    highlight_post_tag: String,
+    show_matches_position: bool,
+    sort: Option<Vec<String>>,
+    show_ranking_score: bool,
+    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<'_>,
+    format: AttributesFormat,
+    matching_words: milli::MatchingWords,
+    documents_ids: Vec<u32>,
+    document_scores: Vec<Vec<ScoreDetails>>,
+) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
+    let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
+    let displayed_ids =
+        index.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);
+
+    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 {
+            if attr == "*" {
+                ids.clone_from(&displayed_ids);
+                break;
+            }
+
+            if let Some(id) = fields_ids_map.id(attr) {
+                ids.insert(id);
+            }
+        }
+        ids
+    };
+    let to_retrieve_ids: BTreeSet<_> = format
+        .attributes_to_retrieve
+        .as_ref()
+        .map(fids)
+        .unwrap_or_else(|| displayed_ids.clone())
+        .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(
+        &attr_to_highlight,
+        &attr_to_crop,
+        format.crop_length,
+        &to_retrieve_ids,
+        &fields_ids_map,
+        &displayed_ids,
+    );
+    let mut tokenizer_builder = TokenizerBuilder::default();
+    tokenizer_builder.create_char_map(true);
+    let script_lang_map = index.script_language(rtxn)?;
+    if !script_lang_map.is_empty() {
+        tokenizer_builder.allow_list(&script_lang_map);
+    }
+    let separators = index.allowed_separators(rtxn)?;
+    let separators: Option<Vec<_>> =
+        separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
+    if let Some(ref separators) = separators {
+        tokenizer_builder.separators(separators);
+    }
+    let dictionary = index.dictionary(rtxn)?;
+    let dictionary: Option<Vec<_>> =
+        dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
+    if let Some(ref dictionary) = dictionary {
+        tokenizer_builder.words_dict(dictionary);
+    }
+    let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
+    formatter_builder.crop_marker(format.crop_marker);
+    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()) {
+        // 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,
+            &formatter_builder,
+            &formatted_options,
+            format.show_matches_position,
+            &displayed_ids,
+        )?;
+
+        if let Some(sort) = format.sort.as_ref() {
+            insert_geo_distance(sort, &mut document);
+        }
+
+        let ranking_score =
+            format.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
+        let ranking_score_details =
+            format.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
+
+        let hit = SearchHit {
+            document,
+            formatted,
+            matches_position,
+            ranking_score_details,
+            ranking_score,
+        };
+        documents.push(hit);
+    }
+    Ok(documents)
+}
+
 pub fn perform_facet_search(
     index: &Index,
     search_query: SearchQuery,
@@ -796,6 +1225,103 @@ pub fn perform_facet_search(
     })
 }
 
+pub fn perform_similar(
+    index: &Index,
+    query: SimilarQuery,
+    embedder_name: String,
+    embedder: Arc<Embedder>,
+    retrieve_vectors: RetrieveVectors,
+) -> Result<SimilarResult, ResponseError> {
+    let before_search = Instant::now();
+    let rtxn = index.read_txn()?;
+
+    let SimilarQuery {
+        id,
+        offset,
+        limit,
+        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,
+    // preventing a use-after-move
+    let Some(internal_id) = index.external_documents_ids().get(&rtxn, &id)? else {
+        return Err(ResponseError::from_msg(
+            MeilisearchHttpError::DocumentNotFound(id.into_inner()).to_string(),
+            Code::NotFoundSimilarId,
+        ));
+    };
+
+    let mut similar =
+        milli::Similar::new(internal_id, offset, limit, index, &rtxn, embedder_name, embedder);
+
+    if let Some(ref filter) = query.filter {
+        if let Some(facets) = parse_filter(filter)
+            // inject InvalidSimilarFilter code
+            .map_err(|e| ResponseError::from_msg(e.to_string(), Code::InvalidSimilarFilter))?
+        {
+            similar.filter(facets);
+        }
+    }
+
+    if let Some(ranking_score_threshold) = ranking_score_threshold {
+        similar.ranking_score_threshold(ranking_score_threshold.0);
+    }
+
+    let milli::SearchResult {
+        documents_ids,
+        matching_words: _,
+        candidates,
+        document_scores,
+        degraded: _,
+        used_negative_operator: _,
+    } = similar.execute().map_err(|err| match err {
+        milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
+            ResponseError::from_msg(err.to_string(), Code::InvalidSimilarFilter)
+        }
+        err => err.into(),
+    })?;
+
+    let format = AttributesFormat {
+        attributes_to_retrieve,
+        retrieve_vectors,
+        attributes_to_highlight: None,
+        attributes_to_crop: None,
+        crop_length: DEFAULT_CROP_LENGTH(),
+        crop_marker: DEFAULT_CROP_MARKER(),
+        highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
+        highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
+        show_matches_position: false,
+        sort: None,
+        show_ranking_score,
+        show_ranking_score_details,
+    };
+
+    let hits = make_hits(index, &rtxn, format, Default::default(), documents_ids, document_scores)?;
+
+    let max_total_hits = index
+        .pagination_max_total_hits(&rtxn)
+        .map_err(milli::Error::from)?
+        .map(|x| x as usize)
+        .unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
+
+    let number_of_hits = min(candidates.len() as usize, max_total_hits);
+    let hits_info = HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits };
+
+    let result = SimilarResult {
+        hits,
+        hits_info,
+        id: id.into_inner(),
+        processing_time_ms: before_search.elapsed().as_millis(),
+    };
+    Ok(result)
+}
+
 fn insert_geo_distance(sorts: &[String], document: &mut Document) {
     lazy_static::lazy_static! {
         static ref GEO_REGEX: Regex =

meilisearch/src/search_queue.rs

@@ -40,8 +40,9 @@ 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
-        let _ = futures::executor::block_on(self.sender.send(()));
+        std::mem::drop(tokio::spawn(async move { sender.send(()).await }));
     }
 }
 
@@ -85,8 +86,13 @@ impl SearchQueue {
                 },
 
                 search_request = receive_new_searches.recv() => {
-                    // this unwrap is safe because we're sure the `SearchQueue` still lives somewhere in actix-web
-                    let search_request = search_request.unwrap();
+                    let search_request = match search_request {
+                        Some(search_request) => search_request,
+                        // This should never happen while actix-web is running, but it's not a reason to crash
+                        // and it can generate a lot of noise in the tests.
+                        None => continue,
+                    };
+
                     if searches_running < usize::from(parallelism) && queue.is_empty() {
                         searches_running += 1;
                         // if the search requests die it's not a hard error on our side

meilisearch/tests/common/index.rs

@@ -182,14 +182,10 @@ impl Index<'_> {
         self.service.get(url).await
     }
 
-    pub async fn get_document(
-        &self,
-        id: u64,
-        options: Option<GetDocumentOptions>,
-    ) -> (Value, StatusCode) {
+    pub async fn get_document(&self, id: u64, options: Option<Value>) -> (Value, StatusCode) {
         let mut url = format!("/indexes/{}/documents/{}", urlencode(self.uid.as_ref()), id);
-        if let Some(fields) = options.and_then(|o| o.fields) {
-            let _ = write!(url, "?fields={}", fields.join(","));
+        if let Some(options) = options {
+            write!(url, "?{}", yaup::to_string(&options).unwrap()).unwrap();
         }
         self.service.get(url).await
     }
@@ -205,18 +201,11 @@ impl Index<'_> {
     }
 
     pub async fn get_all_documents(&self, options: GetAllDocumentsOptions) -> (Value, StatusCode) {
-        let mut url = format!("/indexes/{}/documents?", urlencode(self.uid.as_ref()));
-        if let Some(limit) = options.limit {
-            let _ = write!(url, "limit={}&", limit);
-        }
-
-        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(","));
-        }
+        let url = format!(
+            "/indexes/{}/documents?{}",
+            urlencode(self.uid.as_ref()),
+            yaup::to_string(&options).unwrap()
+        );
 
         self.service.get(url).await
     }
@@ -380,6 +369,43 @@ impl Index<'_> {
         self.service.get(url).await
     }
 
+    /// Performs both GET and POST similar queries
+    pub async fn similar(
+        &self,
+        query: Value,
+        test: impl Fn(Value, StatusCode) + UnwindSafe + Clone,
+    ) {
+        let post = self.similar_post(query.clone()).await;
+
+        let query = yaup::to_string(&query).unwrap();
+        let get = self.similar_get(&query).await;
+
+        insta::allow_duplicates! {
+            let (response, code) = post;
+            let t = test.clone();
+            if let Err(e) = catch_unwind(move || t(response, code)) {
+                eprintln!("Error with post search");
+                resume_unwind(e);
+            }
+
+            let (response, code) = get;
+            if let Err(e) = catch_unwind(move || test(response, code)) {
+                eprintln!("Error with get search");
+                resume_unwind(e);
+            }
+        }
+    }
+
+    pub async fn similar_post(&self, query: Value) -> (Value, StatusCode) {
+        let url = format!("/indexes/{}/similar", urlencode(self.uid.as_ref()));
+        self.service.post_encoded(url, query, self.encoder).await
+    }
+
+    pub async fn similar_get(&self, query: &str) -> (Value, StatusCode) {
+        let url = format!("/indexes/{}/similar?{}", urlencode(self.uid.as_ref()), query);
+        self.service.get(url).await
+    }
+
     pub async fn facet_search(&self, query: Value) -> (Value, StatusCode) {
         let url = format!("/indexes/{}/facet-search", urlencode(self.uid.as_ref()));
         self.service.post_encoded(url, query, self.encoder).await
@@ -398,13 +424,11 @@ impl Index<'_> {
     }
 }
 
-pub struct GetDocumentOptions {
-    pub fields: Option<Vec<&'static str>>,
-}
-
-#[derive(Debug, Default)]
+#[derive(Debug, Default, serde::Serialize)]
+#[serde(rename_all = "camelCase")]
 pub struct GetAllDocumentsOptions {
     pub limit: Option<usize>,
     pub offset: Option<usize>,
-    pub attributes_to_retrieve: Option<Vec<&'static str>>,
+    pub retrieve_vectors: bool,
+    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, GetDocumentOptions};
+pub use index::GetAllDocumentsOptions;
 use meili_snap::json_string;
 use serde::{Deserialize, Serialize};
 #[allow(unused)]
@@ -65,7 +65,7 @@ impl Display for Value {
         write!(
             f,
             "{}",
-            json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]" })
+            json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]", ".processingTimeMs" => "[duration]" })
         )
     }
 }

meilisearch/tests/documents/errors.rs

@@ -795,3 +795,70 @@ 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, GetDocumentOptions, Server, Value};
+use crate::common::{GetAllDocumentsOptions, Server, Value};
 use crate::json;
 
 // TODO: partial test since we are testing error, amd error is not yet fully implemented in
@@ -59,8 +59,7 @@ async fn get_document() {
         })
     );
 
-    let (response, code) =
-        index.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["id"]) })).await;
+    let (response, code) = index.get_document(0, Some(json!({ "fields": ["id"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -69,9 +68,8 @@ async fn get_document() {
         })
     );
 
-    let (response, code) = index
-        .get_document(0, Some(GetDocumentOptions { fields: Some(vec!["nested.content"]) }))
-        .await;
+    let (response, code) =
+        index.get_document(0, Some(json!({ "fields": ["nested.content"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -211,7 +209,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            attributes_to_retrieve: Some(vec!["name"]),
+            fields: Some(vec!["name"]),
             ..Default::default()
         })
         .await;
@@ -225,9 +223,19 @@ 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 {
-            attributes_to_retrieve: Some(vec![]),
+            fields: Some(vec!["wrong"]),
             ..Default::default()
         })
         .await;
@@ -242,22 +250,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            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"]),
+            fields: Some(vec!["name", "tags"]),
             ..Default::default()
         })
         .await;
@@ -270,10 +263,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
     }
 
     let (response, code) = index
-        .get_all_documents(GetAllDocumentsOptions {
-            attributes_to_retrieve: Some(vec!["*"]),
-            ..Default::default()
-        })
+        .get_all_documents(GetAllDocumentsOptions { fields: Some(vec!["*"]), ..Default::default() })
         .await;
     assert_eq!(code, 200);
     assert_eq!(response["results"].as_array().unwrap().len(), 20);
@@ -283,7 +273,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
 
     let (response, code) = index
         .get_all_documents(GetAllDocumentsOptions {
-            attributes_to_retrieve: Some(vec!["*", "wrong"]),
+            fields: Some(vec!["*", "wrong"]),
             ..Default::default()
         })
         .await;
@@ -316,12 +306,10 @@ 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(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
+    let (response, code) = index.get_document(0, Some(json!({ "fields": ["content"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(response, json!({}));
-    let (response, code) =
-        index.get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
+    let (response, code) = index.get_document(1, Some(json!({ "fields": ["content"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -333,9 +321,7 @@ async fn get_document_s_nested_attributes_to_retrieve() {
         })
     );
 
-    let (response, code) = index
-        .get_document(0, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
-        .await;
+    let (response, code) = index.get_document(0, Some(json!({ "fields": ["content.truc"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -343,9 +329,7 @@ async fn get_document_s_nested_attributes_to_retrieve() {
             "content.truc": "foobar",
         })
     );
-    let (response, code) = index
-        .get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
-        .await;
+    let (response, code) = index.get_document(1, Some(json!({ "fields": ["content.truc"] }))).await;
     assert_eq!(code, 200);
     assert_eq!(
         response,
@@ -540,3 +524,217 @@ 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": {
+            "manual": {
+              "embeddings": [],
+              "regenerate": false
+            }
+          }
+        }
+      ],
+      "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": {
+            "manual": {
+              "embeddings": [],
+              "regenerate": false
+            }
+          }
+        }
+      ],
+      "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

@@ -1859,8 +1859,7 @@ async fn import_dump_v6_containing_experimental_features() {
     {
       "vectorStore": false,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -1939,3 +1938,210 @@ 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

@@ -0,0 +1,25 @@
+---
+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

@@ -0,0 +1,19 @@
+---
+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/features/mod.rs

@@ -20,8 +20,7 @@ async fn experimental_features() {
     {
       "vectorStore": false,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -32,8 +31,7 @@ async fn experimental_features() {
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -44,8 +42,7 @@ async fn experimental_features() {
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -57,8 +54,7 @@ async fn experimental_features() {
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -70,8 +66,7 @@ async fn experimental_features() {
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 }
@@ -90,8 +85,7 @@ async fn experimental_feature_metrics() {
     {
       "vectorStore": false,
       "metrics": true,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -146,7 +140,7 @@ async fn errors() {
     meili_snap::snapshot!(code, @"400 Bad Request");
     meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
     {
-      "message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`, `exportPuffinReports`",
+      "message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`",
       "code": "bad_request",
       "type": "invalid_request",
       "link": "https://docs.meilisearch.com/errors#bad_request"

meilisearch/tests/integration.rs

@@ -8,10 +8,12 @@ mod index;
 mod logs;
 mod search;
 mod settings;
+mod similar;
 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

@@ -107,6 +107,39 @@ 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";
 
@@ -239,3 +272,35 @@ 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

@@ -167,6 +167,74 @@ 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;
@@ -321,6 +389,40 @@ 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;
@@ -505,7 +607,7 @@ 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`",
+      "message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`, `frequency`",
       "code": "invalid_search_matching_strategy",
       "type": "invalid_request",
       "link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@@ -527,7 +629,7 @@ 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`",
+      "message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`, `frequency`",
       "code": "invalid_search_matching_strategy",
       "type": "invalid_request",
       "link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@@ -1038,3 +1140,66 @@ 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

@@ -117,3 +117,69 @@ 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

@@ -5,7 +5,10 @@ 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> {
+async fn index_with_documents_user_provided<'a>(
+    server: &'a Server,
+    documents: &Value,
+) -> Index<'a> {
     let index = server.index("test");
 
     let (response, code) = server.set_features(json!({"vectorStore": true})).await;
@@ -15,8 +18,7 @@ async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Inde
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -34,7 +36,38 @@ async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Inde
     index
 }
 
-static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
+async fn index_with_documents_hf<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
+    let index = server.index("test");
+
+    let (response, code) = server.set_features(json!({"vectorStore": true})).await;
+
+    meili_snap::snapshot!(code, @"200 OK");
+    meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
+    {
+      "vectorStore": true,
+      "metrics": false,
+      "logsRoute": false
+    }
+    "###);
+
+    let (response, code) = index
+        .update_settings(json!({ "embedders": {"default": {
+            "source": "huggingFace",
+            "model": "sentence-transformers/all-MiniLM-L6-v2",
+            "revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
+            "documentTemplate": "{{doc.title}}, {{doc.desc}}"
+        }}} ))
+        .await;
+    assert_eq!(202, code, "{:?}", response);
+    index.wait_task(response.uid()).await;
+
+    let (response, code) = index.add_documents(documents.clone(), None).await;
+    assert_eq!(202, code, "{:?}", response);
+    index.wait_task(response.uid()).await;
+    index
+}
+
+static SIMPLE_SEARCH_DOCUMENTS_VEC: Lazy<Value> = Lazy::new(|| {
     json!([
     {
         "title": "Shazam!",
@@ -56,7 +89,7 @@ static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
     }])
 });
 
-static SINGLE_DOCUMENT: Lazy<Value> = Lazy::new(|| {
+static SINGLE_DOCUMENT_VEC: Lazy<Value> = Lazy::new(|| {
     json!([{
             "title": "Shazam!",
             "desc": "a Captain Marvel ersatz",
@@ -65,48 +98,145 @@ static SINGLE_DOCUMENT: Lazy<Value> = Lazy::new(|| {
     }])
 });
 
+static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
+    json!([
+    {
+        "title": "Shazam!",
+        "desc": "a Captain Marvel ersatz",
+        "id": "1",
+    },
+    {
+        "title": "Captain Planet",
+        "desc": "He's not part of the Marvel Cinematic Universe",
+        "id": "2",
+    },
+    {
+        "title": "Captain Marvel",
+        "desc": "a Shazam ersatz",
+        "id": "3",
+    }])
+});
+
 #[actix_rt::test]
 async fn simple_search() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}}),
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": 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":[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["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["semanticHitCount"], @"0");
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true}),
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true, "retrieveVectors": 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":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
+    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["semanticHitCount"], @"2");
+
+    let (response, code) = index
+        .search_post(
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true, "retrieveVectors": 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["semanticHitCount"], @"3");
+}
+
+#[actix_rt::test]
+async fn limit_offset() {
+    let server = Server::new().await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
+
+    let (response, code) = index
+        .search_post(
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true, "offset": 1, "limit": 1}),
+        )
+        .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}}}]"###);
+    snapshot!(response["semanticHitCount"], @"0");
+    assert_eq!(response["hits"].as_array().unwrap().len(), 1);
+
+    let server = Server::new().await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
+
+    let (response, code) = index
+        .search_post(
+            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.9}, "retrieveVectors": true, "offset": 1, "limit": 1}),
+        )
+        .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}}}]"###);
+    snapshot!(response["semanticHitCount"], @"1");
+    assert_eq!(response["hits"].as_array().unwrap().len(), 1);
+}
+
+#[actix_rt::test]
+async fn simple_search_hf() {
+    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}})).await;
+    snapshot!(code, @"200 OK");
+    snapshot!(response["hits"], @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"}]"###);
+    snapshot!(response["semanticHitCount"], @"0");
+
+    let (response, code) = index
+        .search_post(
+            // disable ranking score as the vectors between architectures are not equal
+            json!({"q": "Captain", "hybrid": {"semanticRatio": 0.55}, "showRankingScore": false}),
+        )
+        .await;
+    snapshot!(code, @"200 OK");
+    snapshot!(response["hits"], @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"}]"###);
     snapshot!(response["semanticHitCount"], @"1");
 
     let (response, code) = index
         .search_post(
-            json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true}),
+            json!({"q": "Captain", "hybrid": {"semanticRatio": 0.8}, "showRankingScore": false}),
         )
         .await;
     snapshot!(code, @"200 OK");
-    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["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
+    snapshot!(response["semanticHitCount"], @"3");
+
+    let (response, code) = index
+        .search_post(
+            json!({"q": "Movie World", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
+        )
+        .await;
+    snapshot!(code, @"200 OK");
+    snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"}]"###);
+    snapshot!(response["semanticHitCount"], @"3");
+
+    let (response, code) = index
+        .search_post(
+            json!({"q": "Wonder replacement", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
+        )
+        .await;
+    snapshot!(code, @"200 OK");
+    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
     snapshot!(response["semanticHitCount"], @"3");
 }
 
 #[actix_rt::test]
 async fn distribution_shift() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).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}});
+    let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}, "retrieveVectors": true});
     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":[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["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}]"###);
 
     let (response, code) = index
         .update_settings(json!({
@@ -127,31 +257,34 @@ 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":[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}]"###);
+    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}]"###);
 }
 
 #[actix_rt::test]
 async fn highlighter() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
 
     let (response, code) = index
         .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
             "hybrid": {"semanticRatio": 0.2},
-            "attributesToHighlight": [
-                     "desc"
+           "retrieveVectors": true,
+           "attributesToHighlight": [
+                     "desc",
+                     "_vectors",
                    ],
-                   "highlightPreTag": "**BEGIN**",
-                   "highlightPostTag": "**END**"
+           "highlightPreTag": "**BEGIN**",
+           "highlightPostTag": "**END**",
         }))
         .await;
     snapshot!(code, @"200 OK");
-    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["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["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"
@@ -161,13 +294,14 @@ async fn highlighter() {
         }))
         .await;
     snapshot!(code, @"200 OK");
-    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["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["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"
@@ -177,14 +311,14 @@ async fn highlighter() {
         }))
         .await;
     snapshot!(code, @"200 OK");
-    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["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["semanticHitCount"], @"3");
 }
 
 #[actix_rt::test]
 async fn invalid_semantic_ratio() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
 
     let (response, code) = index
         .search_post(
@@ -256,45 +390,45 @@ async fn invalid_semantic_ratio() {
 #[actix_rt::test]
 async fn single_document() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SINGLE_DOCUMENT).await;
+    let index = index_with_documents_user_provided(&server, &SINGLE_DOCUMENT_VEC).await;
 
     let (response, code) = index
     .search_post(
-        json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
+        json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
     )
     .await;
 
     snapshot!(code, @"200 OK");
-    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["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["semanticHitCount"], @"1");
 }
 
 #[actix_rt::test]
 async fn query_combination() {
     let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
+    let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
 
     // search without query and vector, but with hybrid => still placeholder
     let (response, code) = index
-        .search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
+        .search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
         .await;
 
     snapshot!(code, @"200 OK");
-    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["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["semanticHitCount"], @"null");
 
     // same with a different semantic ratio
     let (response, code) = index
-        .search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true}))
+        .search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true, "retrieveVectors": true}))
         .await;
 
     snapshot!(code, @"200 OK");
-    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["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["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}))
+    .search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
     .await;
 
     snapshot!(code, @"400 Bad Request");
@@ -309,34 +443,34 @@ async fn query_combination() {
 
     // full vector
     let (response, code) = index
-    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
+    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
     .await;
 
     snapshot!(code, @"200 OK");
-    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["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["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}))
+    .search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
     .await;
 
     snapshot!(code, @"200 OK");
-    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["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["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}))
+    .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": 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":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.8848484848484849}]"###);
+    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["semanticHitCount"], @"null");
 
     // query + vector, no hybrid keyword =>
     let (response, code) = index
-        .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true}))
+        .search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true, "retrieveVectors": true}))
         .await;
 
     snapshot!(code, @"400 Bad Request");
@@ -352,7 +486,7 @@ 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}),
+            json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
         )
         .await;
 
@@ -369,11 +503,93 @@ 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}),
+            json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true, "retrieveVectors": 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":[1.0,2.0]},"_rankingScore":0.9848484848484848}]"###);
+    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["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

@@ -0,0 +1,128 @@
+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

@@ -7,6 +7,7 @@ mod facet_search;
 mod formatted;
 mod geo;
 mod hybrid;
+mod matching_strategy;
 mod multi;
 mod pagination;
 mod restrict_searchable;
@@ -47,6 +48,31 @@ 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!([
         {
@@ -275,7 +301,7 @@ async fn negative_special_cases_search() {
     index.add_documents(documents, None).await;
     index.wait_task(0).await;
 
-    index.update_settings(json!({"synonyms": { "escape": ["glass"] }})).await;
+    index.update_settings(json!({"synonyms": { "escape": ["gläss"] }})).await;
     index.wait_task(1).await;
 
     // There is a synonym for escape -> glass but we don't want "escape", only the derivates: glass
@@ -680,6 +706,26 @@ async fn search_facet_distribution() {
             },
         )
         .await;
+
+    index.update_settings(json!({"filterableAttributes": ["doggos.name"]})).await;
+    index.wait_task(5).await;
+
+    index
+        .search(
+            json!({
+                "facets": ["doggos.name"]
+            }),
+            |response, code| {
+                assert_eq!(code, 200, "{}", response);
+                let dist = response["facetDistribution"].as_object().unwrap();
+                assert_eq!(dist.len(), 1);
+                assert_eq!(
+                    dist["doggos.name"],
+                    json!({ "bobby": 1, "buddy": 1, "gros bill": 1, "turbo": 1, "fast": 1})
+                );
+            },
+        )
+        .await;
 }
 
 #[actix_rt::test]
@@ -895,9 +941,9 @@ async fn test_score_details() {
                     "id": "166428",
                     "_vectors": {
                       "manual": [
-                        -100,
-                        231,
-                        32
+                        -100.0,
+                        231.0,
+                        32.0
                       ]
                     },
                     "_rankingScoreDetails": {
@@ -921,7 +967,7 @@ async fn test_score_details() {
                         "order": 3,
                         "attributeRankingOrderScore": 1.0,
                         "queryWordDistanceScore": 0.8095238095238095,
-                        "score": 0.9727891156462584
+                        "score": 0.8095238095238095
                       },
                       "exactness": {
                         "order": 4,
@@ -939,6 +985,213 @@ 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;
@@ -1037,21 +1290,38 @@ async fn experimental_feature_vector_store() {
     index.add_documents(json!(documents), None).await;
     index.wait_task(0).await;
 
-    let (response, code) = index
-        .search_post(json!({
+    index
+        .search(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");
@@ -1084,6 +1354,7 @@ async fn experimental_feature_vector_store() {
         .search_post(json!({
             "vector": [1.0, 2.0, 3.0],
             "showRankingScore": true,
+            "retrieveVectors": true,
         }))
         .await;
 
@@ -1095,11 +1366,16 @@ async fn experimental_feature_vector_store() {
         "title": "Shazam!",
         "id": "287947",
         "_vectors": {
-          "manual": [
-            1,
-            2,
-            3
-          ]
+          "manual": {
+            "embeddings": [
+              [
+                1.0,
+                2.0,
+                3.0
+              ]
+            ],
+            "regenerate": false
+          }
         },
         "_rankingScore": 1.0
       },
@@ -1107,11 +1383,16 @@ async fn experimental_feature_vector_store() {
         "title": "Captain Marvel",
         "id": "299537",
         "_vectors": {
-          "manual": [
-            1,
-            2,
-            54
-          ]
+          "manual": {
+            "embeddings": [
+              [
+                1.0,
+                2.0,
+                54.0
+              ]
+            ],
+            "regenerate": false
+          }
         },
         "_rankingScore": 0.9129111766815186
       },
@@ -1119,11 +1400,16 @@ async fn experimental_feature_vector_store() {
         "title": "Gläss",
         "id": "450465",
         "_vectors": {
-          "manual": [
-            -100,
-            340,
-            90
-          ]
+          "manual": {
+            "embeddings": [
+              [
+                -100.0,
+                340.0,
+                90.0
+              ]
+            ],
+            "regenerate": false
+          }
         },
         "_rankingScore": 0.8106412887573242
       },
@@ -1131,11 +1417,16 @@ async fn experimental_feature_vector_store() {
         "title": "How to Train Your Dragon: The Hidden World",
         "id": "166428",
         "_vectors": {
-          "manual": [
-            -100,
-            231,
-            32
-          ]
+          "manual": {
+            "embeddings": [
+              [
+                -100.0,
+                231.0,
+                32.0
+              ]
+            ],
+            "regenerate": false
+          }
         },
         "_rankingScore": 0.7412010431289673
       },
@@ -1143,11 +1434,16 @@ async fn experimental_feature_vector_store() {
         "title": "Escape Room",
         "id": "522681",
         "_vectors": {
-          "manual": [
-            10,
-            -23,
-            32
-          ]
+          "manual": {
+            "embeddings": [
+              [
+                10.0,
+                -23.0,
+                32.0
+              ]
+            ],
+            "regenerate": false
+          }
         },
         "_rankingScore": 0.6972063183784485
       }
@@ -1405,9 +1701,9 @@ async fn simple_search_with_strange_synonyms() {
                 "id": "166428",
                 "_vectors": {
                   "manual": [
-                    -100,
-                    231,
-                    32
+                    -100.0,
+                    231.0,
+                    32.0
                   ]
                 }
               }
@@ -1426,9 +1722,9 @@ async fn simple_search_with_strange_synonyms() {
                 "id": "166428",
                 "_vectors": {
                   "manual": [
-                    -100,
-                    231,
-                    32
+                    -100.0,
+                    231.0,
+                    32.0
                   ]
                 }
               }
@@ -1447,9 +1743,9 @@ async fn simple_search_with_strange_synonyms() {
                 "id": "166428",
                 "_vectors": {
                   "manual": [
-                    -100,
-                    231,
-                    32
+                    -100.0,
+                    231.0,
+                    32.0
                   ]
                 }
               }

meilisearch/tests/search/multi.rs

@@ -75,9 +75,9 @@ async fn simple_search_single_index() {
             "id": "450465",
             "_vectors": {
               "manual": [
-                -100,
-                340,
-                90
+                -100.0,
+                340.0,
+                90.0
               ]
             }
           }
@@ -96,9 +96,9 @@ async fn simple_search_single_index() {
             "id": "299537",
             "_vectors": {
               "manual": [
-                1,
-                2,
-                54
+                1.0,
+                2.0,
+                54.0
               ]
             }
           }
@@ -194,9 +194,9 @@ async fn simple_search_two_indexes() {
             "id": "450465",
             "_vectors": {
               "manual": [
-                -100,
-                340,
-                90
+                -100.0,
+                340.0,
+                90.0
               ]
             }
           }
@@ -227,9 +227,9 @@ async fn simple_search_two_indexes() {
             "cattos": "pésti",
             "_vectors": {
               "manual": [
-                1,
-                2,
-                3
+                1.0,
+                2.0,
+                3.0
               ]
             }
           },
@@ -249,9 +249,9 @@ async fn simple_search_two_indexes() {
             ],
             "_vectors": {
               "manual": [
-                1,
-                2,
-                54
+                1.0,
+                2.0,
+                54.0
               ]
             }
           }

meilisearch/tests/search/restrict_searchable.rs

@@ -285,10 +285,10 @@ async fn attributes_ranking_rule_order() {
                 @r###"
             [
               {
-                "id": "2"
+                "id": "1"
               },
               {
-                "id": "1"
+                "id": "2"
               }
             ]
             "###

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

@@ -0,0 +1,20 @@
+---
+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

@@ -0,0 +1,18 @@
+---
+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/settings/get_settings.rs

@@ -98,8 +98,7 @@ async fn secrets_are_hidden_in_settings() {
     {
       "vectorStore": true,
       "metrics": false,
-      "logsRoute": false,
-      "exportPuffinReports": false
+      "logsRoute": false
     }
     "###);
 
@@ -113,7 +112,8 @@ async fn secrets_are_hidden_in_settings() {
                 "default": {
                     "source": "rest",
                     "url": "https://localhost:7777",
-                    "apiKey": "My super secret value you will never guess"
+                    "apiKey": "My super secret value you will never guess",
+                    "dimensions": 4,
                 }
             }
         }))
@@ -184,6 +184,7 @@ async fn secrets_are_hidden_in_settings() {
         "default": {
           "source": "rest",
           "apiKey": "My suXXXXXX...",
+          "dimensions": 4,
           "documentTemplate": "{% for field in fields %} {{ field.name }}: {{ field.value }}\n{% endfor %}",
           "url": "https://localhost:7777",
           "query": null,
@@ -211,6 +212,7 @@ async fn secrets_are_hidden_in_settings() {
         "default": {
           "source": "rest",
           "apiKey": "My suXXXXXX...",
+          "dimensions": 4,
           "url": "https://localhost:7777"
         }
       }

meilisearch/tests/similar/errors.rs

@@ -0,0 +1,809 @@
+use meili_snap::*;
+
+use super::DOCUMENTS;
+use crate::common::Server;
+use crate::json;
+
+#[actix_rt::test]
+async fn similar_unexisting_index() {
+    let server = Server::new().await;
+    let index = server.index("test");
+    server.set_features(json!({"vectorStore": true})).await;
+
+    let expected_response = json!({
+        "message": "Index `test` not found.",
+        "code": "index_not_found",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#index_not_found"
+    });
+
+    index
+        .similar(json!({"id": 287947}), |response, code| {
+            assert_eq!(code, 404);
+            assert_eq!(response, expected_response);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn similar_unexisting_parameter() {
+    let server = Server::new().await;
+    let index = server.index("test");
+    server.set_features(json!({"vectorStore": true})).await;
+
+    index
+        .similar(json!({"id": 287947, "marin": "hello"}), |response, code| {
+            assert_eq!(code, 400, "{}", response);
+            assert_eq!(response["code"], "bad_request");
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn similar_feature_not_enabled() {
+    let server = Server::new().await;
+    let index = server.index("test");
+
+    let (response, code) = index.similar_post(json!({"id": 287947})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Using the similar API 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"
+    }
+    "###);
+}
+
+#[actix_rt::test]
+async fn similar_bad_id() {
+    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!({"id": ["doggo"]})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
+      "code": "invalid_similar_id",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_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;
+    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!({"id": "http://invalid-docid/"})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
+      "code": "invalid_similar_id",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_id"
+    }
+    "###);
+}
+
+#[actix_rt::test]
+async fn similar_not_found_id() {
+    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!({"id": "definitely-doesnt-exist"})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Document `definitely-doesnt-exist` not found.",
+      "code": "not_found_similar_id",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#not_found_similar_id"
+    }
+    "###);
+}
+
+#[actix_rt::test]
+async fn similar_bad_offset() {
+    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!({"id": 287947, "offset": "doggo"})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value type at `.offset`: expected a positive integer, but found a string: `\"doggo\"`",
+      "code": "invalid_similar_offset",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
+    }
+    "###);
+
+    let (response, code) = index.similar_get("id=287947&offset=doggo").await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value in parameter `offset`: could not parse `doggo` as a positive integer",
+      "code": "invalid_similar_offset",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
+    }
+    "###);
+}
+
+#[actix_rt::test]
+async fn similar_bad_limit() {
+    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!({"id": 287947, "limit": "doggo"})).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value type at `.limit`: expected a positive integer, but found a string: `\"doggo\"`",
+      "code": "invalid_similar_limit",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
+    }
+    "###);
+
+    let (response, code) = index.similar_get("id=287946&limit=doggo").await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid value in parameter `limit`: could not parse `doggo` as a positive integer",
+      "code": "invalid_similar_limit",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
+    }
+    "###);
+}
+
+#[actix_rt::test]
+async fn similar_bad_filter() {
+    // Since a filter is deserialized as a json Value it will never fail to deserialize.
+    // Thus the error message is not generated by deserr but written by us.
+    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;
+
+    snapshot!(code, @"202 Accepted");
+
+    let documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let (response, code) = index.similar_post(json!({ "id": 287947, "filter": true })).await;
+    snapshot!(code, @"400 Bad Request");
+    snapshot!(json_string!(response), @r###"
+    {
+      "message": "Invalid syntax for the filter parameter: `expected String, Array, found: true`.",
+      "code": "invalid_similar_filter",
+      "type": "invalid_request",
+      "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    }
+    "###);
+    // Can't make the `filter` fail with a get search since it'll accept anything as a strings.
+}
+
+#[actix_rt::test]
+async fn filter_invalid_syntax_object() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": "title & Glass"}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_invalid_syntax_array() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": ["title & Glass"]}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_invalid_syntax_string() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "Found unexpected characters at the end of the filter: `XOR title = Glass`. You probably forgot an `OR` or an `AND` rule.\n15:32 title = Glass XOR title = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(
+            json!({"id": 287947, "filter": "title = Glass XOR title = Glass"}),
+            |response, code| {
+                assert_eq!(response, expected_response);
+                assert_eq!(code, 400);
+            },
+        )
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_invalid_attribute_array() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": ["many = Glass"]}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_invalid_attribute_string() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": "many = Glass"}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_geo_attribute_array() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": ["_geo = Glass"]}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_geo_attribute_string() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": "_geo = Glass"}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_attribute_array() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": ["_geoDistance = Glass"]}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_attribute_string() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+       "message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": "_geoDistance = Glass"}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_geo_point_array() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+        "message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": ["_geoPoint = Glass"]}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .await;
+}
+
+#[actix_rt::test]
+async fn filter_reserved_geo_point_string() {
+    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 documents = DOCUMENTS.clone();
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    index.wait_task(value.uid()).await;
+
+    let expected_response = json!({
+       "message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
+        "code": "invalid_similar_filter",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
+    });
+    index
+        .similar(json!({"id": 287947, "filter": "_geoPoint = Glass"}), |response, code| {
+            assert_eq!(response, expected_response);
+            assert_eq!(code, 400);
+        })
+        .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

@@ -0,0 +1,731 @@
+mod errors;
+
+use meili_snap::{json_string, snapshot};
+use once_cell::sync::Lazy;
+
+use crate::common::{Server, Value};
+use crate::json;
+
+static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
+    json!([
+        {
+            "title": "Shazam!",
+            "release_year": 2019,
+            "id": "287947",
+            // Three semantic properties:
+            // 1. magic, anything that reminds you of magic
+            // 2. authority, anything that inspires command
+            // 3. horror, anything that inspires fear or dread
+            "_vectors": { "manual": [0.8, 0.4, -0.5]},
+        },
+        {
+            "title": "Captain Marvel",
+            "release_year": 2019,
+            "id": "299537",
+            "_vectors": { "manual": [0.6, 0.8, -0.2] },
+        },
+        {
+            "title": "Escape Room",
+            "release_year": 2019,
+            "id": "522681",
+            "_vectors": { "manual": [0.1, 0.6, 0.8] },
+        },
+        {
+            "title": "How to Train Your Dragon: The Hidden World",
+            "release_year": 2019,
+            "id": "166428",
+            "_vectors": { "manual": [0.7, 0.7, -0.4] },
+        },
+        {
+            "title": "All Quiet on the Western Front",
+            "release_year": 1930,
+            "id": "143",
+            "_vectors": { "manual": [-0.5, 0.3, 0.85] },
+        }
+    ])
+});
+
+#[actix_rt::test]
+async fn basic() {
+    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, "retrieveVectors": true}), |response, code| {
+            snapshot!(code, @"200 OK");
+            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
+                  }
+                }
+              },
+              {
+                "title": "Captain Marvel",
+                "release_year": 2019,
+                "id": "299537",
+                "_vectors": {
+                  "manual": {
+                    "embeddings": [
+                      [
+                        0.6000000238418579,
+                        0.800000011920929,
+                        -0.20000000298023224
+                      ]
+                    ],
+                    "regenerate": false
+                  }
+                }
+              },
+              {
+                "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
+                  }
+                }
+              },
+              {
+                "title": "Shazam!",
+                "release_year": 2019,
+                "id": "287947",
+                "_vectors": {
+                  "manual": {
+                    "embeddings": [
+                      [
+                        0.800000011920929,
+                        0.4000000059604645,
+                        -0.5
+                      ]
+                    ],
+                    "regenerate": false
+                  }
+                }
+              }
+            ]
+            "###);
+        })
+        .await;
+
+    index
+        .similar(json!({"id": "299537", "retrieveVectors": true}), |response, code| {
+            snapshot!(code, @"200 OK");
+            snapshot!(json_string!(response["hits"]), @r###"
+            [
+              {
+                "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
+                  }
+                }
+              },
+              {
+                "title": "Shazam!",
+                "release_year": 2019,
+                "id": "287947",
+                "_vectors": {
+                  "manual": {
+                    "embeddings": [
+                      [
+                        0.800000011920929,
+                        0.4000000059604645,
+                        -0.5
+                      ]
+                    ],
+                    "regenerate": false
+                  }
+                }
+              },
+              {
+                "title": "Escape Room",
+                "release_year": 2019,
+                "id": "522681",
+                "_vectors": {
+                  "manual": {
+                    "embeddings": [
+                      [
+                        0.10000000149011612,
+                        0.6000000238418579,
+                        0.800000011920929
+                      ]
+                    ],
+                    "regenerate": false
+                  }
+                }
+              },
+              {
+                "title": "All Quiet on the Western Front",
+                "release_year": 1930,
+                "id": "143",
+                "_vectors": {
+                  "manual": {
+                    "embeddings": [
+                      [
+                        -0.5,
+                        0.30000001192092896,
+                        0.8500000238418579
+                      ]
+                    ],
+                    "regenerate": false
+                  }
+                }
+              }
+            ]
+            "###);
+        })
+        .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;
+    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", "release_year"]}))
+        .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": 522681, "filter": "release_year = 2019", "retrieveVectors": true}),
+            |response, code| {
+                snapshot!(code, @"200 OK");
+                snapshot!(json_string!(response["hits"]), @r###"
+                [
+                  {
+                    "title": "Captain Marvel",
+                    "release_year": 2019,
+                    "id": "299537",
+                    "_vectors": {
+                      "manual": {
+                        "embeddings": [
+                          [
+                            0.6000000238418579,
+                            0.800000011920929,
+                            -0.20000000298023224
+                          ]
+                        ],
+                        "regenerate": false
+                      }
+                    }
+                  },
+                  {
+                    "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
+                      }
+                    }
+                  },
+                  {
+                    "title": "Shazam!",
+                    "release_year": 2019,
+                    "id": "287947",
+                    "_vectors": {
+                      "manual": {
+                        "embeddings": [
+                          [
+                            0.800000011920929,
+                            0.4000000059604645,
+                            -0.5
+                          ]
+                        ],
+                        "regenerate": false
+                      }
+                    }
+                  }
+                ]
+                "###);
+            },
+        )
+        .await;
+
+    index
+        .similar(
+            json!({"id": 522681, "filter": "release_year < 2000", "retrieveVectors": true}),
+            |response, code| {
+                snapshot!(code, @"200 OK");
+                snapshot!(json_string!(response["hits"]), @r###"
+                [
+                  {
+                    "title": "All Quiet on the Western Front",
+                    "release_year": 1930,
+                    "id": "143",
+                    "_vectors": {
+                      "manual": {
+                        "embeddings": [
+                          [
+                            -0.5,
+                            0.30000001192092896,
+                            0.8500000238418579
+                          ]
+                        ],
+                        "regenerate": false
+                      }
+                    }
+                  }
+                ]
+                "###);
+            },
+        )
+        .await;
+}
+
+#[actix_rt::test]
+async fn limit_and_offset() {
+    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, "limit": 1, "retrieveVectors": true}), |response, code| {
+            snapshot!(code, @"200 OK");
+            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
+                  }
+                }
+              }
+            ]
+            "###);
+        })
+        .await;
+
+    index
+        .similar(
+            json!({"id": 143, "limit": 1, "offset": 1, "retrieveVectors": true}),
+            |response, code| {
+                snapshot!(code, @"200 OK");
+                snapshot!(json_string!(response["hits"]), @r###"
+                [
+                  {
+                    "title": "Captain Marvel",
+                    "release_year": 2019,
+                    "id": "299537",
+                    "_vectors": {
+                      "manual": {
+                        "embeddings": [
+                          [
+                            0.6000000238418579,
+                            0.800000011920929,
+                            -0.20000000298023224
+                          ]
+                        ],
+                        "regenerate": false
+                      }
+                    }
+                  }
+                ]
+                "###);
+            },
+        )
+        .await;
+}

meilisearch/tests/snapshot/mod.rs

@@ -1,6 +1,5 @@
 use std::time::Duration;
 
-use actix_rt::time::sleep;
 use meili_snap::{json_string, snapshot};
 use meilisearch::option::ScheduleSnapshot;
 use meilisearch::Opt;
@@ -32,6 +31,7 @@ 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();
@@ -53,11 +53,29 @@ async fn perform_snapshot() {
 
     index.load_test_set().await;
 
-    server.index("test1").create(Some("prim")).await;
+    let (task, code) = server.index("test1").create(Some("prim")).await;
+    meili_snap::snapshot!(code, @"202 Accepted");
 
-    index.wait_task(2).await;
+    index.wait_task(task.uid()).await;
 
-    sleep(Duration::from_secs(2)).await;
+    // wait for the _next task_ to process, aka the snapshot that should be enqueued at some point
+
+    println!("waited for the next task to finish");
+    let now = std::time::Instant::now();
+    let next_task = task.uid() + 1;
+    loop {
+        let (value, code) = index.get_task(next_task).await;
+        dbg!(&value);
+        if code != 404 && value["status"].as_str() == Some("succeeded") {
+            break;
+        }
+
+        if now.elapsed() > Duration::from_secs(30) {
+            panic!("The snapshot didn't schedule in 30s even though it was supposed to be scheduled every 2s: {}",
+                serde_json::to_string_pretty(&value).unwrap()
+            );
+        }
+    }
 
     let temp = tempfile::tempdir().unwrap();
 

meilisearch/tests/vector/mod.rs

@@ -0,0 +1,603 @@
+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": {
+            "manual": {
+              "embeddings": [],
+              "regenerate": false
+            }
+          }
+        }
+      ],
+      "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": {
+            "manual": {
+              "embeddings": [],
+              "regenerate": false
+            }
+          }
+        }
+      ],
+      "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": {
+            "manual": {
+              "embeddings": [],
+              "regenerate": false
+            }
+          }
+        }
+      ],
+      "offset": 0,
+      "limit": 20,
+      "total": 1
+    }
+    "###);
+}

meilisearch/tests/vector/settings.rs

@@ -0,0 +1,228 @@
+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

@@ -0,0 +1,19 @@
+---
+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

@@ -0,0 +1,19 @@
+---
+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

@@ -0,0 +1,23 @@
+---
+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]"
+}

meilitool/src/main.rs

@@ -80,9 +80,7 @@ fn main() -> anyhow::Result<()> {
 /// Clears the task queue located at `db_path`.
 fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
     let path = db_path.join("tasks");
-    let env = EnvOpenOptions::new()
-        .max_dbs(100)
-        .open(&path)
+    let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&path) }
         .with_context(|| format!("While trying to open {:?}", path.display()))?;
 
     eprintln!("Deleting tasks from the database...");
@@ -129,7 +127,7 @@ fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
         }
     }
 
-    eprintln!("Sucessfully deleted {count} content files from disk!");
+    eprintln!("Successfully deleted {count} content files from disk!");
 
     Ok(())
 }
@@ -193,9 +191,7 @@ fn export_a_dump(
         FileStore::new(db_path.join("update_files")).context("While opening the FileStore")?;
 
     let index_scheduler_path = db_path.join("tasks");
-    let env = EnvOpenOptions::new()
-        .max_dbs(100)
-        .open(&index_scheduler_path)
+    let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&index_scheduler_path) }
         .with_context(|| format!("While trying to open {:?}", index_scheduler_path.display()))?;
 
     eprintln!("Dumping the keys...");