mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-29 08:14:26 +01:00
add a batch of tests
This commit is contained in:
Tamo
parent
7cef2299cf
commit
3493093c4f
@ -2016,6 +2016,7 @@ mod tests {
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// Wait for one successful batch.
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#[track_caller]
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fn advance_one_successful_batch(&mut self) {
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self.index_scheduler.assert_internally_consistent();
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self.advance_till([Start, BatchCreated]);
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loop {
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match self.advance() {
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@ -2025,12 +2026,16 @@ mod tests {
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// the batch went successfully, we can stop the loop and go on with the next states.
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ProcessBatchSucceeded => break,
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AbortedIndexation => panic!("The batch was aborted.\n{}", snapshot_index_scheduler(&self.index_scheduler)),
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ProcessBatchFailed => panic!("The batch failed.\n{}", snapshot_index_scheduler(&self.index_scheduler)),
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ProcessBatchFailed => {
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while self.advance() != Start {}
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panic!("The batch failed.\n{}", snapshot_index_scheduler(&self.index_scheduler))
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},
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breakpoint => panic!("Encountered an impossible breakpoint `{:?}`, this is probably an issue with the test suite.", breakpoint),
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}
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}
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self.advance_till([AfterProcessing]);
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self.index_scheduler.assert_internally_consistent();
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}
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// Wait for one failed batch.
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@ -5012,7 +5017,6 @@ mod tests {
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false,
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)
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.unwrap();
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index_scheduler.assert_internally_consistent();
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snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after_registering_settings_task_vectors");
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@ -5105,7 +5109,6 @@ mod tests {
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false,
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)
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.unwrap();
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index_scheduler.assert_internally_consistent();
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snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after adding Intel");
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@ -5180,7 +5183,6 @@ mod tests {
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false,
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)
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.unwrap();
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index_scheduler.assert_internally_consistent();
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snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir");
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@ -5303,9 +5305,7 @@ mod tests {
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false,
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)
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.unwrap();
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index_scheduler.assert_internally_consistent();
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handle.advance_one_successful_batch();
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index_scheduler.assert_internally_consistent();
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let index = index_scheduler.index("doggos").unwrap();
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let rtxn = index.read_txn().unwrap();
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@ -5452,9 +5452,7 @@ mod tests {
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false,
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)
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.unwrap();
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index_scheduler.assert_internally_consistent();
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handle.advance_one_successful_batch();
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index_scheduler.assert_internally_consistent();
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// the document with the id 3 should have its original embedding updated
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let rtxn = index.read_txn().unwrap();
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@ -5481,4 +5479,166 @@ mod tests {
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assert!(!embedding.is_empty());
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}
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#[test]
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fn delete_document_containing_vector() {
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// 1. Add an embedder
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// 2. Push two documents containing a simple vector
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// 3. Delete the first document
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// 4. The user defined roaring bitmap shouldn't contains the id of the first document anymore
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// 5. Clear the index
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// 6. The user defined roaring bitmap shouldn't contains the id of the second document
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let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
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let setting = meilisearch_types::settings::Settings::<Unchecked> {
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embedders: Setting::Set(maplit::btreemap! {
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S("manual") => Setting::Set(EmbeddingSettings {
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source: Setting::Set(milli::vector::settings::EmbedderSource::UserProvided),
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dimensions: Setting::Set(3),
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..Default::default()
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})
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}),
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..Default::default()
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};
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index_scheduler
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.register(
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KindWithContent::SettingsUpdate {
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index_uid: S("doggos"),
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new_settings: Box::new(setting),
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is_deletion: false,
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allow_index_creation: true,
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},
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None,
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false,
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)
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.unwrap();
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handle.advance_one_successful_batch();
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let content = serde_json::json!(
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[
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{
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"id": 0,
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"doggo": "kefir",
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"_vectors": {
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"manual": vec![0, 0, 0],
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}
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},
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{
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"id": 1,
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"doggo": "intel",
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"_vectors": {
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"manual": vec![1, 1, 1],
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}
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},
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]
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);
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let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0_u128).unwrap();
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let documents_count =
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read_json(serde_json::to_string_pretty(&content).unwrap().as_bytes(), &mut file)
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.unwrap();
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snapshot!(documents_count, @"2");
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file.persist().unwrap();
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index_scheduler
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.register(
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KindWithContent::DocumentAdditionOrUpdate {
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index_uid: S("doggos"),
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primary_key: None,
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method: ReplaceDocuments,
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content_file: uuid,
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documents_count,
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allow_index_creation: false,
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},
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None,
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false,
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)
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.unwrap();
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handle.advance_one_successful_batch();
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index_scheduler
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.register(
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KindWithContent::DocumentDeletion {
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index_uid: S("doggos"),
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documents_ids: vec![S("1")],
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},
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None,
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false,
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)
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.unwrap();
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handle.advance_one_successful_batch();
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let index = index_scheduler.index("doggos").unwrap();
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let rtxn = index.read_txn().unwrap();
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let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
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let field_ids = field_ids_map.ids().collect::<Vec<_>>();
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let documents = index
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.all_documents(&rtxn)
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.unwrap()
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.map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
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.collect::<Vec<_>>();
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snapshot!(serde_json::to_string(&documents).unwrap(), @r###"[{"id":0,"doggo":"kefir"}]"###);
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let conf = index.embedding_configs(&rtxn).unwrap();
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// TODO: Here the user provided vectors should NOT contains 1
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snapshot!(format!("{conf:#?}"), @r###"
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[
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IndexEmbeddingConfig {
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name: "manual",
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config: EmbeddingConfig {
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embedder_options: UserProvided(
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EmbedderOptions {
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dimensions: 3,
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distribution: None,
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},
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),
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prompt: PromptData {
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template: "{% for field in fields %} {{ field.name }}: {{ field.value }}\n{% endfor %}",
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},
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},
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user_provided: RoaringBitmap<[0, 1]>,
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},
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]
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"###);
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let docid = index.external_documents_ids.get(&rtxn, "0").unwrap().unwrap();
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let embeddings = index.embeddings(&rtxn, docid).unwrap();
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let embedding = &embeddings["manual"];
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assert!(!embedding.is_empty(), "{embedding:?}");
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index_scheduler
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.register(KindWithContent::DocumentClear { index_uid: S("doggos") }, None, false)
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.unwrap();
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handle.advance_one_successful_batch();
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let index = index_scheduler.index("doggos").unwrap();
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let rtxn = index.read_txn().unwrap();
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let field_ids_map = index.fields_ids_map(&rtxn).unwrap();
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let field_ids = field_ids_map.ids().collect::<Vec<_>>();
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let documents = index
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.all_documents(&rtxn)
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.unwrap()
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.map(|ret| obkv_to_json(&field_ids, &field_ids_map, ret.unwrap().1).unwrap())
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.collect::<Vec<_>>();
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snapshot!(serde_json::to_string(&documents).unwrap(), @"[]");
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let conf = index.embedding_configs(&rtxn).unwrap();
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// TODO: Here the user provided vectors should contains nothing
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snapshot!(format!("{conf:#?}"), @r###"
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[
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IndexEmbeddingConfig {
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name: "manual",
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config: EmbeddingConfig {
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embedder_options: UserProvided(
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EmbedderOptions {
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dimensions: 3,
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distribution: None,
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},
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),
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prompt: PromptData {
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template: "{% for field in fields %} {{ field.name }}: {{ field.value }}\n{% endfor %}",
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},
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},
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user_provided: RoaringBitmap<[0, 1]>,
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},
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]
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"###);
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}
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}
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@ -1,5 +1,8 @@
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mod settings;
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use meili_snap::{json_string, snapshot};
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use crate::common::index::Index;
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use crate::common::{GetAllDocumentsOptions, Server};
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use crate::json;
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@ -147,3 +150,78 @@ async fn add_remove_user_provided() {
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}
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"###);
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}
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async fn generate_default_user_provided_documents(server: &Server) -> Index {
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let index = server.index("doggo");
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let (value, code) = server.set_features(json!({"vectorStore": true})).await;
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snapshot!(code, @"200 OK");
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snapshot!(value, @r###"
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{
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"vectorStore": true,
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"metrics": false,
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"logsRoute": false
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}
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"###);
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"manual": {
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"source": "userProvided",
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"dimensions": 3,
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}
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},
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}))
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.await;
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snapshot!(code, @"202 Accepted");
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server.wait_task(response.uid()).await;
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let documents = json!([
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{"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
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{"id": 1, "name": "echo", "_vectors": { "manual": [1, 1, 1] }},
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{"id": 2, "name": "billou", "_vectors": { "manual": [[2, 2, 2], [2, 2, 3]] }},
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{"id": 3, "name": "intel", "_vectors": { "manual": { "userProvided": true, "embeddings": [3, 3, 3] }}},
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{"id": 4, "name": "max", "_vectors": { "manual": { "userProvided": true, "embeddings": [[4, 4, 4], [4, 4, 5]] }}},
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]);
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let (value, code) = index.add_documents(documents, None).await;
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snapshot!(code, @"202 Accepted");
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index.wait_task(value.uid()).await;
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index
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}
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#[actix_rt::test]
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async fn clear_documents() {
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let server = Server::new().await;
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let index = generate_default_user_provided_documents(&server).await;
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let (value, _code) = index.clear_all_documents().await;
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index.wait_task(value.uid()).await;
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// Make sure the documents DB has been cleared
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let (documents, _code) = index
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.get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
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.await;
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snapshot!(json_string!(documents), @r###"
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{
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"results": [],
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"offset": 0,
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"limit": 20,
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"total": 0
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}
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"###);
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// Make sure the arroy DB has been cleared
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let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
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snapshot!(json_string!(documents), @r###"
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{
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"hits": [],
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"query": "",
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"processingTimeMs": 0,
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"limit": 20,
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"offset": 0,
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"estimatedTotalHits": 0,
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"semanticHitCount": 0
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}
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"###);
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}
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161
meilisearch/tests/vector/settings.rs
Normal file
161
meilisearch/tests/vector/settings.rs
Normal file
@ -0,0 +1,161 @@
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use meili_snap::{json_string, snapshot};
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use crate::common::{GetAllDocumentsOptions, Server};
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use crate::json;
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use crate::vector::generate_default_user_provided_documents;
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#[actix_rt::test]
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async fn update_embedder() {
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let server = Server::new().await;
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let index = server.index("doggo");
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let (value, code) = server.set_features(json!({"vectorStore": true})).await;
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snapshot!(code, @"200 OK");
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snapshot!(value, @r###"
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{
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"vectorStore": true,
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"metrics": false,
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"logsRoute": false
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}
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"###);
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let (response, code) = index
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.update_settings(json!({
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"embedders": { "manual": {}},
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}))
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.await;
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snapshot!(code, @"202 Accepted");
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server.wait_task(response.uid()).await;
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"manual": {
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"source": "userProvided",
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"dimensions": 2,
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}
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},
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}))
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.await;
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snapshot!(code, @"202 Accepted");
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let ret = server.wait_task(response.uid()).await;
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snapshot!(ret, @r###"
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{
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"uid": 1,
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"indexUid": "doggo",
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"status": "failed",
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"type": "settingsUpdate",
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"canceledBy": null,
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"details": {
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"embedders": {
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"manual": {
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"source": "userProvided",
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"dimensions": 2
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}
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}
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},
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"error": {
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"message": "`.embedders.manual`: Field `model` unavailable for source `userProvided` (only available for sources: `huggingFace`, `openAi`, `ollama`). Available fields: `source`, `dimensions`, `distribution`",
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"code": "invalid_settings_embedders",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
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},
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"duration": "[duration]",
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"enqueuedAt": "[date]",
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"startedAt": "[date]",
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"finishedAt": "[date]"
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}
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"###);
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}
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#[actix_rt::test]
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async fn reset_embedder_documents() {
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let server = Server::new().await;
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let index = generate_default_user_provided_documents(&server).await;
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let (response, code) = index.delete_settings().await;
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snapshot!(code, @"202 Accepted");
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server.wait_task(response.uid()).await;
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// Make sure the documents are still present
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let (documents, _code) = index.get_all_documents(Default::default()).await;
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snapshot!(json_string!(documents), @r###"
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{
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"results": [
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{
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"id": 0,
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"name": "kefir"
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},
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{
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"id": 1,
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"name": "echo"
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},
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{
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"id": 2,
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"name": "billou"
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},
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{
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"id": 3,
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"name": "intel"
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},
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{
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"id": 4,
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"name": "max"
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}
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],
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"offset": 0,
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"limit": 20,
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"total": 5
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}
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"###);
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// Make sure we are still able to retrieve their vectors
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let (documents, _code) = index
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.get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
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.await;
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snapshot!(json_string!(documents), @r###"
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{
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"results": [
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{
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"id": 0,
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"name": "kefir",
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"_vectors": {}
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},
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{
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"id": 1,
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"name": "echo",
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"_vectors": {}
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},
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{
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"id": 2,
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"name": "billou",
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"_vectors": {}
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},
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{
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"id": 3,
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"name": "intel",
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"_vectors": {}
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},
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{
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"id": 4,
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"name": "max",
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"_vectors": {}
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}
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],
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"offset": 0,
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"limit": 20,
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"total": 5
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}
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"###);
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// Make sure the arroy DB has been cleared
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let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
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snapshot!(json_string!(documents), @r###"
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{
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"message": "Cannot find embedder with name `default`.",
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"code": "invalid_embedder",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_embedder"
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}
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"###);
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}
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