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 binary_quantize_before_sending_documents() { 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, "editDocumentsByFunction": false, "containsFilter": false } "###); let (response, code) = index .update_settings(json!({ "embedders": { "manual": { "source": "userProvided", "dimensions": 3, "binaryQuantized": true, } }, })) .await; snapshot!(code, @"202 Accepted"); server.wait_task(response.uid()).await; let documents = json!([ {"id": 0, "name": "kefir", "_vectors": { "manual": [-1.2, -2.3, 3.2] }}, {"id": 1, "name": "echo", "_vectors": { "manual": [2.5, 1.5, -130] }}, ]); let (value, code) = index.add_documents(documents, None).await; snapshot!(code, @"202 Accepted"); 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###" { "message": "internal: Invalid distance provided. Got binary quantized angular but expected angular.", "code": "internal", "type": "internal", "link": "https://docs.meilisearch.com/errors#internal" } "###); // Make sure the arroy DB has been cleared let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await; snapshot!(documents, @r###" { "message": "internal: Invalid distance provided. Got binary quantized angular but expected angular.", "code": "internal", "type": "internal", "link": "https://docs.meilisearch.com/errors#internal" } "###); } #[actix_rt::test] async fn binary_quantize_after_sending_documents() { 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, "editDocumentsByFunction": false, "containsFilter": 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": [-1.2, -2.3, 3.2] }}, {"id": 1, "name": "echo", "_vectors": { "manual": [2.5, 1.5, -130] }}, ]); let (value, code) = index.add_documents(documents, None).await; snapshot!(code, @"202 Accepted"); index.wait_task(value.uid()).await; let (response, code) = index .update_settings(json!({ "embedders": { "manual": { "source": "userProvided", "dimensions": 3, "binaryQuantized": true, } }, })) .await; snapshot!(code, @"202 Accepted"); server.wait_task(response.uid()).await; // Make sure the documents are binary quantized 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": [ [ -1.0, -1.0, 1.0 ] ], "regenerate": false } } }, { "id": 1, "name": "echo", "_vectors": { "manual": { "embeddings": [ [ 1.0, 1.0, -1.0 ] ], "regenerate": false } } } ], "offset": 0, "limit": 20, "total": 2 } "###); } #[actix_rt::test] async fn try_to_disable_binary_quantization() { 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, "editDocumentsByFunction": false, "containsFilter": false } "###); let (response, code) = index .update_settings(json!({ "embedders": { "manual": { "source": "userProvided", "dimensions": 3, "binaryQuantized": true, } }, })) .await; snapshot!(code, @"202 Accepted"); server.wait_task(response.uid()).await; let (response, code) = index .update_settings(json!({ "embedders": { "manual": { "source": "userProvided", "dimensions": 3, "binaryQuantized": false, } }, })) .await; snapshot!(code, @"202 Accepted"); let ret = server.wait_task(response.uid()).await; snapshot!(ret, @r###" { "uid": "[uid]", "indexUid": "doggo", "status": "failed", "type": "settingsUpdate", "canceledBy": null, "details": { "embedders": { "manual": { "source": "userProvided", "dimensions": 3, "binaryQuantized": false } } }, "error": { "message": "`.embedders.manual.binaryQuantized`: Cannot disable the binary quantization", "code": "invalid_settings_embedders", "type": "invalid_request", "link": "https://docs.meilisearch.com/errors#invalid_settings_embedders" }, "duration": "[duration]", "enqueuedAt": "[date]", "startedAt": "[date]", "finishedAt": "[date]" } "###); } #[actix_rt::test] async fn binary_quantize_clear_documents() { let server = Server::new().await; let index = generate_default_user_provided_documents(&server).await; let (response, code) = index .update_settings(json!({ "embedders": { "manual": { "binaryQuantized": true, } }, })) .await; snapshot!(code, @"202 Accepted"); server.wait_task(response.uid()).await.succeeded(); 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 } "###); }