mod rest; mod settings; use meili_snap::{json_string, snapshot}; use crate::common::index::Index; use crate::common::{GetAllDocumentsOptions, Server}; use crate::json; #[actix_rt::test] async fn add_remove_user_provided() { let server = Server::new().await; let index = server.index("doggo"); let (value, code) = server.set_features(json!({"vectorStore": true})).await; snapshot!(code, @"200 OK"); snapshot!(value, @r###" { "vectorStore": true, "metrics": false, "logsRoute": false, "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": [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, "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": [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 user_provided_vectors_error() { let server = Server::new().await; let index = generate_default_user_provided_documents(&server).await; // First case, we forget to specify `_vectors` let documents = json!([{"id": 40, "name": "kefir"}, {"id": 41, "name": "intel"}, {"id": 42, "name": "max"}, {"id": 43, "name": "venus"}, {"id": 44, "name": "eva"}]); 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": 5, "indexedDocuments": 0 }, "error": { "message": "While embedding documents for embedder `manual`: no vectors provided for document \"40\" and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`", "code": "vector_embedding_error", "type": "invalid_request", "link": "https://docs.meilisearch.com/errors#vector_embedding_error" }, "duration": "[duration]", "enqueuedAt": "[date]", "startedAt": "[date]", "finishedAt": "[date]" } "###); // Second case, we provide `_vectors` with a typo let documents = json!({"id": 42, "name": "kefir", "_vector": { "manaul": [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": 3, "indexUid": "doggo", "status": "failed", "type": "documentAdditionOrUpdate", "canceledBy": null, "details": { "receivedDocuments": 1, "indexedDocuments": 0 }, "error": { "message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).", "code": "vector_embedding_error", "type": "invalid_request", "link": "https://docs.meilisearch.com/errors#vector_embedding_error" }, "duration": "[duration]", "enqueuedAt": "[date]", "startedAt": "[date]", "finishedAt": "[date]" } "###); // Third case, we specify the embedder with a typo let documents = json!({"id": 42, "name": "kefir", "_vectors": { "manaul": [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": 4, "indexUid": "doggo", "status": "failed", "type": "documentAdditionOrUpdate", "canceledBy": null, "details": { "receivedDocuments": 1, "indexedDocuments": 0 }, "error": { "message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).", "code": "vector_embedding_error", "type": "invalid_request", "link": "https://docs.meilisearch.com/errors#vector_embedding_error" }, "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, "editDocumentsByFunction": false, "containsFilter": 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 } "###); }