mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-12-13 06:46:29 +01:00
b75f1f4c17
# Conflicts: # crates/index-scheduler/src/batch.rs # crates/index-scheduler/src/snapshots/lib.rs/fail_in_process_batch_for_document_deletion/after_removing_the_documents.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_bad_primary_key/fifth_task_succeeds.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_bad_primary_key/fourth_task_fails.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_multiple_primary_key/second_task_fails.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_multiple_primary_key/third_task_fails.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_multiple_primary_key_batch_wrong_key/second_and_third_tasks_fails.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_set_and_null_primary_key_inference_works/all_other_tasks_succeeds.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_set_and_null_primary_key_inference_works/second_task_fails.snap # crates/index-scheduler/src/snapshots/lib.rs/test_document_addition_with_set_and_null_primary_key_inference_works/third_task_succeeds.snap # Conflicts: # crates/index-scheduler/src/batch.rs # crates/meilisearch/src/search/mod.rs # crates/meilisearch/tests/vector/mod.rs # Conflicts: # crates/index-scheduler/src/batch.rs
744 lines
24 KiB
Rust
744 lines
24 KiB
Rust
mod binary_quantized;
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mod openai;
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mod rest;
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mod settings;
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use std::str::FromStr;
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use meili_snap::{json_string, snapshot};
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use meilisearch::option::MaxThreads;
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use crate::common::index::Index;
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use crate::common::{default_settings, GetAllDocumentsOptions, Server};
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use crate::json;
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async fn get_server_vector() -> Server {
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let server = Server::new().await;
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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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"editDocumentsByFunction": false,
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"containsFilter": false
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}
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"###);
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server
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}
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#[actix_rt::test]
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async fn add_remove_user_provided() {
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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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"editDocumentsByFunction": false,
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"containsFilter": 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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]);
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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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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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"manual": {
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"embeddings": [
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[
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0.0,
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0.0,
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0.0
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]
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],
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"regenerate": false
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}
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}
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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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"manual": {
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"embeddings": [
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[
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1.0,
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1.0,
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1.0
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]
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],
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"regenerate": false
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}
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}
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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": 2
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}
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"###);
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let documents = json!([
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{"id": 0, "name": "kefir", "_vectors": { "manual": [10, 10, 10] }},
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{"id": 1, "name": "echo", "_vectors": { "manual": null }},
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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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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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"manual": {
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"embeddings": [
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[
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10.0,
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10.0,
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10.0
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]
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],
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"regenerate": false
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}
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}
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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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"manual": {
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"embeddings": [],
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"regenerate": false
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}
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}
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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": 2
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}
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"###);
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let (value, code) = index.delete_document(0).await;
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snapshot!(code, @"202 Accepted");
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index.wait_task(value.uid()).await;
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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": 1,
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"name": "echo",
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"_vectors": {
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"manual": {
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"embeddings": [],
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"regenerate": false
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}
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}
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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": 1
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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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"editDocumentsByFunction": false,
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"containsFilter": 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": { "regenerate": false, "embeddings": [3, 3, 3] }}},
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{"id": 4, "name": "max", "_vectors": { "manual": { "regenerate": false, "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 user_provided_embeddings_error() {
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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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// First case, we forget to specify the `regenerate`
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let documents =
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json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [0, 0, 0] }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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// Second case, we don't specify anything
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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": {}}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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// Third case, we specify something wrong in place of regenerate
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let documents =
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json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": "yes please" }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Could not parse `._vectors.manual.regenerate`: invalid type: string \"yes please\", expected a boolean at line 1 column 26",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": true, "regenerate": true }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings`: expected null or an array, but found a boolean: `true`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [true], "regenerate": true }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [[true]], "regenerate": false }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [23, 0.1, -12], "regenerate": true }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task["status"], @r###""succeeded""###);
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let documents =
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json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task["status"], @r###""succeeded""###);
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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [0.1, [0.2, 0.3]] }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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"status": "failed",
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"type": "documentAdditionOrUpdate",
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"canceledBy": null,
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"details": {
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"receivedDocuments": 1,
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"indexedDocuments": 0
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},
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"error": {
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"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
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"code": "invalid_vectors_type",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
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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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let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [[0.1, 0.2], 0.3] }}});
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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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let task = index.wait_task(value.uid()).await;
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snapshot!(task, @r###"
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{
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"uid": "[uid]",
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"batchUid": "[batch_uid]",
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"indexUid": "doggo",
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|
"status": "failed",
|
|
"type": "documentAdditionOrUpdate",
|
|
"canceledBy": null,
|
|
"details": {
|
|
"receivedDocuments": 1,
|
|
"indexedDocuments": 0
|
|
},
|
|
"error": {
|
|
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.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": "[uid]",
|
|
"batchUid": "[batch_uid]",
|
|
"indexUid": "doggo",
|
|
"status": "failed",
|
|
"type": "documentAdditionOrUpdate",
|
|
"canceledBy": null,
|
|
"details": {
|
|
"receivedDocuments": 1,
|
|
"indexedDocuments": 0
|
|
},
|
|
"error": {
|
|
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.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 temp = tempfile::tempdir().unwrap();
|
|
let mut options = default_settings(temp.path());
|
|
// If we have more than one indexing thread the error messages below may become inconsistent
|
|
options.indexer_options.max_indexing_threads = MaxThreads::from_str("1").unwrap();
|
|
let server = Server::new_with_options(options).await.unwrap();
|
|
|
|
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": "[uid]",
|
|
"batchUid": "[batch_uid]",
|
|
"indexUid": "doggo",
|
|
"status": "failed",
|
|
"type": "documentAdditionOrUpdate",
|
|
"canceledBy": null,
|
|
"details": {
|
|
"receivedDocuments": 5,
|
|
"indexedDocuments": 0
|
|
},
|
|
"error": {
|
|
"message": "Index `doggo`: 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": "[uid]",
|
|
"batchUid": "[batch_uid]",
|
|
"indexUid": "doggo",
|
|
"status": "failed",
|
|
"type": "documentAdditionOrUpdate",
|
|
"canceledBy": null,
|
|
"details": {
|
|
"receivedDocuments": 1,
|
|
"indexedDocuments": 0
|
|
},
|
|
"error": {
|
|
"message": "Index `doggo`: 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": "[uid]",
|
|
"batchUid": "[batch_uid]",
|
|
"indexUid": "doggo",
|
|
"status": "failed",
|
|
"type": "documentAdditionOrUpdate",
|
|
"canceledBy": null,
|
|
"details": {
|
|
"receivedDocuments": 1,
|
|
"indexedDocuments": 0
|
|
},
|
|
"error": {
|
|
"message": "Index `doggo`: 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], "hybrid": {"embedder": "manual"} })).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], "hybrid": {"semanticRatio": 1.0, "embedder": "manual"} }),
|
|
)
|
|
.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
|
|
}
|
|
"###);
|
|
}
|