mirror of
https://github.com/meilisearch/MeiliSearch
synced 2025-07-03 11:57:07 +02:00
Merge branch 'main' into tmp-release-v1.11.0
This commit is contained in:
commit
cf6ad1ae5e
1071 changed files with 263 additions and 106 deletions
380
crates/meilisearch/tests/vector/binary_quantized.rs
Normal file
380
crates/meilisearch/tests/vector/binary_quantized.rs
Normal file
|
@ -0,0 +1,380 @@
|
|||
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 retrieve_binary_quantize_status_in_the_settings() {
|
||||
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.succeeded();
|
||||
|
||||
let (settings, code) = index.settings().await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(settings["embedders"]["manual"], @r###"{"source":"userProvided","dimensions":3}"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
"binaryQuantized": false,
|
||||
}
|
||||
},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let (settings, code) = index.settings().await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(settings["embedders"]["manual"], @r###"{"source":"userProvided","dimensions":3,"binaryQuantized":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.succeeded();
|
||||
|
||||
let (settings, code) = index.settings().await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(settings["embedders"]["manual"], @r###"{"source":"userProvided","dimensions":3,"binaryQuantized":true}"###);
|
||||
}
|
||||
|
||||
#[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.succeeded();
|
||||
|
||||
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.succeeded();
|
||||
|
||||
// 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 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.succeeded();
|
||||
|
||||
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.succeeded();
|
||||
|
||||
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.succeeded();
|
||||
|
||||
// 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.succeeded();
|
||||
|
||||
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.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
|
||||
"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.succeeded();
|
||||
|
||||
// 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!({ "hybrid": { "embedder": "manual" }, "vector": [1, 1, 1] })).await;
|
||||
snapshot!(documents, @r###"
|
||||
{
|
||||
"hits": [],
|
||||
"query": "",
|
||||
"processingTimeMs": "[duration]",
|
||||
"limit": 20,
|
||||
"offset": 0,
|
||||
"estimatedTotalHits": 0,
|
||||
"semanticHitCount": 0
|
||||
}
|
||||
"###);
|
||||
}
|
BIN
crates/meilisearch/tests/vector/intel_gen.txt.gz
Normal file
BIN
crates/meilisearch/tests/vector/intel_gen.txt.gz
Normal file
Binary file not shown.
734
crates/meilisearch/tests/vector/mod.rs
Normal file
734
crates/meilisearch/tests/vector/mod.rs
Normal file
|
@ -0,0 +1,734 @@
|
|||
mod binary_quantized;
|
||||
mod openai;
|
||||
mod rest;
|
||||
mod settings;
|
||||
|
||||
use std::str::FromStr;
|
||||
|
||||
use meili_snap::{json_string, snapshot};
|
||||
use meilisearch::option::MaxThreads;
|
||||
|
||||
use crate::common::index::Index;
|
||||
use crate::common::{default_settings, GetAllDocumentsOptions, Server};
|
||||
use crate::json;
|
||||
|
||||
async fn get_server_vector() -> Server {
|
||||
let server = Server::new().await;
|
||||
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
|
||||
}
|
||||
"###);
|
||||
server
|
||||
}
|
||||
|
||||
#[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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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 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]",
|
||||
"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": "[uid]",
|
||||
"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": "[uid]",
|
||||
"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], "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
|
||||
}
|
||||
"###);
|
||||
}
|
1876
crates/meilisearch/tests/vector/openai.rs
Normal file
1876
crates/meilisearch/tests/vector/openai.rs
Normal file
File diff suppressed because it is too large
Load diff
BIN
crates/meilisearch/tests/vector/openai_responses.json.gz
Normal file
BIN
crates/meilisearch/tests/vector/openai_responses.json.gz
Normal file
Binary file not shown.
Binary file not shown.
2045
crates/meilisearch/tests/vector/rest.rs
Normal file
2045
crates/meilisearch/tests/vector/rest.rs
Normal file
File diff suppressed because it is too large
Load diff
278
crates/meilisearch/tests/vector/settings.rs
Normal file
278
crates/meilisearch/tests/vector/settings.rs
Normal file
|
@ -0,0 +1,278 @@
|
|||
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 field_unavailable_for_source() {
|
||||
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", "documentTemplate": "{{doc.documentTemplate}}"}},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "`.embedders.manual`: Field `documentTemplate` unavailable for source `userProvided` (only available for sources: `huggingFace`, `openAi`, `ollama`, `rest`). Available fields: `source`, `dimensions`, `distribution`, `binaryQuantized`",
|
||||
"code": "invalid_settings_embedders",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": { "default": {"source": "openAi", "revision": "42"}},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "`.embedders.default`: Field `revision` unavailable for source `openAi` (only available for sources: `huggingFace`). Available fields: `source`, `model`, `apiKey`, `documentTemplate`, `dimensions`, `distribution`, `url`, `binaryQuantized`",
|
||||
"code": "invalid_settings_embedders",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn update_embedder() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("doggo");
|
||||
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(value, @r###"
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false,
|
||||
"editDocumentsByFunction": false,
|
||||
"containsFilter": false
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": { "manual": {}},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 2,
|
||||
}
|
||||
},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
|
||||
let ret = server.wait_task(response.uid()).await;
|
||||
snapshot!(ret, @r###"
|
||||
{
|
||||
"uid": "[uid]",
|
||||
"indexUid": "doggo",
|
||||
"status": "succeeded",
|
||||
"type": "settingsUpdate",
|
||||
"canceledBy": null,
|
||||
"details": {
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 2
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": null,
|
||||
"duration": "[duration]",
|
||||
"enqueuedAt": "[date]",
|
||||
"startedAt": "[date]",
|
||||
"finishedAt": "[date]"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn reset_embedder_documents() {
|
||||
let server = Server::new().await;
|
||||
let index = generate_default_user_provided_documents(&server).await;
|
||||
|
||||
let (response, code) = index.delete_settings().await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
// Make sure the documents are still present
|
||||
let (documents, _code) = index
|
||||
.get_all_documents(GetAllDocumentsOptions {
|
||||
limit: None,
|
||||
offset: None,
|
||||
retrieve_vectors: false,
|
||||
fields: None,
|
||||
})
|
||||
.await;
|
||||
snapshot!(json_string!(documents), @r###"
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"id": 0,
|
||||
"name": "kefir"
|
||||
},
|
||||
{
|
||||
"id": 1,
|
||||
"name": "echo"
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"name": "billou"
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"name": "intel"
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"name": "max"
|
||||
}
|
||||
],
|
||||
"offset": 0,
|
||||
"limit": 20,
|
||||
"total": 5
|
||||
}
|
||||
"###);
|
||||
|
||||
// Make sure we are still able to retrieve their vectors
|
||||
let (documents, _code) = index
|
||||
.get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
|
||||
.await;
|
||||
snapshot!(json_string!(documents), @r###"
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"id": 0,
|
||||
"name": "kefir",
|
||||
"_vectors": {
|
||||
"manual": {
|
||||
"embeddings": [
|
||||
[
|
||||
0.0,
|
||||
0.0,
|
||||
0.0
|
||||
]
|
||||
],
|
||||
"regenerate": false
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 1,
|
||||
"name": "echo",
|
||||
"_vectors": {
|
||||
"manual": {
|
||||
"embeddings": [
|
||||
[
|
||||
1.0,
|
||||
1.0,
|
||||
1.0
|
||||
]
|
||||
],
|
||||
"regenerate": false
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"name": "billou",
|
||||
"_vectors": {
|
||||
"manual": {
|
||||
"embeddings": [
|
||||
[
|
||||
2.0,
|
||||
2.0,
|
||||
2.0
|
||||
],
|
||||
[
|
||||
2.0,
|
||||
2.0,
|
||||
3.0
|
||||
]
|
||||
],
|
||||
"regenerate": false
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"name": "intel",
|
||||
"_vectors": {
|
||||
"manual": {
|
||||
"embeddings": [
|
||||
[
|
||||
3.0,
|
||||
3.0,
|
||||
3.0
|
||||
]
|
||||
],
|
||||
"regenerate": false
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"name": "max",
|
||||
"_vectors": {
|
||||
"manual": {
|
||||
"embeddings": [
|
||||
[
|
||||
4.0,
|
||||
4.0,
|
||||
4.0
|
||||
],
|
||||
[
|
||||
4.0,
|
||||
4.0,
|
||||
5.0
|
||||
]
|
||||
],
|
||||
"regenerate": false
|
||||
}
|
||||
}
|
||||
}
|
||||
],
|
||||
"offset": 0,
|
||||
"limit": 20,
|
||||
"total": 5
|
||||
}
|
||||
"###);
|
||||
|
||||
// Make sure the arroy DB has been cleared
|
||||
let (documents, _code) =
|
||||
index.search_post(json!({ "vector": [1, 1, 1], "hybrid": {"embedder": "default"} })).await;
|
||||
snapshot!(json_string!(documents), @r###"
|
||||
{
|
||||
"message": "Cannot find embedder with name `default`.",
|
||||
"code": "invalid_embedder",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_embedder"
|
||||
}
|
||||
"###);
|
||||
}
|
|
@ -0,0 +1,19 @@
|
|||
---
|
||||
source: meilisearch/tests/vector/mod.rs
|
||||
---
|
||||
{
|
||||
"uid": "[uid]",
|
||||
"indexUid": "doggo",
|
||||
"status": "succeeded",
|
||||
"type": "documentAdditionOrUpdate",
|
||||
"canceledBy": null,
|
||||
"details": {
|
||||
"receivedDocuments": 1,
|
||||
"indexedDocuments": 1
|
||||
},
|
||||
"error": null,
|
||||
"duration": "[duration]",
|
||||
"enqueuedAt": "[date]",
|
||||
"startedAt": "[date]",
|
||||
"finishedAt": "[date]"
|
||||
}
|
|
@ -0,0 +1,19 @@
|
|||
---
|
||||
source: meilisearch/tests/vector/mod.rs
|
||||
---
|
||||
{
|
||||
"uid": "[uid]",
|
||||
"indexUid": "doggo",
|
||||
"status": "succeeded",
|
||||
"type": "documentAdditionOrUpdate",
|
||||
"canceledBy": null,
|
||||
"details": {
|
||||
"receivedDocuments": 1,
|
||||
"indexedDocuments": 1
|
||||
},
|
||||
"error": null,
|
||||
"duration": "[duration]",
|
||||
"enqueuedAt": "[date]",
|
||||
"startedAt": "[date]",
|
||||
"finishedAt": "[date]"
|
||||
}
|
|
@ -0,0 +1,23 @@
|
|||
---
|
||||
source: meilisearch/tests/vector/mod.rs
|
||||
---
|
||||
{
|
||||
"uid": "[uid]",
|
||||
"indexUid": "doggo",
|
||||
"status": "succeeded",
|
||||
"type": "settingsUpdate",
|
||||
"canceledBy": null,
|
||||
"details": {
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": null,
|
||||
"duration": "[duration]",
|
||||
"enqueuedAt": "[date]",
|
||||
"startedAt": "[date]",
|
||||
"finishedAt": "[date]"
|
||||
}
|
Loading…
Add table
Add a link
Reference in a new issue