Merge branch 'main' into tmp-release-v1.11.0

This commit is contained in:
Tamo 2024-11-04 16:14:44 +01:00
commit cf6ad1ae5e
1071 changed files with 263 additions and 106 deletions

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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
}
"###);
}

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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
}
"###);
}

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@ -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"
}
"###);
}

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@ -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]"
}

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@ -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]"
}

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@ -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]"
}