mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-30 16:52:55 +01:00
232 lines
5.3 KiB
Rust
232 lines
5.3 KiB
Rust
use meili_snap::{json_string, snapshot};
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use crate::common::{GetAllDocumentsOptions, Server};
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use crate::json;
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use crate::vector::generate_default_user_provided_documents;
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#[actix_rt::test]
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async fn update_embedder() {
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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": { "manual": {}},
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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 (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": 2,
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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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let ret = server.wait_task(response.uid()).await;
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snapshot!(ret, @r###"
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{
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"uid": "[uid]",
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"indexUid": "doggo",
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"status": "succeeded",
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"type": "settingsUpdate",
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"canceledBy": null,
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"details": {
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"embedders": {
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"manual": {
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"source": "userProvided",
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"dimensions": 2
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}
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}
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},
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"error": null,
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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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}
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#[actix_rt::test]
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async fn reset_embedder_documents() {
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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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let (response, code) = index.delete_settings().await;
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snapshot!(code, @"202 Accepted");
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server.wait_task(response.uid()).await;
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// Make sure the documents are still present
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let (documents, _code) = index
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.get_all_documents(GetAllDocumentsOptions {
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limit: None,
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offset: None,
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retrieve_vectors: false,
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fields: None,
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})
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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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},
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{
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"id": 1,
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"name": "echo"
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},
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{
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"id": 2,
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"name": "billou"
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},
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{
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"id": 3,
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"name": "intel"
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},
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{
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"id": 4,
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"name": "max"
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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": 5
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}
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"###);
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// Make sure we are still able to retrieve their vectors
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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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"id": 2,
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"name": "billou",
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"_vectors": {
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"manual": {
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"embeddings": [
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[
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2.0,
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2.0,
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2.0
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],
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[
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2.0,
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2.0,
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3.0
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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": 3,
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"name": "intel",
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"_vectors": {
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"manual": {
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"embeddings": [
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[
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3.0,
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3.0,
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3.0
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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": 4,
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"name": "max",
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"_vectors": {
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"manual": {
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"embeddings": [
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[
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4.0,
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4.0,
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4.0
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],
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[
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4.0,
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4.0,
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5.0
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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": 5
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}
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"###);
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// Make sure the arroy DB has been cleared
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let (documents, _code) =
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index.search_post(json!({ "vector": [1, 1, 1], "hybrid": {"embedder": "default"} })).await;
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snapshot!(json_string!(documents), @r###"
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{
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"message": "Cannot find embedder with name `default`.",
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"code": "invalid_embedder",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#invalid_embedder"
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}
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"###);
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}
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