2024-09-02 13:37:01 +02:00

2046 lines
62 KiB
Rust

use std::collections::BTreeMap;
use std::sync::atomic::{AtomicUsize, Ordering};
use meili_snap::{json_string, snapshot};
use reqwest::IntoUrl;
use wiremock::matchers::{method, path};
use wiremock::{Mock, MockServer, Request, ResponseTemplate};
use crate::common::Value;
use crate::json;
use crate::vector::{get_server_vector, GetAllDocumentsOptions};
async fn create_mock() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let counter = AtomicUsize::new(0);
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |_req: &Request| {
let counter = counter.fetch_add(1, Ordering::Relaxed);
ResponseTemplate::new(200).set_body_json(json!({ "data": vec![counter; 3] }))
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"dimensions": 3,
"request": "{{text}}",
"response": {
"data": "{{embedding}}"
}
});
(mock_server, embedder_settings)
}
async fn create_mock_map() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let text_to_embedding: BTreeMap<_, _> = vec![
// text -> embedding
("name: kefir\n", [0.0, 0.1, 0.2]),
]
// turn into btree
.into_iter()
.collect();
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |req: &Request| {
let text: String = req.body_json().unwrap();
match text_to_embedding.get(text.as_str()) {
Some(embedding) => {
ResponseTemplate::new(200).set_body_json(json!({ "data": embedding }))
}
None => ResponseTemplate::new(404)
.set_body_json(json!({"error": "text not found", "text": text})),
}
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"dimensions": 3,
"request": "{{text}}",
"response": {
"data": "{{embedding}}"
}
});
(mock_server, embedder_settings)
}
#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
struct MultipleRequest {
input: Vec<String>,
}
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
struct MultipleResponse {
output: Vec<SingleResponse>,
}
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
struct SingleResponse {
text: String,
embedding: Vec<f32>,
}
async fn create_mock_multiple() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let counter = AtomicUsize::new(0);
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |req: &Request| {
let req: MultipleRequest = match req.body_json() {
Ok(req) => req,
Err(error) => {
return ResponseTemplate::new(400).set_body_json(json!({
"error": format!("Invalid request: {error}")
}));
}
};
let output = req
.input
.into_iter()
.map(|text| SingleResponse {
text,
embedding: vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3],
})
.collect();
let response = MultipleResponse { output };
ResponseTemplate::new(200).set_body_json(response)
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"dimensions": 3,
"request": {
"input": ["{{text}}", "{{..}}"]
},
"response": {
"output": [
{
"embedding": "{{embedding}}"
},
"{{..}}"
]
}
});
(mock_server, embedder_settings)
}
#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
struct SingleRequest {
input: String,
}
async fn create_mock_single_response_in_array() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let counter = AtomicUsize::new(0);
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |req: &Request| {
let req: SingleRequest = match req.body_json() {
Ok(req) => req,
Err(error) => {
return ResponseTemplate::new(400).set_body_json(json!({
"error": format!("Invalid request: {error}")
}));
}
};
let output = vec![SingleResponse {
text: req.input,
embedding: vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3],
}];
let response = MultipleResponse { output };
ResponseTemplate::new(200).set_body_json(response)
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"dimensions": 3,
"request": {
"input": "{{text}}"
},
"response": {
"output": [
{
"embedding": "{{embedding}}"
}
]
}
});
(mock_server, embedder_settings)
}
async fn create_mock_raw_with_custom_header() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let counter = AtomicUsize::new(0);
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |req: &Request| {
match req.headers.get("my-nonstandard-auth") {
Some(x) if x == "bearer of the ring" => {}
Some(x) => {
return ResponseTemplate::new(401).set_body_json(
json!({"error": format!("thou shall not pass, {}", x.to_str().unwrap())}),
)
}
None => {
return ResponseTemplate::new(401)
.set_body_json(json!({"error": "missing header 'my-nonstandard-auth'"}))
}
}
let _req: String = match req.body_json() {
Ok(req) => req,
Err(error) => {
return ResponseTemplate::new(400).set_body_json(json!({
"error": format!("Invalid request: {error}")
}));
}
};
let output = vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3];
ResponseTemplate::new(200).set_body_json(output)
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"request": "{{text}}",
"response": "{{embedding}}",
"headers": {"my-nonstandard-auth": "bearer of the ring"}
});
(mock_server, embedder_settings)
}
async fn create_mock_raw() -> (MockServer, Value) {
let mock_server = MockServer::start().await;
let counter = AtomicUsize::new(0);
Mock::given(method("POST"))
.and(path("/"))
.respond_with(move |req: &Request| {
let _req: String = match req.body_json() {
Ok(req) => req,
Err(error) => {
return ResponseTemplate::new(400).set_body_json(json!({
"error": format!("Invalid request: {error}")
}));
}
};
let output = vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3];
ResponseTemplate::new(200).set_body_json(output)
})
.mount(&mock_server)
.await;
let url = mock_server.uri();
let embedder_settings = json!({
"source": "rest",
"url": url,
"dimensions": 3,
"request": "{{text}}",
"response": "{{embedding}}"
});
(mock_server, embedder_settings)
}
pub async fn post<T: IntoUrl>(url: T) -> reqwest::Result<reqwest::Response> {
reqwest::Client::builder().build()?.post(url).send().await
}
#[actix_rt::test]
async fn dummy_testing_the_mock() {
let (mock, _setting) = create_mock().await;
let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
snapshot!(body, @r###"{"data":[0,0,0]}"###);
let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
snapshot!(body, @r###"{"data":[1,1,1]}"###);
let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
snapshot!(body, @r###"{"data":[2,2,2]}"###);
let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
snapshot!(body, @r###"{"data":[3,3,3]}"###);
let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
snapshot!(body, @r###"{"data":[4,4,4]}"###);
}
#[actix_rt::test]
async fn bad_request() {
let (mock, _setting) = create_mock().await;
let server = get_server_vector().await;
let index = server.index("doggo");
// No placeholder string appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "54", "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request`: \"{{text}}\" not found",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears inside a repeated value
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": [
{
"input": [
"{{text}}",
"{{..}}"
]
},
"{{..}}"
]
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.input.input`: \"{{..}}\" appears nested inside of a value that is itself repeated",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears outside of an array
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": {
"input": "{{text}}",
"repeat": "{{..}}"
}
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.input.repeat`: \"{{..}}\" appears outside of an array",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears in an array, but not in the second position
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": [
"{{..}}",
"{{text}}"
]
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.input`: \"{{..}}\" expected at position #1, but found at position #0",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": [
"{{text}}",
"42",
"{{..}}",
]
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.input`: \"{{..}}\" expected at position #1, but found at position #2",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeated value lacks a placeholder
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": [
"42",
"{{..}}",
]
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.input[0]`: Expected \"{{text}}\" inside of the repeated value",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// Multiple repeat strings appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": [
"{{text}}",
"{{..}}",
],
"data": [
"42",
"{{..}}",
],
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.data`: Found \"{{..}}\", but it was already present in `request.input`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// Multiple placeholder strings appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": "{{text}}",
"data": "{{text}}",
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.data`: Found \"{{text}}\", but it was already present in `request.input`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request":
{"repeated": [{
"input": "{{text}}",
"data": [42, "{{text}}"],
}, "{{..}}"]}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.repeated.data[1]`: Found \"{{text}}\", but it was already present in `request.repeated.input`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A placeholder appears both inside a repeated value and outside of it
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
"input": ["{{text}}", "{{..}}"],
"data": "{{text}}",
}, "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request.data`: Found \"{{text}}\", but it was already present in `request.input[0]` (repeated)",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
}
#[actix_rt::test]
async fn bad_response() {
let (mock, _setting) = create_mock().await;
let server = get_server_vector().await;
let index = server.index("doggo");
// No placeholder string appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "42" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response`: \"{{embedding}}\" not found",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears inside a repeated value
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [
{
"output": [
"{{embedding}}",
"{{..}}"
]
},
"{{..}}"
]
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.output.output`: \"{{..}}\" appears nested inside of a value that is itself repeated",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears outside of an array
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": {
"output": "{{embedding}}",
"repeat": "{{..}}"
}
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.output.repeat`: \"{{..}}\" appears outside of an array",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeat string appears in an array, but not in the second position
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [
"{{..}}",
"{{embedding}}"
]
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.output`: \"{{..}}\" expected at position #1, but found at position #0",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [
"{{embedding}}",
"42",
"{{..}}",
]
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.output`: \"{{..}}\" expected at position #1, but found at position #2",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A repeated value lacks a placeholder
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [
"42",
"{{..}}",
]
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.output[0]`: Expected \"{{embedding}}\" inside of the repeated value",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// Multiple repeat strings appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [
"{{embedding}}",
"{{..}}",
],
"data": [
"42",
"{{..}}",
],
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.data`: Found \"{{..}}\", but it was already present in `response.output`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// Multiple placeholder strings appear in the template
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": [{"type": "data", "data": "{{embedding}}"}],
"data": "{{embedding}}",
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.data`: Found \"{{embedding}}\", but it was already present in `response.output[0].data`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response":
{"repeated": [{
"output": "{{embedding}}",
"data": [42, "{{embedding}}"],
}, "{{..}}"]}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.repeated.data[1]`: Found \"{{embedding}}\", but it was already present in `response.repeated.output`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// A placeholder appears both inside a repeated value and outside of it
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"output": ["{{embedding}}", "{{..}}"],
"data": "{{embedding}}",
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response.data`: Found \"{{embedding}}\", but it was already present in `response.output[0]` (repeated)",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// request sends a single text but response expects multiple embeddings
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"data": ["{{embedding}}", "{{..}}"],
}, "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response`: `response` has multiple embeddings, but `request` has only one text to embed",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
// request sends multiple texts but response expects a single embedding
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": {
"data": "{{embedding}}",
}, "request": {"data": ["{{text}}", "{{..}}"]} }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response`: `response` has a single embedding, but `request` has multiple texts to embed",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
}
#[actix_rt::test]
async fn bad_settings() {
let (mock, _setting) = create_mock().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "request": 42, "response": 42 }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `request`: \"{{text}}\" not found",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": "kefir", "request": 42, "response": 42 }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "`.embedders.rest.url`: could not parse `kefir`: relative URL without a base",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "response": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "`.embedders.rest`: Missing field `request` (note: this field is mandatory for source rest)",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}" }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "`.embedders.rest`: Missing field `response` (note: this field is mandatory for source rest)",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": 42 }),
},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Error while generating embeddings: user error: in `response`: \"{{embedding}}\" not found",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}"
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting a single \"{{embedding}}\", expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
// Validate an embedder with a bad dimension of 2 instead of 3
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": { "data": "{{embedding}}" }, "dimensions": 2 }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task["status"], @r###""succeeded""###);
let (response, code) = index.add_documents(json!( { "id": 1, "name": "kefir" }), None).await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.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 `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
"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 add_vector_and_user_provided() {
let (_mock, setting) = create_mock().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task["status"], @r###""succeeded""###);
let documents = json!([
{"id": 0, "name": "kefir"},
{"id": 1, "name": "echo", "_vectors": { "rest": [1, 1, 1] }},
{"id": 2, "name": "intel"},
]);
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": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 3,
"indexedDocuments": 3
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
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": {
"rest": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": true
}
}
},
{
"id": 1,
"name": "echo",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": false
}
}
},
{
"id": 2,
"name": "intel",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": true
}
}
}
],
"offset": 0,
"limit": 20,
"total": 3
}
"###);
}
#[actix_rt::test]
async fn server_returns_bad_request() {
let (mock, _setting) = create_mock_multiple().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}"
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"test\\\", expected struct MultipleRequest at line 1 column 6\"}`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"searchableAttributes": ["name", "missing_field"],
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "{{embedding}}", "dimensions": 3 }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "succeeded",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"searchableAttributes": [
"name",
"missing_field"
],
"embedders": {
"rest": {
"source": "rest",
"dimensions": 3,
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}"
}
}
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index.add_documents(json!( { "id": 1, "name": "kefir" }), None).await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.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 `rest`: user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"name: kefir\\\\n\\\", expected struct MultipleRequest at line 1 column 15\"}`",
"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 server_returns_bad_response() {
let (mock, _setting) = create_mock_multiple().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(),
"request": {
"input": ["{{text}}", "{{..}}"]
},
"response": ["{{embedding}}", "{{..}}"] }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": {
"input": [
"{{text}}",
"{{..}}"
]
},
"response": [
"{{embedding}}",
"{{..}}"
]
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting the array of \"{{embedding}}\"s, configuration expects `response` to be an array with at least 1 item(s) but server sent an object with 1 field(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]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(),
"request": {
"input": ["{{text}}", "{{..}}"]
},
"response": {
"output": ["{{embedding}}", "{{..}}"]
} }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": {
"input": [
"{{text}}",
"{{..}}"
]
},
"response": {
"output": [
"{{embedding}}",
"{{..}}"
]
}
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting item #0 from the array of \"{{embedding}}\"s, expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(),
"request": {
"input": ["{{text}}"]
},
"response": {
"output": "{{embedding}}"
} }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": {
"input": [
"{{text}}"
]
},
"response": {
"output": "{{embedding}}"
}
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output`, while extracting a single \"{{embedding}}\", expected `output` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected f32",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(),
"request": {
"input": ["{{text}}", "{{..}}"]
},
"response": {
"output": [{ "embedding":
{
"data": "{{embedding}}"
}
}, "{{..}}"]
} }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": {
"input": [
"{{text}}",
"{{..}}"
]
},
"response": {
"output": [
{
"embedding": {
"data": "{{embedding}}"
}
},
"{{..}}"
]
}
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.embedding`, while extracting item #0 from the array of \"{{embedding}}\"s, configuration expects `embedding` to be an object with key `data` but server sent an array of size 3",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(),
"request": {
"input": ["{{text}}"]
},
"response": {
"output": [
{ "embeddings":
{
"data": "{{embedding}}"
}
}
]
} }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": {
"input": [
"{{text}}"
]
},
"response": {
"output": [
{
"embeddings": {
"data": "{{embedding}}"
}
}
]
}
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output[0]`, while extracting a single \"{{embedding}}\", configuration expects key \"embeddings\", which is missing in response\n - Hint: item #0 inside `output` has key `embedding`, did you mean `response.output[0].embedding` in embedder configuration?",
"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 server_returns_multiple() {
let (_mock, setting) = create_mock_multiple().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task["status"], @r###""succeeded""###);
let documents = json!([
{"id": 0, "name": "kefir"},
{"id": 1, "name": "echo", "_vectors": { "rest": [1, 1, 1] }},
{"id": 2, "name": "intel"},
]);
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": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 3,
"indexedDocuments": 3
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
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": {
"rest": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": true
}
}
},
{
"id": 1,
"name": "echo",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": false
}
}
},
{
"id": 2,
"name": "intel",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": true
}
}
}
],
"offset": 0,
"limit": 20,
"total": 3
}
"###);
}
#[actix_rt::test]
async fn server_single_input_returns_in_array() {
let (_mock, setting) = create_mock_single_response_in_array().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task["status"], @r###""succeeded""###);
let documents = json!([
{"id": 0, "name": "kefir"},
{"id": 1, "name": "echo", "_vectors": { "rest": [1, 1, 1] }},
{"id": 2, "name": "intel"},
]);
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": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 3,
"indexedDocuments": 3
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
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": {
"rest": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": true
}
}
},
{
"id": 1,
"name": "echo",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": false
}
}
},
{
"id": 2,
"name": "intel",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": true
}
}
}
],
"offset": 0,
"limit": 20,
"total": 3
}
"###);
}
#[actix_rt::test]
async fn server_raw() {
let (_mock, setting) = create_mock_raw().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task["status"], @r###""succeeded""###);
let documents = json!([
{"id": 0, "name": "kefir"},
{"id": 1, "name": "echo", "_vectors": { "rest": [1, 1, 1] }},
{"id": 2, "name": "intel"},
]);
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": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 3,
"indexedDocuments": 3
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
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": {
"rest": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": true
}
}
},
{
"id": 1,
"name": "echo",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": false
}
}
},
{
"id": 2,
"name": "intel",
"_vectors": {
"rest": {
"embeddings": [
[
1.0,
1.0,
1.0
]
],
"regenerate": true
}
}
}
],
"offset": 0,
"limit": 20,
"total": 3
}
"###);
}
#[actix_rt::test]
async fn server_custom_header() {
let (mock, setting) = create_mock_raw_with_custom_header().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "{{embedding}}" }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}"
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"missing header 'my-nonstandard-auth'\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": json!({ "source": "rest", "url": mock.uri(), "request": "{{text}}", "response": "{{embedding}}", "headers": {"my-nonstandard-auth": "Balrog"} }),
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}",
"headers": {
"my-nonstandard-auth": "Balrog"
}
}
}
},
"error": {
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"thou shall not pass, Balrog\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "succeeded",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"rest": {
"source": "rest",
"url": "[url]",
"request": "{{text}}",
"response": "{{embedding}}",
"headers": {
"my-nonstandard-auth": "bearer of the ring"
}
}
}
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
}
#[actix_rt::test]
async fn searchable_reindex() {
let (_mock, setting) = create_mock_map().await;
let server = get_server_vector().await;
let index = server.index("doggo");
let (response, code) = index
.update_settings(json!({
"searchableAttributes": ["name", "missing_field"],
"embedders": {
"rest": setting,
},
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "succeeded",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"searchableAttributes": [
"name",
"missing_field"
],
"embedders": {
"rest": {
"source": "rest",
"dimensions": 3,
"url": "[url]",
"request": "{{text}}",
"response": {
"data": "{{embedding}}"
}
}
}
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) =
index.add_documents(json!( { "id": 1, "name": "kefir", "breed": "patou" }), None).await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"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]"
}
"###);
// triggers reindexing with the new searchable attribute.
// as the mock intentionally doesn't know of this text, the task will fail, outputting the putative rendered text.
let (response, code) = index
.update_settings(json!({
"searchableAttributes": ["breed"],
}))
.await;
snapshot!(code, @"202 Accepted");
let task = server.wait_task(response.uid()).await;
snapshot!(task, @r###"
{
"uid": "[uid]",
"indexUid": "doggo",
"status": "failed",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"searchableAttributes": [
"breed"
]
},
"error": {
"message": "While embedding documents for embedder `rest`: error: received unexpected HTTP 404 from embedding server\n - server replied with `{\"error\":\"text not found\",\"text\":\"breed: patou\\n\"}`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
},
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
}