mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-25 14:24:26 +01:00
2066 lines
63 KiB
Rust
2066 lines
63 KiB
Rust
use std::collections::BTreeMap;
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use std::sync::atomic::{AtomicUsize, Ordering};
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use meili_snap::{json_string, snapshot};
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use reqwest::IntoUrl;
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use wiremock::matchers::{method, path};
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use wiremock::{Mock, MockServer, Request, ResponseTemplate};
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use crate::common::Value;
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use crate::json;
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use crate::vector::{get_server_vector, GetAllDocumentsOptions};
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async fn create_mock() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let counter = AtomicUsize::new(0);
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |_req: &Request| {
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let counter = counter.fetch_add(1, Ordering::Relaxed);
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ResponseTemplate::new(200).set_body_json(json!({ "data": vec![counter; 3] }))
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"dimensions": 3,
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"request": "{{text}}",
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"response": {
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"data": "{{embedding}}"
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}
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});
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(mock_server, embedder_settings)
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}
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async fn create_mock_map() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let text_to_embedding: BTreeMap<_, _> = vec![
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// text -> embedding
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("name: kefir\n", [0.0, 0.1, 0.2]),
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]
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// turn into btree
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.into_iter()
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.collect();
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |req: &Request| {
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let text: String = req.body_json().unwrap();
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match text_to_embedding.get(text.as_str()) {
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Some(embedding) => {
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ResponseTemplate::new(200).set_body_json(json!({ "data": embedding }))
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}
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None => ResponseTemplate::new(404)
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.set_body_json(json!({"error": "text not found", "text": text})),
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}
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"dimensions": 3,
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"request": "{{text}}",
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"response": {
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"data": "{{embedding}}"
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}
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});
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(mock_server, embedder_settings)
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}
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#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
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struct MultipleRequest {
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input: Vec<String>,
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}
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#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
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struct MultipleResponse {
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output: Vec<SingleResponse>,
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}
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#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
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struct SingleResponse {
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text: String,
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embedding: Vec<f32>,
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}
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async fn create_mock_multiple() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let counter = AtomicUsize::new(0);
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |req: &Request| {
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let req: MultipleRequest = match req.body_json() {
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Ok(req) => req,
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Err(error) => {
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return ResponseTemplate::new(400).set_body_json(json!({
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"error": format!("Invalid request: {error}")
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}));
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}
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};
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let output = req
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.input
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.into_iter()
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.map(|text| SingleResponse {
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text,
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embedding: vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3],
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})
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.collect();
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let response = MultipleResponse { output };
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ResponseTemplate::new(200).set_body_json(response)
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"dimensions": 3,
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"request": {
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"input": ["{{text}}", "{{..}}"]
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},
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"response": {
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"output": [
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{
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"embedding": "{{embedding}}"
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},
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"{{..}}"
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]
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}
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});
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(mock_server, embedder_settings)
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}
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#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
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struct SingleRequest {
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input: String,
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}
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async fn create_mock_single_response_in_array() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let counter = AtomicUsize::new(0);
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |req: &Request| {
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let req: SingleRequest = match req.body_json() {
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Ok(req) => req,
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Err(error) => {
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return ResponseTemplate::new(400).set_body_json(json!({
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"error": format!("Invalid request: {error}")
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}));
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}
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};
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let output = vec![SingleResponse {
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text: req.input,
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embedding: vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3],
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}];
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let response = MultipleResponse { output };
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ResponseTemplate::new(200).set_body_json(response)
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"dimensions": 3,
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"request": {
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"input": "{{text}}"
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},
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"response": {
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"output": [
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{
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"embedding": "{{embedding}}"
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}
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]
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}
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});
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(mock_server, embedder_settings)
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}
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async fn create_mock_raw_with_custom_header() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let counter = AtomicUsize::new(0);
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |req: &Request| {
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match req.headers.get("my-nonstandard-auth") {
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Some(x) if x == "bearer of the ring" => {}
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Some(x) => {
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return ResponseTemplate::new(401).set_body_json(
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json!({"error": format!("thou shall not pass, {}", x.to_str().unwrap())}),
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)
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}
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None => {
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return ResponseTemplate::new(401)
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.set_body_json(json!({"error": "missing header 'my-nonstandard-auth'"}))
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}
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}
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let _req: String = match req.body_json() {
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Ok(req) => req,
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Err(error) => {
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return ResponseTemplate::new(400).set_body_json(json!({
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"error": format!("Invalid request: {error}")
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}));
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}
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};
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let output = vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3];
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ResponseTemplate::new(200).set_body_json(output)
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"request": "{{text}}",
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"response": "{{embedding}}",
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"headers": {"my-nonstandard-auth": "bearer of the ring"}
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});
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(mock_server, embedder_settings)
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}
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async fn create_mock_raw() -> (MockServer, Value) {
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let mock_server = MockServer::start().await;
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let counter = AtomicUsize::new(0);
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Mock::given(method("POST"))
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.and(path("/"))
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.respond_with(move |req: &Request| {
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let _req: String = match req.body_json() {
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Ok(req) => req,
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Err(error) => {
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return ResponseTemplate::new(400).set_body_json(json!({
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"error": format!("Invalid request: {error}")
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}));
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}
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};
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let output = vec![counter.fetch_add(1, Ordering::Relaxed) as f32; 3];
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ResponseTemplate::new(200).set_body_json(output)
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})
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.mount(&mock_server)
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.await;
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let url = mock_server.uri();
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let embedder_settings = json!({
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"source": "rest",
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"url": url,
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"dimensions": 3,
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"request": "{{text}}",
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"response": "{{embedding}}"
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});
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(mock_server, embedder_settings)
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}
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pub async fn post<T: IntoUrl>(url: T) -> reqwest::Result<reqwest::Response> {
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reqwest::Client::builder().build()?.post(url).send().await
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}
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#[actix_rt::test]
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async fn dummy_testing_the_mock() {
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let (mock, _setting) = create_mock().await;
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let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
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snapshot!(body, @r###"{"data":[0,0,0]}"###);
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let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
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snapshot!(body, @r###"{"data":[1,1,1]}"###);
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let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
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snapshot!(body, @r###"{"data":[2,2,2]}"###);
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let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
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snapshot!(body, @r###"{"data":[3,3,3]}"###);
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let body = post(&mock.uri()).await.unwrap().text().await.unwrap();
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snapshot!(body, @r###"{"data":[4,4,4]}"###);
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}
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#[actix_rt::test]
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async fn bad_request() {
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let (mock, _setting) = create_mock().await;
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let server = get_server_vector().await;
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let index = server.index("doggo");
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// No placeholder string appear in the template
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": "54", "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request`: \"{{text}}\" not found",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// A repeat string appears inside a repeated value
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": [
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{
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"input": [
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"{{text}}",
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"{{..}}"
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]
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},
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"{{..}}"
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]
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.input.input`: \"{{..}}\" appears nested inside of a value that is itself repeated",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// A repeat string appears outside of an array
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": {
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"input": "{{text}}",
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"repeat": "{{..}}"
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}
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.input.repeat`: \"{{..}}\" appears outside of an array",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// A repeat string appears in an array, but not in the second position
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": [
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"{{..}}",
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"{{text}}"
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]
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.input`: \"{{..}}\" expected at position #1, but found at position #0",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": [
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"{{text}}",
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"42",
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"{{..}}",
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]
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.input`: \"{{..}}\" expected at position #1, but found at position #2",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// A repeated value lacks a placeholder
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": [
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"42",
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"{{..}}",
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]
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.input[0]`: Expected \"{{text}}\" inside of the repeated value",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// Multiple repeat strings appear in the template
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": [
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"{{text}}",
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"{{..}}",
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],
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"data": [
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"42",
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"{{..}}",
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],
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.data`: Found \"{{..}}\", but it was already present in `request.input`",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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// Multiple placeholder strings appear in the template
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request": {
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"input": "{{text}}",
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"data": "{{text}}",
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}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.data`: Found \"{{text}}\", but it was already present in `request.input`",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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|
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let (response, code) = index
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.update_settings(json!({
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"embedders": {
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"rest": json!({ "source": "rest", "url": mock.uri(), "request":
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{"repeated": [{
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"input": "{{text}}",
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"data": [42, "{{text}}"],
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}, "{{..}}"]}, "response": "{{embedding}}" }),
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},
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}))
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.await;
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snapshot!(code, @"400 Bad Request");
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snapshot!(response, @r###"
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{
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"message": "Error while generating embeddings: user error: in `request.repeated.data[1]`: Found \"{{text}}\", but it was already present in `request.repeated.input`",
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"code": "vector_embedding_error",
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"type": "invalid_request",
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"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
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}
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"###);
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|
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// A placeholder appears both inside a repeated value and outside of it
|
|
let (response, code) = index
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|
.update_settings(json!({
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"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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]",
|
|
"batchUid": "[batch_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]"
|
|
}
|
|
"###);
|
|
}
|