Add similar route

This commit is contained in:
Louis Dureuil 2024-04-09 12:03:40 +02:00
parent 3bd9d2478c
commit ca6cc4654b
No known key found for this signature in database
9 changed files with 620 additions and 128 deletions

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@ -189,3 +189,4 @@ merge_with_error_impl_take_error_message!(ParseTaskKindError);
merge_with_error_impl_take_error_message!(ParseTaskStatusError); merge_with_error_impl_take_error_message!(ParseTaskStatusError);
merge_with_error_impl_take_error_message!(IndexUidFormatError); merge_with_error_impl_take_error_message!(IndexUidFormatError);
merge_with_error_impl_take_error_message!(InvalidSearchSemanticRatio); merge_with_error_impl_take_error_message!(InvalidSearchSemanticRatio);
merge_with_error_impl_take_error_message!(InvalidSimilarId);

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@ -246,7 +246,7 @@ InvalidSearchCropMarker , InvalidRequest , BAD_REQUEST ;
InvalidSearchFacets , InvalidRequest , BAD_REQUEST ; InvalidSearchFacets , InvalidRequest , BAD_REQUEST ;
InvalidSearchSemanticRatio , InvalidRequest , BAD_REQUEST ; InvalidSearchSemanticRatio , InvalidRequest , BAD_REQUEST ;
InvalidFacetSearchFacetName , InvalidRequest , BAD_REQUEST ; InvalidFacetSearchFacetName , InvalidRequest , BAD_REQUEST ;
InvalidRecommendId , InvalidRequest , BAD_REQUEST ; InvalidSimilarId , InvalidRequest , BAD_REQUEST ;
InvalidSearchFilter , InvalidRequest , BAD_REQUEST ; InvalidSearchFilter , InvalidRequest , BAD_REQUEST ;
InvalidSimilarFilter , InvalidRequest , BAD_REQUEST ; InvalidSimilarFilter , InvalidRequest , BAD_REQUEST ;
InvalidSearchHighlightPostTag , InvalidRequest , BAD_REQUEST ; InvalidSearchHighlightPostTag , InvalidRequest , BAD_REQUEST ;
@ -494,6 +494,17 @@ impl fmt::Display for deserr_codes::InvalidSearchSemanticRatio {
} }
} }
impl fmt::Display for deserr_codes::InvalidSimilarId {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(
f,
"the value of `id` is invalid. \
A document identifier can be of type integer or string, \
only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_)."
)
}
}
#[macro_export] #[macro_export]
macro_rules! internal_error { macro_rules! internal_error {
($target:ty : $($other:path), *) => { ($target:ty : $($other:path), *) => {

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@ -23,8 +23,6 @@ pub enum MeilisearchHttpError {
InvalidContentType(String, Vec<String>), InvalidContentType(String, Vec<String>),
#[error("Document `{0}` not found.")] #[error("Document `{0}` not found.")]
DocumentNotFound(String), DocumentNotFound(String),
#[error("Document `{0}` not found.")]
InvalidDocumentId(String),
#[error("Sending an empty filter is forbidden.")] #[error("Sending an empty filter is forbidden.")]
EmptyFilter, EmptyFilter,
#[error("Invalid syntax for the filter parameter: `expected {}, found: {1}`.", .0.join(", "))] #[error("Invalid syntax for the filter parameter: `expected {}, found: {1}`.", .0.join(", "))]
@ -72,7 +70,6 @@ impl ErrorCode for MeilisearchHttpError {
MeilisearchHttpError::MissingPayload(_) => Code::MissingPayload, MeilisearchHttpError::MissingPayload(_) => Code::MissingPayload,
MeilisearchHttpError::InvalidContentType(_, _) => Code::InvalidContentType, MeilisearchHttpError::InvalidContentType(_, _) => Code::InvalidContentType,
MeilisearchHttpError::DocumentNotFound(_) => Code::DocumentNotFound, MeilisearchHttpError::DocumentNotFound(_) => Code::DocumentNotFound,
MeilisearchHttpError::InvalidDocumentId(_) => Code::InvalidDocumentId,
MeilisearchHttpError::EmptyFilter => Code::InvalidDocumentFilter, MeilisearchHttpError::EmptyFilter => Code::InvalidDocumentFilter,
MeilisearchHttpError::InvalidExpression(_, _) => Code::InvalidSearchFilter, MeilisearchHttpError::InvalidExpression(_, _) => Code::InvalidSearchFilter,
MeilisearchHttpError::PayloadTooLarge(_) => Code::PayloadTooLarge, MeilisearchHttpError::PayloadTooLarge(_) => Code::PayloadTooLarge,

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@ -29,6 +29,7 @@ pub mod documents;
pub mod facet_search; pub mod facet_search;
pub mod search; pub mod search;
pub mod settings; pub mod settings;
pub mod similar;
pub fn configure(cfg: &mut web::ServiceConfig) { pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service( cfg.service(
@ -48,6 +49,7 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
.service(web::scope("/documents").configure(documents::configure)) .service(web::scope("/documents").configure(documents::configure))
.service(web::scope("/search").configure(search::configure)) .service(web::scope("/search").configure(search::configure))
.service(web::scope("/facet-search").configure(facet_search::configure)) .service(web::scope("/facet-search").configure(facet_search::configure))
.service(web::scope("/similar").configure(similar::configure))
.service(web::scope("/settings").configure(settings::configure)), .service(web::scope("/settings").configure(settings::configure)),
); );
} }

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@ -0,0 +1,171 @@
use actix_web::web::{self, Data};
use actix_web::{HttpRequest, HttpResponse};
use deserr::actix_web::{AwebJson, AwebQueryParameter};
use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::query_params::Param;
use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
use meilisearch_types::error::deserr_codes::{
InvalidEmbedder, InvalidSimilarAttributesToRetrieve, InvalidSimilarFilter, InvalidSimilarId,
InvalidSimilarLimit, InvalidSimilarOffset, InvalidSimilarShowRankingScore,
InvalidSimilarShowRankingScoreDetails,
};
use meilisearch_types::error::{ErrorCode as _, ResponseError};
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::keys::actions;
use meilisearch_types::serde_cs::vec::CS;
use serde_json::Value;
use tracing::debug;
use super::ActionPolicy;
use crate::analytics::{Analytics, SimilarAggregator};
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::search::{
add_search_rules, perform_similar, SearchKind, SimilarQuery, SimilarResult,
DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
};
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(
web::resource("")
.route(web::get().to(SeqHandler(similar_get)))
.route(web::post().to(SeqHandler(similar_post))),
);
}
pub async fn similar_get(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
params: AwebQueryParameter<SimilarQueryGet, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.0.try_into().map_err(|code: InvalidSimilarId| {
ResponseError::from_msg(code.to_string(), code.error_code())
})?;
let mut aggregate = SimilarAggregator::from_query(&query, &req);
debug!(parameters = ?query, "Similar get");
let similar = similar(index_scheduler, index_uid, query).await;
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.get_similar(aggregate);
let similar = similar?;
debug!(returns = ?similar, "Similar get");
Ok(HttpResponse::Ok().json(similar))
}
pub async fn similar_post(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
params: AwebJson<SimilarQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.into_inner();
debug!(parameters = ?query, "Similar post");
let mut aggregate = SimilarAggregator::from_query(&query, &req);
let similar = similar(index_scheduler, index_uid, query).await;
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.post_similar(aggregate);
let similar = similar?;
debug!(returns = ?similar, "Similar post");
Ok(HttpResponse::Ok().json(similar))
}
async fn similar(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: IndexUid,
mut query: SimilarQuery,
) -> Result<SimilarResult, ResponseError> {
let features = index_scheduler.features();
features.check_vector("Using the similar API")?;
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
add_search_rules(&mut query.filter, search_rules);
}
let index = index_scheduler.index(&index_uid)?;
let (embedder_name, embedder) =
SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
tokio::task::spawn_blocking(move || perform_similar(&index, query, embedder_name, embedder))
.await?
}
#[derive(Debug, deserr::Deserr)]
#[deserr(error = DeserrQueryParamError, rename_all = camelCase, deny_unknown_fields)]
pub struct SimilarQueryGet {
#[deserr(error = DeserrQueryParamError<InvalidSimilarId>)]
id: Param<String>,
#[deserr(default = Param(DEFAULT_SEARCH_OFFSET()), error = DeserrQueryParamError<InvalidSimilarOffset>)]
offset: Param<usize>,
#[deserr(default = Param(DEFAULT_SEARCH_LIMIT()), error = DeserrQueryParamError<InvalidSimilarLimit>)]
limit: Param<usize>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarAttributesToRetrieve>)]
attributes_to_retrieve: Option<CS<String>>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarFilter>)]
filter: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScore>)]
show_ranking_score: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScoreDetails>)]
show_ranking_score_details: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
pub embedder: Option<String>,
}
impl TryFrom<SimilarQueryGet> for SimilarQuery {
type Error = InvalidSimilarId;
fn try_from(
SimilarQueryGet {
id,
offset,
limit,
attributes_to_retrieve,
filter,
show_ranking_score,
show_ranking_score_details,
embedder,
}: SimilarQueryGet,
) -> Result<Self, Self::Error> {
let filter = match filter {
Some(f) => match serde_json::from_str(&f) {
Ok(v) => Some(v),
_ => Some(Value::String(f)),
},
None => None,
};
Ok(SimilarQuery {
id: id.0.try_into()?,
offset: offset.0,
limit: limit.0,
filter,
embedder,
attributes_to_retrieve: attributes_to_retrieve.map(|o| o.into_iter().collect()),
show_ranking_score: show_ranking_score.0,
show_ranking_score_details: show_ranking_score_details.0,
})
}
}

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@ -11,7 +11,7 @@ use indexmap::IndexMap;
use meilisearch_auth::IndexSearchRules; use meilisearch_auth::IndexSearchRules;
use meilisearch_types::deserr::DeserrJsonError; use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::deserr_codes::*; use meilisearch_types::error::deserr_codes::*;
use meilisearch_types::error::ResponseError; use meilisearch_types::error::{Code, ResponseError};
use meilisearch_types::heed::RoTxn; use meilisearch_types::heed::RoTxn;
use meilisearch_types::index_uid::IndexUid; use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy}; use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
@ -417,6 +417,59 @@ impl SearchQueryWithIndex {
} }
} }
#[derive(Debug, Clone, PartialEq, Deserr)]
#[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
pub struct SimilarQuery {
#[deserr(error = DeserrJsonError<InvalidSimilarId>)]
pub id: ExternalDocumentId,
#[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSimilarOffset>)]
pub offset: usize,
#[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSimilarLimit>)]
pub limit: usize,
#[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
pub filter: Option<Value>,
#[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
pub embedder: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
pub attributes_to_retrieve: Option<BTreeSet<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScore>, default)]
pub show_ranking_score: bool,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScoreDetails>, default)]
pub show_ranking_score_details: bool,
}
#[derive(Debug, Clone, PartialEq, Deserr)]
#[deserr(try_from(Value) = TryFrom::try_from -> InvalidSimilarId)]
pub struct ExternalDocumentId(String);
impl AsRef<str> for ExternalDocumentId {
fn as_ref(&self) -> &str {
&self.0
}
}
impl ExternalDocumentId {
pub fn into_inner(self) -> String {
self.0
}
}
impl TryFrom<String> for ExternalDocumentId {
type Error = InvalidSimilarId;
fn try_from(value: String) -> Result<Self, Self::Error> {
serde_json::Value::String(value).try_into()
}
}
impl TryFrom<Value> for ExternalDocumentId {
type Error = InvalidSimilarId;
fn try_from(value: Value) -> Result<Self, Self::Error> {
Ok(Self(milli::documents::validate_document_id_value(value).map_err(|_| InvalidSimilarId)?))
}
}
#[derive(Debug, Copy, Clone, PartialEq, Eq, Deserr)] #[derive(Debug, Copy, Clone, PartialEq, Eq, Deserr)]
#[deserr(rename_all = camelCase)] #[deserr(rename_all = camelCase)]
pub enum MatchingStrategy { pub enum MatchingStrategy {
@ -538,6 +591,16 @@ impl fmt::Debug for SearchResult {
} }
} }
#[derive(Serialize, Debug, Clone, PartialEq)]
#[serde(rename_all = "camelCase")]
pub struct SimilarResult {
pub hits: Vec<SearchHit>,
pub id: String,
pub processing_time_ms: u128,
#[serde(flatten)]
pub hits_info: HitsInfo,
}
#[derive(Serialize, Debug, Clone, PartialEq)] #[derive(Serialize, Debug, Clone, PartialEq)]
#[serde(rename_all = "camelCase")] #[serde(rename_all = "camelCase")]
pub struct SearchResultWithIndex { pub struct SearchResultWithIndex {
@ -719,131 +782,52 @@ pub fn perform_search(
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?, SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
}; };
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap(); let SearchQuery {
q,
vector: _,
hybrid: _,
// already computed from prepare_search
offset: _,
limit,
page,
hits_per_page,
attributes_to_retrieve,
attributes_to_crop,
crop_length,
attributes_to_highlight,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
filter: _,
sort,
facets,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy: _,
attributes_to_search_on: _,
} = query;
let displayed_ids = index let format = AttributesFormat {
.displayed_fields_ids(&rtxn)? attributes_to_retrieve,
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>()) attributes_to_highlight,
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect()); attributes_to_crop,
crop_length,
let fids = |attrs: &BTreeSet<String>| { crop_marker,
let mut ids = BTreeSet::new(); highlight_pre_tag,
for attr in attrs { highlight_post_tag,
if attr == "*" { show_matches_position,
ids.clone_from(&displayed_ids); sort,
break; show_ranking_score,
} show_ranking_score_details,
if let Some(id) = fields_ids_map.id(attr) {
ids.insert(id);
}
}
ids
}; };
// The attributes to retrieve are the ones explicitly marked as to retrieve (all by default), let documents =
// but these attributes must be also be present make_hits(index, &rtxn, format, matching_words, documents_ids, document_scores)?;
// - in the fields_ids_map
// - in the displayed attributes
let to_retrieve_ids: BTreeSet<_> = query
.attributes_to_retrieve
.as_ref()
.map(fids)
.unwrap_or_else(|| displayed_ids.clone())
.intersection(&displayed_ids)
.cloned()
.collect();
let attr_to_highlight = query.attributes_to_highlight.unwrap_or_default();
let attr_to_crop = query.attributes_to_crop.unwrap_or_default();
// Attributes in `formatted_options` correspond to the attributes that will be in `_formatted`
// These attributes are:
// - the attributes asked to be highlighted or cropped (with `attributesToCrop` or `attributesToHighlight`)
// - the attributes asked to be retrieved: these attributes will not be highlighted/cropped
// But these attributes must be also present in displayed attributes
let formatted_options = compute_formatted_options(
&attr_to_highlight,
&attr_to_crop,
query.crop_length,
&to_retrieve_ids,
&fields_ids_map,
&displayed_ids,
);
let mut tokenizer_builder = TokenizerBuilder::default();
tokenizer_builder.create_char_map(true);
let script_lang_map = index.script_language(&rtxn)?;
if !script_lang_map.is_empty() {
tokenizer_builder.allow_list(&script_lang_map);
}
let separators = index.allowed_separators(&rtxn)?;
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref separators) = separators {
tokenizer_builder.separators(separators);
}
let dictionary = index.dictionary(&rtxn)?;
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref dictionary) = dictionary {
tokenizer_builder.words_dict(dictionary);
}
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
formatter_builder.crop_marker(query.crop_marker);
formatter_builder.highlight_prefix(query.highlight_pre_tag);
formatter_builder.highlight_suffix(query.highlight_post_tag);
let mut documents = Vec::new();
let documents_iter = index.documents(&rtxn, documents_ids)?;
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
// First generate a document with all the displayed fields
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
// select the attributes to retrieve
let attributes_to_retrieve = to_retrieve_ids
.iter()
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
let mut document =
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
let (matches_position, formatted) = format_fields(
&displayed_document,
&fields_ids_map,
&formatter_builder,
&formatted_options,
query.show_matches_position,
&displayed_ids,
)?;
if let Some(sort) = query.sort.as_ref() {
insert_geo_distance(sort, &mut document);
}
let ranking_score =
query.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
let ranking_score_details =
query.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
let hit = SearchHit {
document,
formatted,
matches_position,
ranking_score_details,
ranking_score,
};
documents.push(hit);
}
let number_of_hits = min(candidates.len() as usize, max_total_hits); let number_of_hits = min(candidates.len() as usize, max_total_hits);
let hits_info = if is_finite_pagination { let hits_info = if is_finite_pagination {
let hits_per_page = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT); let hits_per_page = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
// If hit_per_page is 0, then pages can't be computed and so we respond 0. // If hit_per_page is 0, then pages can't be computed and so we respond 0.
let total_pages = (number_of_hits + hits_per_page.saturating_sub(1)) let total_pages = (number_of_hits + hits_per_page.saturating_sub(1))
.checked_div(hits_per_page) .checked_div(hits_per_page)
@ -851,15 +835,15 @@ pub fn perform_search(
HitsInfo::Pagination { HitsInfo::Pagination {
hits_per_page, hits_per_page,
page: query.page.unwrap_or(1), page: page.unwrap_or(1),
total_pages, total_pages,
total_hits: number_of_hits, total_hits: number_of_hits,
} }
} else { } else {
HitsInfo::OffsetLimit { limit: query.limit, offset, estimated_total_hits: number_of_hits } HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits }
}; };
let (facet_distribution, facet_stats) = match query.facets { let (facet_distribution, facet_stats) = match facets {
Some(ref fields) => { Some(ref fields) => {
let mut facet_distribution = index.facets_distribution(&rtxn); let mut facet_distribution = index.facets_distribution(&rtxn);
@ -896,7 +880,7 @@ pub fn perform_search(
let result = SearchResult { let result = SearchResult {
hits: documents, hits: documents,
hits_info, hits_info,
query: query.q.unwrap_or_default(), query: q.unwrap_or_default(),
processing_time_ms: before_search.elapsed().as_millis(), processing_time_ms: before_search.elapsed().as_millis(),
facet_distribution, facet_distribution,
facet_stats, facet_stats,
@ -907,6 +891,130 @@ pub fn perform_search(
Ok(result) Ok(result)
} }
struct AttributesFormat {
attributes_to_retrieve: Option<BTreeSet<String>>,
attributes_to_highlight: Option<HashSet<String>>,
attributes_to_crop: Option<Vec<String>>,
crop_length: usize,
crop_marker: String,
highlight_pre_tag: String,
highlight_post_tag: String,
show_matches_position: bool,
sort: Option<Vec<String>>,
show_ranking_score: bool,
show_ranking_score_details: bool,
}
fn make_hits(
index: &Index,
rtxn: &RoTxn<'_>,
format: AttributesFormat,
matching_words: milli::MatchingWords,
documents_ids: Vec<u32>,
document_scores: Vec<Vec<ScoreDetails>>,
) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
let displayed_ids = index
.displayed_fields_ids(rtxn)?
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
let fids = |attrs: &BTreeSet<String>| {
let mut ids = BTreeSet::new();
for attr in attrs {
if attr == "*" {
ids.clone_from(&displayed_ids);
break;
}
if let Some(id) = fields_ids_map.id(attr) {
ids.insert(id);
}
}
ids
};
let to_retrieve_ids: BTreeSet<_> = format
.attributes_to_retrieve
.as_ref()
.map(fids)
.unwrap_or_else(|| displayed_ids.clone())
.intersection(&displayed_ids)
.cloned()
.collect();
let attr_to_highlight = format.attributes_to_highlight.unwrap_or_default();
let attr_to_crop = format.attributes_to_crop.unwrap_or_default();
let formatted_options = compute_formatted_options(
&attr_to_highlight,
&attr_to_crop,
format.crop_length,
&to_retrieve_ids,
&fields_ids_map,
&displayed_ids,
);
let mut tokenizer_builder = TokenizerBuilder::default();
tokenizer_builder.create_char_map(true);
let script_lang_map = index.script_language(rtxn)?;
if !script_lang_map.is_empty() {
tokenizer_builder.allow_list(&script_lang_map);
}
let separators = index.allowed_separators(rtxn)?;
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref separators) = separators {
tokenizer_builder.separators(separators);
}
let dictionary = index.dictionary(rtxn)?;
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref dictionary) = dictionary {
tokenizer_builder.words_dict(dictionary);
}
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
formatter_builder.crop_marker(format.crop_marker);
formatter_builder.highlight_prefix(format.highlight_pre_tag);
formatter_builder.highlight_suffix(format.highlight_post_tag);
let mut documents = Vec::new();
let documents_iter = index.documents(rtxn, documents_ids)?;
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
// First generate a document with all the displayed fields
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
// select the attributes to retrieve
let attributes_to_retrieve = to_retrieve_ids
.iter()
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
let mut document =
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
let (matches_position, formatted) = format_fields(
&displayed_document,
&fields_ids_map,
&formatter_builder,
&formatted_options,
format.show_matches_position,
&displayed_ids,
)?;
if let Some(sort) = format.sort.as_ref() {
insert_geo_distance(sort, &mut document);
}
let ranking_score =
format.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
let ranking_score_details =
format.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
let hit = SearchHit {
document,
formatted,
matches_position,
ranking_score_details,
ranking_score,
};
documents.push(hit);
}
Ok(documents)
}
pub fn perform_facet_search( pub fn perform_facet_search(
index: &Index, index: &Index,
search_query: SearchQuery, search_query: SearchQuery,
@ -941,6 +1049,95 @@ pub fn perform_facet_search(
}) })
} }
pub fn perform_similar(
index: &Index,
query: SimilarQuery,
embedder_name: String,
embedder: Arc<Embedder>,
) -> Result<SimilarResult, ResponseError> {
let before_search = Instant::now();
let rtxn = index.read_txn()?;
let SimilarQuery {
id,
offset,
limit,
filter: _,
embedder: _,
attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
} = query;
// using let-else rather than `?` so that the borrow checker identifies we're always returning here,
// preventing a use-after-move
let Some(internal_id) = index.external_documents_ids().get(&rtxn, &id)? else {
return Err(ResponseError::from_msg(
MeilisearchHttpError::DocumentNotFound(id.into_inner()).to_string(),
Code::NotFoundSimilarId,
));
};
let mut similar =
milli::Similar::new(internal_id, offset, limit, index, &rtxn, embedder_name, embedder);
if let Some(ref filter) = query.filter {
if let Some(facets) = parse_filter(filter)
// inject InvalidSimilarFilter code
.map_err(|e| ResponseError::from_msg(e.to_string(), Code::InvalidSimilarFilter))?
{
similar.filter(facets);
}
}
let milli::SearchResult {
documents_ids,
matching_words: _,
candidates,
document_scores,
degraded: _,
used_negative_operator: _,
} = similar.execute().map_err(|err| match err {
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
ResponseError::from_msg(err.to_string(), Code::InvalidSimilarFilter)
}
err => err.into(),
})?;
let format = AttributesFormat {
attributes_to_retrieve,
attributes_to_highlight: None,
attributes_to_crop: None,
crop_length: DEFAULT_CROP_LENGTH(),
crop_marker: DEFAULT_CROP_MARKER(),
highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
show_matches_position: false,
sort: None,
show_ranking_score,
show_ranking_score_details,
};
let hits = make_hits(index, &rtxn, format, Default::default(), documents_ids, document_scores)?;
let max_total_hits = index
.pagination_max_total_hits(&rtxn)
.map_err(milli::Error::from)?
.map(|x| x as usize)
.unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
let number_of_hits = min(candidates.len() as usize, max_total_hits);
let hits_info = HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits };
let result = SimilarResult {
hits,
hits_info,
id: id.into_inner(),
processing_time_ms: before_search.elapsed().as_millis(),
};
Ok(result)
}
fn insert_geo_distance(sorts: &[String], document: &mut Document) { fn insert_geo_distance(sorts: &[String], document: &mut Document) {
lazy_static::lazy_static! { lazy_static::lazy_static! {
static ref GEO_REGEX: Regex = static ref GEO_REGEX: Regex =

View File

@ -63,6 +63,7 @@ pub use self::heed_codec::{
}; };
pub use self::index::Index; pub use self::index::Index;
pub use self::search::facet::{FacetValueHit, SearchForFacetValues}; pub use self::search::facet::{FacetValueHit, SearchForFacetValues};
pub use self::search::similar::Similar;
pub use self::search::{ pub use self::search::{
FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy, FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy,
Search, SearchResult, SemanticSearch, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET, Search, SearchResult, SemanticSearch, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET,

View File

@ -24,6 +24,7 @@ pub mod facet;
mod fst_utils; mod fst_utils;
pub mod hybrid; pub mod hybrid;
pub mod new; pub mod new;
pub mod similar;
#[derive(Debug, Clone)] #[derive(Debug, Clone)]
pub struct SemanticSearch { pub struct SemanticSearch {

111
milli/src/search/similar.rs Normal file
View File

@ -0,0 +1,111 @@
use std::sync::Arc;
use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use crate::score_details::{self, ScoreDetails};
use crate::vector::Embedder;
use crate::{filtered_universe, DocumentId, Filter, Index, Result, SearchResult};
pub struct Similar<'a> {
id: DocumentId,
// this should be linked to the String in the query
filter: Option<Filter<'a>>,
offset: usize,
limit: usize,
rtxn: &'a heed::RoTxn<'a>,
index: &'a Index,
embedder_name: String,
embedder: Arc<Embedder>,
}
impl<'a> Similar<'a> {
pub fn new(
id: DocumentId,
offset: usize,
limit: usize,
index: &'a Index,
rtxn: &'a heed::RoTxn<'a>,
embedder_name: String,
embedder: Arc<Embedder>,
) -> Self {
Self { id, filter: None, offset, limit, rtxn, index, embedder_name, embedder }
}
pub fn filter(&mut self, filter: Filter<'a>) -> &mut Self {
self.filter = Some(filter);
self
}
pub fn execute(&self) -> Result<SearchResult> {
let universe = filtered_universe(self.index, self.rtxn, &self.filter)?;
let embedder_index =
self.index
.embedder_category_id
.get(self.rtxn, &self.embedder_name)?
.ok_or_else(|| crate::UserError::InvalidEmbedder(self.embedder_name.to_owned()))?;
let readers: std::result::Result<Vec<_>, _> =
self.index.arroy_readers(self.rtxn, embedder_index).collect();
let readers = readers?;
let mut results = Vec::new();
for reader in readers.iter() {
let nns_by_item = reader.nns_by_item(
self.rtxn,
self.id,
self.limit + self.offset + 1,
None,
Some(&universe),
)?;
if let Some(mut nns_by_item) = nns_by_item {
results.append(&mut nns_by_item);
} else {
break;
}
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
let mut documents_ids = Vec::with_capacity(self.limit);
let mut document_scores = Vec::with_capacity(self.limit);
// list of documents we've already seen, so that we don't return the same document multiple times.
// initialized to the target document, that we never want to return.
let mut documents_seen = RoaringBitmap::new();
documents_seen.insert(self.id);
for (docid, distance) in results
.into_iter()
// skip documents we've already seen & mark that we saw the current document
.filter(|(docid, _)| documents_seen.insert(*docid))
.skip(self.offset)
// take **after** filter and skip so that we get exactly limit elements if available
.take(self.limit)
{
documents_ids.push(docid);
let score = 1.0 - distance;
let score = self
.embedder
.distribution()
.map(|distribution| distribution.shift(score))
.unwrap_or(score);
let score = ScoreDetails::Vector(score_details::Vector { similarity: Some(score) });
document_scores.push(vec![score]);
}
Ok(SearchResult {
matching_words: Default::default(),
candidates: universe,
documents_ids,
document_scores,
degraded: false,
used_negative_operator: false,
})
}
}