fix tests

This commit is contained in:
airycanon 2024-11-14 16:40:38 +08:00
parent a476f1aeb6
commit fdcd483740
31 changed files with 322 additions and 250 deletions

View File

@ -448,20 +448,20 @@ impl IndexScheduler {
match (document_import, settings) {
(
Some(Batch::IndexOperation {
op:
IndexOperation::DocumentOperation {
primary_key,
documents_counts,
operations,
tasks: document_import_tasks,
..
},
..
}),
op:
IndexOperation::DocumentOperation {
primary_key,
documents_counts,
operations,
tasks: document_import_tasks,
..
},
..
}),
Some(Batch::IndexOperation {
op: IndexOperation::Settings { settings, tasks: settings_tasks, .. },
..
}),
op: IndexOperation::Settings { settings, tasks: settings_tasks, .. },
..
}),
) => Ok(Some(Batch::IndexOperation {
op: IndexOperation::SettingsAndDocumentOperation {
index_uid,
@ -618,12 +618,7 @@ impl IndexScheduler {
/// The list of tasks that were processed. The metadata of each task in the returned
/// list is updated accordingly, with the exception of the its date fields
/// [`finished_at`](meilisearch_types::tasks::Task::finished_at) and [`started_at`](meilisearch_types::tasks::Task::started_at).
#[tracing::instrument(
level = "trace",
skip(self, batch),
target = "indexing::scheduler",
fields(batch=batch.to_string())
)]
#[tracing::instrument(level = "trace", skip(self, batch), target = "indexing::scheduler", fields(batch=batch.to_string()))]
pub(crate) fn process_batch(&self, batch: Batch) -> Result<Vec<Task>> {
#[cfg(test)]
{
@ -656,10 +651,10 @@ impl IndexScheduler {
task.status = Status::Succeeded;
match &mut task.details {
Some(Details::TaskCancelation {
matched_tasks: _,
canceled_tasks,
original_filter: _,
}) => {
matched_tasks: _,
canceled_tasks,
original_filter: _,
}) => {
*canceled_tasks = Some(canceled_tasks_content_uuids.len() as u64);
}
_ => unreachable!(),
@ -713,10 +708,10 @@ impl IndexScheduler {
match &mut task.details {
Some(Details::TaskDeletion {
matched_tasks: _,
deleted_tasks,
original_filter: _,
}) => {
matched_tasks: _,
deleted_tasks,
original_filter: _,
}) => {
*deleted_tasks = Some(deleted_tasks_count);
}
_ => unreachable!(),
@ -772,7 +767,8 @@ impl IndexScheduler {
let index = self.index_mapper.index(&rtxn, name)?;
let dst = temp_snapshot_dir.path().join("indexes").join(uuid.to_string());
fs::create_dir_all(&dst)?;
index.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)
index
.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)
.map_err(|e| Error::from_milli(e, Some(name.to_string())))?;
}
@ -873,25 +869,21 @@ impl IndexScheduler {
if status == Status::Enqueued {
let content_file = self.file_store.get_update(content_file)?;
let reader = DocumentsBatchReader::from_reader(content_file)
.map_err(|e| Error::Milli {
error: e.into(),
index_name: index_uid.clone(),
let reader =
DocumentsBatchReader::from_reader(content_file).map_err(|e| {
Error::Milli { error: e.into(), index_name: index_uid.clone() }
})?;
let (mut cursor, documents_batch_index) =
reader.into_cursor_and_fields_index();
while let Some(doc) = cursor.next_document()
.map_err(|e| Error::Milli {
error: e.into(),
index_name: index_uid.clone(),
})?
{
dump_content_file.push_document(&obkv_to_object(
&doc,
&documents_batch_index,
).map_err(|e| Error::from_milli(e, index_uid.clone()))?)?;
while let Some(doc) = cursor.next_document().map_err(|e| {
Error::Milli { error: e.into(), index_name: index_uid.clone() }
})? {
dump_content_file.push_document(
&obkv_to_object(&doc, &documents_batch_index)
.map_err(|e| Error::from_milli(e, index_uid.clone()))?,
)?;
}
dump_content_file.flush()?;
}
@ -905,18 +897,22 @@ impl IndexScheduler {
let metadata = IndexMetadata {
uid: uid.to_owned(),
primary_key: index.primary_key(&rtxn)?.map(String::from),
created_at: index.created_at(&rtxn)
created_at: index
.created_at(&rtxn)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
updated_at: index.updated_at(&rtxn)
updated_at: index
.updated_at(&rtxn)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
};
let mut index_dumper = dump.create_index(uid, &metadata)?;
let fields_ids_map = index.fields_ids_map(&rtxn)?;
let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
let embedding_configs = index.embedding_configs(&rtxn)
let embedding_configs = index
.embedding_configs(&rtxn)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
let documents = index.all_documents(&rtxn)
let documents = index
.all_documents(&rtxn)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
// 3.1. Dump the documents
@ -925,14 +921,16 @@ impl IndexScheduler {
return Err(Error::AbortedTask);
}
let (id, doc) = ret
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
let (id, doc) =
ret.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
let mut document =
milli::obkv_to_json(&all_fields, &fields_ids_map, doc)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
'inject_vectors: {
let embeddings = index.embeddings(&rtxn, id)
let embeddings = index
.embeddings(&rtxn, id)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
if embeddings.is_empty() {
@ -944,21 +942,24 @@ impl IndexScheduler {
.or_insert(serde_json::Value::Object(Default::default()));
let serde_json::Value::Object(vectors) = vectors else {
return Err(Error::from_milli(milli::Error::UserError(
milli::UserError::InvalidVectorsMapType {
document_id: {
if let Ok(Some(Ok(index))) = index
.external_id_of(&rtxn, std::iter::once(id))
.map(|it| it.into_iter().next())
{
index
} else {
format!("internal docid={id}")
}
return Err(Error::from_milli(
milli::Error::UserError(
milli::UserError::InvalidVectorsMapType {
document_id: {
if let Ok(Some(Ok(index))) = index
.external_id_of(&rtxn, std::iter::once(id))
.map(|it| it.into_iter().next())
{
index
} else {
format!("internal docid={id}")
}
},
value: vectors.clone(),
},
value: vectors.clone(),
},
), Some(uid.to_string())));
),
Some(uid.to_string()),
));
};
for (embedder_name, embeddings) in embeddings {
@ -988,7 +989,8 @@ impl IndexScheduler {
index,
&rtxn,
meilisearch_types::settings::SecretPolicy::RevealSecrets,
).map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
index_dumper.settings(&settings)?;
Ok(())
})?;
@ -1078,10 +1080,12 @@ impl IndexScheduler {
);
builder.set_primary_key(primary_key);
let must_stop_processing = self.must_stop_processing.clone();
builder.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
builder
.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
index_wtxn.commit()?;
}
@ -1122,11 +1126,11 @@ impl IndexScheduler {
let number_of_documents = || -> Result<u64> {
let index = self.index_mapper.index(&wtxn, &index_uid)?;
let index_rtxn = index.read_txn()?;
Ok(index.number_of_documents(&index_rtxn)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?
)
index
.number_of_documents(&index_rtxn)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))
}()
.unwrap_or_default();
.unwrap_or_default();
// The write transaction is directly owned and committed inside.
match self.index_mapper.delete_index(wtxn, &index_uid) {
@ -1244,7 +1248,8 @@ impl IndexScheduler {
) -> Result<Vec<Task>> {
match operation {
IndexOperation::DocumentClear { index_uid, mut tasks, .. } => {
let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()
let count = milli::update::ClearDocuments::new(index_wtxn, index)
.execute()
.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
let mut first_clear_found = false;
@ -1284,10 +1289,10 @@ impl IndexScheduler {
Some(pk) => {
if primary_key != pk {
return Err(Error::from_milli(
milli::UserError::PrimaryKeyCannotBeChanged(pk.to_string()).into(),
milli::UserError::PrimaryKeyCannotBeChanged(pk.to_string())
.into(),
Some(index_uid.clone()),
)
.into());
));
}
}
// if the primary key was set and there was no primary key set for this index
@ -1296,10 +1301,12 @@ impl IndexScheduler {
let mut builder =
milli::update::Settings::new(index_wtxn, index, indexer_config);
builder.set_primary_key(primary_key);
builder.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.clone().get(),
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
builder
.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.clone().get(),
)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
primary_key_has_been_set = true;
}
}
@ -1307,7 +1314,8 @@ impl IndexScheduler {
let config = IndexDocumentsConfig { update_method: method, ..Default::default() };
let embedder_configs = index.embedding_configs(index_wtxn)
let embedder_configs = index
.embedding_configs(index_wtxn)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
// TODO: consider Arc'ing the map too (we only need read access + we'll be cloning it multiple times, so really makes sense)
let embedders = self.embedders(index_uid.clone(), embedder_configs)?;
@ -1319,15 +1327,19 @@ impl IndexScheduler {
config,
|indexing_step| tracing::trace!(?indexing_step, "Update"),
|| must_stop_processing.get(),
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
for (operation, task) in operations.into_iter().zip(tasks.iter_mut()) {
match operation {
DocumentOperation::Add(content_uuid) => {
let content_file = self.file_store.get_update(content_uuid)?;
let reader = DocumentsBatchReader::from_reader(content_file)
.map_err(|e| Error::from_milli(e.into(), Some(index_uid.clone())))?;
let (new_builder, user_result) = builder.add_documents(reader)
let reader =
DocumentsBatchReader::from_reader(content_file).map_err(|e| {
Error::from_milli(e.into(), Some(index_uid.clone()))
})?;
let (new_builder, user_result) = builder
.add_documents(reader)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
builder = new_builder;
@ -1335,9 +1347,9 @@ impl IndexScheduler {
let received_documents =
if let Some(Details::DocumentAdditionOrUpdate {
received_documents,
..
}) = task.details
received_documents,
..
}) = task.details
{
received_documents
} else {
@ -1364,9 +1376,9 @@ impl IndexScheduler {
}
}
DocumentOperation::Delete(document_ids) => {
let (new_builder, user_result) =
builder.remove_documents(document_ids)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
let (new_builder, user_result) = builder
.remove_documents(document_ids)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
builder = new_builder;
// Uses Invariant: remove documents actually always returns Ok for the inner result
let count = user_result.unwrap();
@ -1390,7 +1402,8 @@ impl IndexScheduler {
}
if !tasks.iter().all(|res| res.error.is_some()) {
let addition = builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid)))?;
let addition =
builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid)))?;
tracing::info!(indexing_result = ?addition, processed_in = ?started_processing_at.elapsed(), "document indexing done");
} else if primary_key_has_been_set {
// Everything failed but we've set a primary key.
@ -1398,10 +1411,12 @@ impl IndexScheduler {
let mut builder =
milli::update::Settings::new(index_wtxn, index, indexer_config);
builder.reset_primary_key();
builder.execute(
|indexing_step| tracing::trace!(update = ?indexing_step),
|| must_stop_processing.clone().get(),
).map_err(|e| Error::from_milli(e, Some(index_uid)))?;
builder
.execute(
|indexing_step| tracing::trace!(update = ?indexing_step),
|| must_stop_processing.clone().get(),
)
.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
}
Ok(tasks)
@ -1424,8 +1439,14 @@ impl IndexScheduler {
self.index_mapper.indexer_config(),
self.must_stop_processing.clone(),
index,
index_uid
);
)
.map_err(|err| match err {
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
Error::from_milli(err, Some(index_uid.clone()))
.with_custom_error_code(Code::InvalidDocumentFilter)
}
e => Error::from_milli(e, Some(index_uid.clone())),
});
let (original_filter, context, function) = if let Some(Details::DocumentEdition {
original_filter,
context,
@ -1552,14 +1573,17 @@ impl IndexScheduler {
config,
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
let (new_builder, _count) =
builder.remove_documents_from_db_no_batch(&to_delete)
builder
.remove_documents_from_db_no_batch(&to_delete)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
builder = new_builder;
let _ = builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
let _ =
builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
Ok(tasks)
}
@ -1578,10 +1602,12 @@ impl IndexScheduler {
}
let must_stop_processing = self.must_stop_processing.clone();
builder.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
).map_err(|e| Error::from_milli(e, Some(index_uid)))?;
builder
.execute(
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
)
.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
Ok(tasks)
}
@ -1773,17 +1799,11 @@ fn edit_documents_by_function<'a>(
indexer_config: &IndexerConfig,
must_stop_processing: MustStopProcessing,
index: &'a Index,
index_uid: String,
) -> Result<(u64, u64)> {
) -> milli::Result<(u64, u64)> {
let candidates = match filter.as_ref().map(Filter::from_json) {
Some(Ok(Some(filter))) => filter.evaluate(wtxn, index).map_err(|err| match err {
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
Error::from_milli(err, Some(index_uid.clone())).with_custom_error_code(Code::InvalidDocumentFilter)
}
e => Error::from_milli(e.into(), Some(index_uid.clone())),
})?,
Some(Ok(Some(filter))) => filter.evaluate(wtxn, index)?,
None | Some(Ok(None)) => index.documents_ids(wtxn)?,
Some(Err(e)) => return Err(Error::from_milli(e.into(), Some(index_uid.clone()))),
Some(Err(e)) => return Err(e),
};
let config = IndexDocumentsConfig {
@ -1798,15 +1818,11 @@ fn edit_documents_by_function<'a>(
config,
|indexing_step| tracing::debug!(update = ?indexing_step),
|| must_stop_processing.get(),
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
)?;
let (new_builder, count) = builder.edit_documents(
&candidates,
context,
code
).map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
let (new_builder, count) = builder.edit_documents(&candidates, context, code)?;
builder = new_builder;
let _ = builder.execute().map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
let _ = builder.execute()?;
Ok(count.unwrap())
}

View File

@ -8,9 +8,8 @@ use time::OffsetDateTime;
use uuid::Uuid;
use super::IndexStatus::{self, Available, BeingDeleted, Closing, Missing};
use crate::clamp_to_page_size;
use crate::lru::{InsertionOutcome, LruMap};
use crate::{clamp_to_page_size};
/// Keep an internally consistent view of the open indexes in memory.
///
/// This view is made of an LRU cache that will evict the least frequently used indexes when new indexes are opened.

View File

@ -3,19 +3,19 @@ use std::sync::{Arc, RwLock};
use std::time::Duration;
use std::{fs, thread};
use self::index_map::IndexMap;
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
use crate::uuid_codec::UuidCodec;
use crate::{Error, Result};
use meilisearch_types::heed::types::{SerdeJson, Str};
use meilisearch_types::heed::{Database, Env, RoTxn, RwTxn};
use meilisearch_types::milli;
use meilisearch_types::milli::update::IndexerConfig;
use meilisearch_types::milli::{FieldDistribution, Index};
use serde::{Deserialize, Serialize};
use time::OffsetDateTime;
use tracing::error;
use uuid::Uuid;
use meilisearch_types::milli;
use self::index_map::IndexMap;
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
use crate::uuid_codec::UuidCodec;
use crate::{Error, Result};
mod index_map;
@ -183,13 +183,18 @@ impl IndexMapper {
// Error if the UUIDv4 somehow already exists in the map, since it should be fresh.
// This is very unlikely to happen in practice.
// TODO: it would be better to lazily create the index. But we need an Index::open function for milli.
let index = self.index_map.write().unwrap().create(
&uuid,
&index_path,
date,
self.enable_mdb_writemap,
self.index_base_map_size,
).map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
let index = self
.index_map
.write()
.unwrap()
.create(
&uuid,
&index_path,
date,
self.enable_mdb_writemap,
self.index_base_map_size,
)
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
wtxn.commit()?;
@ -357,7 +362,8 @@ impl IndexMapper {
};
let index_path = self.base_path.join(uuid.to_string());
// take the lock to reopen the environment.
reopen.reopen(&mut self.index_map.write().unwrap(), &index_path)
reopen
.reopen(&mut self.index_map.write().unwrap(), &index_path)
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
continue;
}
@ -373,13 +379,15 @@ impl IndexMapper {
Missing => {
let index_path = self.base_path.join(uuid.to_string());
break index_map.create(
&uuid,
&index_path,
None,
self.enable_mdb_writemap,
self.index_base_map_size,
).map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
break index_map
.create(
&uuid,
&index_path,
None,
self.enable_mdb_writemap,
self.index_base_map_size,
)
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
}
Available(index) => break index,
Closing(_) => {
@ -460,7 +468,8 @@ impl IndexMapper {
None => {
let index = self.index(rtxn, index_uid)?;
let index_rtxn = index.read_txn()?;
IndexStats::new(&index, &index_rtxn).map_err(|e| Error::from_milli(e, Some(uuid.to_string())))
IndexStats::new(&index, &index_rtxn)
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))
}
}
}

View File

@ -1210,8 +1210,9 @@ impl IndexScheduler {
tracing::info!("A batch of tasks was successfully completed with {success} successful tasks and {failure} failed tasks.");
}
// If we have an abortion error we must stop the tick here and re-schedule tasks.
Err(Error::Milli{
error: milli::Error::InternalError(milli::InternalError::AbortedIndexation), ..
Err(Error::Milli {
error: milli::Error::InternalError(milli::InternalError::AbortedIndexation),
..
})
| Err(Error::AbortedTask) => {
#[cfg(test)]
@ -1232,7 +1233,8 @@ impl IndexScheduler {
// 3. resize it
// 4. re-schedule tasks
Err(Error::Milli {
error: milli::Error::UserError(milli::UserError::MaxDatabaseSizeReached), ..
error: milli::Error::UserError(milli::UserError::MaxDatabaseSizeReached),
..
}) if index_uid.is_some() => {
// fixme: add index_uid to match to avoid the unwrap
let index_uid = index_uid.unwrap();
@ -1481,11 +1483,12 @@ impl IndexScheduler {
config: milli::vector::EmbeddingConfig { embedder_options, prompt, quantized },
..
}| {
let prompt =
Arc::new(prompt.try_into()
let prompt = Arc::new(
prompt
.try_into()
.map_err(meilisearch_types::milli::Error::from)
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?
);
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?,
);
// optimistically return existing embedder
{
let embedders = self.embedders.read().unwrap();
@ -5204,7 +5207,7 @@ mod tests {
insta::assert_json_snapshot!(simple_hf_config.embedder_options);
let simple_hf_name = name.clone();
let configs = index_scheduler.embedders(configs).unwrap();
let configs = index_scheduler.embedders("doggos".to_string(), configs).unwrap();
let (hf_embedder, _, _) = configs.get(&simple_hf_name).unwrap();
let beagle_embed = hf_embedder.embed_one(S("Intel the beagle best doggo")).unwrap();
let lab_embed = hf_embedder.embed_one(S("Max the lab best doggo")).unwrap();

View File

@ -9,8 +9,8 @@ source: index-scheduler/src/lib.rs
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
1 {uid: 1, status: succeeded, details: { received_documents: 3, indexed_documents: Some(3) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 3, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_document_ids: 1, deleted_documents: Some(1) }, kind: DocumentDeletion { index_uid: "doggos", documents_ids: ["1"] }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
4 {uid: 4, status: failed, error: ResponseError { code: 200, message: "Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
4 {uid: 4, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
5 {uid: 5, status: succeeded, details: { original_filter: "catto EXISTS", deleted_documents: Some(1) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("catto EXISTS") }}
----------------------------------------------------------------------
### Status:

View File

@ -9,7 +9,7 @@ source: index-scheduler/src/lib.rs
0 {uid: 0, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":0,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":1,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
4 {uid: 4, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:

View File

@ -9,7 +9,7 @@ source: index-scheduler/src/lib.rs
0 {uid: 0, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":0,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Document doesn't have a `bork` attribute: `{\"id\":1,\"doggo\":\"jean bob\"}`.", error_code: "missing_document_id", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#missing_document_id" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:

View File

@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:

View File

@ -7,8 +7,8 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bloup"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued []

View File

@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `id`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:

View File

@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
4 {uid: 4, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}

View File

@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}

View File

@ -7,7 +7,7 @@ source: index-scheduler/src/lib.rs
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
1 {uid: 1, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Index already has a primary key: `doggoid`.", error_code: "index_primary_key_already_exists", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#index_primary_key_already_exists" }, details: { received_documents: 1, indexed_documents: Some(0) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("bork"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("doggoid"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000002, documents_count: 1, allow_index_creation: true }}
3 {uid: 3, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000003, documents_count: 1, allow_index_creation: true }}
4 {uid: 4, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000004, documents_count: 1, allow_index_creation: true }}

View File

@ -4,10 +4,10 @@ use byte_unit::{Byte, UnitType};
use meilisearch_types::document_formats::{DocumentFormatError, PayloadType};
use meilisearch_types::error::{Code, ErrorCode, ResponseError};
use meilisearch_types::index_uid::{IndexUid, IndexUidFormatError};
use meilisearch_types::milli;
use meilisearch_types::milli::OrderBy;
use serde_json::Value;
use tokio::task::JoinError;
use meilisearch_types::milli;
#[derive(Debug, thiserror::Error)]
pub enum MeilisearchHttpError {
@ -105,7 +105,7 @@ impl ErrorCode for MeilisearchHttpError {
MeilisearchHttpError::SerdeJson(_) => Code::Internal,
MeilisearchHttpError::HeedError(_) => Code::Internal,
MeilisearchHttpError::IndexScheduler(e) => e.error_code(),
MeilisearchHttpError::Milli{error, ..} => error.error_code(),
MeilisearchHttpError::Milli { error, .. } => error.error_code(),
MeilisearchHttpError::Payload(e) => e.error_code(),
MeilisearchHttpError::FileStore(_) => Code::Internal,
MeilisearchHttpError::DocumentFormat(e) => e.error_code(),

View File

@ -185,7 +185,8 @@ pub async fn search(
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
let search_kind = search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index, features)?;
let search_kind =
search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index, features)?;
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_facet_search(

View File

@ -107,7 +107,10 @@ pub async fn list_indexes(
if !filters.is_index_authorized(uid) {
return Ok(None);
}
Ok(Some(IndexView::new(uid.to_string(), index).map_err(|e| Error::from_milli(e, Some(uid.to_string())))?))
Ok(Some(
IndexView::new(uid.to_string(), index)
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
))
})?;
// Won't cause to open all indexes because IndexView doesn't keep the `Index` opened.
let indexes: Vec<IndexView> = indexes.into_iter().flatten().collect();

View File

@ -243,11 +243,19 @@ pub async fn search_with_url_query(
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
let search_kind = search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let search_kind =
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(index_uid.to_string(), &index, query, search_kind, retrieve_vector, index_scheduler.features())
perform_search(
index_uid.to_string(),
&index,
query,
search_kind,
retrieve_vector,
index_scheduler.features(),
)
})
.await;
permit.drop().await;
@ -287,12 +295,20 @@ pub async fn search_with_post(
let features = index_scheduler.features();
let search_kind = search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let search_kind =
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(index_uid.to_string(), &index, query, search_kind, retrieve_vectors, index_scheduler.features())
perform_search(
index_uid.to_string(),
&index,
query,
search_kind,
retrieve_vectors,
index_scheduler.features(),
)
})
.await;
permit.drop().await;

View File

@ -103,8 +103,13 @@ async fn similar(
let index = index_scheduler.index(&index_uid)?;
let (embedder_name, embedder, quantized) =
SearchKind::embedder(&index_scheduler, index_uid.to_string(), &index, &query.embedder, None)?;
let (embedder_name, embedder, quantized) = SearchKind::embedder(
&index_scheduler,
index_uid.to_string(),
&index,
&query.embedder,
None,
)?;
tokio::task::spawn_blocking(move || {
perform_similar(

View File

@ -127,14 +127,26 @@ pub async fn multi_search_with_post(
let index_uid_str = index_uid.to_string();
let search_kind =
search_kind(&query, index_scheduler.get_ref(), index_uid_str.clone(), &index, features)
.with_index(query_index)?;
let search_kind = search_kind(
&query,
index_scheduler.get_ref(),
index_uid_str.clone(),
&index,
features,
)
.with_index(query_index)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)
.with_index(query_index)?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(index_uid_str.clone(), &index, query, search_kind, retrieve_vector, features)
perform_search(
index_uid_str.clone(),
&index,
query,
search_kind,
retrieve_vector,
features,
)
})
.await
.with_index(query_index)?;

View File

@ -560,7 +560,8 @@ pub fn perform_federated_search(
// use an immediately invoked lambda to capture the result without returning from the function
let res: Result<(), ResponseError> = (|| {
let search_kind = search_kind(&query, index_scheduler, index_uid.to_string(), &index, features)?;
let search_kind =
search_kind(&query, index_scheduler, index_uid.to_string(), &index, features)?;
let canonicalization_kind = match (&search_kind, &query.q) {
(SearchKind::SemanticOnly { .. }, _) => {
@ -636,7 +637,8 @@ pub fn perform_federated_search(
search.offset(0);
search.limit(required_hit_count);
let (result, _semantic_hit_count) = super::search_from_kind(index_uid.to_string(), search_kind, search)?;
let (result, _semantic_hit_count) =
super::search_from_kind(index_uid.to_string(), search_kind, search)?;
let format = AttributesFormat {
attributes_to_retrieve: query.attributes_to_retrieve,
retrieve_vectors,
@ -670,8 +672,10 @@ pub fn perform_federated_search(
let formatter_builder = HitMaker::formatter_builder(matching_words, tokenizer);
let hit_maker = HitMaker::new(&index, &rtxn, format, formatter_builder)
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
let hit_maker =
HitMaker::new(&index, &rtxn, format, formatter_builder).map_err(|e| {
MeilisearchHttpError::from_milli(e, Some(index_uid.to_string()))
})?;
results_by_query.push(SearchResultByQuery {
federation_options,

View File

@ -19,7 +19,9 @@ use meilisearch_types::locales::Locale;
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
use meilisearch_types::milli::vector::Embedder;
use meilisearch_types::milli::{FacetValueHit, InternalError, OrderBy, SearchForFacetValues, TimeBudget};
use meilisearch_types::milli::{
FacetValueHit, InternalError, OrderBy, SearchForFacetValues, TimeBudget,
};
use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
use meilisearch_types::{milli, Document};
use milli::tokenizer::{Language, TokenizerBuilder};
@ -1077,17 +1079,20 @@ pub fn search_from_kind(
) -> Result<(milli::SearchResult, Option<u32>), MeilisearchHttpError> {
let (milli_result, semantic_hit_count) = match &search_kind {
SearchKind::KeywordOnly => {
let results = search.execute()
let results = search
.execute()
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
(results, None)
},
}
SearchKind::SemanticOnly { .. } => {
let results = search.execute()
let results = search
.execute()
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
let semantic_hit_count = results.document_scores.len() as u32;
(results, Some(semantic_hit_count))
}
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)
SearchKind::Hybrid { semantic_ratio, .. } => search
.execute_hybrid(*semantic_ratio)
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid)))?,
};
Ok((milli_result, semantic_hit_count))
@ -1285,11 +1290,7 @@ impl<'a> HitMaker<'a> {
})
}
pub fn make_hit(
&self,
id: u32,
score: &[ScoreDetails],
) -> milli::Result<SearchHit> {
pub fn make_hit(&self, id: u32, score: &[ScoreDetails]) -> milli::Result<SearchHit> {
let (_, obkv) =
self.index.iter_documents(self.rtxn, std::iter::once(id))?.next().unwrap()?;
@ -1332,7 +1333,10 @@ impl<'a> HitMaker<'a> {
.is_some_and(|conf| conf.user_provided.contains(id));
let embeddings =
ExplicitVectors { embeddings: Some(vector.into()), regenerate: !user_provided };
vectors.insert(name, serde_json::to_value(embeddings).map_err(InternalError::SerdeJson)?);
vectors.insert(
name,
serde_json::to_value(embeddings).map_err(InternalError::SerdeJson)?,
);
}
document.insert("_vectors".into(), vectors.into());
}
@ -1937,7 +1941,7 @@ fn parse_filter_array(arr: &[Value]) -> Result<Option<Filter>, MeilisearchHttpEr
}
}
Ok(Filter::from_array(ands).map_err(|e|MeilisearchHttpError::from_milli(e,None))?)
Filter::from_array(ands).map_err(|e| MeilisearchHttpError::from_milli(e, None))
}
#[cfg(test)]

View File

@ -1446,7 +1446,7 @@ async fn error_document_field_limit_reached_over_multiple_documents() {
"indexedDocuments": 0
},
"error": {
"message": "A document cannot contain more than 65,535 fields.",
"message": "Index `test`: A document cannot contain more than 65,535 fields.",
"code": "max_fields_limit_exceeded",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#max_fields_limit_exceeded"
@ -2242,7 +2242,7 @@ async fn add_invalid_geo_and_then_settings() {
]
},
"error": {
"message": "Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
"message": "Index `test`: Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
"code": "invalid_document_geo_field",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"

View File

@ -602,7 +602,7 @@ async fn delete_document_by_filter() {
"originalFilter": "\"doggo = bernese\""
},
"error": {
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
"message": "Index `EMPTY_INDEX`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
"code": "invalid_document_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
@ -633,7 +633,7 @@ async fn delete_document_by_filter() {
"originalFilter": "\"catto = jorts\""
},
"error": {
"message": "Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
"message": "Index `SHARED_DOCUMENTS`: Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
"code": "invalid_document_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"

View File

@ -95,7 +95,7 @@ async fn error_update_existing_primary_key() {
let response = index.wait_task(2).await;
let expected_response = json!({
"message": "Index already has a primary key: `id`.",
"message": "Index `test`: Index already has a primary key: `id`.",
"code": "index_primary_key_already_exists",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#index_primary_key_already_exists"

View File

@ -711,7 +711,7 @@ async fn filter_invalid_attribute_array() {
index.wait_task(task.uid()).await;
let expected_response = json!({
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
"code": "invalid_search_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
@ -733,7 +733,7 @@ async fn filter_invalid_attribute_string() {
index.wait_task(task.uid()).await;
let expected_response = json!({
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
"code": "invalid_search_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
@ -940,7 +940,7 @@ async fn sort_unsortable_attribute() {
index.wait_task(response.uid()).await.succeeded();
let expected_response = json!({
"message": "Attribute `title` is not sortable. Available sortable attributes are: `id`.",
"message": format!("Index `{}`: Attribute `title` is not sortable. Available sortable attributes are: `id`.", index.uid),
"code": "invalid_search_sort",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
@ -998,7 +998,7 @@ async fn sort_unset_ranking_rule() {
index.wait_task(response.uid()).await.succeeded();
let expected_response = json!({
"message": "You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.",
"message": format!("Index `{}`: You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.", index.uid),
"code": "invalid_search_sort",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
@ -1018,8 +1018,8 @@ async fn sort_unset_ranking_rule() {
#[actix_rt::test]
async fn search_on_unknown_field() {
let server = Server::new_shared();
let index = server.unique_index();
let server = Server::new().await;
let index = server.index("test");
let (response, _code) =
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
index.wait_task(response.uid()).await.succeeded();
@ -1031,7 +1031,7 @@ async fn search_on_unknown_field() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"code": "invalid_search_attributes_to_search_on",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
@ -1044,8 +1044,8 @@ async fn search_on_unknown_field() {
#[actix_rt::test]
async fn search_on_unknown_field_plus_joker() {
let server = Server::new_shared();
let index = server.unique_index();
let server = Server::new().await;
let index = server.index("test");
let (response, _code) =
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
index.wait_task(response.uid()).await.succeeded();
@ -1057,7 +1057,7 @@ async fn search_on_unknown_field_plus_joker() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"code": "invalid_search_attributes_to_search_on",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
@ -1074,7 +1074,7 @@ async fn search_on_unknown_field_plus_joker() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"message": "Index `test`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
"code": "invalid_search_attributes_to_search_on",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
@ -1087,8 +1087,8 @@ async fn search_on_unknown_field_plus_joker() {
#[actix_rt::test]
async fn distinct_at_search_time() {
let server = Server::new_shared();
let index = server.unique_index();
let server = Server::new().await;
let index = server.index("test");
let (task, _) = index.create(None).await;
index.wait_task(task.uid()).await.succeeded();
@ -1097,7 +1097,7 @@ async fn distinct_at_search_time() {
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
@ -1112,7 +1112,7 @@ async fn distinct_at_search_time() {
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
@ -1127,7 +1127,7 @@ async fn distinct_at_search_time() {
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
"message": "Index `test`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"

View File

@ -1070,7 +1070,7 @@ async fn federation_one_query_error() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[1]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
"message": "Inside `.queries[1]`: Index `nested`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
"code": "invalid_search_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
@ -1102,7 +1102,7 @@ async fn federation_one_query_sort_error() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
"code": "invalid_search_sort",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
@ -1166,7 +1166,7 @@ async fn federation_multiple_query_errors() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[0]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
"code": "invalid_search_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
@ -1198,7 +1198,7 @@ async fn federation_multiple_query_sort_errors() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[0]`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
"code": "invalid_search_sort",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
@ -1231,7 +1231,7 @@ async fn federation_multiple_query_errors_interleaved() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[1]`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
"code": "invalid_search_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
@ -1264,7 +1264,7 @@ async fn federation_multiple_query_sort_errors_interleaved() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
"code": "invalid_search_sort",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"

View File

@ -529,7 +529,7 @@ async fn test_summarized_delete_documents_by_filter() {
"originalFilter": "\"doggo = bernese\""
},
"error": {
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
"message": "Index `test`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
"code": "invalid_document_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"

View File

@ -317,7 +317,7 @@ async fn try_to_disable_binary_quantization() {
}
},
"error": {
"message": "`.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
"message": "Index `doggo`: `.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"

View File

@ -249,7 +249,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -278,7 +278,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -308,7 +308,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -337,7 +337,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -366,7 +366,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -395,7 +395,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -436,7 +436,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -464,7 +464,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -492,7 +492,7 @@ async fn user_provided_embeddings_error() {
"indexedDocuments": 0
},
"error": {
"message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
"message": "Index `doggo`: Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
"code": "invalid_vectors_type",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
@ -532,7 +532,7 @@ async fn user_provided_vectors_error() {
"indexedDocuments": 0
},
"error": {
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"40\" and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"40\" and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
@ -561,7 +561,7 @@ async fn user_provided_vectors_error() {
"indexedDocuments": 0
},
"error": {
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
@ -590,7 +590,7 @@ async fn user_provided_vectors_error() {
"indexedDocuments": 0
},
"error": {
"message": "While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document \"42\"\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"

View File

@ -700,7 +700,7 @@ async fn bad_api_key() {
}
},
"error": {
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
@ -743,7 +743,7 @@ async fn bad_api_key() {
}
},
"error": {
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
"code": "vector_embedding_error",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"

View File

@ -937,7 +937,7 @@ async fn bad_settings() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -976,7 +976,7 @@ async fn bad_settings() {
"indexedDocuments": 0
},
"error": {
"message": "While embedding documents for embedder `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
"message": "Index `doggo`: 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"
@ -1127,7 +1127,7 @@ async fn server_returns_bad_request() {
}
},
"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\"}`",
"message": "Index `doggo`: 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"
@ -1194,7 +1194,7 @@ async fn server_returns_bad_request() {
"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\"}`",
"message": "Index `doggo`: 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"
@ -1252,7 +1252,7 @@ async fn server_returns_bad_response() {
}
},
"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)",
"message": "Index `doggo`: 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"
@ -1307,7 +1307,7 @@ async fn server_returns_bad_response() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -1358,7 +1358,7 @@ async fn server_returns_bad_response() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -1421,7 +1421,7 @@ async fn server_returns_bad_response() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -1484,7 +1484,7 @@ async fn server_returns_bad_response() {
}
},
"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?",
"message": "Index `doggo`: 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"
@ -1846,7 +1846,7 @@ async fn server_custom_header() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -1888,7 +1888,7 @@ async fn server_custom_header() {
}
},
"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",
"message": "Index `doggo`: 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"
@ -2031,7 +2031,7 @@ async fn searchable_reindex() {
]
},
"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\"}`",
"message": "Index `doggo`: 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"