Meilisearch v1.10 release notes - Meilisearch Documentation

New Features

Federated search

Use the new federation setting of the /multi-search route to return a single search result object combining results from multiple indexes:

curl \
 -X POST 'http://localhost:7700/multi-search' \
 -H 'Content-Type: application/json' \
 --data-binary << 'EOF'
{
 "federation": {
 "offset": 5,
 "limit": 10
 },
 "queries": [
 {
 "q": "Batman",
 "indexUid": "movies"
 },
 {
 "q": "Batman",
 "indexUid": "comics"
 }
 ]
}
EOF

Response includes results merged in descending ranking score order with federation metadata:

{
  "hits": [
    {
      "id": 42,
      "title": "Batman returns",
      "overview": "..",
      "_federation": {
        "indexUid": "movies",
        "queriesPosition": 0
      }
    }
  ],
  "processingTimeMs": 0,
  "limit": 20,
  "offset": 0,
  "estimatedTotalHits": 2,
  "semanticHitCount": 0
}

Control the relevancy weight of each index using federationOptions in each query:

curl \
 -X POST 'http://localhost:7700/multi-search' \
 -H 'Content-Type: application/json' \
 --data-binary << 'EOF'
{
 "federation": {},
 "queries": [
 {
 "q": "apple red",
 "indexUid": "fruits",
 "federationOptions": {
 "weight": 3.0
 }
 },
 {
 "q": "apple red",
 "indexUid": "fruits",
 "federationOptions": {
 "weight": 0.5
 }
 }
 ]
}
EOF

The weight parameter controls how likely results from each index appear in the final results. Values less than 1.0 make results less likely to appear, while values greater than 1.0 make them more likely. Default is 1.0.

Language settings

Explicitly define which languages are used in your documents for better search accuracy, particularly helpful for datasets with multiple languages or those that previously required workarounds. Set languages during indexing with localizedAttributes:

curl \
 -X PATCH 'http://localhost:7700/indexes/movies/settings' \
 -H 'Content-Type: application/json' \
 --data-binary << 'EOF'
{
 "localizedAttributes": [
 {
 "locales": ["jpn"],
 "attributePatterns": ["*_ja"]
 },
 {
 "locales": ["eng"],
 "attributePatterns": ["*_en"]
 },
 {
 "locales": ["cmn"],
 "attributePatterns": ["*_zh"]
 },
 {
 "locales": ["fra", "ita"],
 "attributePatterns": ["latin.*"]
 },
 {
 "locales": ,
 "attributePatterns": ["*"]
 }
 ]
}
EOF

Supported language codes include: epo, eng, rus, cmn, spa, por, ita, ben, fra, deu, ukr, kat, ara, hin, jpn, heb, yid, pol, amh, jav, kor, nob, dan, swe, fin, tur, nld, hun, ces, ell, bul, bel, mar, kan, ron, slv, hrv, srp, mkd, lit, lav, est, tam, vie, urd, tha, guj, uzb, pan, aze, ind, tel, pes, mal, ori, mya, nep, sin, khm, tuk, aka, zul, sna, afr, lat, slk, cat, tgl, hye. Set language at search time with the locales parameter:

curl \
 -X POST http://localhost:7700/indexes/movies/search \
 -H 'Content-Type: application/json' \
 --data-binary '{"q": "進撃の巨人", "locales": ["jpn"]}'

Experimental: CONTAINS filter operator

Enable the containsFilter experimental feature to filter results containing partial string matches:

curl \
 -X PATCH 'http://localhost:7700/experimental-features/' \
 -H 'Content-Type: application/json' \
 --data-binary '{"containsFilter": true}'

Use the CONTAINS operator in filter expressions:

curl \
 -X POST http://localhost:7700/indexes/movies/search \
 -H 'Content-Type: application/json' \
 --data-binary '{"q": "super hero", "filter": "synopsis CONTAINS spider"}'

Experimental: Edit documents with a Rhai function

Update a subset of your documents using a function directly from Meilisearch without needing to fetch, modify, and reindex them. First, enable the experimental feature:

curl \
 -X PATCH 'http://localhost:7700/experimental-features/' \
 -H 'Content-Type: application/json' \
 --data-binary '{"editDocumentsByFunction": true}'

Then use the /documents/edit route:

curl http://localhost:7700/indexes/movies/documents/edit \
 -H 'content-type: application/json' \
 --data-binary '{"function": "doc.title = `✨ ${doc.title.to_upper} ✨`", "filter": "id > 3000"}'

The function parameter accepts Rhai code that can modify document fields. Use the filter parameter to target specific documents and context to pass data to your function.

Improvements

Search performance

Implemented intersection at the end of the search pipeline for faster search operations.

Indexing performance

Stopped opening indexes just to check if they exist, reducing unnecessary overhead during indexing operations.

AI-powered search enhancements

Several quality-of-life improvements for REST embedders and remote embedding services:

Add custom headers to REST embedders using the optional headers parameter to include additional headers in requests to remote embedders
Add optional url parameter to OpenAI embedder to specify a custom embedding endpoint
dimensions parameter now available for Ollama embedders
Improved error messages when embeddings are missing or model configurations cannot be loaded
Exponential backoff duration is now randomized when REST embedder requests fail
OpenAI embeddings that exceed max tokens are now truncated rather than embedded by chunk

Error handling and messaging

Improved tenant token error messages for better debugging
Wrong HTTP status and confusing error messages on incorrect payloads have been fixed
Errors at the main Meilisearch binary level are now logged with ERROR level for better visibility

Improved documentation of natural language processing

Added null byte as hard context separator and included all math symbols in the default separator list for better text processing across languages.

Heavy load handling

Optimized search queue handling to spawn only one search queue in actix-web
Improved index scheduler reliability to prevent stopping during heavy loads
Explicitly drop search permits to free resources more efficiently
Stop processing searches that take longer than one minute to prevent resource exhaustion

Document operations

Made autobatching of document deletions with document deletions by filter possible, unclogging the task queue for users performing these operations heavily.

Search configuration

Added experimental CLI flags to fine-tune search behavior:

--experimental-nb-searches-per-core: Configure how many searches Meilisearch can process concurrently per core
--experimental-drop-search-after: Set how many seconds before Meilisearch considers a search irrelevant and drops it without processing

Other

Breaking changes

REST embedder configuration

The REST embedder configuration has been simplified and changed in v1.10: Old v1.9 format:

{
  "source": "rest",
  "url": "https://localhost:10006",
  "query": {
    "model": "minillm"
  },
  "inputField": [
    "prompt"
  ],
  "inputType": "text",
  "embeddingObject": [
    "embedding"
  ]
}

New v1.10 format:

{
  "source": "rest",
  "url": "https://localhost:10006",
  "request": {
    "model": "minillm",
    "prompt": "{{text}}"
  },
  "response": {
    "embedding": "{{embedding}}"
  }
}

The request object represents the request sent to the remote embedder, with {{text}} as a placeholder for the text to embed. The response object represents the response structure, with {{embedding}} as a placeholder for the embedding vector. If you have dumps with REST embedder configurations from v1.9, you must remove embedders with source "rest" before importing into v1.10. Attempting to import will result in an error about unknown fields.

Minimum Ubuntu version requirement

Meilisearch now requires Ubuntu 20.04 or later. Ubuntu 18.04 is no longer supported due to GitHub Actions runner requirements. Find more information on GitHub

​New Features

​Federated search

​Language settings

​Experimental: CONTAINS filter operator

​Experimental: Edit documents with a Rhai function

​Improvements

​Search performance

​Indexing performance

​AI-powered search enhancements

​Error handling and messaging

​Improved documentation of natural language processing

​Heavy load handling

​Document operations

​Search configuration

​Other

​Breaking changes

​REST embedder configuration

​Minimum Ubuntu version requirement