Meilisearch v1.55 release notes - Meilisearch Documentation

New Features

Preview the effect of a dynamic search rule

You can now apply an inline-specified dynamic search rule to a search query without saving it permanently. This lets you test how a rule would affect search results before deploying it. The POST /indexes/{:indexUid}/search and POST /multi-search endpoints now accept an optional inlineRule parameter in the search query object. When provided, Meilisearch will apply the rule’s actions to that specific search as if it had been saved. When you include the Meili-Include-Metadata: true header, the response’s metadata will show whether the inline rule’s conditions were satisfied and why (if not). Note: This feature requires Meilisearch Enterprise Edition and the dynamicSearchRules experimental feature. Example: Apply a user-specific rule to boost Batman movies

{
  "q": "super hero",
  "inlineRule": {
    "uid": "user-likes-batman",
    "actions": {
      "scale": [
        {
          "filter": "hero = batman AND release_time = fresh",
          "weight": 1.2
        }
      ]
    }
  }
}

Example: Compare search results with and without a rule

{
  "queries": [
    {
      "q": "fashion",
      "filter": "color = blue AND category = shirt"
    },
    {
      "q": "fashion",
      "filter": "color = blue AND category = shirt",
      "inlineRule": {
        "uid": "special-sales",
        "conditions": {
          "query": {
            "words": "pants"
          },
          "filter": {
            "values": {
              "color": "yellow",
              "stock_intent": "destock"
            }
          }
        }
      }
    }
  ]
}

Improvements

The performanceDetails in search responses now includes timing information for facet distribution computation. When you set showPerformanceDetails to true, you’ll see separate entries for:

compute facet distribution: Time spent computing facet counts
compute facet stats: Time spent computing facet statistics
facet distribution: Total time for all facet-related operations

This helps you identify whether facet computation is affecting your search performance. Example response with facet performance details

{
  "performanceDetails": {
    "process > execute local > facet distribution > compute facet distribution": "315.75µs",
    "process > execute local > facet distribution > compute facet stats": "27.71µs",
    "process > execute local > facet distribution": "432.62µs"
  }
}

Other

Fixed ranking score threshold performance

Meilisearch now stops searching immediately after finding the first document below the rankingScoreThreshold, rather than continuing to evaluate additional documents. This significantly improves search performance when using this parameter. Note: This fix may change result ordering in some cases, as allowed by our compatibility policy.

Breaking change: Binary quantization cannot be disabled

If your embedder is configured with binary quantization, you can no longer disable it by passing binaryQuantization: null in an embedder settings update. Doing so now returns an error. Binary quantization is permanent for an index because the exact embedding values cannot be recovered after quantization. Find more information on GitHub

​New Features

​Preview the effect of a dynamic search rule

​Improvements

​Better performance tracking for facet distribution

​Other

​Fixed ranking score threshold performance

​Breaking change: Binary quantization cannot be disabled