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5371: Composite embedders r=irevoire a=dureuill
# Pull Request
## Related issue
Fixes#5343
## What does this PR do?
- Implement [public usage](https://www.notion.so/meilisearch/Composite-embedder-usage-14a4b06b651f81859dc3df21e8cd02a0)
- Refactor the way we check if a parameter is mandatory/allowed/disallowed for a given source
- Take the "nesting context" into account for computer if a parameter is mandatory/allowed/disallowed
- Add tests checking all parameters with all sources, and made sure the results didn't change compared with v1.13
## Dumpless Upgrade
- This adds a new value for an existing parameter => compatible without change
- This adds new optional parameters => compatible without change
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
**Changes:**
The searchable database extraction is now relying on the AttributePatterns and FieldIdMapWithMetadata to match the field to extract.
Remove the SearchableExtractor trait to make the code less complex.
**Impact:**
- Document Addition/modification searchable indexing
- Document deletion searchable indexing
**Changes:**
The Documents changes now take a selector closure instead of a list of field to match the field to extract.
The seek_leaf_values_in_object function now uses a selector closure of a list of field to match the field to extract
The facet database extraction is now relying on the FilterableAttributesRule to match the field to extract.
The facet-search database extraction is now relying on the FieldIdMapWithMetadata to select the field to index.
The facet level database extraction is now relying on the FieldIdMapWithMetadata to select the field to index.
**Important:**
Because the filterable attributes are patterns now,
the fieldIdMap will only register the fields that exists in at least one document.
if a field doesn't exist in any document, it will not be registered even if it has been specified in the filterable fields.
**Impact:**
- Document Addition/modification facet indexing
- Document deletion facet indexing
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5351: Bring back v1.13.0 changes into main r=irevoire a=Kerollmops
This PR brings back the changes made in v1.13 into the main branch.
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: Clémentine <clementine@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
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5316: Fix the dumpless upgrade corruption r=dureuill a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/5280
## What does this PR do?
- Add a test that ensure we write the version in the index-scheduler even if we have a bug while writing the VERSION file
- Do what was described in the issue
Co-authored-by: Tamo <tamo@meilisearch.com>
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5288: Improve AI logging r=dureuill a=Kerollmops
This PR fixes#5285 and brings the changes from #5233 to simplify debugging indexation and search performance issues related to AI. The following texts can be found in the logs to debug and understand performance issues:
- `embed_one: search` represents the time we spent waiting for the embedding generation, i.e., OpenAI, local HuggingFace, Ollama.
- `filtered_universe: search::universe` the time spent filtering the documents.
- ~`next_bucket: search::vector_sort` is the time spent finding the nearest neighbors (ANNs) in the vector store (arroy), locally~ was being triggered too many times.
- `indexing::vectors` is the time arroy spends indexing the new vectors for a batch.
- `documents::extract vectors` and `documents::merge vectors` to see the time spent generating and writing the embeddings.
Co-authored-by: Kerollmops <clement@meilisearch.com>
