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Changes related to Meilisearch v1.9.0 #301

@curquiza

Description

@curquiza

This issue gathers the changes related to the v1.9.0 of Meilisearch that will impact the integrations scope.

📅 Release date: 1st July

Timelines & steps

Pre-release

  • With the help of the Product team and this CI, define which integrations should be updated and how (New feature? Update README? Update tests?) -> Fill in the "What to implement?" section below in this issue 👇.
    Minial implementation: PHP, JS, Instant-meilisearch.
  • Create a branch by running Octopus script: only open branches for the integrations we choose to update (defined in the previous step) + Kubernetes repository + Cloud provider repository (changing the version)
  • Update integrations according to the decisions (cf "What to implement?" section below in this issue 👇)
    • JS
    • PHP
    • Instant-meilisearch (update meilisearch-js version)
    • Java: adapt tests following relevancy changes
    • Go: update tests for vector search + add retrieveAttributes
    • Ruby: update tests for vector search
  • Add code samples for the chosen up-to-date integrations with the new version of Meilisearch
  • Update the library version of the related integrations and prepare the changelogs

Release day

  • Release the integrations
    • PHP
    • JS
    • Go
    • instant-meilisearch
  • Merge
    • Java branch
    • Ruby branch
  • Merge the related PR in K8s repository
  • Publish DevOps tools:
    • create the git tag
    • publish images (steps are in CONTRIBUTING.md)
  • Open issues in the repositories that are not up-to-date with the latest version of Meilisearch (including code samples)
    • Hybird search
    • Filter by score
    • frequency matching stregy
    • Get similar documents
    • distinctAttribute at search

What to implement?

AI improvements

Related issue in the engine:

Usage: https://meilisearch.notion.site/v1-9-AI-search-changes-e90d6803eca8417aa70a1ac5d0225697?pvs=74

Changes:

  • Breaking: _vectors no longer returned in documents (by default). Use retrieveVectors during the search to see it.
  • Extension to the _vectors field in documents: in the _vectors field, text can be an object and accept embeddings and regenerate fields
    • embeddings is an array of embeddings, as text can be
    • regenerate is a boolean

TODO:

Vector search feature fully available in: PHP, JS, Python, Go
Vector search feature partially available: Dart, Ruby
Feature not implemented at all: Dotnet, Rust, Swift, Java.

Filter by score

Issue: meilisearch/meilisearch#4609
Usage: https://meilisearch.notion.site/Filter-by-score-usage-224a183ce7b24ca99b6a9a8da755668a?pvs=74

TODO:

frequency matching stregy

Issue: meilisearch/meilisearch#3773

Usage: https://meilisearch.notion.site/frequency-matching-strategy-89868fb7fc584026bc56e378eb854a7f?pvs=74

TODO:

Get similar documents

Issue: meilisearch/meilisearch#4610

Usage: https://meilisearch.notion.site/Get-similar-documents-usage-540919ca755c4da0b7cdee273db3f290?pvs=74

TODO:

Relevancy changes

TODO

  • Adapt Java tests

distinctAttribute at search

Issue: meilisearch/meilisearch#4611

Usage: https://meilisearch.notion.site/Set-distinctAttribute-at-search-usage-947187b312c04616a8ca8ef5bcc5c63c?pvs=74

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