build(deps): bump objectbox_flutter_libs, objectbox and objectbox_generator

[dependabot]

Bumps objectbox_flutter_libs, objectbox and objectbox_generator. These dependencies needed to be updated together.
Updates objectbox_flutter_libs from 2.5.1 to 4.0.1

Release notes

Sourced from objectbox_flutter_libs's releases.

v4.0.1

• Export ObjectWithScore and IdWithScore used by the new find with score Query methods. #637
• Add simple vectorsearch_cities Dart Native example application.

Note: this release includes the same versions of the Android library and ObjectBox pod as release 4.0.0. See update instructions there.

V4.0 Vector Search

To upgrade to this major release run flutter pub upgrade objectbox --major-versions (or for Dart Native apps dart pub upgrade objectbox --major-versions).

ObjectBox now supports Vector Search to enable efficient similarity searches.

This is particularly useful for AI/ML/RAG applications, e.g. image, audio, or text similarity. Other use cases include semantic search or recommendation engines.

Create a Vector (HNSW) index for a floating point vector property. For example, a City with a location vector:

@Entity()
class City {
@​HnswIndex(dimensions: 2)
@​Property(type: PropertyType.floatVector)
List<double>? location;
}

Perform a nearest neighbor search using the new nearestNeighborsF32(queryVector, maxResultCount) query condition and the new "find with scores" query methods (the score is the distance to the query vector). For example, find the 2 closest cities:

final madrid = [40.416775, -3.703790];
final query = box
    .query(City_.location.nearestNeighborsF32(madrid, 2))
    .build();
final closest = query.findWithScores()[0].object;

For an introduction to Vector Search, more details and other supported languages see the Vector Search documentation.

• The generator correctly errors when using an unsupported index on a vector type.
• Flutter for Linux/Windows, Dart Native: update to objectbox-c 4.0.0.
• Flutter for Android: update to objectbox-android 4.0.0. If you are using Admin, make sure to update to io.objectbox:objectbox-android-objectbrowser:4.0.0 in android/app/build.gradle.
• Flutter for iOS/macOS: update to objectbox-swift 2.0.0. Existing projects may have to run pod repo update and pod update ObjectBox.

Commits

• a4c88f2 Prepare release 4.0.1
• 93efa5f READMEs: update vector search docs link, hint at on-device
• 564b3dc Merge branch '106-vector-search-example' into 'main'
• aceaa52 Cities: add first basic Vector Search example using Cities
• 61a04a7 Merge branch 'gh-637-export-with-score-wrappers' into 'main'
• fbbd4e4 Regression: export with score wrapper classes GH#637
• 045460f Prepare for next release
• 6a54675 Prepare release 4.0.0
• 52e9f9d CHANGELOG: clarify generator errors on unsupported indexes on vectors
• 210a139 README: fix line breaks
• Additional commits viewable in compare view

Updates objectbox from 2.5.1 to 4.0.1

Release notes

Sourced from objectbox's releases.

v4.0.1

• Export ObjectWithScore and IdWithScore used by the new find with score Query methods. #637
• Add simple vectorsearch_cities Dart Native example application.

Note: this release includes the same versions of the Android library and ObjectBox pod as release 4.0.0. See update instructions there.

V4.0 Vector Search

To upgrade to this major release run flutter pub upgrade objectbox --major-versions (or for Dart Native apps dart pub upgrade objectbox --major-versions).

ObjectBox now supports Vector Search to enable efficient similarity searches.

This is particularly useful for AI/ML/RAG applications, e.g. image, audio, or text similarity. Other use cases include semantic search or recommendation engines.

Create a Vector (HNSW) index for a floating point vector property. For example, a City with a location vector:

@Entity()
class City {
@​HnswIndex(dimensions: 2)
@​Property(type: PropertyType.floatVector)
List<double>? location;
}

Perform a nearest neighbor search using the new nearestNeighborsF32(queryVector, maxResultCount) query condition and the new "find with scores" query methods (the score is the distance to the query vector). For example, find the 2 closest cities:

final madrid = [40.416775, -3.703790];
final query = box
    .query(City_.location.nearestNeighborsF32(madrid, 2))
    .build();
final closest = query.findWithScores()[0].object;

For an introduction to Vector Search, more details and other supported languages see the Vector Search documentation.

• The generator correctly errors when using an unsupported index on a vector type.
• Flutter for Linux/Windows, Dart Native: update to objectbox-c 4.0.0.
• Flutter for Android: update to objectbox-android 4.0.0. If you are using Admin, make sure to update to io.objectbox:objectbox-android-objectbrowser:4.0.0 in android/app/build.gradle.
• Flutter for iOS/macOS: update to objectbox-swift 2.0.0. Existing projects may have to run pod repo update and pod update ObjectBox.

Commits

• a4c88f2 Prepare release 4.0.1
• 93efa5f READMEs: update vector search docs link, hint at on-device
• 564b3dc Merge branch '106-vector-search-example' into 'main'
• aceaa52 Cities: add first basic Vector Search example using Cities
• 61a04a7 Merge branch 'gh-637-export-with-score-wrappers' into 'main'
• fbbd4e4 Regression: export with score wrapper classes GH#637
• 045460f Prepare for next release
• 6a54675 Prepare release 4.0.0
• 52e9f9d CHANGELOG: clarify generator errors on unsupported indexes on vectors
• 210a139 README: fix line breaks
• Additional commits viewable in compare view

Updates objectbox_generator from 2.5.1 to 4.0.1

Release notes

Sourced from objectbox_generator's releases.

v4.0.1

• Export ObjectWithScore and IdWithScore used by the new find with score Query methods. #637
• Add simple vectorsearch_cities Dart Native example application.

Note: this release includes the same versions of the Android library and ObjectBox pod as release 4.0.0. See update instructions there.

V4.0 Vector Search

To upgrade to this major release run flutter pub upgrade objectbox --major-versions (or for Dart Native apps dart pub upgrade objectbox --major-versions).

ObjectBox now supports Vector Search to enable efficient similarity searches.

This is particularly useful for AI/ML/RAG applications, e.g. image, audio, or text similarity. Other use cases include semantic search or recommendation engines.

Create a Vector (HNSW) index for a floating point vector property. For example, a City with a location vector:

@Entity()
class City {
@​HnswIndex(dimensions: 2)
@​Property(type: PropertyType.floatVector)
List<double>? location;
}

Perform a nearest neighbor search using the new nearestNeighborsF32(queryVector, maxResultCount) query condition and the new "find with scores" query methods (the score is the distance to the query vector). For example, find the 2 closest cities:

final madrid = [40.416775, -3.703790];
final query = box
    .query(City_.location.nearestNeighborsF32(madrid, 2))
    .build();
final closest = query.findWithScores()[0].object;

For an introduction to Vector Search, more details and other supported languages see the Vector Search documentation.

• The generator correctly errors when using an unsupported index on a vector type.
• Flutter for Linux/Windows, Dart Native: update to objectbox-c 4.0.0.
• Flutter for Android: update to objectbox-android 4.0.0. If you are using Admin, make sure to update to io.objectbox:objectbox-android-objectbrowser:4.0.0 in android/app/build.gradle.
• Flutter for iOS/macOS: update to objectbox-swift 2.0.0. Existing projects may have to run pod repo update and pod update ObjectBox.

Commits

• a4c88f2 Prepare release 4.0.1
• 93efa5f READMEs: update vector search docs link, hint at on-device
• 564b3dc Merge branch '106-vector-search-example' into 'main'
• aceaa52 Cities: add first basic Vector Search example using Cities
• 61a04a7 Merge branch 'gh-637-export-with-score-wrappers' into 'main'
• fbbd4e4 Regression: export with score wrapper classes GH#637
• 045460f Prepare for next release
• 6a54675 Prepare release 4.0.0
• 52e9f9d CHANGELOG: clarify generator errors on unsupported indexes on vectors
• 210a139 README: fix line breaks
• Additional commits viewable in compare view

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