Add string-based filter deletion alongside the Filter.Expression-based deletion
for Milvus vector store, providing consistent deletion capabilities with
other vector store implementations.
Key changes:
- Add delete(Filter.Expression) implementation for Milvus store
- Leverage existing MilvusFilterExpressionConverter for filter translation
- Use Milvus client's native delete API with filter expressions
- Add comprehensive integration tests for filter deletion
- Support both simple and complex filter expressions
This maintains consistency with other vector store implementations while
utilizing Milvus-specific APIs for efficient metadata-based deletion.
Add string-based filter deletion alongside the Filter.Expression-based deletion
for MariaDB vector store, providing consistent deletion capabilities with
other vector store implementations.
Key changes:
- Add delete(Filter.Expression) implementation for MariaDB store
- Integrate with existing MariaDBFilterExpressionConverter
- Add comprehensive integration tests for filter deletion
- Support both simple and complex filter expressions
This maintains consistency with other vector store implementations and
enables flexible document deletion based on metadata filters.
Testcontainers 1.20.4 provides a new module for typesense with
TypesenseContainer implementation.
Signed-off-by: Eddú Meléndez <eddu.melendez@gmail.com>
Add string-based filter deletion alongside the Filter.Expression-based deletion
for vector stores. This provides a more convenient API for simple filter cases
while maintaining the full flexibility of expression-based filtering.
Key changes:
- Add delete(Filter.Expression) and delete(String) methods to VectorStore
- Add default string filter implementation in VectorStore interface
- Implement filter deletion in Chroma/Elasticsearch/PgVector stores
- Add integration tests for both filter APIs across implementations
This extends vector store deletion capabilities while maintaining consistent
behavior across implementations.
Moving BatchingStrategy configuration from individual vector store implementations
to the base AbstractVectorStoreBuilder to reduce code duplication and provide consistent
batching behavior across all vector stores.
The default TokenCountBatchingStrategy is now set in the base builder class.
* Remove use of Document.getContext method from spring-ai-core, use getText
* Remove deprecated ChatOptionsBuilder class
* Remove deprecated FunctionCallingOptionsBuilder class
Updated the manual configuration examples in the following docs to show
the correct usage of the inner builder class:
- azure.adoc: Show builder(searchIndexClient, embeddingModel) with all available options
- chroma.adoc: Show builder(chromaApi, embeddingModel) with collection config
- oracle.adoc: Show builder(jdbcTemplate, embeddingModel) with database options
The examples now reflect the current implementation where the builder takes
both the client and embedding model as constructor arguments.
- Rename all specific builder inner classes (PineconeBuilder, MongoDBBuilder, etc.)
to simply Builder for consistency across vector store implementations
- Update code references to use the new standardized Builder class names
The change establishes a consistent naming convention for builder classes
across the vector store implementations, improving code uniformity.
- Replace Document.getContent() with getText() across all vector store implementations
- Fix incorrect package declarations in package-info.java files
- Make builder constructors private and implement proper builder patterns
- Add @Nullable annotations for better null safety
- Simplify PineconeVectorStore builder API by requiring essential parameters in factory method
- Make static Map fields final
- Clean up code and improve JavaDoc documentation
The changes focus on making the vector store APIs more consistent,
type-safe, and maintainable while following best practices for
builder patterns and null safety.
This commit refactors the builder pattern implementation across all VectorStore
implementations to make the EmbeddingModel a required constructor parameter
rather than an optional builder method. Key changes include:
- Move embeddingModel from being a builder method to a required constructor parameter
- Make embeddingModel final in AbstractVectorStoreBuilder
- Remove redundant validate() methods since EmbeddingModel validation now happens
in constructor
- Update all VectorStore builder instantiations to pass EmbeddingModel in builder
creation
- Add @Nullable annotations to appropriate methods in VectorStore interface
This change improves the API design by:
1. Enforcing that EmbeddingModel is provided at builder creation time
2. Removing the possibility of forgotten EmbeddingModel configuration
3. Simplifying the builder implementation by moving validation to construction
4. Making the dependency on EmbeddingModel more explicit in the API
Breaking Changes:
- VectorStore builders must now be created with an EmbeddingModel parameter
- The embeddingModel() builder method has been removed from all implementations
The Ollama options builder API has been refactored to follow standard Java
builder pattern conventions. This change deprecates all builder methods
prefixed with 'with' in favor of more concise method names, improving API
consistency and usability.
The deprecated methods are marked for removal in version 1.0.0-M5, giving
users time to migrate to the new builder pattern. This change aligns with
our goal of providing a more intuitive and maintainable API surface.
Breaking Changes:
* builder() method now returns Builder instead of OllamaOptions
* Clients using the old fluent API will need to migrate to the new builder pattern
Refactor Ollama options builder methods
This commit deprecates builder methods with the "with" prefix in the VectorStoreObservationContext class
and introduces new methods without the prefix for a cleaner API. For example:
withCollectionName() → collectionName()
withDimensions() → dimensions()
withNamespace() → namespace()
The old methods are marked as deprecated for maintaining backward compatibility.
All vector store implementations have been updated to use the new method names.
Introduces a builder pattern for configuring QdrantVectorStore instances to
provide a more flexible and type-safe way to create and configure vector stores.
This change:
- Makes configuration more intuitive through fluent builder methods
- Improves validation by enforcing required parameters at compile time
- Deprecates old constructors in favor of the builder pattern
- Adds comprehensive builder tests to ensure reliability
- Updates reference documentation with builder usage examples
- Maintains backward compatibility while providing a clear migration path
The builder pattern simplifies QdrantVectorStore configuration by providing
clear method names, proper validation, and better IDE support through method
chaining. This makes the API more user-friendly and helps prevent configuration
errors at compile time rather than runtime.
Introduces a builder pattern for configuring MariaDBVectorStore instances and
improves the overall implementation. This change:
- Makes configuration more flexible and type-safe through builder methods
- Deprecates old constructors and builder in favor of the new builder pattern
- Adds comprehensive validation of configuration options
- Improves documentation with clear examples and better structure
- Updates all test classes to use the new builder pattern
- Adds comprehensive builder tests
- Updated reference documentation
The builder pattern provides a more maintainable and user-friendly way to
configure vector stores while ensuring configuration validity at compile time.
This aligns with the project's move towards using builder patterns across all
vector store implementations.
Introduces a builder pattern for configuring TypesenseVectorStore instances and
moves the implementation to the org.springframework.ai.vectorstore.typesense
package. This change:
- Makes configuration more flexible and type-safe through builder methods
- Improves code organization by moving to a dedicated vector store package
- Deprecates old constructors in favor of the builder pattern
- Adds comprehensive validation of configuration options
- Enhances documentation with clear usage examples
- Adds dedicated builder test class for better test coverage
- Add builder tests
- update reference docs
The builder pattern simplifies TypesenseVectorStore configuration while ensuring
proper validation of all settings. The package move aligns with Spring AI's
architectural patterns and improves maintainability by grouping related classes
together.
review
Introduces a builder pattern for configuring WeaviateVectorStore instances and
moves the implementation to the org.springframework.ai.vectorstore.weaviate
package. This change:
- Makes configuration more flexible and type-safe through builder methods
- Improves code organization by moving to a dedicated vector store package
- Deprecates old constructors in favor of the builder pattern
- Adds builder tests
- Enables better IDE support through method chaining
