- upadate bedrockruntime version to 2.26.7 and align it with aws sdk dependecy.
- minor ITs configuration, consistency and statbility fixes
Use the EnvironmentVariableCredentialsProvider instead of the Profile credential provider.
- update the Bedrock getting started documentation.
- update the Genemi Prerequisites docs.
Currently, in order to use an OpenSearch instance provided by AWS,
additional steps are needed. This commit introduces the required
configuration.
Add new starter and update docs
- Added additional support for ZhiPuAi models including vision model GLM-4V
- Default model changed to GLM_4_Air and update documentation
- Added additional unit and integration tests
- Add documentation for vision model
This change allows users to specify custom names, facilitating management of multiple vector databases within a single database instance.
Key changes:
- Implement configurable schema, table, and index names for PgVectorStore
- Add properties to set custom schema and table names
- Introduce optional schema/table & field validation for custom configurations
- Include additional tests for new configurations and existing deployments
Additional improvements:
- Rename properties to schemaName, tableName, and schemaValidation
- Update pgvector documentation with new properties
- Add schema/table name tests to PgVectorStoreAutoConfigurationIT and PgVectorStorePropertiesTests
- Create standalone PgVectorSchemaValidator class for schema/table validation
- Add missing 'CREATE SCHEMA IF NOT EXISTS' when initializeSchema=true
- Remove redundant code and classes
Resolves#747
Co-authored-by: Christian Tzolov <ctzolov@vmware.com>
- Adds spring boot auto-configuration support for GemFireVectorStore
- Adds integration test GemFireVectorStoreAutoConfigurationIT
- Includes gemfire-testcontainers in integration tests
- Adds unit test GemFireVectorStorePropertiesTests
- Refactors GemFireVectorStore.java extracting GemFireVectorStoreConfig.java
- Renames spring-ai-gemfire to spring-ai-gemfire-store
- Adds GemFireConnectionDetails
- Adds GemFireVectorStoreProperties with default values
- Remove gemfire-release-repo maven repository
Co-authored-by: Louis Jacome <louis.jacome@broadcom.com>
Co-authored-by: Jason Huyn <jason.huynh@broadcom.com>
- Add `withContentFieldName` and `withDistanceMetadataFieldName` to Pinecone Config Builder
- Add `spring.ai.vectorstore.pinecone.contentFieldName` and `spring.ai.vectorstore.pinecone.distanceMetadataFieldName`
properties to the auto-config
- Default content field name: "document_content", distance field: "distance"
- Update tests and docs
Resolves#882
- knn instead of script_score, removed initialization
- only using normalized similarities, adjusted unit test
- making l2norm's distances consistent with others
- update dependency version and docs
- upate autoconfigure ITs
- replace RestTemplate by RestClient but default to SimpleClientHttpRequestFactory as Chroma seems to have issues with HTTP2.
- update the documentation.
- update the ghcr.io/chroma-core/chroma version to 0.5.0. Fix the withBasicAuthCredentials.
Co-authored-by: Christian Tzolov <ctzolov@vmware.com>
- implement OpensSearchVectorStore
- add opensearch auto-configuration and boot starter
- add documentation for OpenSearch VectorStore
- add bom dependecies
- align with to new Spirng AI API
- autoconfigure setup
- add post bean initialization and create method
- add embedding field
- create collection add nested field options
- add typesense tests
- use embedding variable instead of word vec
- check in runtime the number of documents in the collection
- add typesense expression converter
- add filter tests. add update document test and search with threshold test
- distance threshold and add distance key into metadata
- add typesesne boot starter
- add typesense docs
- add client properties in autoconfigure
- add embedding dimension method
- add typesense vector store autoconfiguration tests
- add docs to nav.adoc and vectorsdb.adoc.
- fix module name.
- move the expression converter to the typesense project.
* Added tips for running PGvector as a Spring Boot dev service
* Fixed typos in code snippets
* Updated the PGvector image name
* Improved syntax
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* Added Spring Boot Starter for Spring AI Hugging Face
* Updated documentation with instructions using the starter dependency
* Fixed naming inconsistencies in the docs for Hugging Face
Fixes gh-838
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
