This version is still in development and is not considered stable yet. For the latest snapshot version, please use Spring AI 1.0.0-SNAPSHOT!spring-doc.cn
The Run Oracle Database 23ai locally appendix shows how to start a database with a lightweight Docker container.
this is a breaking change! In earlier versions of Spring AI, this schema initialization happened by default.
Refer to the Dependency Management section to add the Spring AI BOM to your build file. Refer to the Repositories section to add Milestone and/or Snapshot Repositories to your build file.
Check the list of configuration parameters to learn about the default values and configuration options.
Property Description Default value

spring.ai.vectorstore.oracle.index-typespring-doc.cn

Nearest neighbor search index type. Options are NONE - exact nearest neighbor search, IVF - Inverted Flat File index. It has faster build times and uses less memory than HNSW, but has lower query performance (in terms of speed-recall tradeoff). HNSW - creates a multilayer graph. It has slower build times and uses more memory than IVF, but has better query performance (in terms of speed-recall tradeoff).spring-doc.cn

NONEspring-doc.cn

spring.ai.vectorstore.oracle.distance-typespring-doc.cn

Search distance type among COSINE (default), DOT, EUCLIDEAN, EUCLIDEAN_SQUARED, and MANHATTAN.spring-doc.cn

NOTE: If vectors are normalized, you can use DOT or COSINE for best performance.spring-doc.cn

COSINEspring-doc.cn

spring.ai.vectorstore.oracle.forced-normalizationspring-doc.cn

Allows enabling vector normalization (if true) before insertion and for similarity search.spring-doc.cn

CAUTION: Setting this to true is a requirement to allow for search request similarity threshold.spring-doc.cn

NOTE: If vectors are normalized, you can use DOT or COSINE for best performance.spring-doc.cn

falsespring-doc.cn

spring.ai.vectorstore.oracle.dimensionsspring-doc.cn

Embeddings dimension. If not specified explicitly the OracleVectorStore will allow the maximum: 65535. Dimensions are set to the embedding column on table creation. If you change the dimensions your would have to re-create the table as well.spring-doc.cn

65535spring-doc.cn

spring.ai.vectorstore.oracle.remove-existing-vector-store-tablespring-doc.cn

Drops the existing table on start up.spring-doc.cn

falsespring-doc.cn

spring.ai.vectorstore.oracle.initialize-schemaspring-doc.cn

Whether to initialize the required schema.spring-doc.cn

falsespring-doc.cn

spring.ai.vectorstore.oracle.search-accuracyspring-doc.cn

Denote the requested accuracy target in the presence of index. Disabled by default. You need to provide an integer in the range [1,100] to override the default index accuracy (95). Using lower accuracy provides approximate similarity search trading off speed versus accuracy.spring-doc.cn

-1 (DEFAULT_SEARCH_ACCURACY)spring-doc.cn
These filter expressions are converted into the equivalent OracleVectorStore filters.
Refer to the Dependency Management section to add the Spring AI BOM to your build file.