Fixes: #886
Add ability to configure path prefix for OpenSearch API endpoints via properties.
This allows connecting to OpenSearch instances running behind a reverse proxy
with a non-root path, similar to Spring Elasticsearch's path-prefix property.
- Add pathPrefix property to OpenSearchVectorStoreProperties
- Apply pathPrefix to OpenSearchClient when configured
- Add documentation and unit tests
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
Fixes GH-3151
Follow-up of commit ca843e85887aa1da6300c77550c379c103500897,`includeCompletion` is renamed to `logCompletion`.
Signed-off-by: Yanming Zhou <zhouyanming@gmail.com>
Changes introduced for https://github.com/spring-projects/spring-ai/issues/2954
introduced a regression in the way OpenSearch works with test containers.
Restore the retrieval of HttpHost from OpenSearchConnectionDetails insted of getting
them directly from properties.
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
Fixes: #1949
- Rename 'disallowSchemaChanges(boolean)' to 'initializeSchema(boolean)' for consistency
with other vector store implementations
- Maintain semantic meaning by inverting the default value (from disallowSchemaChanges=false
to initializeSchema=true) in the CassandraVectorStore implementation
- Keep default behavior in auto-configuration consistent with other vector stores
- Remove unused 'returnEmbeddings' functionality and related code
- Update test cases to use the new initialization parameter
- Ref docs and javadocs updates
This change improves API consistency across Spring AI vector stores while
preserving the same behavior in the Cassandra implementation.
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
This removes the possible large amount of data that was attached
to spans and it logs the data out. This change also removes the direct
dependency on the OTel SDK. approach for content in Spring AI.
Refactors the observability approach for content in Spring AI:
- Replace content observation filters with logging handlers
- Rename configuration properties to better reflect their purpose:
- `include-prompt` → `log-prompt`
- `include-completion` → `log-completion`
- `include-query-response` → `log-query-response`
- Add TracingAwareLoggingObservationHandler for trace-aware logging
- Replace micrometer-tracing-bridge-otel with micrometer-tracing
- Remove event-based tracing in favor of direct logging
- Update documentation to reflect these changes (add breaking-changes section)
- Rename includePrompt to logPrompt in observation properties. Updated in ChatClientBuilderProperties, ChatObservationProperties, and ImageObservationProperties.
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
Fixes: #2954
* fixed authorization to multiple hosts
* ability to provide SSL certs via `SslBundles`
* ability to set connectTimeout/readTimeout
Signed-off-by: Linar Abzaltdinov <abzaltdinov@gmail.com>
- Set spring.ai.vectorstore.opensearch.aws.enabled=false to enable non AWS condition to instantiate OpenSearch client
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Add OpenSearchNonAwsCondition to robustly activate non-AWS OpenSearch auto-configuration if either:
- AWS SDK classes are missing, OR
- spring.ai.vectorstore.opensearch.aws.enabled=false
- Update OpenSearchVectorStoreAutoConfiguration to use the new condition for non-AWS configuration.
- Ensure AWS-specific auto-configuration is only active when AWS SDKs are present and the property is true (default).
- Add Javadoc to OpenSearchNonAwsCondition and clarify Javadoc on AWS config.
- Update integration test (OpenSearchVectorStoreNonAwsFallbackIT) to verify fallback logic works with AWS SDKs present.
- Add and refine documentation in opensearch.adoc:
- Explain the purpose and usage of the spring.ai.vectorstore.opensearch.aws.enabled property.
- Document the fallback logic and how to explicitly select AWS or non-AWS OpenSearch support.
Fixes#1901
Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
- Update dependencies and module names in maven pom.xml files affecting couchbase vector store support
- Rename artifact from spring-ai-couchbase-store-spring-boot-starter to spring-ai-starter-vector-store-couchbase
- Update imports and related cleanup
- Update corresponding documentation references
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
- Introduce top level properties to support conditional logic
- The properties will have the format like "spring.ai.vectorstore.type=<vectorstore provider>" to enable specific vectore store implementation
- By default, these will be enabled when no specific properties are set. To disable, set any value other than the provider name for example, none"
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
- Conditionally enable invidividual models within the provider
- Introduce top level properties to support conditional logic
- The properties will have the format like "spring.ai.model.<chat/embedding/image etc.,>=<provider>" to enable specific chat/embedding/image/audio/moderation models by the provider. By default, these will be enabled when no specific properties are set. To disable, set any value other than the provider name for example, "none"
- For the auto configurations where the provider has multiple models, split the autoconfiguration into per model auto-configuration classes. This will enable the isolated auto-configurations for each provider and its model.
- This PR addresses this for OpenAI and others will follow in subsequent PRs
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
Update the vector store starters with the new observation autoconfig dependency
Other maven configuraiton changes
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
Move vector store auto-configuration classes to dedicated modules under auto-configurations/vector-stores/:
- Creates separate modules for Cassandra, Chroma, Elasticsearch, GemFire, HanaDB, MariaDB, MongoDB Atlas, Neo4j, OpenSearch, Oracle, PGVector, and Redis vector stores
- Updates package names to follow the pattern org.springframework.ai.vectorstore.<implementation>.autoconfigure
- Renames corresponding starter modules to follow the pattern spring-ai-starter-vector-store-<implementation>
- Updates import paths in affected classes
- Relocates test resources alongside their respective implementations
- Updates imports in spring-ai-spring-boot-docker-compose and spring-ai-spring-boot-testcontainers
This change improves modularity by allowing each vector store implementation to be
independently versioned and maintained, following the migration pattern established
with previous vector store autoconfiguraiton and starters .
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
Move vector store auto-configuration classes to dedicated modules under auto-configurations/vector-stores/:
- Creates separate modules for Milvus, Pinecone, Qdrant, and Typesense vector stores
- Moves CommonVectorStoreProperties to spring-ai-core for better reusability
- Updates pom.xml dependencies to maintain proper relationships between modules
- Name the artifacts based on the pattern spring-ai-autoconfigure-vector-store-<implementation>.
For example - spring-ai-autoconfigure-vectore-store-milvus
- Package names follow the pattern org.springframework.ai.vectorstore.<implementation>.autoconfigure
- Naming the correspondinbg starter modules accordingly (spring-ai-starter-vector-store-milvus for example).
This change improves modularity by allowing each vector store implementation to be
independently versioned and maintained, continuing the migration pattern established
with previous vector stores.
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
