Implemented a new configuration property 'useKeylessAuth' to toggle
between API key and Azure default credential authentication.
Added necessary dependencies and updated tests to reflect the new changes.
co-authored-by: mattgotteiner <mattgotteiner@users.noreply.github.com>
Query Analysis
* Introduce Query Analysis Module
* Define QueryTransformer API and TranslationQueryTransformer implementation
* Define QueryExpander API and MultiQueryExpander implementation
* Support QueryTransformer in RetrievalAugmentationAdvisor (support for QueryExpander will be in the next PR together with the needed DocumentFuser API).
Improvements
* Refine Retrieval and Augmentation Modules for increased robustness
* Expand test coverage for both modules
* Define clone() method for ChatClient.Builder
Tests
* Introduce “spring-ai-integration-tests” for full-fledged integration tests
* Add integration tests for RAG modules
* Add integration tests for RAG advisor
Query Analysis
* Introduce Query Analysis Module
* Define QueryTransformer API and TranslationQueryTransformer implementation
* Define QueryExpander API and MultiQueryExpander implementation
* Support QueryTransformer in RetrievalAugmentationAdvisor (support for QueryExpander will be in the next PR together with the needed DocumentFuser API).
Improvements
* Refine Retrieval and Augmentation Modules for increased robustness
* Expand test coverage for both modules
* Define clone() method for ChatClient.Builder
Tests
* Introduce “spring-ai-integration-tests” for full-fledged integration tests
* Add integration tests for RAG modules
* Add integration tests for RAG advisor
Relates to #gh-1603
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Add maven properties for all vector stores such as
skip.vectorstore.azure-cosmos-db to control IT test execution
- Chroma and PGVector IT tests are enabled by default
- Docker Compose and Testcontainers module ITs are skipped by default
- Add parallel job to run docker-compose and testcontainers ITs
This change enables more flexible integration between Spring AI and LLM function
calling capabilities while maintaining type safety and ease of use.
- Add new MethodFunctionCallback class to support method invocation via reflection
- Supports both static and non-static method calls
- Handles multiple parameter types including primitives, objects, collections
- Supports empty parameters and empty response
- Auto-generates JSON schema from method parameters
- Special handling for ToolContext parameters
- Builder pattern for easy configuration
- Add comprehensive unit tests for MethodFunctionCallback
- Add integration tests for MethodFunctionCallback with both Anthropic and OpenAI clients
- Add jackson-module-jsonSchema dependency
- Modify FunctionCallback to check for empty tool context
Testing coverage includes:
- Static method invocation scenarios
- Non-static method calls with various parameter types
- Void return type methods
- Complex parameter types (enums, records, lists)
- Tool context handling
- Error cases and validation
Add MethodFunctionCallback reference docs
Adds Oracle Cloud Infrastructure (OCI) Generative AI's Cohere chat model support
to expand Spring AI's cloud provider capabilities. This allows developers to use
OCI's managed Cohere models through both dedicated and on-demand serving modes.
The integration provides auto-configuration for simple setup while allowing full
customization of model parameters through OCICohereChatOptions. Teams can now
use OCI's Cohere models alongside other providers in Spring AI applications.
This change complements the existing OCI embedding support, offering a complete
set of GenAI capabilities for Oracle Cloud users.
Signed-off-by: Anders Swanson <anders.swanson@oracle.com>
Integrates Oracle Coherence 24.09+ as a vector store backend for Spring AI. The
implementation provides:
- Support for vector similarity search with configurable distance metrics (Cosine,
Inner Product, L2)
- Multiple indexing options including HNSW and Binary Quantization indexes
- Filter expression evaluation for metadata-based filtering
- Vector normalization capabilities
- Comprehensive test coverage including integration tests
The implementation includes:
- CoherenceVectorStore main implementation
- CoherenceFilterExpressionConverter for Spring AI to Coherence filter conversion
- Auto-configuration support via spring-boot-starter
- Documentation and usage examples
Requires Oracle Coherence 24.09 or later.
Introduces support for Amazon Bedrock Converse API through a new BedrockProxyChatModel
implementation. This enables integration with Bedrock's conversation models with features
including:
- Support for sync/async chat completions
- Stream response handling
- Tool/function calling capabilities
- System message support
- Image input support
- Observation and metrics integration
- Configurable model parameters and AWS credentials
Adds core support classes:
- BedrockUsage: Implements Usage interface for token tracking
- ConverseApiUtils: Utility class for handling Bedrock API responses including:
- Tool use event aggregation and processing
- Chat response transformation from stream outputs
- Model options conversion
- Support for metadata aggregation
- URLValidator: Utility for URL validation and normalization with support for:
- Basic and strict URL validation
- URL normalization
- Multimodal input handling
- Enhanced FunctionCallingOptionsBuilder with merge capabilities for both ChatOptions
and FunctionCallingOptions
- Added BEDROCK_CONVERSE to AiProvider enum for metrics tracking
- Extended AWS credentials support with session token capability
- Added configurable session token property to BedrockAwsConnectionProperties
Adds new auto-configuration support:
- BedrockConverseProxyChatAutoConfiguration for automatic setup of the Bedrock Converse chat model
- BedrockConverseProxyChatProperties for configuration including:
- Model selection (defaults to Claude 3 Sonnet)
- Timeout settings (defaults to 5 minutes)
- Temperature and token control
- Top-K and Top-P sampling parameters
- Integration with existing BedrockAwsConnectionConfiguration for AWS credentials
Updates to testing infrastructure:
- Adds comprehensive test suite for Bedrock Converse properties and auto-configuration
- Integration tests for chat completion and streaming scenarios
- Property validation tests for configuration options
- Temporarily disabled other Bedrock tests due to AWS quota limitations
- Added ObjectMapper configuration for proper JSON handling
Added new spring-ai-bedrock-converse-spring-boot-starter module
Updates module configuration in parent POM and BOM to include new bedrock-converse
modules and starters. Adds necessary auto-configuration imports for seamless integration
with Spring Boot applications.
Unrelated changes:
- Disabled several Bedrock model tests (Jurassic2, Llama, Titan) due to AWS quota limitations
- Disabled PaLM2 tests due to API decommissioning by Google
Resolves#809, #802
Add docs and fix configs
- Move timeout configuration from chat properties to connection properties
- Add comprehensive documentation for Bedrock Converse API usage and configuration
- Update tests to reflect configuration changes
Co-authored-by: maxjiang153 <maxjiang153@users.noreply.github.com>
Standardize AWS credential handling in integration tests
- Improve how we manage AWS credentials across our integration test
suite and ensures consistent test configuration. We're replacing individual
environment variable checks with @RequiresAwsCredentials
annotation and standardizing the use of BedrockTestUtils for context creation
in tests
We also align all AWS regions to US_EAST_1 for consistency and add missing
dependency versioning for Oracle Free.
These changes make our AWS tests more easier to maintain.
Key changes:
- Replace @EnabledIfEnvironmentVariable with @RequiresAwsCredentials
- Standardize context creation via BedrockTestUtils
- Set AWS region to US_EAST_1
- Add Oracle Free dependency version in pom.xml
When using a non-default database, MilvusVectorStore's doDelete method wasn't
passing the specified databaseName in DeleteParam, causing searches to fall back
to the default database where collections couldn't be found. Added explicit
databaseName parameter to fix this issue.
- Add databaseName to DeleteParam builder
- Upgrade milvus-sdk from 2.3.4 to 2.3.5
- Define the version for Azure Cosmos DB
- Add dependencies for the azure-cosmos-db-store module and boot starter
- Include the artifacts in spring-ai-bom
Signed-off-by: jitokim <pigberger70@gmail.com>
This commit configures Maven to support compiling Kotlin
main and test classes, and adds a JacksonUtilsKotlinTests
class that ensures that serialization and deserialization
of Kotlin data classes works as expected.
The Maven configuration follows recommendations from
https://kotlinlang.org/docs/maven.html.
- Implement core vector store module for CosmosDB integration
- Add Spring Boot auto-configuration capabilities
- Integrate batch processing strategy for optimized operations
- Include comprehensive tests for core and auto-config modules
- Add reference docs for the CosmosDB vector store support
- Remove unnecessary spring-web dependencies
- Update third-party library versions
- Refactor API classes to use consistent header handling
- Remove ApiUtils class and inline its functionality
- Adjust RestClient and WebClient builder usage in autoconfiguration
- Replace direct RestClient.Builder injections with ObjectProvider<RestClient.Builder>
and WebClient.Builder injections with ObjectProvider<WebClient.Builder>
- Update ChromaVectorStoreAutoConfiguration to use ObjectProvider
- Rename MongoDbAtlasLocalContainerConnectionDetailsFactoryTest to IT
- Switch spring-ai-chroma-store dependency from spring-web to spring-webflux
- Simplify ChromaApi constructor by using method reference for default headers
- Adjust import order
Resolves#1066Resolves#524
This commit introduces support for Oracle Cloud Infrastructure (OCI)
GenAI embedding models in Spring AI. It includes:
* New OCIEmbeddingModel class for interacting with OCI GenAI API
* Auto-configuration for easy setup and integration
* Properties for configuring OCI connection and embedding options
* Documentation updates explaining usage and configuration
* Integration tests to verify functionality
Signed-off-by: Anders Swanson <anders.swanson@oracle.com>
This commit introduces a new Markdown document reader with several
key features and improvements:
* Add support for text with various formatting elements
* Implement handling for horizontal rules and hard line breaks
* Add functionality for inline and block code sections
* Incorporate blockquote handling
* Support ordered and unordered lists
* Introduce additional metadata capabilities
* Include JavaDocs
Update ETL documentation to reflect these new features and usage.
Fixes#105
- Breaking changes: Classes from the org.springframework.ai.openai.metadata.audio.transcription package have been moved to the org.springframework.ai.audio.transcription package.
- The AzureOpenAiAudioTranscriptionModel has been added to the auto-configuration.
- The spring.ai.azure.openai.audio.transcription prefix was introduced for properties.
- Introduces options properties which cover all of them (see: AzureOpenAiAudioTranscriptionOptions).
- fix missing MutableResponseMetadata
- add docs
- adjust code to updated ResponseMetadata design
- add test to AzureOpenAiAutoConfiguration
- add missing AzureOpenAiAudioTranscriptionModel tests
- provides a flexible schema, can be combined with a vector store, and supports time-to-live rows.
- fix initialize-schema docs and so that it actually works.
- move CommonVectorStoreProperties to .vectorstore. package
- add CassandraAutoConfiguration to the AutoConfiguration.imports
- add new spring-ai-vertex-ai-embedding project.
- add VertexAiTextEmbeddingModel and VertexAiMultimodalEmbeddingMode with related options configuration classes.
- add ITs
- add auto-configuraiton and boot starters.
- register to BOM.
- add documentation.
- add multimodal embedding documentation
- extend the Embedding metdata so that it can keep references to the source document's data, Id, mediatype
Resolves#1013
Related to #1009
- 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.
