- Add new Maven profile 'ci-fast-integration-tests' for running selective ITs
- Remove redundant vector store skip flags from properties section
- Update maven-failsafe-plugin to version 3.5.2
- Configure test exclusions for various components:
- Most model integration tests (Anthropic and OpenAI)
- Most vector store tests (except PgVector and Chroma)
- Most auto-configuration tests
- All test containers and docker compose tests
- AI evaluation tests
- Convert the docker-compose tests into ITs
- Convert the testcontainers tests into ITs
- Updated README.md
- Explain the new profile and also the new integration tests repo
- Describe ways to run integration tests for specific modules
- Add badge for https://github.com/spring-projects/spring-ai-integration-tests
- 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
- Disable project-wide Checkstyle checks to unblock development
- Add documentation for enabling Checkstyle locally
- Fix remaining checkstyle violations in current codebase
Fixes#1669
- Extend the Spring AI Message with getMediaData() : List<MediaData>
MediaData is a pair of MimeType and data of type Object.
Message#getContent() return text only.
- VertexAI Gemini Support
- implement VertexAiGeiminChatClient for ChatClient and StreamingChat client and support for MediaData content.
add IT tests for Chat, Streaming and Multimodality
- add Auto-configuration + ITs
- add Gemini Spring Boot starter.
- add clients and boot starters to the Spring AI BOM.
- add Anotra documentation for the Gemini chat client.
- update gemini to latest 26.33.0 BOM.
- add vertex ai gemini dependencies to the BOM.
- add Vertex AI Gemini API Function Calling support
- add Gemini API Function Calling Streaming support
- add vertex ai gemini function calling documentation
- factor out the Function Calling functionality into common abstraction used by OpenAI, Azure and Gemini.
- group the VertexAI documentation under a common parent
- add PortableFunctionCallingOption that implements FunctionCallingOptions and ChatOptions and provide builder for it.
- remove some deprecated code.
- allow authorization with GoogleCredentials form json file.
- add AOT support for VertexAI Gemini.
- move legacy Vertex AI into VertexAI PaLM2.
- better handling for empty chat responses.
- update the Gemini version to latest 26.33.0. This required lifting the protobuf-java to 3.25.2 as well.
- fix a bug for handling System messages with Gemini.
- Implement Azure OpenAI Function Calling
Uses the same the common abstractions used by OpenAI and Gemini: FunctionCallingOptions and AbstractFunctionCallSupport
- Introducing a new OpenAiApi native client for OpenAI API and get rid of the theokanning library.
Amongst others the OpenAiApi allows:
- easy base-url configuration (e.g. TAS-AI)
- Flux response for streaming OpenAI results.
- Exposes the http headers containing important metadata
- Pure Spring ecosystem, making it easier for Graal VM
- Define a new AiStreamClient interface returning Flux<AiResponse>
- Refactor OpenAiClient and to use the new OpenAiApi and implement the AiStreamClient.
- Use spring-retry to improve the OpenAI EmbeddingClient stability on 503 error.
- Remove the OpenAI http header interceptor as the OpenAiApi returns ResponseEntity<T> that provides direct access to the headers.
- Refactor the metadata headers and usage extraction.
- Remove redundant and obsolete classes.
- Fix dependency issue with Pinecone, netty-codec-http2 and Spring Boot 3.2
- Collapses all VectorStore similiaritySearch methdos into one with SearchRequest builder.
- Fix all affected code and tests.
- Bump the project version to 0.7.1.
- Add tests
- Add autoconfigurations for milvus, pinecone and pgvecor stores.
- Improve and unify the VectorStore ITs.
- Make use of TrasformersEmbeddingClient for auto-configurations ITs.
- Add ContentFormatter and DefaultContentFormatter that can filter the metadata
and format the Document metadata and text according to predefined templates.
- Add content formatter tests
- Allow the TextSplitter to copy the document content-formatter to the children.
When the splitter breaks the parent Document into multiple chunks (e.g.
into a list of children Documents) copy the source content formatter to
the chunks by default. Use the copyContentFormatter flag to enable/disable copping.
- Add TextSplitter IT tests
- Add MetadataExtractors as DocumentTransformers.
- Bump spring-ai project version to 0.7.0-SNAPSHOT
- Configurable metadata-mode for EmbeddingClients
- Make the metadata mode configurable for the EmbeddingClient implementations.
- Use the EMBED mode by default.
Resolves#44
Resolves#19
* Clear and stream line. Inject search distance response as metadata
* Fix similarity threshold by metric type
- Fix the similary search with threshold for L2 and IP types.
- Create config Builder Config (inspired by Neo4jVectorStore impelementation.
- add database-name, metric-type, index-type and index-param configurations.
* update vector store doc and readme
