- Avoid overlapping package names
Changed in spring-ai-commons package from org.sf.ai.model to org.sf.ai.content
Refactor advisor module name to be spring-ai-advisors-vector-store
Moved advisors into org.springframework.ai.chat.client.advisor.vectorstore
- Created top level memory directory
- Create new module spring-ai-model-chat-memory-neo4j and moved neo4j memory classes out of the vectorstore module
Updated neo4j autoconfiguation
- Remove model specific Usage implementations
- Add `Object getNativeUsage()` to Usage interface
- This will allow the model specific Usage data to be returned
- At the client side, client needs to cast the return type of `getNativeUsage` into the corresponding Usage returned by the model API
- Rename `generationTokens` to `completionTokens`
- Since `completion` token name is more common among the models, renaming generation tokens into completion tokens
- Maintain JSON deserialization compatibility for legacy `generationTokens` field
- Remove deprecated Long-based constructors to avoid API ambiguity
- Change the prompt, completion and total token return types from Long to Integer
- This is a breaking change that requires updating all constructor calls
- Integer is sufficient for token counts and aligns better with most model APIs
- Use DefaultUsage for most of the model specific usage handling
- When initializing set the native usage to the model specific usage type
- Ensure immutability by making all fields final and removing setters
- Add comprehensive test coverage for all functionality including edge cases
Resolves#1407
* Remove use of Document.getContext method from spring-ai-core, use getText
* Remove deprecated ChatOptionsBuilder class
* Remove deprecated FunctionCallingOptionsBuilder class
The Document class requires exactly one of text or media to be specified.
Updated textImageAndVideoEmbedding test to create separate Document
instances for text, image, and video content instead of combining them
in a single document.
The Document class requires exactly one of text or media to be specified.
Updated textImageAndVideoEmbedding test to create separate Document
instances for text, image, and video content instead of combining them
in a single document.
The Document class previously allowed multiple media entries while also having a
text field, leading to ambiguity in content handling. This change enforces a
clear separation between text and media documents to prevent content type
confusion and simplify document processing.
A Document now must contain either text content or a single media entry, but
never both. This aligns with the class's primary use in ETL pipelines where
clear content type boundaries are essential for proper embedding generation and
vector database storage.
Additional architectural changes:
- Document now implements a cleaner API by removing deprecated methods
- Removed MediaContent interface implementation from Document class
- Document.getMedia() now returns a single Media object instead of Collection
- Removed EMPTY_TEXT constant in favor of proper null handling
- Constructor signatures simplified and streamlined
- Builder pattern improved to enforce single content type constraint
The breaking changes include:
- Media is now a single entry instead of a collection
- Content field renamed to text for clarity
- Removed support for mixed content types
- Simplified builder API to prevent ambiguous construction
Prefer using text-related methods over deprecated content methods to
better reflect the actual content type being handled and improve API clarity.
- Add BedrockMediaFormat class to handle media format conversions for documents, images and videos
- Enhance Media class with builder pattern and comprehensive format constants
- Refactor BedrockProxyChatModel to support multimodal content handling
- Add integration tests for PDF, image and video processing
- Add unit tests for Media and BedrockMediaFormat classes
- Upgrade AWS SDK version from 2.26.7 to 2.29.29
- Remove redundant aws.sdk.version property in favor of awssdk.version
Documentation updates for Bedrock Converse API
- Added multimodal support documentation (images, video, documents)
- Added deprecation notices for existing Bedrock model implementations
- Updated feature comparison table
- Added warning notes about transitioning to Converse API
Document
* Introduced “score” attribute in Document API. It stores the similarity score.
* Consolidate “distance” metadata for Documents. It stores the distance measurement.
* Adopted prefix-less naming convention in Document.Builder and deprecated old methods.
* Deprecated the many overloaded Document constructors in favour of Document.Builder.
Vector Stores
* Every vector store implementation now configures a “score” attribute with the similarity score of the Document embedding. It also includes the “distance” metadata with the distance measurement.
* Fixed error in Elasticsearch where distance and similarity were mixed up.
* Added missing integration tests for SimpleVectorStore.
* The Azure Vector Store and HanaDB Vector Store do not include those measurements because the product documentation do not include information about how the similarity score is returned, and without access to the cloud products I could not verify that via debugging.
* Improved tests to actually assert the result of the similarity search based on the returned score.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Remove deprecated types,methods and references
- Remove usage of "Generation(String text)" and replace with
"Generation(AssistantMessage)"
- Remove MiniMaxApi,MootShotApi,OpenAiApi,ZhiPuAiApi
ChatCompletionFinishReason's FUNCTION_CALL
- Remove OllamaApi's deprecated types
- Remove deprecated constructors from PostgresMlEmbeddingModel
- Remove deprecated constructor from Media
- Remove tokenNames usage from antlr4 FiltersLexer and FiltersParser
- Remove deprecated methods from CassandraVectorStoreProperties
- Remove deprecated constructor and static config class from QdrantVectorStore
- Minor cleanups on removing deprecated models and versions
- Remove old name for mixtral models
Resolves#1599
OpenAI's API returns additional token usage metrics that provide deeper
insight into API consumption. This adds support for:
- acceptedPredictionTokens: Tokens from accepted model predictions
- audioTokens: Tokens used for audio processing
- rejectedPredictionTokens: Tokens from rejected model predictions
These fields help track resource utilization and costs more accurately
by breaking down token usage by type. Added @JsonIgnoreProperties to
maintain compatibility with future OpenAI API additions.
Fixes warning logging in RetryUtils.SHORT_RETRY_TEMPLATE to reduce noise
in test output.
- Disable project-wide Checkstyle checks to unblock development
- Add documentation for enabling Checkstyle locally
- Fix remaining checkstyle violations in current codebase
Fixes#1669
- 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
Resolves https://github.com/spring-projects/spring-ai/issues/832
Introduces retry functionality to VertexAI embedding and
chat models, enhancing their resilience against transient failures.
It also corrects a typo in the VertexAiEmbeddingConnectionDetails
class name.
Key changes:
* Add RetryTemplate to VertexAiTextEmbeddingModel and VertexAiGeminiChatModel
* Introduce spring-ai-retry dependency
* Refactor code to support retry logic
* Update auto-configuration classes to incorporate retry functionality
* Fix typo in VertexAiEmbeddingConnectionDetails class name
remove extraneous commented out code
Add missing copyright headers, author etc.
* Add model and dimensions to option abstraction
* Use abstraction in Observations directly instead of dedicated implementation
* Clean-up the merge of runtime and default embedding options in OpenAI
Relates to #gh-1148
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* Remove inheritance from HashMap
* No more subclasses per model provider
* Builder class for ChatResponse
* Fix the AbstractResponseMetadata#AI_METADATA_STRING parameter order
* ChatResponseMetadata ignore Null values.
- 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
