Introduces a simplified, type-safe builder pattern for function callbacks to
improve developer experience and code reliability. The new hierarchical API
separates concerns between direct function invocation and method reflection,
while providing better compile-time safety.
This change deprecates the older FunctionCallbackWrapper in favor of a more
intuitive FunctionCallback.Builder that better handles generic types via
ParameterizedTypeReference. It also adds automatic function description
generation as a fallback when none is provided, though explicit descriptions
are still recommended.
The update standardizes function callback handling across all AI model
implementations (OpenAI, Ollama, Minimax, etc.) and improves response
handling with configurable converters.
Core API Enhancements:
- New Builder Interface: Replaced FunctionCallbackWrapper.builder() with
FunctionCallback.builder(), introducing a hierarchical approach that improves
customization and type safety.
- Specialized Builders: Introduced FunctionInvokerBuilder for direct Function/BiFunction
implementations and MethodInvokerBuilder for reflection-based invocations.
- Generic Type Support: Added ParameterizedTypeReference for better handling of generic parameters.
- Unified Method Definition: Merged method() and argumentTypes() into a single method() call
for simplicity and type safety.
- Automatic Descriptions: Implemented auto-generation of function descriptions, with warnings
to encourage explicit descriptions.
- Configurable Response Converters: Enhanced response handling with support for custom
converters, reducing unnecessary JSON conversions.
Architecture Improvements:
- Established common Builder interface for shared properties
- Separated function object handling from constructor
- Added method-specific configuration (name, arg types, target)
- Added JSON schema generation support for ResolvableType
- Moved to standardized schema types across AI providers
- Set OPEN_API_SCHEMA as default for Vertex AI Gemini
Builder Pattern Standardization:
- Standardized builder method ordering across implementations
- Moved function() call after description() for consistency
- Improved function callback configuration with unified patterns
- Enhanced error handling and validation in DefaultFunctionCallbackBuilder
Deprecations:
- FunctionCallbackWrapper.Builder replaced by DefaultFunctionCallbackBuilder
- Removed CustomizedTypeReference in favor of ParameterizedTypeReference
- Deprecated older ChatClient API methods for function handling
Testing & Documentation:
- Updated all AI model implementations (OpenAI, Ollama, Minimax, Moonshot, ZhiPuAI)
- Added comprehensive integration tests for static/instance methods
- Added integration tests for auto-generated descriptions
- Updated documentation to reflect new builder pattern usage
- Added Kotlin extension for inputType() support
Co-authored-by: Sébastien Deleuze <sebastien.deleuze@broadcom.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
The DEFAULT_RETRY_TEMPLATE uses exponential backoff starting at 2s with max 3min
delay between retries, making tests run unnecessarily long. This change
introduces SHORT_RETRY_TEMPLATE with fixed 100ms backoff to speed up test
execution while preserving the same retry behavior and error handling.
- Disable project-wide Checkstyle checks to unblock development
- Add documentation for enabling Checkstyle locally
- Fix remaining checkstyle violations in current codebase
Fixes#1669
- Remove @NestedConfigurationProperty and @ConstructorBinding annotations from model options classes
- Remove spring-boot dependency from spring-ai-openai module
- Add exclusion for spring-boot-autoconfigure in spring-cloud-function-context dependency
- Move configuration metadata to spring-ai-spring-boot-autoconfigure module
This change decouples the core AI model implementations from Spring Boot,
making the core modules more lightweight and allowing them to be used in
non-Spring Boot applications. Configuration properties are now handled by
the spring-ai-spring-boot-autoconfigure module instead.
Fixes#1540
All output parser functionality has already been migrated to the converter package
since milestone M1.
Changes:
- Replace all instances of 'parser' with 'converter' in variable names and test cases
- Delete (pre M1) deprecated parser package and all associated classes
- Remove Output Parsers section from README.md
- Update Javadoc comments to reference converters instead of parsers
This commit adds support for tool context in various chat options classes across
different AI model implementations and enhances function calling capabilities.
The tool context allows passing additional contextual information to function callbacks.
- Add toolContext field to chat options classes
- Update builder classes to support setting toolContext
- Enhance FunctionCallback interface to support context-aware function calls
- Update AbstractFunctionCallback to implement BiFunction instead of Function
- Modify FunctionCallbackWrapper to support both Function and BiFunction and
to use the new SchemaType location
- Add support for BiFunction in TypeResolverHelper
- Update ChatClient interface and DefaultChatClient implementation to support
new function calling methods with Function, BiFunction and FunctionCallback arguments
- Refactor AbstractToolCallSupport to pass tool context to function execution
- Update all affected <Model>ChatOptions with tool context support
- Simplify OpenAiChatClientMultipleFunctionCallsIT test
- Add tests for function calling with tool context
- Add new test cases for function callbacks with context in various integration tests
- Modify existing tests to incorporate new context-aware function calling capabilities
- Add docs in in openai function calling
Resolves#864, #1303, #991
Add support for PortableFunctionCallingOptions across AI models
- Modify FunctionCallingOptions interface to extend ChatOptions for better integration
- Refactor option handling in chat models to accommodate both ChatOptions and FunctionCallingOptions
- Implement handling of FunctionCallingOptions in Anthropic, Azure OpenAI,
MistralAI, Ollama, OpenAI, VertexAI Gemini, and other models
- Update existing function calling tests to use new FunctionCallingOptions.
Resolves#624
- Removed the assertion checking for a non-null 'name' in ToolResponseMessage
- This change affects multiple AI model implementations:
AzureOpenAiChatModel, MiniMaxChatModel, MistralAiChatModel,
MoonshotChatModel, OpenAiChatModel, and ZhiPuAiChatModel
Resolves#1410
This commit introduces a new proxyToolCalls option for various chat
models in the Spring AI project. When enabled, it allows the client to
handle function calls externally instead of being processed internally
by Spring AI.
The change affects multiple chat model implementations, including:
AnthropicChatModel
AzureOpenAiChatModel
MiniMaxChatModel
MistralAiChatModel
MoonshotChatModel
OllamaChatModel
OpenAiChatModel
VertexAiGeminiChatModel
ZhiPuAiChatModel
The proxyToolCalls option is added to the respective chat options
classes and integrated into the AbstractToolCallSupport class for
consistent handling across different implementations.
The proxyToolCalls option can be set either programmatically via
the <ModelName>ChatOptions.builder().withProxyToolCalls() method
or the spring.ai.<model-name>.chat.options.proxy-tool-calls
application property.
Documentation for the new option is also updated in the relevant
Antora pages.
Added ITs for proxy tool calls
Remove ChatClientPromptRequestSpec and all ChatClient.prompt() overloads can how take advantage of the full fluent API. Docs updated
Resolves#1367
This change updates the type of portable chat options from Float to
Double. Affected options include:
- frequencyPenalty
- presencePenalty
- temperature
- topP
The motivation for this change is to simplify coding. In Java, Float
values require an "f" suffix (e.g., 0.5f), while Double values don't
need any suffix. This makes Double easier to type and reduces
potential errors from forgetting the "f" suffix.
APIs, tests, and documentation have been updated to reflect this
change.
Fixes gh-712
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* Surface more configuration APIs to ChatOptions
* Use abstraction in Observations directly instead of dedicated implementation
* Simplify metadata config in observations for defined models
* Improve merging of runtime and default options in OpenAI
* Fix missing option in Mistral AI
Relates to gh-1148
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- introduce copy() method to the ChatOptions.
- make sure that the DefaultChatClientRequestSpec takes a copy of the input chat options to prevent multation.
- add a OpenAiChatClientMultipleFunctionCallsIT to reproduce the problem and verify the solution.
Resolves#1064
- 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
