- Extends the ToolCallingAutoConfiguration to support both FunctionCallback and ToolCallback types.
- The toolCallbackResolver bean now handles both callback types through ObjectProvider injection.
- Added comprehensive tests to verify the resolution of multiple function and tool callbacks.
- Introduce new StaticToolCallbackProvider implementation
- Update ToolCallbackProvider to return FunctionCallback[]
- Migrate from List to ToolCallbackProvider in configurations
- Update tests to use new provider pattern
- Enhance tool callback providers to support multiple clients
- Refactor AsyncMcpToolCallbackProvider and SyncMcpToolCallbackProvider to handle multiple MCP clients
- Add ToolCallbackProvider support to ChatClient API
- Deprecate direct tool callback list methods in favor of providers
- Fix typos in Closeable class names
- Update MCP documentation with new examples and usage patterns
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
Spring AI milestones are now published to Maven Central. This PR updates all the places where we used to reference Spring Milestones repository.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Update AnthropicChatModel to use the new ToolCallingManager API, while ensuring full API backward compatibility.
- Introduce Builder to instantiate a new AnthropicChatModel since the number of overloaded constructors is growing too big.
- Update documentation about tool calling and Anthropic support for that.
Part of the #2207 epic
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Migrate from function calling to tool calling API
- Add support for Gemini 2.0 models (flash, flash-lite)
- Implement JSON schema to OpenAPI schema conversion
- Add builder pattern for improved configuration
- Deprecate legacy function calling constructors and methods
- Update default model to GEMINI_2_0_FLASH
- Add comprehensive test coverage for tool calling
- Upgrade victools dependency to 4.37.0
- Update the Vertex Tool calling docs
Part of the #2207 epic
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Replace function calling with tool calling in BedrockProxyChatModel
- Deprecate function calling related code and APIs
- Add new tool calling manager and options
- Update builder pattern to remove "with" prefix from methods
- Update tests and documentation for tool calling
Part of the #2207 epic
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Use the new ToolCallingManager API for AzureOpenAI chat model
- Add Builder to construct AzureOpenAI chat model instance
- Deprecate existing constructors
- Update documentation about the change
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Update MistralAiChatModel to use the new ToolCallingManager API, while ensuring full API backward compatibility.
- Introduce Builder to instantiate a new MistralAiChatModel since the number of overloaded constructors is growing too big.
- Update documentation about tool calling and Mistral AI support for that.
- Add extra validation to ensure the uniqueness of tool names when aggregated from different sources.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Document delete APIs with ID lists and filter expressions
- Add versioning use case with metadata-based updates
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
- Update OpenAiChatModel to use the new ToolCallingManager API, while ensuring full API backward compatibility.
- Introduce Builder to instantiate a new OpenAiChatModel since the number of overloaded constructors is growing too big.
- Update documentation about tool calling and OpenAI support for that.
- Add extra validation to ensure the uniqueness of tool names when aggregated from different sources.
- Ensure consistent merging of options, following Spring Boot strategy.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Enhance MCP server boot starter documentation with:
- Improved formatting and organization
- More detailed examples and code snippets
- Better explanations of features and capabilities
- Links to MCP specification
- Example applications section
- Remove standalone documentation files in favor of Antora structure
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Expand client customization documentation with detailed sections
- Add comprehensive descriptions of MCP components and capabilities
- Improve code examples and explanations
- Add example applications sections for both client and server
- Fix typos and enhance overall documentation structure
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
Core Architecture Changes:
- Split MCP into dedicated client/server modules
- Created separate starters: spring-ai-starter-mcp-webmvc and spring-ai-starter-mcp-webflux
- Removed property-based transport configuration in favor of auto-configuration
- Added support for multiple transport types (STDIO, WebMVC, WebFlux)
Client Improvements:
- Added support for both synchronous and asynchronous MCP clients
- Fixed client auto-configuration issues
- Added root change notification property to common properties
Configuration Enhancements:
- Improved configuration properties organization and validation
- Added ConditionalOnMissingBean for WebMvc/WebFlux configurations
- Enhanced lifecycle management and customization support
Testing and Documentation:
- Added comprehensive integration tests for McpClientAutoConfiguration
- Updated McpServerAutoConfigurationIT
- Added extensive JavaDoc documentation
- Improved MCP client/server starter documentation
- Added documentation for common utilities
- Updated navigation for new MCP documentation sections
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Spring AI's dependencies management to derive from Spring Boot 3.4.2
- Remove explicit versioning of dependencies
- Update upgrade notes for Spring Boot 3.4.2
- Fix ElasticSearch client changes with the latest dependency derived from Spring Boot 3.4.2
Adds comprehensive Model Context Protocol (MCP) integration to Spring AI, including:
Core Features:
- MCP client implementation with Spring AI tool calling capabilities
- Spring-friendly abstractions for MCP clients and servers
- Both synchronous and asynchronous MCP server operation modes
- Add MCP client autoconfiguration with support for STDIO, WebMVC and WebFlux transports
- Auto-configuration for MCP server components
- Spring Boot starter (spring-ai-starter-mcp) with WebFlux and WebMVC support
- MCP dependency management with BOM
- Add close() method to McpToolCallback for proper resource cleanup
- Add initialize flag to control MCP client initialization
- Add comprehensive integration tests and documentation for MCP client configuration
Technical Improvements:
- Split WebMvc and WebFlux configurations into separate auto-configuration classes
- Server type configurable via 'spring.ai.mcp.server.type' property (SYNC/ASYNC)
- Comprehensive test coverage including McpServerAutoConfigurationIT
- Utility classes for converting between Spring AI tools and MCP tools
- MCP SDK version management in parent pom
Reorganize MCP tool utilities and client configuration
- Rename ToolUtils to McpToolUtils for better MCP-specific naming
- Rename McpToolCallbackProvider to SyncMcpToolCallbackProvider
- Add utility methods for handling tool callbacks in McpToolUtils
- Extract client configuration logic into new McpClientDefinitions class
- Add tool callback support to ChatClient interface and implementations
- Remove redundant integration test
Introduce MCP client customization support
- Add McpSyncClientCustomizer interface for customizing MCP sync clients
- Replace McpClientDefinitions with McpSyncClientConfigurer
- Refactor MCP client initialization to support customization
- Remove redundant close() method from McpToolCallback
- Fix conditional class dependencies in WebMvc/Flux configurations
Add MCP AOT hints
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
Introduces a new API key interface that allows users to customize how
API keys are provided and managed in their Spring AI applications. This
change improves security and flexibility by:
- Adding core ApiKey interface and SimpleApiKey implementation
- Adding builder pattern for OpenAiApi creation
- Deprecating public constructors in favor of builder API (since 1.0.0.M6)
- Added docs
The new system enables users to implement their own key management
strategies while maintaining backward compatibility with property-based
configuration.
Introduce a utility class `LoggingMarkers` providing an SLF4J marker for tagging log entries with Personally Identifiable Information (PII). Update `BeanOutputConverter` to use the `PII_MARKER` in error logs for invalid JSON conversions. Enhance tests to verify PII marker usage in logging.
- Set Java version dynamically and configure Kotlin compiler
- Updated Maven configurations to dynamically reference the Java version using `${java.version}`. Added Kotlin compiler settings, including `jvmTarget` alignment with Java version and enabling `javaParameters`. This ensures consistency and better compatibility across builds.
- Fix log assertion in BeanOutputConverterTest to use Java 17
- Updated the test to assert log size explicitly before accessing the first log entry. This ensures the test is more robust and avoids potential issues with accessing logs unexpectedly.
- Use placeholders in logger.error to prevent string concatenation.
- Replaced string concatenation with a placeholder in the logger.error call to improve performance and maintain consistency with logging best practices. This helps avoid unnecessary overhead when logging is disabled.
- Update logging markers and improve data classification
- Replaced `PII_MARKER` with `SENSITIVE_DATA_MARKER`. Introduced `RESTRICTED_DATA_MARKER`, `REGULATED_DATA_MARKER` and `PUBLIC_DATA_MARKER`
- Updated associated logging logic and tests to reflect these changes.
- Fix punctuation in Javadoc comments for LoggingMarkers.
- Added missing periods to improve consistency and clarity in the Javadoc comments. This change ensures proper formatting and adheres to standard writing conventions.
Signed-off-by: Konstantin Pavlov <{ID}+{username}@users.noreply.github.com>
* Completed new documentation for Tool Calling
* Added deprecation notes and migration guide to documentation
* Made “call” methods explicit in ToolCallback API
* Consolidated naming: ToolCallExceptionConverter -> ToolExecutionExceptionProcessor
* Consolidated naming: ToolCallResultConvert.apply() -> ToolCallResultConvert.convert()
* Redraw diagrams for consistency
Relates to gh-2049
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* Introduced new ToolParam annotation for defining a description for tool parameters and marking them as (non)required.
* Improved the JSON Schema generation for tools, solving inconsistencies between methods and functions, and ensuring a predictable outcome.
* Added support for returning tool results directly to the user instead of passing them back to the model. Introduced new ToolExecutionResult API to propagate this information.
* Consolidated naming of tool-related options in ToolCallingChatOptions.
* Fixed varargs issue in ChatClient when passing ToolCallback[].
* Introduced new documentation for the tool calling capabilities in Spring AI, and deprecated the old one.
* Bumped jsonschema dependency to 4.37.0.
Relates to gh-2049
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
Adds getNativeClient API to VectorStore interface allowing access to the underlying native client implementation.
This change:
- Adds getNativeClient() default method to VectorStore interface returning Optional<T>
- Implements getNativeClient() in all vector store implementations exposing their respective native clients
- Adds integration tests verifying native client access for all implementations
Fixes: #2137
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
- Amzon Bedrock chat models were deprecated to support Amazon Bedrock Converse API for the chat models.
- This PR removes all the references of the deprecated Amazon Bedrock chat models
- Remove Amazon Bedrock chat models for anthropic, anthropic3, cohere, jurassic2, titan
- Remove API, chat options and model
- Remove tests and doc references
- Update the doc to reflect the changes
- Update upgrade notes
Resolves#2124
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- 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
Testcontainers 1.20.4 provides a new module for typesense with
TypesenseContainer implementation.
Signed-off-by: Eddú Meléndez <eddu.melendez@gmail.com>
Add string-based filter deletion alongside the Filter.Expression-based deletion
for vector stores. This provides a more convenient API for simple filter cases
while maintaining the full flexibility of expression-based filtering.
Key changes:
- Add delete(Filter.Expression) and delete(String) methods to VectorStore
- Add default string filter implementation in VectorStore interface
- Implement filter deletion in Chroma/Elasticsearch/PgVector stores
- Add integration tests for both filter APIs across implementations
This extends vector store deletion capabilities while maintaining consistent
behavior across implementations.
