- Introduce new TemplateRenderer API providing the logic for rendering an input template.
- Update the PromptTemplate API to accept a TemplateRenderer object at construction time.
- Move ST logic to StTemplateRenderer implementation, used by default in PromptTemplate. Additionally, make start and end delimiter character configurable.
Relates to gh-2655
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Replace model-specific enabled properties with unified spring.ai.model.embedding property
- Update documentation for Bedrock Cohere and Titan embedding models
- Add missing dependency information for RAG advisors in documentation
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Update MCP SDK version to 0.9.0
- Add baseUrl and sseEndpoint properties to McpServerProperties
- Update WebFlux and WebMvc server transport providers to use new URL configuration properties
- Remove deprecated backward compatibility code and related tests
- Remove deprecated methods from McpToolUtils
- Update MCP SDK version to 0.9.0-SNAPSHOT
- Add tool filtering capability to MCP Tool Callback Providers
Introduces a BiPredicate-based filtering mechanism for both Sync and Async
MCP Tool Callback Providers, allowing selective tool discovery based on
custom criteria. This enables filtering tools by name, client, or
any combination of properties.
* Apply filter in getToolCallbacks() methods for both providers
* Add tests for various filtering scenarios
- Add utility method to retrieve MCP exchange from tool context
* Add constant TOOL_CONTEXT_MCP_EXCHANGE_KEY to replace hardcoded exchange string
* Implement getMcpExchange utility method to safely retrieve the MCP exchange object
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Docker Desktop 4.40 has released a Docker Model Runner, which is OpenAI compatible.
- Add docs for Docker Model Runner
Signed-off-by: Eddú Meléndez <eddu.melendez@gmail.com>
This change modifies the voice parameter in OpenAI Audio Speech API from using the
Voice enum directly to using the string value of the enum. This provides more
flexibility for handling voice options, especially for custom voices or when voice
names come from configuration.
- Change voice parameter type from Voice enum to String
- Add overloaded methods to accept both enum and string values
- Update tests and documentation to reflect these changes
Signed-off-by: jonghoon park <dev@jonghoonpark.com>
Introduce a new ToolExecutionEligibilityChecker interface to provide a more flexible way to determine
when tool execution should be performed based on model responses. This abstraction replaces the
hardcoded logic previously scattered across the codebase.
- Adds a new ToolExecutionEligibilityChecker interface in spring-ai-core
- Integrates the checker into OpenAiChatModel with appropriate defaults
- Updates OpenAiChatAutoConfiguration to support the new interface
- Provides a default implementation that maintains backward compatibility
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
refactor: Replace ToolExecutionEligibilityChecker with ToolExecutionEligibilityPredicate
- Replacing ToolExecutionEligibilityChecker with ToolExecutionEligibilityPredicate
- Changing from Function<ChatResponse, Boolean> to BiPredicate<ChatOptions, ChatResponse>
- Adding a DefaultToolExecutionEligibilityPredicate implementation
- Updating AnthropicChatModel and OpenAiChatModel to use the new predicate
- Updating auto-configurations to inject the new predicate
- Adding comprehensive tests for the new predicate implementation
The new approach provides a cleaner and more consistent way to determine when tool execution should be performed based on both prompt options and chat responses.
Add Bedrock Converse support
add mistral support
Add ollama and vertex gemini
add ToolExecutionEligibilityPredicate docs
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
When generating the JSON Schema for a tool input from a method, ToolContext is now excluded since it's not something we want the model to provide. The framework takes care of passing a value for it when actually executing the tool call.
Fixes gh-2366
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Fix to include the correct top level property to enable/disable image/audio models
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Since the model autoconfiguration enable/disable flags are no longer used, remove them
- Currently, the model autoconfigurations can be enabled/disabled via top level Spring AI properties such as spring.ai.model.chat/embedding/image/moderation=<model-provider-name>
- Update documentation to add note section about this change
- Update note on the autoconfiguration section to point to the configuration changes
- Align the vertex ai text/multimodal keys in line with the other properties
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Rename Registration classes to Specification (SyncToolRegistration → SyncToolSpecification)
- Update transport classes to use Provider suffix (WebFluxSseServerTransport → WebFluxSseServerTransportProvider)
- Add exchange parameter to handler methods for better context passing
- Introduce McpBackwardCompatibility class to maintain backward compatibility
- Update MCP Server documentation to reflect new API patterns
- Add tests for backward compatibility
- Update mcp version to 0.8.0
- Add mcp 0.8.0 breaking change note-
The changes align with the MCP specification evolution while maintaining backward compatibility through deprecated APIs.
refactor: Extract MCP tool callback configuration into separate auto-configuration
Extracts the MCP tool callback functionality from McpClientAutoConfiguration into a
new dedicated McpToolCallbackAutoConfiguration that is disabled by default.
- Created new McpToolCallbackAutoConfiguration class that handles tool callback registration
- Made tool callbacks opt-in by requiring explicit configuration with spring.ai.mcp.client.toolcallback.enabled=true
- Removed deprecated tool callback methods from McpClientAutoConfiguration
- Updated ClientMcpTransport references to McpClientTransport to align with MCP library changes
- Added tests for the new auto-configuration and its conditions
refactor: standardize tool names to use underscores instead of hyphens
- Change separator in McpToolUtils.prefixedToolName from hyphen to underscore
- Add conversion of any remaining hyphens to underscores in formatted tool names
- Update affected tests to reflect the new naming convention
- Add comprehensive tests for McpToolUtils.prefixedToolName method
- Add integration test for payment transaction tools with Vertex AI Gemini
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Update dependencies and module names in maven pom.xml files affecting couchbase vector store support
- Rename artifact from spring-ai-couchbase-store-spring-boot-starter to spring-ai-starter-vector-store-couchbase
- Update imports and related cleanup
- Update corresponding documentation references
Signed-off-by: Soby Chacko <soby.chacko@broadcom.com>
- Update the documentation references to replace the artifact ID name change for the model starters
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Split spring-ai-spring-boot-autoconfigure into modules
- This PR addresses the restructuring of the following spring boot autoconfigurations:
- spring-ai retry -> common
- spring-ai chat client/model/memory -> chat
- spring-ai chat/embedding/image observation -> observation
- spring-ai chat/embedding models -> models
- Update the Spring AI BOM and boot starters with the new autoconfigure modules
- Rename the autoconfiguration and starters
- The package name for the models in autoconfiguration classes will have `org.springframework.ai.model.<name>.autoconfigure`
- Both the autoconfiguration and starters will have the prefix `spring-ai-autoconfigure-model` and `spring-ai-starter-model` respectively
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
