- Add web search mode response in choice.message for enhanced
compatibility
- Implement web search mode for stream mode
- Add comprehensive unit tests for new features
Related to #1292
feat: enhance the compatibility of the minimax model and tests, related issue #1292
Refactoring and enhancements to the advisor functionality.
New Advisor interfaces in the org.springframework.ai.chat.client.advisor.api package:
- Advisor: Base interface for all advisor types.
- RequestAdvisor: For advising on request data before execution.
- ResponseAdvisor: For advising on response data after execution, with enhanced streaming modes.
- CallAroundAdvisor and StreamAroundAdvisor: For around advice on synchronous and streaming requests respectively.
- AroundAdvisorChain and DefaultAroundAdvisorChain: To manage chaining of around advisors.
Advisor Chain and Prompt Generation:
- Added the DefaultAroundAdvisorChain class to manage the sequence of advisors applied around chat model methods.
- Adjusted the prompt generation (toPrompt) to integrate with the refactored AdvisedRequest object.
Refactoring and Updates:
- Replaced the deprecated RequestResponseAdvisor interface with RequestAdvisor and ResponseAdvisor across the spring-ai-core and test modules.
- Updated the DefaultChatClient and related classes to use the new Advisor interface, improving modularity and consistency.
- Refactored DefaultAdvisorSpec and DefaultChatClientRequestSpec to handle the new Advisor type, and revised advisor lists and methods accordingly.
- Enhanced the handling of streaming responses, introducing StreamResponseMode for better control during streaming scenarios.
* Fixes an issue with advisor name resolution
* Streamlines repeating code
* Add a new advisor strategy for ON_FINISH_REASON streaming responses, which is used by the Q&A advisor
* Improve observable instrumentation by passing the parent observation to the advisor observation
Implement web search functionality for the MiniMax model.
Includes unit tests
This enhancement expands the model's ability to access and utilize current information from the internet.
Resolves#1245
Implement function call capability for MiniMax model and add unit tests based on new tool classes.
Address most scenarios, but note limitations in complex English contexts
with multiple function calls. Weather query example: may stop
prematurely when querying multiple locations due to single-location
parameter limit. This behavior stems from model performance constraints.
Streaming function calling is not passing tests, will be address seperately.
Resolves#1077
Implement function call capability for the Moonshot model. Include unit
tests to verify the new functionality. This feature addresses the
requirements outlined in issue #1058.
fix: MiniMax function call
review
Resolve issue with AzureOpenAiChatModel processing non-public images as
byte arrays. Implement handling for both URL strings and byte arrays,
converting latter to base64 encoded data URLs. Add test case for
resource-based media data. Update documentation with sample for
classpath resources.
This commit introduces the OpenAiModerationModel and related classes:
- Add OpenAiModerationModel for content moderation
- Create OpenAiModerationOptions for configuration
- Implement OpenAiModerationProperties for Spring Boot setup
- Add integration tests in OpenAiModerationModelIT
- Add documentation
Co-authored-by: hemeda3 <hemeda3@users.noreply.github.com>
This commit introduces a new boolean option 'maskSensitiveInfo' for
the MiniMax API model support in Spring AI. This feature allows users
to control whether sensitive information in the output is masked.
Relevant unit tests have been added to ensure proper functionality.
Resolves: #1216
* Consolidate usage of “db.collection.name” attribute to track table name, collection name, index name, document name, or whatever concept a vector database uses to store data. Removed “db.index” that was use sometimes instead of “db.collection.name”. This usage is in line with the OpenTelemetry Semantic Conventions.
* Configure query response content to be included as a “span event” instead of a “span attribute” if the backend system supports that, similar to how we do for the model observations.
* Structure vector store observation attributes in dedicated enums, including one for the Spring AI Kinds to avoid hard-coding the same value in a lot of places. This follows the OpenTelemetry Semantic Conventions as much as possible. Also, adopt Spring usual non-null-by-default strategy as much as possible.
* Align vector store conventions to the chat model ones, and follow alphabetical order for values. This is particularly useful for the convention classes, for which the Micrometer performance of exporting telemetry data improves when key values are added already sorted to the context.
* Fix flaky test in Mistral AI.
* Improve Qdrant integration tests.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
Handle the case where AnthropicChatResponse content is empty to prevent
an out of bounds exception. This ensures that the model behaves correctly
even when no content is returned in the response.
- When embedding documents, allow batching the documents using some criteria.
- `BatchingStrategy` interface with a `TokenCountBatchingStrategy` implementation that uses
the openai max input token size of 8191 as the default.
- Add a default method in EmbeddingModel to embed document using this new batching strategy.
- Change `MilvusVectorStore` to make use of this new batching API.
- Adding unit tests for `TokenCountBatchingStrategy`.
- Adding openai integration test to call the embed API that uses batching.
Resolves https://github.com/spring-projects/spring-ai/issues/1214
Other vector stores will be updated seperately
The withRateLimit call is redundant as rateLimit is already handled conditionally elsewhere. Its removal helps simplify the code and improves maintainability.
* 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>
- Add `TEXT` to the supported ResponseFormat types
- Add JsonSchema record for structured output configuration
- Update OpenAI chat documentation with details on Structured Outputs
- Clarify usage of JSON_SCHEMA response format in properties and code examples
- Update Structured Output Converter docs to mention OpenAI Structured Outputs
- Added support for OpenAI's structured outputs feature, which allows specifying a JSON schema for the model to match
- Introduced new record to configure the desired response format
- Added support for configuring the response format via application properties or the chat options builder
- Extend teh BeanOutputConverter to help generate JSON schema from a target domain object and convert the response.
- Added comprehensive tests to cover the new response format functionality
Resolves#1196
- Updated OpenAiChatModel, OpenAiApi, and OpenAiStreamFunctionCallingHelper to include the `refusal` field in metadata.
- Adjusted constructors and methods to handle the new `refusal` attribute.
- Modified related tests to account for the new `refusal` field.
- Add the refusal field value to the Spring AI AssistantMessage metadata
Resolves#1178
Integrated Micrometer's Observation into the OpenAiChatModel#stream reactive chain.
Included changes:
- Added ability to aggregate streaming responses for use in Observation metadata.
- Improved error handling and logging for chat response processing.
- Updated unit tests to include new observation logic and subscribe to Flux responses.
- Refined validation of observations in both normal and streaming chat operations.
- Disabled retry for streaming which used RetryTemplate - should use .retryWhen operator as the next step.
- Added an integration test.
Resolves#1190
Co-authored-by Christian Tzolov <ctzolov@vmware.com>
* 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>
* Add style to option abstraction
* Use abstraction in Observations directly instead of dedicated implementation
* Clean-up the merge of runtime and default image options in OpenAI and Stability AI
Related to #1148
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Update OllamaEmbeddingModel to support batch embedding requests
- Rename EmbeddingRequest/Response to EmbeddingsRequest/Response
- Add truncate option to control input truncation
- Update documentation and tests for new embedding API
- Remove deprecated withModel and withDefaultOptions methods
- Adjust default values for various Ollama model options
- Include response medata with response model name
Resolves#1158
- Add org-id and project-id properties with unified merging logic
- Update autoconfig and docs for all OpenAI models
- Introduce OpenAiChatOptions#httpHeaders option
- Add integration test for httpHeaders and update docs
Resolves#1141
* Observation APIs for chat, embedding and image models
* Conventions based on OpenTelemetry Semantic Conventions for GenAI
* Instrumentation for OpenAI chat, embedding, and image models
* Autoconfiguration for observability for OpenAI
Fixes gh-953
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
The autoconfiguration adds the FunctionCallbacks directly to the model's ChatOptions,
which results in the FunctionCallback being included in the request each time it is called.
The modification registers the container's FunctionCallback directly to the model's functionCallbackRegister
using the parent AbstractToolCallSupport constsructor.
Replace the handleFunctionCallbackConfigurations by simplified runtimeFunctionCallbackConfigurations.
Co-authored-by Christian Tzolov <ctzolov@vmware.com>
