- Add VectorSearchAggregation used to actually preform the search
on a given collection with embeddings.
- add MongoDBVectorStore
- Add MongoDBVectorStoreIT. Integration test runs fine given...
- You have a mongo atlas cluster to connect to (local or remote)
- You have the search index "spring_ai_vector_search" setup correctly
- Need to explore getting around this
- Need to filter results using threshold
- Add postfilter for threshold values - While a post filter is not ideal,
it gets the job done. The mongo team seems to be working on having
it availible as a prefilter option, in which this implementation
can be updated to use later.
- implement filtering threshold
- fix a few sonar issues
- formatting
- use higher default num_candidates
- use builder for configuration
- add documentation and some refactor
- use consistent property in integration test
- finish implementing filter support
- add documentation to filter converter
- add vector search index auto creation
- Add to BOM.
- Fix version to 1.0.0-SN.
- Move expresion converter from core to models/mongodb.
- Fix style and license headers
- tename /api/clients/ into /api/chat
- move the the image from /api/clients to /api
- fix the layout inside the chat and embeddings docs. Moving the runtime options and sample controllers at top level.
- adjust all affected links.
* Fix Typo: Duplicate 'for' in documentation text
* Fix Typo: Duplicate 'to' in documentation text
* Fix broken links in documentation
* Correct grammar by deleting unnecessary 'an' in documentation
* Fix typo: Change 'tunning' to 'tuning' in documentation
* Fix typo: Change 'an' to 'can' in documentation
* Fix typo: Change 'generats' to 'generates' in documentation
* Fix grammatical error: Change 'a AI' to 'an AI' in documentation
* Fix grammatical error: Change 'a AI' to 'an AI' in code
* Fix Typo: Duplicate 'for' in code
* Azure uses 'deployment-name' when provisioning models and is what needs to
be passed in to the client, not the model name.
This is a difference with the OpenAI API that doesn't have a deployment-name
This change aligns the terminology used with Azure so that there is
less confusion when setting configuration property values
Fixes#10
- Extends the reactor logic to to allow aggregation of the chunked tool-calls messages and
leverage the exsiting fnctoin calling infrastructure.
- Seamples experience for the streaming functionality.
- Add Message ID and FinishReason to the returned Generations properties.
- Establish a new "spring-ai-retry" project, implementing a default HTTP error handler,
RetryTemplate, and handling both Transient and Non-Transient Exceptions.
- Streamline existing clients (e.g., OpenAI and MistralAI) to utilize "spring-ai-retry."
- Integrate retry auto-configuration with customizable properties, extending it to OpenAI and MistralAI Auto-Configs.
- Allow configuration of RetryTemplate and ResponseErrorHandler for various clients, including OpenAIChatClient,
OpenAiEmbeddingClient, OpenAiAudioTranscriptionCline, OpenAiImageClient, MistralAiChatClient, and MistralAiEmbeddingClient.
- Add tests for default RestTemplate and ResponseErrorHandler configurations in OpenAI and MistralAI.
- Introduce new retry auto-config properties: "onClientErrors" and "onHttpCodes".
- Implement tests for retry auto-config properties.
- Generate missing license headers.
