Add a default collection name similar to other vector store
implementations. Currently, when using starters, qdrant requires
a collection name. Otherwise, it fails.
Currently, `QdrantClient` and `WeaviateClient` are not exposed as
beans. Having access to those would benefit to perform operations
with an already configured client.
- Deprecate QdrantVectorStoreConfig.
- Update Qdrant manual config adoc.
- Improve Qdrant adoc.
- Update Weaviate docs.
- In ITs rename property spring.ai.azure.openai.chat.options.model to spring.ai.azure.openai.chat.options.deployment-name.
- Resolve compilation issues after the client library update.
- add index configuration and add support for ES response error handling.
- rename dims to dimension propety.
- add property javadocs
- improve the elasticsearch javadoc.
- add concurrency to store.add(..) (bc embeddingClient is slow)
- CassandraVectorStoreAutoConfiguration uses CassandraAutoConfiguration
- driver profiles for production stability+performance,
- small cleanups and naming fixes,
- main doc tidy-up
- astradb compatibility (protocol V4)
– don't create embeddings again for documents that already have them
similar to https://github.com/spring-projects/spring-ai/pull/413
The CassandraVectorStore is for managing and querying vector data in an Apache Cassandra db.
It offers functionalities like adding, deleting, and performing similarity searches on documents.
The store utilizes CQL to index and search vector data. It allows for custom metadata fields in
the documents to be stored alongside the vector and content data.
This class requires a CassandraVectorStoreConfig configuration object for initialization, which
includes settings like connection details, index name, field names, etc. It also requires an
EmbeddingClient to convert documents into embeddings before storing them.
A schema matching the configuration is automatically created if it doesn't exist. Missing columns
and indexes in existing tables will also be automatically created. Disable this with the disallowSchemaCreation.
This class is designed to work with brand new tables that it creates for you, or on top of existing
Cassandra tables. The latter is appropriate when wanting to keep data in place, creating embeddings
next to it, and performing vector similarity searches in-situ.
Instances of this class are not dynamic against server-side schema changes. If you change the schema
server-side you need a new CassandraVectorStore instance.
- Add auto-configure with tests.
- reformat code style
- Change field terminology to column (as appropriate for cassandra and cql)
- Add doc page with an advanced example.
- Add the dependencies to Spring AI BOM
– add to `AutoConfiguration.imports`
- Add @since annotation
- Fix javadoc issue
- Streamline the adoc content and layout
- Implement a HanaCloudVectorStore and tests
- Implement Autoconfiguraiton + properties
- Add boot starter
- Update BOM with vector store and boot dependencies.
- Add antora docuementation
- added junit for HanaCloudVectorStoreProperties.java and documentation
to create a BTP trial account and provision an instance for SAP Hana Cloud db
- updated license, formatting and javadoc
- IT for HanaCloudVectorStoreAutoConfiguration
- IT for HanaCloudVectorStoreAutoConfiguration
Additional
- add @AutoConfiguration(after = { JpaRepositoriesAutoConfiguration.class })
- update the handa docs structure.
Configure the amount of time to allow the client to complete the execution of an API call.
This timeout covers the entire client execution except for marshalling. This includes request handler execution,
all HTTP requests including retries, unmarshalling, etc. This value should always be positive, if present.
- Add timeout filed to the AbstractBedrockApi, used to initialize the BedrockRuntimeClient and the
BedrockStreamingRuntimeClient. Update all classes that extend the AbstractBedrockApi.
- Keep the previous constructors for backward compatibility using timeout value of 5 min.
- Add a common AWS connection timeout auto-config property and update the documentation.
Defaults to 5 min.
Additional changes:
- Fix Anthropic 3 straming response - add bedrock metrics field.
- Increate the default timeout to 5 min. Update the docs.
- Increase the ITs.
- expanded the AnthropicApi to include Tool, facilitating request and response abstractions.
- extended AnthropicChatClient to inherit AbstractFunctionCallSupport, with
implementation of all necessary methods and function registration protocols.
- implemented FunctionCallingOptions interface in AnthropicChatOptions.
- added tools integration tests for AnthropoicApi and AnthropicChatClient.
- extended the auto-configuration with functional calling functionality.
- added ITs for tools auto-config.
- updated documentation on anthropic function calling and relevant pages for comprehensive coverage.
- fix: remove non-sense underscore checking
- fix: check the model is included in request parameters
- fix: refactor, use constant
- fix: add jsonproperty decorator to additional attribute
- feat: allow additional params merging into the default watsonx option
- fix: remove not needed key
- fix: remove default values in watsonx ai options class
- fix: add default property
- Add a new autoconfig property spring.ai.retry.on-http-codes that list status codes (scuh as 429)
for which the retry should be attemptd.
- Updated the docs.
Resolves#433
- Requires LLaVa or Bakllava models.
- Extend the Ollama chat client to support the Spring AI Medi type inputs.
- Add OllamaChatClientMultimodalIT.java
- Add Multimodal section in Ollama's docs.
Resolves#421
- feat: setup watsonx ai api
- feat: add watsonx ai model options
- feat: setup watsonx chat client
- feat: add watsonx records/models
- add watsonx-ai module to pom
- add watsonx-ai module to bom
- feat: add connection properties watsonx
- feat: add WatsonxAiAutoConfiguration with api client
- feat: add starter watsonx.ai
- feat: add generate method in watsonx ai api
- feat: add watsonx ai api streaming generation method
- feat: add watsonx message to prompt converter util
- feat: implement call and stream mehtod
- feat: add watsonx ai runtime hints
- fix: filter null fields
- feat: watsonx options tests
- feat: add test dependencies
- feat: add runtime hints tests
- feat: add watsonx client tests
- fix: apply linter
- feat: add tests for message to prompt converter
- feat: add signature
- fix: change deprecated IamAuthenticator
- fix: do not keep baseUrl in a class variable
- fix: webClient request
- feat: add default base url to autoconfigure
- feat: add watsonx ai integration docs
- fix: model options json
- feat: add watsonx-ai spring boot starter
- feat: enable watsonx api on watsonx chat client
- fix: remove condition
- feat: add watsonx autoconfigure import
- feat: add watsonx module resource aot import
- feat: add pom for watsonx ai module
Additional pre-merge adjustments:
- Rename all WatsonxAIXxx classes to WatsonxAiXxx.
- Rename WatsonxChatClient to WatsonxAiChatClient.
- Move WatsonxAiChatOptions out of the API.
- Implement a Builder for WatsonxAiChatOptions (replace the inline withXxx code).
- Add a WatsonxAiChatOptions field to WatsonxAiChatClient as default options.
Later, it is also set by the auto-configuration properties.
- Implement merging logic for default vs runtime options in WatsonxAiChatClient.
- In Auto-config, add WatsonxAiChatProperties with enabled and options fields.
Options are passed to the client.
- Update the adoc to include the .chat.options properties.
- Add the watsonxai doc to the nav.adoc.
- Fix license headers and javadocs.
- Move dependency versioning to the parent POM.
- Created low-leverl anthropic messages API for Claude 3.
Use the new message API.
- Add Chat Client with tests.
- Add bedrok anthropic 3 docs.
- Add multibudality support + tests.
- Add auto-configuraiton & tests.
- Rename Athropic to Athropic3 in class names to avoid confusion with previous Bedrock Anthropic 2 impl.
This commit introduces support for the Anthropic Claude3 Message API
(https://api.anthropic.com), enabling direct interaction with its services.
This is not a Bedrock Anthropic Claude3 implemenation.
Changes include:
- Implementation of a low-level client, AnthropicApi, to interact with
the message API endpoints specified in the Anthropic documentation
(https://docs.anthropic.com/claude/reference/messages_post), including support for streaming.
- Addition of AnthropicApi tests to ensure functionality and reliability.
- Support for multimodal requests within AnthropicApi.
- Adding the spring-ai-anthropic and boot starter into BOM and parent POM modules for streamlined usage.
- Add Anthropic Auto-configuration and Boot Starter for seamless integration into existing projects.
- Implementation of AnthropicChatClient with capabilities for synchronous and streaming communication,
including support for multimodal messages.
- Inclusion of both unit and integration tests to validate functionality across various scenarios.
- Add Antora documentation with comprehensive guidance on using AnthropicApi and AnthropicChatClient.
- Add of Ahead-of-Time (AOT) hints for AnthropicApi.
- update anthropic diagram
- Implemented Bedrock Jurassic ChatClient
- added documentation reference
- implement auto-configuration and boot starter
- Disable the BedrockAi21Jurassic2ChatClientIT.emojiPenaltyWhenTrueByDefaultApplyPenaltyTest() test
as it fails when run in combination with the other tests.
