Uses of Annotation Interface
dev.langchain4j.Experimental

Packages that use Experimental

Package	Description
dev.langchain4j.agent.tool
dev.langchain4j.data.message
dev.langchain4j.exception
dev.langchain4j.experimental.rag.content.retriever.sql
dev.langchain4j.guardrail
dev.langchain4j.http.client
dev.langchain4j.http.client.apache
dev.langchain4j.http.client.jdk
dev.langchain4j.http.client.okhttp
dev.langchain4j.http.client.sse
dev.langchain4j.mcp.client
dev.langchain4j.memory
dev.langchain4j.micrometer.metrics.listeners
dev.langchain4j.model.anthropic
dev.langchain4j.model.audio
dev.langchain4j.model.azure
dev.langchain4j.model.batch
dev.langchain4j.model.bedrock	AWS Bedrock integration for LangChain4j.
dev.langchain4j.model.catalog	Contains interfaces and classes for model catalog functionality.
dev.langchain4j.model.chat
dev.langchain4j.model.chat.response
dev.langchain4j.model.embedding
dev.langchain4j.model.embedding.listener
dev.langchain4j.model.embedding.request
dev.langchain4j.model.embedding.response
dev.langchain4j.model.google.genai
dev.langchain4j.model.googleai
dev.langchain4j.model.image
dev.langchain4j.model.mistralai
dev.langchain4j.model.ollama
dev.langchain4j.model.openai
dev.langchain4j.model.openai.internal
dev.langchain4j.model.openaiofficial
dev.langchain4j.model.scoring
dev.langchain4j.model.scoring.request
dev.langchain4j.model.scoring.response
dev.langchain4j.observability.api.event
dev.langchain4j.observability.api.listener
dev.langchain4j.observability.event
dev.langchain4j.observation.listener
dev.langchain4j.rag
dev.langchain4j.rag.content.aggregator
dev.langchain4j.rag.content.retriever
dev.langchain4j.rag.content.retriever.hibernate
dev.langchain4j.rag.content.retriever.listener
dev.langchain4j.rag.query.router
dev.langchain4j.rag.query.transformer
dev.langchain4j.service
dev.langchain4j.service.guardrail
dev.langchain4j.service.tool
dev.langchain4j.service.tool.search
dev.langchain4j.service.tool.search.simple
dev.langchain4j.service.tool.search.vector
dev.langchain4j.skills
dev.langchain4j.skills.shell
dev.langchain4j.spi
dev.langchain4j.store.embedding
dev.langchain4j.store.embedding.filter.builder.sql
dev.langchain4j.store.embedding.filter.parser.sql
dev.langchain4j.store.embedding.listener
dev.langchain4j.store.memory.chat
dev.langchain4j.web.search

Packages with annotations of type Experimental

Package	Description
dev.langchain4j.observability.api
dev.langchain4j.observability.api.event
dev.langchain4j.observability.event
dev.langchain4j.guardrail
dev.langchain4j.service.guardrail
dev.langchain4j.observability.api.listener

Uses of Experimental in dev.langchain4j.agent.tool

Classes in dev.langchain4j.agent.tool with annotations of type Experimental

Modifier and Type	Class	Description
@interface	CompensateFor	Marks a method as the compensating action for a Tool.
enum	ReturnBehavior	Per-tool setting controlling what happens with a tool's result after execution.
enum	SearchBehavior	Defines the behavior of a tool when dev.langchain4j.service.tool.search.ToolSearchStrategy is configured for an AI Service.

Uses of Experimental in dev.langchain4j.data.message

Methods in dev.langchain4j.data.message with annotations of type Experimental

Modifier and Type	Method	Description
<T> T	AiMessage.attribute(String key, Class<T> type)	Returns additional attribute by it's key.
<T> T	SystemMessage.attribute(String key, Class<T> type)	Returns additional attribute by it's key.
<T> T	UserMessage.attribute(String key, Class<T> type)	Returns additional attribute by it's key.
Map<String,Object>	AiMessage.attributes()	Returns additional attributes, typically provider-specific.
AiMessage.Builder	AiMessage.Builder.attributes(Map<String,Object> attributes)
Map<String,Object>	SystemMessage.attributes()	Returns additional attributes.
Map<String,Object>	UserMessage.attributes()	Returns additional attributes.
ToolExecutionResultMessage.Builder	ToolExecutionResultMessage.Builder.contents(Content... contents)	Sets the contents of the tool execution result.
ToolExecutionResultMessage.Builder	ToolExecutionResultMessage.Builder.contents(List<Content> contents)	Sets the contents of the tool execution result.
List<Content>	ToolExecutionResultMessage.contents()	Returns the Contents of the tool execution result.
boolean	ToolExecutionResultMessage.hasSingleText()	Whether this message contains a single TextContent.
AiMessage.Builder	AiMessage.Builder.thinking(String thinking)
String	AiMessage.thinking()	Get the thinking/reasoning text of the message.

Uses of Experimental in dev.langchain4j.exception

Classes in dev.langchain4j.exception with annotations of type Experimental

Modifier and Type	Class	Description
class	AsyncNotSupportedException	Signals that an asynchronous SPI method (an *Async method, or a reactive Publisher-returning method) is not implemented by a component, and is therefore the internal "this component is not genuinely asynchronous" marker carried by those methods' default implementations.

Uses of Experimental in dev.langchain4j.experimental.rag.content.retriever.sql

Classes in dev.langchain4j.experimental.rag.content.retriever.sql with annotations of type Experimental

Modifier and Type	Class	Description
class	SqlDatabaseContentRetriever	WARNING!

Constructors in dev.langchain4j.experimental.rag.content.retriever.sql with annotations of type Experimental

Modifier	Constructor	Description
	SqlDatabaseContentRetriever(DataSource dataSource, String sqlDialect, String databaseStructure, PromptTemplate promptTemplate, ChatModel chatModel, Integer maxRetries)	Creates an instance of a SqlDatabaseContentRetriever.

Uses of Experimental in dev.langchain4j.guardrail

Methods in dev.langchain4j.guardrail with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<ChatResponse>	ChatExecutor.executeAsync()	Non-blocking counterpart of ChatExecutor.execute().
default CompletableFuture<ChatResponse>	ChatExecutor.executeAsync(List<ChatMessage> chatMessages)	Non-blocking counterpart of ChatExecutor.execute(List).
default CompletableFuture<R>	Guardrail.validateAsync(P request)	Non-blocking counterpart of Guardrail.validate(GuardrailRequest), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes.

Uses of Experimental in dev.langchain4j.http.client

Classes in dev.langchain4j.http.client with annotations of type Experimental

Modifier and Type	Class	Description
class	FormDataFile

Methods in dev.langchain4j.http.client with annotations of type Experimental

Modifier and Type	Method	Description
HttpRequest.Builder	HttpRequest.Builder.addFormDataField(String name, String value)
HttpRequest.Builder	HttpRequest.Builder.addFormDataFile(String name, String fileName, String contentType, byte[] content)
default CompletableFuture<SuccessfulHttpResponse>	HttpClient.executeAsync(HttpRequest request)	Non-blocking counterpart of HttpClient.execute(HttpRequest).
HttpRequest.Builder	HttpRequest.Builder.formDataFields(Map<String,String> formDataFields)
Map<String,String>	HttpRequest.formDataFields()
HttpRequest.Builder	HttpRequest.Builder.formDataFiles(Map<String, FormDataFile> formDataFiles)
Map<String, FormDataFile>	HttpRequest.formDataFiles()
default Flow.Publisher<HttpStreamingEvent>	HttpClient.stream(HttpRequest request)	Executes a streaming HTTP request and exposes the parsed events as a cold Flow.Publisher of HttpStreamingEvents.
default Flow.Publisher<HttpStreamingEvent>	HttpClient.stream(HttpRequest request, ServerSentEventParser parser)	Like HttpClient.stream(HttpRequest), but with a caller-supplied ServerSentEventParser.

Uses of Experimental in dev.langchain4j.http.client.apache

Methods in dev.langchain4j.http.client.apache with annotations of type Experimental

Modifier and Type	Method	Description
Integer	ApacheHttpClientBuilder.streamingBufferSize()
ApacheHttpClientBuilder	ApacheHttpClientBuilder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer used by the streaming (stream) path.

Uses of Experimental in dev.langchain4j.http.client.jdk

Methods in dev.langchain4j.http.client.jdk with annotations of type Experimental

Modifier and Type	Method	Description
Integer	JdkHttpClientBuilder.streamingBufferSize()
JdkHttpClientBuilder	JdkHttpClientBuilder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer used by the streaming (stream) path.

Uses of Experimental in dev.langchain4j.http.client.okhttp

Methods in dev.langchain4j.http.client.okhttp with annotations of type Experimental

Modifier and Type	Method	Description
Integer	OkHttpClientBuilder.streamingBufferSize()
OkHttpClientBuilder	OkHttpClientBuilder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer used by the streaming (stream) path.

Uses of Experimental in dev.langchain4j.http.client.sse

Classes in dev.langchain4j.http.client.sse with annotations of type Experimental

Modifier and Type	Class	Description
class	HttpResponseReceived	HttpStreamingEvent signalling that the HTTP response head (status and headers) was received and the stream opened successfully.
interface	HttpStreamingEvent	An event emitted while consuming a streaming HTTP response via HttpClient.stream(dev.langchain4j.http.client.HttpRequest).
class	ServerSentEventContext
interface	ServerSentEventParsingHandle	Handle that can be used to cancel the parsing of server-sent events.

Methods in dev.langchain4j.http.client.sse with annotations of type Experimental

Modifier and Type	Method	Description
default ServerSentEventParser.Incremental	ServerSentEventParser.incremental()	Returns a fresh ServerSentEventParser.Incremental parser instance backed by the same parsing logic as ServerSentEventParser.parse(InputStream, ServerSentEventListener), but driven by byte chunks instead of a blocking InputStream.
default void	ServerSentEventListener.onEvent(ServerSentEvent event, ServerSentEventContext context)	Handles server-sent event.

Uses of Experimental in dev.langchain4j.mcp.client

Methods in dev.langchain4j.mcp.client with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<ToolExecutionResult>	McpClient.executeToolAsync(ToolExecutionRequest executionRequest, InvocationContext invocationContext)	Non-blocking counterpart of McpClient.executeTool(ToolExecutionRequest, InvocationContext): executes a tool on the MCP server without holding a thread while the result is in flight.

Uses of Experimental in dev.langchain4j.memory

Methods in dev.langchain4j.memory with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<Void>	ChatMemory.addAsync(List<ChatMessage> messages)	Non-blocking counterpart of ChatMemory.add(Iterable), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs.
default CompletableFuture<List<ChatMessage>>	ChatMemory.messagesAsync()	Non-blocking counterpart of ChatMemory.messages(), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs.
default CompletableFuture<Void>	ChatMemory.setAsync(List<ChatMessage> messages)	Non-blocking counterpart of ChatMemory.set(Iterable), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs (e.g. to rewrite memory for tool compensation without blocking the model-delivery thread).

Uses of Experimental in dev.langchain4j.micrometer.metrics.listeners

Classes in dev.langchain4j.micrometer.metrics.listeners with annotations of type Experimental

Modifier and Type	Class	Description
class	MicrometerMetricsChatModelListener	A ChatModelListener that uses a Micrometer MeterRegistry to collect metrics about chat model interactions following OpenTelemetry Semantic Conventions for Generative AI.

Uses of Experimental in dev.langchain4j.model.anthropic

Classes in dev.langchain4j.model.anthropic with annotations of type Experimental

Modifier and Type	Class	Description
final class	AnthropicBatchChatModel	A BatchChatModel for the Anthropic Message Batches API, which processes multiple chat requests asynchronously at 50% of the standard per-token price.
class	AnthropicCacheDiagnostics	Result of Anthropic's (beta) cache diagnostics comparison for a single request, surfaced via AnthropicChatResponseMetadata.cacheDiagnostics().
class	AnthropicServerTool
class	AnthropicServerToolResult	Represents a result from an Anthropic server-executed tool (e.g., web_search, code_execution).
enum	AnthropicSkill	Anthropic-managed Agent Skills that let Claude generate real downloadable documents by running pre-built skills inside the code execution container.
class	AnthropicTokenCountEstimator

Methods in dev.langchain4j.model.anthropic with annotations of type Experimental

Modifier and Type	Method	Description
AnthropicStreamingChatModel.AnthropicStreamingChatModelBuilder	AnthropicStreamingChatModel.AnthropicStreamingChatModelBuilder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer for the reactive (Flow.Publisher) streaming path.

Uses of Experimental in dev.langchain4j.model.audio

Classes in dev.langchain4j.model.audio with annotations of type Experimental

Modifier and Type	Interface	Description
interface	AudioTranscriptionModel	A model that can transcribe audio into text.
class	AudioTranscriptionRequest	Request to transcribe audio.
class	AudioTranscriptionResponse	Response containing the transcription of an audio file.
interface	TextToSpeechModel	A model that can synthesize audio from text.
class	TextToSpeechRequest
class	TextToSpeechResponse	Response containing the audio generated from text.

Uses of Experimental in dev.langchain4j.model.azure

Classes in dev.langchain4j.model.azure with annotations of type Experimental

Modifier and Type	Class	Description
class	AzureOpenAiAudioTranscriptionModel	Represents an Azure OpenAI audio transcription model, such as Whisper.

Uses of Experimental in dev.langchain4j.model.batch

Classes in dev.langchain4j.model.batch with annotations of type Experimental

Modifier and Type	Class	Description
final class	BatchError	Represents an error status for a failed request within a batch operation.
interface	BatchItemResult<T>	Represents the outcome of a single request within a batch operation.
class	BatchPage<T>	Represents a set of batch jobs that is potentially paginated.
final class	BatchPagination
class	BatchRequest<T>	Represents a batch of requests to be processed together.
class	BatchResponse<T>	Represents the responses of a batch operation.
enum	BatchState	Represents the possible states of a batch job.

Uses of Experimental in dev.langchain4j.model.bedrock

Methods in dev.langchain4j.model.bedrock with annotations of type Experimental

Modifier and Type	Method	Description
BedrockChatModel.Builder	BedrockChatModel.Builder.asyncClient(software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeAsyncClient asyncClient)	Sets the async Bedrock client used by chatAsync.
BedrockStreamingChatModel.Builder	BedrockStreamingChatModel.Builder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer for the reactive (Flow.Publisher) streaming path.

Uses of Experimental in dev.langchain4j.model.catalog

Classes in dev.langchain4j.model.catalog with annotations of type Experimental

Modifier and Type	Interface	Description
interface	ModelCatalog	Represents a service that can discover available models from an LLM provider.
class	ModelDescription	Represents metadata about an available model from a provider.
enum	ModelType	Represents the type/category of a model.

Uses of Experimental in dev.langchain4j.model.chat

Classes in dev.langchain4j.model.chat with annotations of type Experimental

Modifier and Type	Interface	Description
interface	BatchChatModel	A model interface for processing multiple chat requests asynchronously in a batch.

Methods in dev.langchain4j.model.chat with annotations of type Experimental

Modifier and Type	Method	Description
default Flow.Publisher<ChatModelStreamingEvent>	StreamingChatModel.chat(ChatMessage... messages)	Reactive convenience overload accepting the messages directly: returns a cold Publisher that streams the response to messages.
default Flow.Publisher<ChatModelStreamingEvent>	StreamingChatModel.chat(ChatRequest request)	Reactive entry point: sends a chat request and returns a Flow.Publisher of ChatModelStreamingEvents.
default Flow.Publisher<String>	StreamingChatModel.chat(String userMessage)	Reactive convenience counterpart of StreamingChatModel.chat(String, StreamingChatResponseHandler): returns a cold Publisher that streams the model's textual response to userMessage, token by token.
default Flow.Publisher<ChatModelStreamingEvent>	StreamingChatModel.chat(List<ChatMessage> messages)	Reactive convenience counterpart of StreamingChatModel.chat(List, StreamingChatResponseHandler): returns a cold Publisher that streams the response to messages.
default CompletableFuture<ChatResponse>	ChatModel.chatAsync(ChatMessage... messages)	Non-blocking convenience counterpart of ChatModel.chat(ChatMessage...).
default CompletableFuture<ChatResponse>	ChatModel.chatAsync(ChatRequest chatRequest)	Non-blocking counterpart of ChatModel.chat(ChatRequest): sends a chat request and returns a CompletableFuture that completes with the ChatResponse once the model responds.
default CompletableFuture<ChatResponse>	ChatModel.chatAsync(ChatRequest chatRequest, ChatRequestOptions options)	Sends a non-blocking chat request with additional invocation options.
default CompletableFuture<String>	ChatModel.chatAsync(String userMessage)	Non-blocking convenience counterpart of ChatModel.chat(String): completes with the text of the model's response.
default CompletableFuture<ChatResponse>	ChatModel.chatAsync(List<ChatMessage> messages)	Non-blocking convenience counterpart of ChatModel.chat(List).
default Flow.Publisher<ChatModelStreamingEvent>	StreamingChatModel.doChat(ChatRequest chatRequest)	Provider-specific implementation of the reactive stream returned by StreamingChatModel.chat(ChatRequest) (which wraps it with ChatModelListener invocation).
default CompletableFuture<ChatResponse>	ChatModel.doChatAsync(ChatRequest chatRequest)	SPI hook for a genuinely non-blocking chat implementation, invoked by ChatModel.chatAsync(ChatRequest).

Uses of Experimental in dev.langchain4j.model.chat.response

Classes in dev.langchain4j.model.chat.response with annotations of type Experimental

Modifier and Type	Interface	Description
interface	ChatModelStreamingEvent	Base type for the events emitted by the reactive stream of a StreamingChatModel — the Flow.Publisher<ChatModelStreamingEvent> returned by StreamingChatModel.chat(dev.langchain4j.model.chat.request.ChatRequest).
class	CompleteResponse	The terminal ChatModelStreamingEvent of a streaming chat: the complete, aggregated ChatResponse.
class	CompleteToolCall	Represents a complete tool call.
class	PartialResponse
class	PartialResponseContext
class	PartialThinking
class	PartialThinkingContext
class	PartialToolCall	Represents a partial tool call.
class	PartialToolCallContext
interface	RawStreamingEvent	A provider-specific streaming event that langchain4j's generic event model does not (yet) map to a dedicated ChatModelStreamingEvent type — for example a web-search, citation or reasoning-summary event.
interface	StreamingHandle	Handle that can be used to cancel the streaming done via StreamingChatResponseHandler.

Methods in dev.langchain4j.model.chat.response with annotations of type Experimental

Modifier and Type	Method	Description
default void	StreamingChatResponseHandler.onCompleteToolCall(CompleteToolCall completeToolCall)	Invoked when the model has finished streaming a single tool call.
default void	StreamingChatResponseHandler.onPartialResponse(PartialResponse partialResponse, PartialResponseContext context)	Invoked each time the model generates a partial textual response, usually a single token.
default void	StreamingChatResponseHandler.onPartialThinking(PartialThinking partialThinking)	Invoked each time the model generates a partial thinking/reasoning text, usually a single token.
default void	StreamingChatResponseHandler.onPartialThinking(PartialThinking partialThinking, PartialThinkingContext context)	Invoked each time the model generates a partial thinking/reasoning text, usually a single token.
default void	StreamingChatResponseHandler.onPartialToolCall(PartialToolCall partialToolCall)	This callback is invoked each time the model generates a partial tool call, which contains a single token of the tool's arguments.
default void	StreamingChatResponseHandler.onPartialToolCall(PartialToolCall partialToolCall, PartialToolCallContext context)	This callback is invoked each time the model generates a partial tool call, which contains a single token of the tool's arguments.
default void	StreamingChatResponseHandler.onUnmappedRawEvent(Object rawEvent)	Invoked when a provider emits a raw streaming event that is not already exposed through one of the typed callbacks (such as StreamingChatResponseHandler.onPartialResponse(PartialResponse, PartialResponseContext), StreamingChatResponseHandler.onPartialThinking(PartialThinking, PartialThinkingContext), StreamingChatResponseHandler.onPartialToolCall(PartialToolCall, PartialToolCallContext) or StreamingChatResponseHandler.onCompleteToolCall(CompleteToolCall)).

Uses of Experimental in dev.langchain4j.model.embedding

Classes in dev.langchain4j.model.embedding with annotations of type Experimental

Modifier and Type	Interface	Description
interface	BatchEmbeddingModel	Used for processing multiple embedding requests asynchronously in a batch.

Methods in dev.langchain4j.model.embedding with annotations of type Experimental

Modifier and Type	Method	Description
default EmbeddingModel	EmbeddingModel.addListener(EmbeddingModelListener listener)	Returns an EmbeddingModel that wraps this one and notifies the given listener around each embedding call.
default EmbeddingModel	EmbeddingModel.addListeners(List<EmbeddingModelListener> listeners)	Returns an EmbeddingModel that wraps this one and notifies the given listeners (in iteration order) around each embedding call.
default EmbeddingRequestParameters	EmbeddingModel.defaultRequestParameters()	The parameters applied to every request unless overridden by the request itself, typically derived from the model's builder-time configuration.
default EmbeddingResponse	EmbeddingModel.doEmbed(EmbeddingRequest request)	Performs the embedding for EmbeddingModel.embed(EmbeddingRequest).
default CompletableFuture<EmbeddingResponse>	EmbeddingModel.doEmbedAsync(EmbeddingRequest request)	Non-blocking counterpart of EmbeddingModel.doEmbed(EmbeddingRequest), called by EmbeddingModel.embedAsync(EmbeddingRequest) after the request's parameters have been merged and validated.
default EmbeddingResponse	EmbeddingModel.embed(EmbeddingRequest request)	Embeds the inputs of the given EmbeddingRequest and returns the resulting embeddings.
default CompletableFuture<EmbeddingResponse>	EmbeddingModel.embedAsync(EmbeddingRequest request)	Non-blocking counterpart of EmbeddingModel.embed(EmbeddingRequest): embeds the request's inputs and completes the returned future with the embeddings, without blocking the calling thread.
default List<EmbeddingModelListener>	EmbeddingModel.listeners()	The EmbeddingModelListeners that are notified around EmbeddingModel.embed(EmbeddingRequest).
default ModelProvider	EmbeddingModel.provider()	The ModelProvider of this embedding model (for example ModelProvider.OPEN_AI).
default Set<ContentType>	EmbeddingModel.supportedContentTypes()	The input content types this model can embed.
default Set<EmbeddingParameter<?>>	EmbeddingModel.supportedParameters()	The per-call parameters this model honors.

Uses of Experimental in dev.langchain4j.model.embedding.listener

Classes in dev.langchain4j.model.embedding.listener with annotations of type Experimental

Modifier and Type	Class	Description
class	EmbeddingModelErrorContext	The context passed to EmbeddingModelListener.onError(EmbeddingModelErrorContext) when an embedding call fails.
static class	EmbeddingModelErrorContext.Builder	Builder for EmbeddingModelErrorContext.
interface	EmbeddingModelListener	An EmbeddingModel listener that listens for requests, responses and errors.
class	EmbeddingModelRequestContext	The context passed to EmbeddingModelListener.onRequest(EmbeddingModelRequestContext) before an embedding call.
static class	EmbeddingModelRequestContext.Builder	Builder for EmbeddingModelRequestContext.
class	EmbeddingModelResponseContext	The context passed to EmbeddingModelListener.onResponse(EmbeddingModelResponseContext) after a successful embedding call.
static class	EmbeddingModelResponseContext.Builder	Builder for EmbeddingModelResponseContext.

Uses of Experimental in dev.langchain4j.model.embedding.request

Classes in dev.langchain4j.model.embedding.request with annotations of type Experimental

Modifier and Type	Class	Description
class	DefaultEmbeddingRequestParameters	The default, map-backed implementation of EmbeddingRequestParameters.
class	EmbeddingInput	A single input to embed: one or more ordered Content parts that are fused into one Embedding.
enum	EmbeddingInputType	The role a piece of text plays in a retrieval task, allowing a provider to encode it differently.
final record	EmbeddingParameter<T>	A typed, stable identifier for a single EmbeddingRequestParameters value.
class	EmbeddingRequest	A request to an EmbeddingModel, containing a batch of EmbeddingInputs to embed and the per-call parameters.
interface	EmbeddingRequestParameters	The per-call parameters of an EmbeddingRequest, such as EmbeddingRequestParameters.dimensions() or EmbeddingRequestParameters.inputType().

Uses of Experimental in dev.langchain4j.model.embedding.response

Classes in dev.langchain4j.model.embedding.response with annotations of type Experimental

Modifier and Type	Class	Description
class	EmbeddingResponse	The result of embedding an EmbeddingRequest: the Embeddings produced for the request's inputs (in the same order) together with the EmbeddingResponseMetadata such as the model name and token usage.
class	EmbeddingResponseMetadata	Metadata returned alongside an EmbeddingResponse, describing the call that produced it: the model name and the token usage.

Uses of Experimental in dev.langchain4j.model.google.genai

Classes in dev.langchain4j.model.google.genai with annotations of type Experimental

Modifier and Type	Class	Description
final class	GoogleGenAiBatchChatModel	Provides an interface for interacting with the Google GenAI Batch API for Chat models.
final class	GoogleGenAiBatchEmbeddingModel	Provides an interface for interacting with the Google GenAI Batch API for Embedding models.
final class	GoogleGenAiBatchImageModel	Provides an interface for interacting with the Google GenAI Batch API for Image generation models.
class	GoogleGenAiChatModel
class	GoogleGenAiEmbeddingModel
class	GoogleGenAiImageModel	Represents a Google GenAI model for image generation and editing using the official com.google.genai SDK.
class	GoogleGenAiStreamingChatModel

Uses of Experimental in dev.langchain4j.model.googleai

Classes in dev.langchain4j.model.googleai with annotations of type Experimental

Modifier and Type	Class	Description
final class	GoogleAiGeminiBatchChatModel	Provides an interface for interacting with the Gemini Batch API, an asynchronous service designed for processing large volumes of requests at a reduced cost (50% of standard).
final class	GoogleAiGeminiBatchEmbeddingModel	Batch embedding model for Google AI Gemini.
final class	GoogleAiGeminiBatchImageModel	Provides an interface for batch image generation using the Gemini Batch API.
class	GoogleAiGeminiImageModel	Represents a Google AI Gemini model for image generation and editing.

Uses of Experimental in dev.langchain4j.model.image

Classes in dev.langchain4j.model.image with annotations of type Experimental

Modifier and Type	Interface	Description
interface	BatchImageModel	A model interface for processing multiple image generation requests asynchronously in a batch.

Uses of Experimental in dev.langchain4j.model.mistralai

Classes in dev.langchain4j.model.mistralai with annotations of type Experimental

Modifier and Type	Class	Description
final class	MistralAiBatchChatModel	A BatchChatModel for the Mistral Batch API, which processes multiple chat requests asynchronously at 50% of the standard per-token price.

Uses of Experimental in dev.langchain4j.model.ollama

Classes in dev.langchain4j.model.ollama with annotations of type Experimental

Modifier and Type	Class	Description
class	OllamaImageModel	Experimental Ollama image generation model.

Uses of Experimental in dev.langchain4j.model.openai

Classes in dev.langchain4j.model.openai with annotations of type Experimental

Modifier and Type	Class	Description
class	OpenAiAudioTranscriptionModel	Represents an OpenAI audio model with a transcription interface, only gpt-4o-transcribe, gpt-4o-mini-transcribe, whisper-1 (which is powered by our open source Whisper V2 model), and gpt-4o-transcribe-diarize are supported.
enum	OpenAiAudioTranscriptionModelName
class	OpenAiEmbeddingRequestParameters	OpenAI-specific EmbeddingRequestParameters, adding the parameters supported by the OpenAI embeddings API on top of the common modelName/dimensions.
class	OpenAiResponsesChatModel
class	OpenAiResponsesStreamingChatModel
class	OpenAiTextToSpeechModel	Represents an OpenAI text-to-speech model with a speech generation interface.
enum	OpenAiTextToSpeechModelName

Methods in dev.langchain4j.model.openai with annotations of type Experimental

Modifier and Type	Method	Description
CompletableFuture<ChatResponse>	OpenAiResponsesChatModel.doChatAsync(ChatRequest chatRequest)
OpenAiResponsesStreamingChatModel.Builder	OpenAiResponsesStreamingChatModel.Builder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer for the reactive streaming path.
OpenAiStreamingChatModel.OpenAiStreamingChatModelBuilder	OpenAiStreamingChatModel.OpenAiStreamingChatModelBuilder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer for the reactive (Flow.Publisher) streaming path.

Uses of Experimental in dev.langchain4j.model.openai.internal

Methods in dev.langchain4j.model.openai.internal with annotations of type Experimental

Modifier and Type	Method	Description
Flow.Publisher<ChatModelStreamingEvent>	OpenAiClient.chatCompletionPublisher(ChatCompletionRequest request, ChatCompletionOptions options)
default CompletableFuture<ParsedAndRawResponse<ResponseContent>>	SyncOrAsync.executeRawAsync()
B	OpenAiClient.Builder.streamingBufferSize(Integer streamingBufferSize)	Sets the size of the bounded back-pressure buffer used by the reactive streaming publisher (chatCompletionPublisher).

Uses of Experimental in dev.langchain4j.model.openaiofficial

Classes in dev.langchain4j.model.openaiofficial with annotations of type Experimental

Modifier and Type	Class	Description
final class	OpenAiOfficialBatchChatModel	Submits chat requests to the OpenAI Batch API, which processes them asynchronously at a reduced cost compared to real-time requests.
class	OpenAiOfficialChatRequestParameters
class	OpenAiOfficialChatResponseMetadata
class	OpenAiOfficialResponsesChatModel	ChatModel implementation using the official OpenAI Java client for the Responses API.
class	OpenAiOfficialResponsesChatRequestParameters
class	OpenAiOfficialResponsesChatResponseMetadata
class	OpenAiOfficialResponsesStreamingChatModel	StreamingChatModel implementation using the official OpenAI Java client for the Responses API.

Uses of Experimental in dev.langchain4j.model.scoring

Methods in dev.langchain4j.model.scoring with annotations of type Experimental

Modifier and Type	Method	Description
default ScoringRequestParameters	ScoringModel.defaultRequestParameters()	The model's default per-call parameters, applied by ScoringModel.scoreAsync(ScoringRequest) to every request and overridden by any parameters set on the request itself.
default CompletableFuture<ScoringResponse>	ScoringModel.doScoreAsync(ScoringRequest request)	The provider hook behind ScoringModel.scoreAsync(ScoringRequest).
default CompletableFuture<ScoringResponse>	ScoringModel.scoreAsync(ScoringRequest request)	Scores the documents of the given request against its query without blocking the calling thread — the asynchronous/reactive counterpart of ScoringModel.scoreAll(List, String), used by the non-blocking RAG flow (see ReRankingContentAggregator).

Uses of Experimental in dev.langchain4j.model.scoring.request

Classes in dev.langchain4j.model.scoring.request with annotations of type Experimental

Modifier and Type	Class	Description
class	DefaultScoringRequestParameters	The default implementation of ScoringRequestParameters.
class	ScoringRequest	A request to score (re-rank) a list of ScoringRequest.documents() against a ScoringRequest.query().
interface	ScoringRequestParameters	The per-call parameters of a ScoringRequest, such as the ScoringRequestParameters.modelName() to use.

Uses of Experimental in dev.langchain4j.model.scoring.response

Classes in dev.langchain4j.model.scoring.response with annotations of type Experimental

Modifier and Type	Class	Description
class	ScoringResponse	The result of scoring a ScoringRequest: one relevance score per request document, in the same order, together with the ScoringResponseMetadata (model name, token/billing usage).
class	ScoringResponseMetadata	The metadata of a ScoringResponse: the ScoringResponseMetadata.modelName() that produced the scores and the ScoringResponseMetadata.tokenUsage() (or provider billing units) the call consumed.

Uses of Experimental in dev.langchain4j.observability.api.event

Classes in dev.langchain4j.observability.api.event with annotations of type Experimental

Modifier and Type	Class	Description
enum	CompensationReason	Why a successfully-executed tool was compensated (rolled back).
interface	ToolCompensatedEvent	Invoked after a successfully-executed tool is compensated (rolled back) - for example when another tool in the same round failed, or when the invocation was cancelled.

Methods in dev.langchain4j.observability.api.event with annotations of type Experimental

Modifier and Type	Method	Description
List<Content>	ToolCompensatedEvent.resultContents()	Returns the contents of the compensated tool's original (successful) result.
ToolCompensatedEvent.ToolCompensatedEventBuilder	ToolCompensatedEvent.ToolCompensatedEventBuilder.resultContents(List<Content> resultContents)	Sets the compensated tool's result contents.
List<Content>	ToolExecutedEvent.resultContents()	Returns the contents of the tool execution result.
ToolExecutedEvent.ToolExecutedEventBuilder	ToolExecutedEvent.ToolExecutedEventBuilder.resultContents(List<Content> resultContents)	Sets the tool execution result contents.

Uses of Experimental in dev.langchain4j.observability.api.listener

Classes in dev.langchain4j.observability.api.listener with annotations of type Experimental

Modifier and Type	Interface	Description
interface	ToolCompensatedEventListener	A listener for ToolCompensatedEvent, which represents an event that occurs after a successfully-executed tool is compensated (rolled back) within an AI Service invocation.

Uses of Experimental in dev.langchain4j.observability.event

Classes in dev.langchain4j.observability.event with annotations of type Experimental

Modifier and Type	Class	Description
class	DefaultToolCompensatedEvent	Default implementation of ToolCompensatedEvent.

Methods in dev.langchain4j.observability.event with annotations of type Experimental

Modifier and Type	Method	Description
List<Content>	DefaultToolCompensatedEvent.resultContents()
List<Content>	DefaultToolExecutedEvent.resultContents()

Uses of Experimental in dev.langchain4j.observation.listener

Classes in dev.langchain4j.observation.listener with annotations of type Experimental

Modifier and Type	Class	Description
class	ObservationChatModelListener	Will use observations and micrometer metrics to generate telemetry based on the ChatModelListener lifecycle.

Uses of Experimental in dev.langchain4j.rag

Methods in dev.langchain4j.rag with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<AugmentationResult>	RetrievalAugmentor.augmentAsync(AugmentationRequest augmentationRequest)	Non-blocking counterpart of RetrievalAugmentor.augment(AugmentationRequest), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes so the RAG flow never blocks the calling thread.
DefaultRetrievalAugmentor.DefaultRetrievalAugmentorBuilder	DefaultRetrievalAugmentor.DefaultRetrievalAugmentorBuilder.offloadBlocking(boolean offloadBlocking)	Controls what DefaultRetrievalAugmentor.augmentAsync(AugmentationRequest) does when a pipeline stage (query transformation, routing, retrieval or aggregation) is not genuinely asynchronous (its *Async method is not implemented).

Constructors in dev.langchain4j.rag with annotations of type Experimental

Modifier	Constructor	Description
	DefaultRetrievalAugmentor(QueryTransformer queryTransformer, QueryRouter queryRouter, ContentAggregator contentAggregator, ContentInjector contentInjector, Executor executor, boolean offloadBlocking)

Uses of Experimental in dev.langchain4j.rag.content.aggregator

Methods in dev.langchain4j.rag.content.aggregator with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<List<Content>>	ContentAggregator.aggregateAsync(Map<Query, Collection<List<Content>>> queryToContents)	Non-blocking counterpart of ContentAggregator.aggregate(Map), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes when RAG is configured.

Uses of Experimental in dev.langchain4j.rag.content.retriever

Methods in dev.langchain4j.rag.content.retriever with annotations of type Experimental

Modifier and Type	Method	Description
default ContentRetriever	ContentRetriever.addListener(ContentRetrieverListener listener)	Wraps this ContentRetriever with a listening retriever that dispatches events to the provided listener.
default ContentRetriever	ContentRetriever.addListeners(Collection<ContentRetrieverListener> listeners)	Wraps this ContentRetriever with a listening retriever that dispatches events to the provided listeners.
EmbeddingStoreContentRetriever.EmbeddingStoreContentRetrieverBuilder	EmbeddingStoreContentRetriever.EmbeddingStoreContentRetrieverBuilder.offloadBlocking(boolean offloadBlocking)	Controls what EmbeddingStoreContentRetriever.retrieveAsync(Query) does when the EmbeddingModel or EmbeddingStore is not genuinely asynchronous (does not implement doEmbedAsync/searchAsync).
default CompletableFuture<List<Content>>	ContentRetriever.retrieveAsync(Query query)	Non-blocking counterpart of ContentRetriever.retrieve(Query), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes when RAG is configured.

Uses of Experimental in dev.langchain4j.rag.content.retriever.hibernate

Classes in dev.langchain4j.rag.content.retriever.hibernate with annotations of type Experimental

Modifier and Type	Class	Description
class	HibernateContentRetriever	Using the SessionFactory and the ChatModel, this ContentRetriever attempts to generate and execute Hibernate queries for given natural language queries.

Constructors in dev.langchain4j.rag.content.retriever.hibernate with annotations of type Experimental

Modifier	Constructor	Description
	HibernateContentRetriever(org.hibernate.SessionFactory sessionFactory, ChatModel chatModel, String databaseStructure, PromptTemplate promptTemplate, Integer maxRetries)	Creates an instance of a HibernateContentRetriever.

Uses of Experimental in dev.langchain4j.rag.content.retriever.listener

Classes in dev.langchain4j.rag.content.retriever.listener with annotations of type Experimental

Modifier and Type	Class	Description
class	ContentRetrieverErrorContext	The content retriever error context.
static class	ContentRetrieverErrorContext.Builder	Builder for ContentRetrieverErrorContext.
interface	ContentRetrieverListener	A ContentRetriever listener that listens for requests, responses and errors.
class	ContentRetrieverRequestContext	The content retriever request context.
static class	ContentRetrieverRequestContext.Builder	Builder for ContentRetrieverRequestContext.
class	ContentRetrieverResponseContext	The content retriever response context.
static class	ContentRetrieverResponseContext.Builder	Builder for ContentRetrieverResponseContext.

Uses of Experimental in dev.langchain4j.rag.query.router

Methods in dev.langchain4j.rag.query.router with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<Collection<ContentRetriever>>	QueryRouter.routeAsync(Query query)	Non-blocking counterpart of QueryRouter.route(Query), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes when RAG is configured.

Uses of Experimental in dev.langchain4j.rag.query.transformer

Methods in dev.langchain4j.rag.query.transformer with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<Collection<Query>>	QueryTransformer.transformAsync(Query query)	Non-blocking counterpart of QueryTransformer.transform(Query), invoked by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service modes when RAG is configured.

Uses of Experimental in dev.langchain4j.service

Classes in dev.langchain4j.service with annotations of type Experimental

Modifier and Type	Interface	Description
interface	AiServiceStreamingEvent	An event emitted by the reactive stream of a non-blocking streaming AI Service — that is, an AI Service method declared to return a Flow.Publisher of AiServiceStreamingEvent.

Methods in dev.langchain4j.service with annotations of type Experimental

Modifier and Type	Method	Description
default TokenStream	TokenStream.onPartialResponseWithContext(BiConsumer<PartialResponse, PartialResponseContext> handler)	The provided consumer will be invoked every time a new partial textual response (usually a single token) from a language model is available.
default TokenStream	TokenStream.onPartialThinking(Consumer<PartialThinking> partialThinkingHandler)	The provided consumer will be invoked every time a new partial thinking/reasoning text (usually a single token) from a language model is available.
default TokenStream	TokenStream.onPartialThinkingWithContext(BiConsumer<PartialThinking, PartialThinkingContext> handler)	The provided consumer will be invoked every time a new partial thinking/reasoning text (usually a single token) from a language model is available.
default TokenStream	TokenStream.onPartialToolCall(Consumer<PartialToolCall> partialToolCallHandler)	The provided consumer will be invoked every time a new partial tool call (usually containing a single token of the tool's arguments) from a language model is available.
default TokenStream	TokenStream.onPartialToolCallWithContext(BiConsumer<PartialToolCall, PartialToolCallContext> handler)	The provided consumer will be invoked every time a new partial tool call (usually containing a single token of the tool's arguments) from a language model is available.
default TokenStream	TokenStream.onUnmappedRawEvent(Consumer<Object> rawEventHandler)	The provided consumer will be invoked when a provider emits a raw streaming event that is not already exposed through one of the typed callbacks (such as TokenStream.onPartialResponse(Consumer), TokenStream.onPartialThinking(Consumer) or TokenStream.onToolExecuted(Consumer)).
AiServices<T>	AiServices.streamingBufferSize(int streamingBufferSize)	Sets the size of the bounded back-pressure buffer used by the reactive (Flow.Publisher) streaming path.

Uses of Experimental in dev.langchain4j.service.guardrail

Methods in dev.langchain4j.service.guardrail with annotations of type Experimental

Modifier and Type	Method	Description
default <MethodKey> CompletableFuture<UserMessage>	GuardrailService.executeGuardrailsAsync(MethodKey method, InputGuardrailRequest request)	Non-blocking counterpart of GuardrailService.executeGuardrails(Object, InputGuardrailRequest): runs the input guardrails without blocking the calling thread and yields the (possibly rewritten) UserMessage.
default <MethodKey, T> CompletableFuture<T>	GuardrailService.executeGuardrailsAsync(MethodKey method, OutputGuardrailRequest request)	Non-blocking counterpart of GuardrailService.executeGuardrails(Object, OutputGuardrailRequest) for the asynchronous (CompletableFuture) and reactive (Flow.Publisher) AI Service modes.
default <MethodKey> CompletableFuture<InputGuardrailResult>	GuardrailService.executeInputGuardrailsAsync(MethodKey method, InputGuardrailRequest request)	Non-blocking counterpart of GuardrailService.executeInputGuardrails(Object, InputGuardrailRequest).
default <MethodKey> CompletableFuture<OutputGuardrailResult>	GuardrailService.executeOutputGuardrailsAsync(MethodKey method, OutputGuardrailRequest request)	Non-blocking counterpart of GuardrailService.executeOutputGuardrails(Object, OutputGuardrailRequest).

Uses of Experimental in dev.langchain4j.service.tool

Classes in dev.langchain4j.service.tool with annotations of type Experimental

Modifier and Type	Class	Description
class	BeforeToolExecution

Methods in dev.langchain4j.service.tool with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<ToolExecutionResult>	ToolExecutor.executeAsync(ToolExecutionRequest request, InvocationContext context)	Non-blocking counterpart of ToolExecutor.executeWithContext(ToolExecutionRequest, InvocationContext), invoked by the asynchronous AI Service tool loop (AI Service methods returning CompletableFuture or CompletionStage), which composes the returned future instead of waiting on a thread.
List<Content>	ToolExecution.resultContents()	Returns the contents of the tool execution result.
ToolExecutionResult.Builder	ToolExecutionResult.Builder.resultContents(List<Content> resultContents)	Sets the contents of the tool execution result.
List<Content>	ToolExecutionResult.resultContents()	Returns the contents of the tool execution result that will be sent to the LLM.

Uses of Experimental in dev.langchain4j.service.tool.search

Classes in dev.langchain4j.service.tool.search with annotations of type Experimental

Modifier and Type	Class	Description
class	ToolSearchRequest	A request to search for tools.
class	ToolSearchResult	The result of a tool search.
interface	ToolSearchStrategy	Strategy for discovering tools dynamically by an LLM during an AI Service invocation.

Uses of Experimental in dev.langchain4j.service.tool.search.simple

Classes in dev.langchain4j.service.tool.search.simple with annotations of type Experimental

Modifier and Type	Class	Description
class	SimpleToolSearchStrategy	A ToolSearchStrategy that allows an LLM to search for available tools using simple case-insensitive contains matching.

Uses of Experimental in dev.langchain4j.service.tool.search.vector

Classes in dev.langchain4j.service.tool.search.vector with annotations of type Experimental

Modifier and Type	Class	Description
class	VectorToolSearchStrategy	A ToolSearchStrategy that uses vector similarity search to find relevant tools based on the semantic meaning of their names and descriptions.

Uses of Experimental in dev.langchain4j.skills

Classes in dev.langchain4j.skills with annotations of type Experimental

Modifier and Type	Class	Description
class	AbstractSkill
class	ActivateSkillToolConfig
class	ClassPathSkillLoader	Loads skills from the classpath (including cases when they are packaged inside a JAR file that is on the classpath).
class	DefaultFileSystemSkill
class	DefaultSkill
class	DefaultSkillResource
interface	FileSystemSkill	A Skill backed by the file system.
class	FileSystemSkillLoader	Loads skills from the file system.
class	ReadResourceToolConfig
interface	Skill	Represents a skill that can be used by an LLM.
interface	SkillResource	An additional resource associated with a Skill, such as a reference file, asset, or template that the LLM can read on demand.
class	Skills	Configures and exposes a set of Skills to an LLM.

Uses of Experimental in dev.langchain4j.skills.shell

Classes in dev.langchain4j.skills.shell with annotations of type Experimental

Modifier and Type	Class	Description
class	RunShellCommandToolConfig
class	ShellSkills	Configures and exposes a set of FileSystemSkills to an LLM using shell commands.

Uses of Experimental in dev.langchain4j.spi

Classes in dev.langchain4j.spi with annotations of type Experimental

Modifier and Type	Interface	Description
interface	ExecutorProvider	SPI for supplying the Executor that LangChain4j uses to offload blocking work and run its asynchronous continuations — concurrent tool execution, blocking RAG / retrieval and embedding-store calls, moderation, in-process embedding models, retry backoff scheduling, and similar.

Uses of Experimental in dev.langchain4j.store.embedding

Methods in dev.langchain4j.store.embedding with annotations of type Experimental

Modifier and Type	Method	Description
default EmbeddingStore<Embedded>	EmbeddingStore.addListener(EmbeddingStoreListener listener)	Wraps this EmbeddingStore with a listening store that dispatches events to the provided listener.
default EmbeddingStore<Embedded>	EmbeddingStore.addListeners(List<EmbeddingStoreListener> listeners)	Wraps this EmbeddingStore with a listening store that dispatches events to the provided listeners.
default CompletableFuture<EmbeddingSearchResult<Embedded>>	EmbeddingStore.searchAsync(EmbeddingSearchRequest request)	Non-blocking counterpart of EmbeddingStore.search(EmbeddingSearchRequest), used by the asynchronous and reactive RAG flow (see EmbeddingStoreContentRetriever.retrieveAsync).

Uses of Experimental in dev.langchain4j.store.embedding.filter.builder.sql

Classes in dev.langchain4j.store.embedding.filter.builder.sql with annotations of type Experimental

Modifier and Type	Class	Description
class	ColumnDefinition
class	LanguageModelSqlFilterBuilder	Given a natural language Query, this class creates a suitable Filter using a language model.
class	TableDefinition

Uses of Experimental in dev.langchain4j.store.embedding.filter.parser.sql

Classes in dev.langchain4j.store.embedding.filter.parser.sql with annotations of type Experimental

Modifier and Type	Class	Description
class	SqlFilterParser	Parses an SQL "WHERE" clause into a Filter object using JSqlParser.

Uses of Experimental in dev.langchain4j.store.embedding.listener

Classes in dev.langchain4j.store.embedding.listener with annotations of type Experimental

Modifier and Type	Class	Description
class	EmbeddingStoreErrorContext<Embedded>	The embedding store error context.
interface	EmbeddingStoreListener	A EmbeddingStore listener that listens for requests, responses and errors.
class	EmbeddingStoreRequestContext<Embedded>	The embedding store request context.
static final class	EmbeddingStoreRequestContext.Add<Embedded>	The add(...) request context.
static final class	EmbeddingStoreRequestContext.AddAll<Embedded>	The addAll(...) request context.
static final class	EmbeddingStoreRequestContext.Remove<Embedded>	The remove(String) request context.
static final class	EmbeddingStoreRequestContext.RemoveAll<Embedded>	The removeAll() request context.
static final class	EmbeddingStoreRequestContext.RemoveAllFilter<Embedded>	The removeAll(Filter) request context.
static final class	EmbeddingStoreRequestContext.RemoveAllIds<Embedded>	The removeAll(ids) request context.
static final class	EmbeddingStoreRequestContext.Search<Embedded>	The search(...) request context.
class	EmbeddingStoreResponseContext<Embedded>	The embedding store response context.
static final class	EmbeddingStoreResponseContext.Add<Embedded>	The add(...) response context.
static final class	EmbeddingStoreResponseContext.AddAll<Embedded>	The addAll(...) response context.
static final class	EmbeddingStoreResponseContext.Remove<Embedded>	The remove(String) response context.
static final class	EmbeddingStoreResponseContext.RemoveAll<Embedded>	The removeAll() response context.
static final class	EmbeddingStoreResponseContext.RemoveAllFilter<Embedded>	The removeAll(Filter) response context.
static final class	EmbeddingStoreResponseContext.RemoveAllIds<Embedded>	The removeAll(ids) response context.
static final class	EmbeddingStoreResponseContext.Search<Embedded>	The search(...) response context.

Uses of Experimental in dev.langchain4j.store.memory.chat

Methods in dev.langchain4j.store.memory.chat with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<Void>	ChatMemoryStore.deleteMessagesAsync(Object memoryId)	Non-blocking counterpart of ChatMemoryStore.deleteMessages(Object), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs.
default CompletableFuture<List<ChatMessage>>	ChatMemoryStore.getMessagesAsync(Object memoryId)	Non-blocking counterpart of ChatMemoryStore.getMessages(Object), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs.
default CompletableFuture<Void>	ChatMemoryStore.updateMessagesAsync(Object memoryId, List<ChatMessage> messages)	Non-blocking counterpart of ChatMemoryStore.updateMessages(Object, List), used by the asynchronous (CompletableFuture/CompletionStage) and reactive (Flow.Publisher) AI Service APIs.

Uses of Experimental in dev.langchain4j.web.search

Methods in dev.langchain4j.web.search with annotations of type Experimental

Modifier and Type	Method	Description
default CompletableFuture<WebSearchResults>	WebSearchEngine.searchAsync(WebSearchRequest webSearchRequest)	Non-blocking counterpart of WebSearchEngine.search(WebSearchRequest), used by the asynchronous and reactive RAG flow (see WebSearchContentRetriever).