All Classes and Interfaces
Class
Description
AI Services is a high-level API of LangChain4j to interact with
ChatModel
and StreamingChatModel
.Parameters for creating an
AiServiceTokenStream
.Builder for
AiServiceTokenStreamParameters
.Represents a chain step that takes an input and produces an output.
Allow to access the
ChatMemory
of any AI service extending it.Provides instances of
ChatMemory
.Represent the result of classification.
DocumentLoader
implementation for loading documents using a ClassPathSource
Specialization of a
DocumentSource
that knows how to read from the classpath.A chain for conversing with a specified
ChatModel
while maintaining a memory of the conversation.A chain for conversing with a specified
ChatModel
based on the information retrieved by a specified ContentRetriever
.Splits the provided
Document
into characters and attempts to fit as many characters as possible
into a single TextSegment
, adhering to the limit set by maxSegmentSize
.Splits the provided
Document
into lines and attempts to fit as many lines as possible
into a single TextSegment
, adhering to the limit set by maxSegmentSize
.Splits the provided
Document
into paragraphs and attempts to fit as many paragraphs as possible
into a single TextSegment
, adhering to the limit set by maxSegmentSize
.Splits the provided
Document
into parts using the provided regex
and attempts to fit as many parts
as possible into a single TextSegment
, adhering to the limit set by maxSegmentSize
.Splits the provided
Document
into sentences and attempts to fit as many sentences as possible
into a single TextSegment
, adhering to the limit set by maxSegmentSize
.Splits the provided
Document
into words and attempts to fit as many words as possible
into a single TextSegment
, adhering to the limit set by maxSegmentSize
.A
TextClassifier
that uses an EmbeddingModel
and predefined examples to perform classification.Base class for hierarchical document splitters.
An
EmbeddingStore
that stores embeddings in memory.Utility class responsible for resolving variable names and values for prompt templates
by leveraging method parameters and their annotations.
The value of a method parameter annotated with @MemoryId will be used to find the memory belonging to that user/conversation.
This chat memory operates as a sliding window of
MessageWindowChatMemory.maxMessages
messages.When a method in the AI Service is annotated with @Moderate, each invocation of this method will call not only the LLM,
but also the moderation model (which must be provided during the construction of the AI Service) in parallel.
Thrown when content moderation fails, i.e., when content is flagged by the moderation model.
Represents the result of an AI Service invocation.
Represents a classification label with score.
Specifies either a complete system message (prompt) or a system message template to be used each time an AI service is invoked.
Classifies a given text based on a set of labels.
Represents a token stream from the model to which you can subscribe and receive updates
when a new partial response (usually a single token) is available,
when the model finishes streaming, or when an error occurs during streaming.
This chat memory operates as a sliding window of
TokenWindowChatMemory.maxTokens
tokens.Represents the execution of a tool, including the request and the result.
A low-level executor/handler of a
ToolExecutionRequest
.A tool provider.
Specifies either a complete user message or a user message template to be used each time an AI service is invoked.
The value of a method parameter annotated with @UserName will be injected into the field 'name' of a UserMessage.
When a parameter of a method in an AI Service is annotated with
@V
,
it becomes a prompt template variable.