All Classes and Interfaces
Class
Description
Base class for aggregation queries used to create aggregation queries for Redis.
Utility class for array conversions.
Abstract base class for all cache implementations.
Base class for all field types in RedisVL.
Base class for message history implementations.
Abstract base class for document rerankers.
Base class for internal storage handling in Redis.
Helper class for key-value pairs used during preprocessing and validation.
Abstract base class for text vectorizers.
Helper class to hold batch cache results.
Represents a cache hit from SemanticCache.
A single chat message exchanged between a user and an LLM.
Reranker that uses Cohere's Rerank API to rerank documents based on query relevance.
Constants used across RedisVL extensions.
Query to count documents matching a filter
Loads and runs ONNX cross-encoder models for document reranking.
Enumeration for distance aggregation methods.
Cache for storing and retrieving text embeddings.
Constants used within the extension classes.
Enumeration of field types supported by RedisVL.
Represents a filter for Redis search
Builder for geo filters
Geographic units for radius queries
Builder for numeric filters
Builder for timestamp filters
A query for running a filtered search with a filter expression (no vector search).
Builder for FilterQuery with defensive copying.
GeoField represents a geographic field in Redis.
Fluent builder for GeoField
Internal subclass of BaseStorage for the Redis hash data type.
HuggingFace Cross-Encoder reranker using real ONNX models.
Builder for creating HFCrossEncoderReranker instances.
Downloads and caches HuggingFace models locally for offline use.
Progress listener for download tracking.
HybridQuery combines text and vector search in Redis using aggregation.
Builder for creating HybridQuery instances with fluent API.
Represents the schema definition for a Redis search index.
Builder for IndexSchema
Inner class to hold index configuration
Storage type for documents in Redis
Internal subclass of BaseStorage for the Redis JSON data type.
LangChain4J-based vectorizer that can work with any LangChain4J EmbeddingModel.
Message History for storing and retrieving LLM conversation history.
Schema for message history index.
Mock vectorizer for testing purposes.
NumericField represents a numeric field in Redis.
Fluent builder for NumericField
Loads and runs ONNX models for generating embeddings.
Represents a prompt-response pair for batch operations.
Configuration for Redis connections.
Manages Redis connections and provides connection pooling.
Base exception for RedisVL operations
Enumeration of available reducer functions for Redis aggregation operations.
Result from a reranking operation containing reranked documents and optional scores.
Model representing a routing path with associated metadata and thresholds.
Custom builder to ensure references list is mutable.
Model representing a matched route with distance information.
Configuration for routing behavior.
Manages Redis search index operations.
Semantic cache for LLM responses using vector similarity.
Builder for SemanticCache.
Semantic Router for managing and querying route vectors.
Builder for SemanticRouter.
Customized index schema for SemanticRouter.
Vectorizer that uses Sentence Transformers models downloaded from HuggingFace.
Storage type for documents in Redis
TagField represents an exact-match field in Redis.
Fluent builder for TagField
TextField represents a full-text searchable field in Redis.
Fluent builder for TextField
Full-text search query
Escape punctuation within an input string.
Utility methods for RedisVL.
VectorField represents a vector field in Redis for similarity search.
Vector indexing algorithms
Distance metrics for vector similarity
Vector data types
Fluent builder for VectorField
Factory class for creating vectorizers with common providers.
Abstract base builder for all vectorizer builders.
Builder for Azure OpenAI embedding vectorizers.
Builder for custom LangChain4J embedding vectorizers.
Builder for HuggingFace embedding vectorizers.
Builder for local ONNX embedding vectorizers.
Builder for Ollama embedding vectorizers.
Builder for OpenAI embedding vectorizers.
Represents a vector similarity search query
Builder for VectorQuery
Vector range query for finding vectors within a distance threshold.
Builder for creating VectorRangeQuery instances.
Reranker that uses VoyageAI's Rerank API to rerank documents based on query relevance.