Module hybrid 

Vector-Graph Hybrid Query System

Combines vector similarity search with graph traversal for AI workloads. Supports semantic search, RAG (Retrieval Augmented Generation), and GNN inference.

Re-exports

pub use cypher_extensions::SimilarityPredicate;

pub use cypher_extensions::VectorCypherExecutor;

pub use cypher_extensions::VectorCypherParser;

pub use graph_neural::GnnConfig;

pub use graph_neural::GraphEmbedding;

pub use graph_neural::GraphNeuralEngine;

pub use graph_neural::LinkPrediction;

pub use graph_neural::NodeClassification;

pub use rag_integration::Context;

pub use rag_integration::Evidence;

pub use rag_integration::RagConfig;

pub use rag_integration::RagEngine;

pub use rag_integration::ReasoningPath;

pub use semantic_search::ClusterResult;

pub use semantic_search::SemanticPath;

pub use semantic_search::SemanticSearch;

pub use semantic_search::SemanticSearchConfig;

pub use vector_index::EmbeddingConfig;

pub use vector_index::HybridIndex;

pub use vector_index::VectorIndexType;

Modules

cypher_extensions

Cypher query extensions for vector similarity

graph_neural

Graph Neural Network inference capabilities

rag_integration

RAG (Retrieval Augmented Generation) integration

semantic_search

Semantic search capabilities for graph queries

vector_index

Vector indexing for graph elements

Structs

HybridQuery

Hybrid query combining graph patterns and vector similarity

HybridResult

Result from a hybrid query

VectorConstraint

Vector similarity constraint for hybrid queries