Crate oxirs_graphrag 

OxiRS GraphRAG

Status: Production Release (v0.1.0)

GraphRAG (Graph Retrieval-Augmented Generation) combines vector similarity search with graph topology traversal for enhanced knowledge retrieval.

Architecture

Query → Embed → Vector KNN + Keyword Search → Fusion → Graph Expansion → LLM Answer

Key Features

• Hybrid Retrieval: Vector similarity + BM25 keyword search
• Graph Expansion: SPARQL-based N-hop neighbor traversal
• Community Detection: Louvain algorithm for hierarchical summarization
• Context Building: Intelligent subgraph extraction for LLM context

Example

use oxirs_graphrag::{GraphRAGEngine, GraphRAGConfig};

let engine = GraphRAGEngine::new(config).await?;
let result = engine.query("What safety issues affect battery cells?").await?;
println!("Answer: {}", result.answer);

Re-exports

pub use cache::query_cache::CacheEntry;

pub use cache::query_cache::CacheStats;

pub use cache::query_cache::QueryCache;

pub use cache::query_cache::QueryCacheConfig;

pub use config::CacheConfiguration;

pub use config::GraphRAGConfig;

pub use embeddings::node2vec::Node2VecConfig;

pub use embeddings::node2vec::Node2VecEmbedder;

pub use embeddings::node2vec::Node2VecEmbeddings;

pub use embeddings::node2vec::Node2VecWalkConfig;

pub use graph::community::CommunityAlgorithm;

pub use graph::community::CommunityConfig;

pub use graph::community::CommunityDetector;

pub use graph::embeddings::CommunityAwareEmbeddings;

pub use graph::embeddings::CommunityStructure;

pub use graph::embeddings::EmbeddingConfig;

pub use graph::traversal::GraphTraversal;

pub use query::planner::QueryPlanner;

pub use retrieval::fusion::FusionStrategy;

Modules

cache

Cache module for GraphRAG query results

community_detector

Graph community detection using a greedy label-propagation approach.

config

GraphRAG configuration

context_builder

Context building for graph-based RAG.

distributed

Distributed GraphRAG: federated subgraph expansion across multiple SPARQL endpoints.

embeddings

Graph embedding algorithms for GraphRAG.

entity_classifier

Entity type classification for knowledge graph nodes.

entity_linker

String-to-RDF entity linking: mention detection and candidate ranking.

entity_linking

Entity linking and disambiguation for knowledge graphs.

federation

Federation layer for distributed GraphRAG queries.

fusion

Fusion and reranking module for GraphRAG

generation

Answer generation module

graph

Graph processing module

graph_embedder

Graph Embedder

graph_partitioner

Graph partitioning using greedy and label-propagation methods.

graph_summarization

Graph Summarization for GraphRAG

knowledge_fusion

Multi-source knowledge fusion.

path_finder

Path Finder for Graph-RAG

path_ranker

Knowledge Graph Path Ranker

query

Query processing module

reasoning

Reasoning module for GraphRAG

retrieval

Retrieval module for GraphRAG

sparql

SPARQL extension functions for GraphRAG

streaming

Streaming subgraph extraction using SPARQL-like patterns.

summarizer

Knowledge Graph Subgraph Summarizer

temporal

Temporal reasoning and time-aware retrieval for GraphRAG

transe_model

TransE Knowledge Graph Embedding Model

triple_extractor

Triple Extractor

Structs

CacheConfig

Cache configuration

CommunitySummary

Community summary for hierarchical retrieval

GraphRAGEngine

Main GraphRAG engine

GraphRAGResult2

GraphRAG query result

QueryProvenance

Query provenance for attribution

ScoredEntity

Entity with relevance score

Triple

Triple representation for RDF data

Enums

GraphRAGError

GraphRAG error types

ScoreSource

Source of entity score

Traits

EmbeddingModelTrait

Trait for embedding model operations

LlmClientTrait

Trait for LLM client operations

SparqlEngineTrait

Trait for SPARQL engine operations

VectorIndexTrait

Trait for vector index operations

Type Aliases

GraphRAGResult