Crate graphrag_core 

GraphRAG Core

Portable core library for GraphRAG - works on both native and WASM platforms.

This is the foundational crate that provides:

• Knowledge graph construction and management
• Entity extraction and linking
• Vector embeddings and similarity search
• Graph algorithms (PageRank, community detection)
• Retrieval systems (semantic, keyword, hybrid)
• Caching and optimization

Platform Support

• Native: Full feature set with optional CUDA/Metal GPU acceleration
• WASM: Browser-compatible with Voy vector search and Candle embeddings

Feature Flags

• wasm: Enable WASM compatibility (uses Voy instead of HNSW)
• cuda: Enable NVIDIA GPU acceleration via Candle
• metal: Enable Apple Silicon GPU acceleration
• webgpu: Enable WebGPU acceleration for browser (via Burn)
• pagerank: Enable PageRank-based retrieval
• lightrag: Enable LightRAG optimizations (6000x token reduction)
• caching: Enable intelligent LLM response caching

Quick Start

use graphrag_core::{GraphRAG, Config};

let config = Config::default();
let mut graphrag = GraphRAG::new(config)?;
graphrag.initialize()?;

Re-exports

pub use crate::config::Config;

pub use crate::core::ChunkId;

pub use crate::core::Document;

pub use crate::core::DocumentId;

pub use crate::core::Entity;

pub use crate::core::EntityId;

pub use crate::core::EntityMention;

pub use crate::core::ErrorContext;

pub use crate::core::ErrorSeverity;

pub use crate::core::GraphRAGError;

pub use crate::core::KnowledgeGraph;

pub use crate::core::Relationship;

pub use crate::core::Result;

pub use crate::core::TextChunk;

pub use crate::core::traits::Embedder;

pub use crate::core::traits::EntityExtractor;

pub use crate::core::traits::GraphStore;

pub use crate::core::traits::LanguageModel;

pub use crate::core::traits::Retriever;

pub use crate::core::traits::Storage;

pub use crate::core::traits::VectorStore;

pub use crate::storage::MemoryStorage;

Modules

async_graphrag

Async GraphRAG implementation Async GraphRAG System

async_processing

Async processing pipelines Async processing utilities for GraphRAG operations

builder

Builder pattern implementations GraphRAG builder module

config

Configuration management and loading

core

Core traits and types Core data structures and abstractions for GraphRAG

embeddings

Embedding generation and providers Embedding generation for GraphRAG

entity

Entity extraction and management

evaluation

Evaluation framework for query results and pipeline validation Evaluation framework for GraphRAG system

generation

Text generation and LLM interactions (async feature only)

graph

Graph data structures and algorithms

inference

Inference module for model predictions Implicit relationship inference system

monitoring

Monitoring, benchmarking, and performance tracking Monitoring and benchmarking utilities for GraphRAG

nlp

Natural language processing utilities Advanced NLP Module

ollama

Ollama LLM integration Ollama LLM integration

parallel

Parallel processing utilities for GraphRAG

persistence

Persistence layer for knowledge graphs (workspace management always available) Persistence layer for GraphRAG knowledge graphs

pipeline

Data processing pipelines Pipeline Module

prelude

Prelude module containing the most commonly used types

query

Query processing and execution

reranking

Reranking utilities for improving search result quality Reranking module for improving retrieval accuracy

retrieval

Retrieval strategies and implementations

storage

Storage backends and persistence Storage layer for GraphRAG

summarization

Text summarization capabilities

text

Text processing and chunking

vector

Vector operations and embeddings

Macros

config_error

Helper macros for creating specific error types

generation_error

Creates a generation error with a message

retrieval_error

Creates a retrieval error with a message

storage_error

Creates a storage error with a message

Structs

GraphRAG

Main GraphRAG system