README
¶
GoRAG is a production-ready Retrieval-Augmented Generation (RAG) framework built for high-scale AI engineering. It features a three-layer architecture that serves developers at all skill levels.
🏗️ Three-Layer Architecture
graph TB
subgraph Pattern层["Pattern Layer (Application)"]
P1["NativeRAG<br/>Vector Retrieval"]
P2["GraphRAG<br/>Knowledge Graph"]
end
subgraph Pipeline层["Pipeline Layer (Assembly)"]
I["Indexer"]
R["Retriever"]
D["Repository"]
end
subgraph Step层["Step Layer (Function)"]
S1["Independent Modules<br/>Rewrite/Chunk/Embed..."]
end
Pattern层 --> Pipeline层
Pipeline层 --> Step层
| Layer | Who Uses | Responsibility |
|---|---|---|
| Pattern | Application Developers | Choose RAG mode, configure Options |
| Pipeline | Advanced Developers | Assemble Indexer/Retriever/Repository |
| Step | Framework Developers | Extend independent modules |
✨ Key Features
- 🚀 Performance First: Concurrent workers and streaming parsers with
O(1)memory efficiency - 🏗️ Pipeline-Based Architecture: Every step is explicit, traceable, and pluggable
- 🧠 Three-Phase Enhancement: Query enhancement → Retrieval → Result enhancement
- 🕸️ Advanced GraphRAG: Native support for Neo4j, SQLite, and BoltDB
- 🔭 Built-in Observability: Comprehensive distributed tracing
- 📦 Zero Dependencies: Pure Go implementation with auto-download models
🚀 Quick Start
NativeRAG (Vector Retrieval)
Best for document QA and semantic search:
import "github.com/DotNetAge/gorag/pkg/pattern"
// Create a NativeRAG with auto-configuration
rag, _ := pattern.NativeRAG("my-app",
pattern.WithBGE("bge-small-zh-v1.5"),
)
// Index documents
rag.IndexDirectory(ctx, "./docs", true)
// Retrieve
results, _ := rag.Retrieve(ctx, []string{"What is GoRAG?"}, 5)
GraphRAG (Knowledge Graph)
Best for complex relationship reasoning:
rag, _ := pattern.GraphRAG("knowledge-graph",
pattern.WithBGE("bge-small-zh-v1.5"),
pattern.WithNeoGraph("neo4j://localhost:7687", "neo4j", "password", "neo4j"),
)
// Add nodes and edges
rag.AddNode(ctx, &core.Node{ID: "person-1", Type: "Person", ...})
rag.AddEdge(ctx, &core.Edge{Source: "person-1", Target: "company-1", ...})
// Query neighbors
neighbors, edges, _ := rag.GetNeighbors(ctx, "person-1", 1, 10)
📚 Documentation
Getting Started
- Quick Start Guide - Pattern layer in 15 minutes
- NativeRAG Details - Three-phase enhancement
- GraphRAG Details - Knowledge graph reasoning
- Options Reference - All configuration options
Advanced Topics
- Development Guide - Pipeline layer development
- Indexer Development - Build custom indexers
- Retriever Development - Build custom retrievers
Step Layer
- Step Development Guide - Create new steps
🔭 Built-in Observability
idx, _ := indexer.DefaultAdvancedIndexer(
indexer.WithZapLogger("./logs/rag.log", 100, 30, 7, true),
indexer.WithPrometheusMetrics(":8080"),
indexer.WithOpenTelemetryTracer(ctx, "jaeger:4317", "RAG"),
)
⚡ Technical Standards
- Go 1.24+: Latest language features
- Zero-CGO SQLite: Painless cross-compilation
- Clean Architecture: Strict separation of interfaces and implementations
- Modular Steps: Reuse steps in any custom pipeline
🤝 Contributing
We aim to build the most robust AI infrastructure for the Go ecosystem.
- Check our Contributing Guidelines
📄 License
GoRAG is licensed under the MIT License.
Directories
¶
| Path | Synopsis |
|---|---|
|
cmd
|
|
|
gorag
command
|
|
|
examples
|
|
|
quickstart
command
|
|
|
pkg
|
|
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core
Package core defines the fundamental entities, interfaces, and types for the goRAG framework.
|
Package core defines the fundamental entities, interfaces, and types for the goRAG framework. |
|
core/env
Package env provides environment configuration and management for the GoRAG runtime.
|
Package env provides environment configuration and management for the GoRAG runtime. |
|
di
Package di provides a lightweight dependency injection container for managing component lifecycle.
|
Package di provides a lightweight dependency injection container for managing component lifecycle. |
|
indexer
Package indexer provides high-level indexers for building RAG pipelines.
|
Package indexer provides high-level indexers for building RAG pipelines. |
|
indexing
Package indexing provides the core indexing pipeline for offline data preparation.
|
Package indexing provides the core indexing pipeline for offline data preparation. |
|
indexing/community
Package community provides community detection algorithms for GraphRAG.
|
Package community provides community detection algorithms for GraphRAG. |
|
logging
Package logging provides structured logging capabilities for the goRAG framework.
|
Package logging provides structured logging capabilities for the goRAG framework. |
|
observability
Package observability provides metrics collection and distributed tracing capabilities.
|
Package observability provides metrics collection and distributed tracing capabilities. |
|
retrieval/answer
Package answer provides answer generation utilities for RAG systems.
|
Package answer provides answer generation utilities for RAG systems. |
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retrieval/enhancement
Package enhancement provides query and document enhancement utilities for RAG systems.
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Package enhancement provides query and document enhancement utilities for RAG systems. |
|
retrieval/fusion
Package fusion provides result fusion strategies for combining multiple retrieval results.
|
Package fusion provides result fusion strategies for combining multiple retrieval results. |
|
retrieval/graph
Package graph provides graph-related utilities for RAG systems.
|
Package graph provides graph-related utilities for RAG systems. |
|
retrieval/query
Package query provides query processing components for the RAG system.
|
Package query provides query processing components for the RAG system. |
|
retriever/graph
Package graph provides GraphRAG retrieval implementation following Microsoft GraphRAG architecture.
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Package graph provides GraphRAG retrieval implementation following Microsoft GraphRAG architecture. |
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steps/crag
Package crag provides evaluation steps for RAG retrieval quality assessment.
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Package crag provides evaluation steps for RAG retrieval quality assessment. |
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steps/decompose
Package decompose provides query decomposition steps for RAG retrieval pipelines.
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Package decompose provides query decomposition steps for RAG retrieval pipelines. |
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steps/filter
Package filter provides query preprocessing steps for RAG pipelines.
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Package filter provides query preprocessing steps for RAG pipelines. |
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steps/fuse
Package fuse provides result fusion steps for RAG retrieval pipelines.
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Package fuse provides result fusion steps for RAG retrieval pipelines. |
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steps/generate
Package generate provides answer generation steps for RAG pipelines.
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Package generate provides answer generation steps for RAG pipelines. |
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steps/graph
Package graph provides GraphRAG retrieval steps following Microsoft GraphRAG architecture.
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Package graph provides GraphRAG retrieval steps following Microsoft GraphRAG architecture. |
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steps/image
Package image provides image retrieval steps for multimodal RAG pipelines.
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Package image provides image retrieval steps for multimodal RAG pipelines. |
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steps/indexing
Package indexing provides document indexing pipeline steps for RAG data preparation.
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Package indexing provides document indexing pipeline steps for RAG data preparation. |
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steps/rerank
Package rerank provides reranking steps for RAG retrieval pipelines.
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Package rerank provides reranking steps for RAG retrieval pipelines. |
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steps/rewrite
Package rewrite provides query rewriting steps for RAG retrieval pipelines.
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Package rewrite provides query rewriting steps for RAG retrieval pipelines. |
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steps/sparse
Package sparse provides sparse retrieval steps using BM25 algorithm.
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Package sparse provides sparse retrieval steps using BM25 algorithm. |
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steps/stepback
Package stepback provides query abstraction steps for RAG pipelines.
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Package stepback provides query abstraction steps for RAG pipelines. |
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