manufacturing-graphrag
제조 추적성 인텔리전스 플랫폼
GraphRAG 기반 에이전트형 AI 플랫폼으로, Neo4j, Amazon Bedrock, MCP를 사용하여 제조 추적성을 제공합니다.
아키텍처
┌─────────────────────────────────────────────────────────────────────┐
│ INGESTION & ENRICHMENT LAYER │
│ Connectors → Chunking → Embeddings → Entity Extraction → │
│ Entity Resolution → Graph Construction │
└──────────────────────────┬──────────────────────────────────────────┘
│
┌──────────────────────────▼──────────────────────────────────────────┐
│ KNOWLEDGE GRAPH (Neo4j) │
│ Product → Requirement → Component → TestCase → TestRun → │
│ Defect → ChangeRequest │
└──────────────────────────┬──────────────────────────────────────────┘
│
┌──────────────────────────▼──────────────────────────────────────────┐
│ RETRIEVAL LAYER │
│ VectorRetriever │ GraphRAGRetriever │ NL2CypherRetriever │ Hybrid │
└──────────────────────────┬──────────────────────────────────────────┘
│
┌──────────────────────────▼──────────────────────────────────────────┐
│ AGENT LAYER │
│ LangGraph Agent (plan→retrieve→reason→validate→respond) │
│ Strands Agent (tool-calling with 5 specialized graph tools) │
└──────────────────────────┬──────────────────────────────────────────┘
│
┌──────────────────────────▼──────────────────────────────────────────┐
│ INTERFACE LAYER │
│ FastAPI REST │ MCP Server (Claude Desktop / Cursor compatible) │
└─────────────────────────────────────────────────────────────────────┘Related MCP server: Knowledge Graph MCP Server
빠른 시작
1. 사전 요구 사항
Neo4j 5.x (APOC 플러그인 포함)
Python 3.11+
Bedrock 액세스 권한이 있는 AWS 자격 증명 (Claude 3.5 Sonnet + Titan Embed v2)
2. 설정
cd manufacturing-graphrag
python -m venv .venv
.venv\Scripts\activate # Windows
pip install -r requirements.txt
python -m spacy download en_core_web_sm
copy .env.example .env # Edit with your credentials3. Neo4j 시작 (Docker)
docker-compose up neo4j -d4. 지식 그래프 시드
set PYTHONPATH=src
python scripts/seed_data.py5. 플랫폼 시작
# API server
python main.py api
# MCP server (for Claude Desktop)
python main.py mcp
# Both
python main.py all6. 문서 수집
python scripts/ingest.py path/to/spec.pdf path/to/requirements.csvAPI 엔드포인트
메서드 | 엔드포인트 | 설명 |
GET |
| 상태 확인 |
GET |
| 레이블별 노드 수 |
POST |
| 문서 업로드 및 수집 |
POST |
| 구조화된 API 레코드 수집 |
POST |
| 하이브리드 GraphRAG 쿼리 |
POST |
| LangGraph 추론 에이전트 |
POST |
| Strands 도구 호출 에이전트 |
GET |
| 전체 결함 추적성 체인 |
GET |
| 제품 추적성 요약 |
예제 쿼리
# Hybrid GraphRAG query
curl -X POST http://localhost:8000/query \
-H "Content-Type: application/json" \
-d '{"question": "What components are affected by the thermal runaway defect?"}'
# LangGraph agent — multi-step reasoning
curl -X POST http://localhost:8000/agent/langgraph \
-d '{"question": "Trace the full impact chain of DEF-001 and identify all change requests needed"}'
# Strands agent — tool-calling
curl -X POST http://localhost:8000/agent/strands \
-d '{"question": "Which critical defects are blocking the EV BMS release?"}'
# Defect traceability
curl http://localhost:8000/traceability/defect/DEF-002MCP 통합 (Claude Desktop)
config/claude_desktop_mcp.json의 내용을 Claude Desktop의 claude_desktop_config.json에 복사하세요.
사용 가능한 MCP 도구:
ask_manufacturing_ai— 하이브리드 GraphRAG Q&Asemantic_search— 벡터 유사도 검색graph_trace— 그래프 탐색 검색natural_language_to_cypher— NL2Cypherget_defect_chain— 전체 결함 추적성get_requirement_traceability— 요구 사항 커버리지product_health_dashboard— 제품 지표
지식 그래프 스키마
(Product)-[:HAS_REQUIREMENT]->(Requirement)
(Component)-[:IMPLEMENTS]->(Requirement)
(TestCase)-[:VALIDATES]->(Requirement)
(TestRun)-[:INSTANCE_OF]->(TestCase)
(TestRun)-[:FOUND_IN]->(Defect)
(Defect)-[:AFFECTS]->(Component)
(Defect)-[:TRIGGERS_CHANGE]->(ChangeRequest)
(ChangeRequest)-[:MODIFIES]->(Component)
(Document)-[:CONTAINS_CHUNK]->(Chunk)
(Chunk)-[:MENTIONS]->(any entity)테스트 실행
set PYTHONPATH=src
pytest tests/ -vThis server cannot be installed
Maintenance
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