graphaura

bring your memories back to life with graphaura. transform photos and docs into an ai-powered 3d knowledge graph of people, places, and moments to explore your memories and share insights.

repos

• graphaura: this monorepo with frontend and backend
• r2r: external service for ingestion, chunking, embeddings, and RAG

tech stack

• frontend: next.js, react, tailwind css, react-force-graph-3d
• backend: fastapi (python 3.13), structlog
• data: neo4j, postgresql + pgvector, redis
• ai: r2r for ingestion, NER, embeddings, and RAG

architecture

graph TB
  u[browser] --> fe[next.js frontend]
  fe -->|rest| be[fastapi backend]
  be -->|http| r2r[r2r service]
  be -->|bolt| neo[(neo4j)]
  be -->|asyncpg + pgvector| pg[(postgres)]
  be -->|redis| redis[(redis)]
  r2r -->|entities + embeddings| be

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data flow

flowchart LR
  files[files, photos, notes, pdfs] --> upload[/upload via ui or api/]
  upload --> r2ringest[r2r ingest + chunk + embed + extract]
  r2ringest --> Entities[Entities + Relationships]
  entities --> neo[(neo4j)]
  r2ringest --> embeds[embeddings]
  embeds --> pg[(postgres pgvector)]
  query[user query] --> api[search apis]
  api --> hybrid[hybrid search]
  hybrid --> docs[r2r document search]
  hybrid --> grph[graph traversal]
  grph --> fevis[3d graph ui]
  docs --> fevis
  neo --> api
  pg --> api

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monorepo layout

graphaura/
  backend/        fastapi app, services, and apis
  frontend/       next.js app with 3d graph visualization

key endpoints

• GET /health - service health
• GET /metrics - vector and graph counts
• POST /api/v1/documents/upload - upload and process document via r2r
• GET /api/v1/documents/{id} - document metadata
• POST /api/v1/documents/create-graph - build graph from documents
• POST /api/v1/graph/entities - create entity
• GET /api/v1/graph/entities/{id} - fetch entity and relationships
• POST /api/v1/search/hybrid - hybrid search across documents and graph