Nano-RAG - Lightweight Edge RAG Framework
Build AI knowledge base apps in 5 minutes with Next.js + Cloudflare Workers
chat.tsx
const response = await fetch('/api/chat', {
method: 'POST',
body: JSON.stringify({
question: userMessage,
messages: history
})
});
// Streaming response with
// thinking steps & sourcesCore Features
Edge Deployment
Powered by Cloudflare Workers, global low latency, millisecond response
Intelligent Retrieval
LangGraph orchestrated multi-stage RAG pipeline, precise context matching
Serverless Storage
D1 database + vector search, no extra services, zero ops cost
Quality Assurance
Built-in hallucination detection, quality checks and auto-repair for reliable answers
Quick Start
terminal
# Clone the project
git clone https://github.com/yompc/nano-rag.gitcd nano-rag# Install dependencies
npm install# Configure environment
cp .dev.vars.example .dev.vars# Edit .dev.vars and add OPENAI_API_KEY# Initialize database and start
npx wrangler d1 execute nano-rag-db --local --file=./migrations/0001_init.sqlnpm run previewTech Stack
Next.js
Frontend Framework
Cloudflare Workers
Edge Runtime
D1 Database
SQLite Storage
LangGraph
AI Orchestration
OpenAI
LLM & Embedding
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