🧠 KnowledgeBase Assistant: Full-Stack AI App with Cloudflare

A hands-on workshop on building a Retrieval-Augmented Generation (RAG) application using Cloudflare Workers, Vectorize, D1, Workflows and Workers AI.

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In this workshop, you’ll build a KnowledgeBase Assistant — a RAG-powered AI app that lets users upload content, ask questions about it, and receive context-aware answers grounded in their own documents.

In this hands-on project, you will:

• Create and deploy a Cloudflare Worker
• Add AI capabilities with Workers AI and AI Gateway
• Embed and search documents using Vectorize
• Store and retrieve metadata using D1
• Use Cloudflare Workflows to handle document processing and embedding
• Build a working Retrieval-Augmented Generation (RAG) app from scratch

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🛠️ Prerequisites

• A free Cloudflare account
• Node.js (v18+) and npm installed
• Basic familiarity with JavaScript
• Wrangler CLI installed:

npm install -g wrangler

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🏗️ Project Setup

Clone the repo and install dependencies:

git clone https://github.com/lauragift21/cf-fullstack-ai-workshop.git
cd cf-fullstack-ai-workshop
npm install

🚀 Running Locally

Start the dev server:

wrangler dev

📦 Deployment

Deploy to Cloudflare:

wrangler deploy

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📦 Workshop Contents

• 🧱 Part 1: Cloudflare Workers Basics
• 🔗 Part 2: Integrating Hono Framework
• 🧠 Part 3: Add AI Capabilities
• 📄 Part 4: Uploading Documents & Automating with Workflows
• 💬 Part 5: Build the RAG Chat Endpoint
• 🚀 Part 6: Extra Enhancements

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💡 Extra Credit

• Add Workers KV to cache responses
• Integrate external models (Anthropic/OpenAI)
• Deploy to a production domain

🧭 Resources

• Cloudflare AI Docs
• Vectorize
• Wrangler CLI
• Cloudflare D1
• Cloudflare Workflows