What is an AI project generator?

An AI project generator creates a runnable starter project from selected options. AI Project Generator generates downloadable Next.js/OpenAI starter projects for chatbots, RAG apps, PDF chat, document chat, and AI agents.

What does AI Project Creator generate?

It generates downloadable Next.js starter projects for OpenAI chatbot UIs, RAG chatbots that answer from uploaded PDFs and documents, and AI agents workflows built with the OpenAI Agents SDK.

Can AI Project Creator generate AI agents?

Yes. The AI Agents project type generates a Next.js/OpenAI starter with @openai/agents, a Prompt Analyzer Agent, a Research Agent, and a server-side /api/agents/chat workflow route.

Does AI Project Creator support Supabase for RAG embeddings?

Yes. RAG projects can use local temporary JSON storage or Supabase database storage with pgvector for document chunks and vector embeddings.

Which OpenAI embedding model does the RAG starter use?

The generated RAG project defaults to text-embedding-3-small for document and query embeddings.

Can the generated project run after download?

Yes. Unzip the project, add OPENAI_API_KEY to .env.local, install dependencies, and run the development server.

AI Project Generator

AI project creator for RAG, chatbot, and AI agents starters.

NextJSClerkSupabaseOpen AIAI Agents

Project type

RAG storage

Local temporary storageStores vectors in conversions/vector-embeddings/index.json.Supabase databaseStores chunks and embeddings in Supabase Postgres with pgvector.

Project name

Include Clerk AuthAdds ClerkProvider, proxy.ts middleware, signed-in UI gates, and protected API routes to the downloaded starter.

50 presets

Scroll down for more colors

Component colors

PagePanelUser bubbleAssistant bubbleTextAccent

Knowledge Assistant

Talk with PDFs and documents

RAG Chatbot

Upload PDFs or documents here, then ask grounded questions from the generated embeddings.

Can you summarize the customer escalation policy and suggest the next action?

Yes. I would first retrieve the relevant policy chunks, identify the escalation threshold, and draft a concise next action with a human approval checkpoint.

Step 1

Upload docs

Step 2

Embed chunks

Step 3

Retrieve context

Ask about your documents...

Generated project contents

app/page.jsapp/api/chat/route.jsapp/globals.cssproxy.ts@clerk/nextjsapp/api/upload/route.jslib/openai.jslib/embeddings.jslib/vector-store.jsscripts/ingest-documents.mjsconversions/documents/sample.mdconversions/vector-embeddings/.gitkeep