Introduction
Welcome to the Ultimate AI-Powered Documentation Starter
VectraDocs
VectraDocs is a next-generation, open-source documentation starter kit designed to provide a premium, AI-native experience out of the box. Built on top of Next.js 15, Fumadocs, LangChain, and Orama, it combines a beautiful UI with powerful client-side RAG (Retrieval-Augmented Generation) search.
100% Open Source
All VectraDocs components are free and open source under the MIT license.
Why "VectraDocs"?
Traditional documentation sites are static. Users search for keywords and hope for matches. VectraDocs changes the game by embedding a context-aware AI Assistant directly into the reading experience.
Key Features
- 🧠 Context-Aware AI Chat: An intelligent assistant that reads your documentation and answers user questions instantly.
- ⚡ Client-Side RAG: Powered by Orama, search indexing happens at build time and runs incredibly fast in the browser or edge.
- 💬 Premium UI Experience:
- Floating Action Bar: A sleek, non-intrusive input bar that expands as you type.
- Rich Markdown Rendering: The chat supports code blocks, bold text, lists, and links.
- Code Copying: One-click copy for all code snippets generated by the AI.
- 🛠️ Easy Configuration: Precise control over the System Prompt, LLM Model (OpenAI, Ollama, Anthropic), and UI styling.
- 🚀 Next.js 15 & React 19: Built on the bleeding edge for maximum performance.
Ecosystem Overview
VectraDocs isn't just one tool — it's an ecosystem of components that work together.
| Component | Description | Links |
|---|---|---|
| VectraDocs (Next.js) | This full starter kit with AI built-in. | GitHub |
| vetradocs-vitepress | VitePress plugin for Vue-based docs. | npm · GitHub |
| vetradocs-docusaurus | Docusaurus plugin for React-based docs. | npm · GitHub |
| vetradocs-scalar | Web Component for Scalar or any HTML site. | npm · GitHub |
| create-vetradocs-backend | CLI to scaffold AI backends (Node.js/Express, Cloudflare Workers). | npm · GitHub |
Quick Links
- Installation Guide: Set up VectraDocs in your project.
- Backend Setup: Create a backend for the frontend plugins.
- VitePress Plugin: Add AI chat to VitePress.
- Docusaurus Plugin: Add AI chat to Docusaurus.
- Scalar / Web Component: Add AI chat to any website.
- AI Configuration: Customize prompts, models, and UI.
- Updates & Changelog: Version history and latest updates.
Architecture
VectraDocs uses a Retrieval-Augmented Generation (RAG) approach:
- Ingestion (
scripts/build-index.mjs): Scans your.mdxfiles at build time and creates a search index. - Storage: The index is saved as a JSON file in
public/search-index.json. - Retrieval (
app/api/chat/route.ts): When a user asks a question, the API loads the index, finds relevant docs, and feeds them to the LLM. - Generation: The LLM (via LangChain) generates a streaming response based only on your documentation.
This approach ensures the AI only answers based on YOUR content, reducing hallucinations.
Open Source
VectraDocs and all its plugins are MIT licensed and free to use.
| Repository | Stars |
|---|---|
| iotserver24/VectraDocs | ⭐ Main Project |
| iotserver24/VectraDocs-Backend | Backend CLI |
| iotserver24/vetradocs-vitepress | VitePress Plugin |
| iotserver24/VetraDocs-Docusaurus | Docusaurus Plugin |
| iotserver24/VetraDocs-Scalar | Web Component |
Contributions are welcome!
Next Steps
Ready to build? Check out the Installation Guide to get started.