VectorBase

Developer-friendly AI Knowledge Base SaaS

Build intelligent, context-aware AI assistants powered by your own data. VectorBase provides a complete RAG (Retrieval-Augmented Generation) infrastructure that integrates seamlessly with automation tools like n8n.

localhost_3000_dashboard_projects_f1444e0d-be21-4d84-b0ad-d07c0e49c698

localhost_3000_dashboard_projects_f1444e0d-be21-4d84-b0ad-d07c0e49c698 (1)

Overview

VectorBase is designed specifically for developers who need programmatic access to AI-powered knowledge bases. Upload documents, crawl websites, sync Notion pages, and query your knowledge base through a simple REST API.

Key Use Cases:

Build customer support chatbots with your documentation
Create internal knowledge assistants for your team
Power AI features in your applications via API
Integrate with n8n, Make, or Zapier for automation workflows

Features

Multiple Source Types - Import from documents (PDF, DOCX, TXT), plain text, Q&A pairs, websites, and Notion
Website Crawling - Automatic sitemap.xml discovery and JavaScript-rendered page support via Playwright
Notion Integration - Connect your Notion workspace and sync pages automatically
Vector Similarity Search - Fast semantic search powered by pgvector with cosine distance
RAG-Powered Chat - Context-aware AI responses with source citations
Streaming Responses - Real-time streaming for chat completions
Multi-Tenancy - Organizations, projects, and team member management
API-First Design - RESTful API with Bearer token authentication
Rate Limiting - Built-in rate limiting (60 requests/minute per project)
Auto-Retrain - Scheduled daily retraining for website and Notion sources
Usage Analytics - Track API usage, tokens consumed, and conversation history
Subscription Management - Stripe integration for billing (Free, Pro, Enterprise plans)

Quick Start

Requirements

Bun (v1.0 or higher)
PostgreSQL (v15+ with pgvector extension)
Supabase account (for auth and database)
OpenAI API key
Stripe account (optional, for billing)

Installation

# Clone the repository
git clone https://github.com/your-org/vectorbase.git
cd vectorbase

# Install dependencies
bun install

Environment Setup

Create a .env file in the project root:

# Database
DATABASE_URL=postgresql://user:password@host:5432/database?pgbouncer=true
DIRECT_URL=postgresql://user:password@host:5432/database

# Application
NEXT_PUBLIC_APP_NAME=VectorBase
NEXT_PUBLIC_APP_URL=http://localhost:3000
NEXT_PUBLIC_SELF_HOSTED=false

# Supabase
NEXT_PUBLIC_SUPABASE_URL=https://your-project.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-anon-key
SUPABASE_SERVICE_ROLE_KEY=your-service-role-key

# OpenAI
OPENAI_API_KEY=sk-your-openai-api-key

# Notion (optional)
NOTION_CLIENT_ID=your-notion-client-id
NOTION_CLIENT_SECRET=your-notion-client-secret
NOTION_REDIRECT_URI=http://localhost:3000/api/notion/callback

# Stripe (optional, for billing)
STRIPE_SECRET_KEY=sk_test_your-stripe-key
STRIPE_WEBHOOK_SECRET=whsec_your-webhook-secret

Database Setup

# Push schema to database
bun run db:push

# Or run migrations for production
bun run db:migrate

# Seed initial data (plans, etc.)
bun run db:seed

# Open Prisma Studio to view data
bun run db:studio

Running

# Development mode
bun run dev

# Production build
bun run build
bun run start

Open http://localhost:3000 to access the dashboard.

Self-Hosted vs Cloud

Feature	Self-Hosted	Cloud
Pricing	Free (your infrastructure)	Free tier + paid plans
Data Location	Your servers	Managed infrastructure
Setup	Manual configuration	Instant
Updates	Manual	Automatic
Support	Community	Priority support (Pro+)

Self-Hosted Configuration:

Set NEXT_PUBLIC_SELF_HOSTED=true in your environment to enable self-hosted mode. This disables Stripe billing integration and removes plan restrictions.

Cloud Plans:

Plan	Price	Projects	Documents	Messages/Month
Free	$0/mo	1	10	20
Starter	$19/mo	3	100 each	1,000
Pro	$49/mo	10	500 each	10,000
Enterprise	$199/mo	Unlimited	Unlimited	Unlimited

API Documentation

All API endpoints require authentication via Bearer token. Generate API keys from the project dashboard.

Authorization: Bearer vb_your-api-key

Rate Limiting

API requests are rate-limited to 60 requests per minute per project. Rate limit headers are included in responses:

X-RateLimit-Limit: 60
X-RateLimit-Remaining: 59
X-RateLimit-Reset: 1704067200

POST /api/v1/query

Perform vector similarity search across your knowledge base.

Request:

curl -X POST https://your-domain.com/api/v1/query \
  -H "Authorization: Bearer vb_your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How do I reset my password?",
    "top_k": 5,
    "threshold": 0.5
  }'

Parameters:

Parameter	Type	Default	Description
`query`	string	required	The search query (max 10,000 characters)
`top_k`	number	5	Number of results to return (max 20)
`threshold`	number	0.5	Minimum similarity score (0-1)

Response:

{
  "results": [
    {
      "id": "chunk-uuid",
      "content": "To reset your password, go to Settings > Security...",
      "metadata": {},
      "similarity": 0.87,
      "source_id": "source-uuid"
    }
  ],
  "query": "How do I reset my password?",
  "project_id": "project-uuid"
}

POST /api/v1/chat

RAG-powered chat with streaming support. The endpoint automatically retrieves relevant context from your knowledge base and augments the AI response.

Request:

curl -X POST https://your-domain.com/api/v1/chat \
  -H "Authorization: Bearer vb_your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [
      {"role": "user", "content": "What are the pricing plans?"}
    ],
    "session_id": "user-session-123",
    "stream": true,
    "model": "gpt-4o-mini",
    "temperature": 0.7,
    "max_tokens": 1000
  }'

Parameters:

Parameter	Type	Default	Description
`messages`	array	required	Array of message objects with `role` and `content`
`session_id`	string	optional	Session ID for conversation tracking
`stream`	boolean	true	Enable streaming response
`model`	string	gpt-4o-mini	OpenAI model to use
`temperature`	number	0.7	Response randomness (0-2)
`max_tokens`	number	1000	Maximum tokens in response

Streaming Response:

When stream: true, the response is a Server-Sent Events stream:

data: {"content": "The"}
data: {"content": " pricing"}
data: {"content": " plans"}
...

Non-Streaming Response:

{
  "message": "Based on the documentation, VectorBase offers three pricing plans...",
  "sources": [
    {
      "id": "chunk-uuid",
      "content": "VectorBase pricing: Free tier includes...",
      "similarity": 0.92
    }
  ]
}

GET /api/v1/sources

List all sources in your project.

Request:

curl -X GET "https://your-domain.com/api/v1/sources?status=completed&limit=10" \
  -H "Authorization: Bearer vb_your-api-key"

Query Parameters:

Parameter	Type	Default	Description
`status`	string	optional	Filter by status (pending, processing, completed, failed)
`type`	string	optional	Filter by type (text, qa, website, document, notion)
`limit`	number	50	Number of results (max 100)
`offset`	number	0	Pagination offset

Response:

{
  "sources": [
    {
      "id": "source-uuid",
      "name": "Product Documentation",
      "type": "website",
      "status": "completed",
      "chunks_count": 150,
      "tokens_count": 45000,
      "created_at": "2024-01-15T10:30:00.000Z",
      "updated_at": "2024-01-15T12:00:00.000Z"
    }
  ]
}

POST /api/v1/sources

Create a new source.

Text Source:

curl -X POST https://your-domain.com/api/v1/sources \
  -H "Authorization: Bearer vb_your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "text",
    "name": "Company FAQ",
    "content": "Your text content here..."
  }'

Q&A Source:

curl -X POST https://your-domain.com/api/v1/sources \
  -H "Authorization: Bearer vb_your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "qa",
    "question": "What is VectorBase?",
    "answer": "VectorBase is a developer-friendly AI knowledge base..."
  }'

Website Source:

curl -X POST https://your-domain.com/api/v1/sources \
  -H "Authorization: Bearer vb_your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "website",
    "name": "Documentation Site",
    "url": "https://docs.example.com"
  }'

Response:

{
  "source": {
    "id": "source-uuid",
    "name": "Company FAQ",
    "type": "text",
    "status": "pending"
  },
  "message": "Source created. Use /api/v1/sources/{id}/process to process it."
}

GET /api/v1/sources/{sourceId}

Get details of a specific source.

Response:

{
  "source": {
    "id": "source-uuid",
    "name": "Product Documentation",
    "type": "website",
    "status": "completed",
    "chunks_count": 150,
    "tokens_count": 45000,
    "error_message": null,
    "created_at": "2024-01-15T10:30:00.000Z",
    "updated_at": "2024-01-15T12:00:00.000Z"
  }
}

POST /api/v1/sources/{sourceId}

Process a pending source (chunk and embed content).

Response:

{
  "success": true,
  "chunks_created": 150,
  "tokens_count": 45000
}

DELETE /api/v1/sources/{sourceId}

Delete a source and all its associated chunks.

Response:

{
  "success": true,
  "message": "Source deleted"
}

Tech Stack

Category	Technology
Framework	Next.js 16 (App Router)
Language	TypeScript
Runtime	Bun
Database	PostgreSQL + pgvector
ORM	Prisma
Auth & DB Hosting	Supabase
AI/LLM	OpenAI (gpt-4o-mini, text-embedding-3-small)
RAG Framework	LangChain.js
Billing	Stripe
UI	Tailwind CSS + shadcn/ui
Web Scraping	Playwright (for JS-heavy sites)

Project Structure

vectorbase/
├── prisma/
│   ├── schema.prisma      # Database schema
│   └── seed.ts            # Database seed script
├── src/
│   ├── app/
│   │   ├── api/
│   │   │   ├── v1/        # Public API endpoints
│   │   │   │   ├── chat/
│   │   │   │   ├── query/
│   │   │   │   └── sources/
│   │   │   ├── cron/      # Scheduled jobs
│   │   │   ├── stripe/    # Billing webhooks
│   │   │   └── notion/    # Notion OAuth
│   │   ├── auth/          # Authentication pages
│   │   └── dashboard/     # Dashboard pages
│   ├── components/        # React components
│   │   ├── ui/            # shadcn/ui components
│   │   ├── dashboard/
│   │   ├── projects/
│   │   └── billing/
│   └── lib/
│       ├── api-auth.ts    # API key authentication
│       ├── embeddings.ts  # OpenAI embeddings
│       ├── chunking.ts    # Text chunking logic
│       ├── crawler.ts     # Website crawler
│       ├── prisma.ts      # Prisma client
│       ├── rate-limit.ts  # Rate limiting
│       ├── stripe.ts      # Stripe integration
│       └── supabase/      # Supabase clients
├── Dockerfile             # Production Docker image
└── package.json

Environment Variables

Variable	Required	Description
`DATABASE_URL`	Yes	PostgreSQL connection string (pooled)
`DIRECT_URL`	Yes	PostgreSQL direct connection string
`NEXT_PUBLIC_APP_NAME`	Yes	Application name displayed in UI
`NEXT_PUBLIC_APP_URL`	Yes	Public URL of the application
`NEXT_PUBLIC_SELF_HOSTED`	Yes	Enable self-hosted mode (true/false)
`NEXT_PUBLIC_SUPABASE_URL`	Yes	Supabase project URL
`NEXT_PUBLIC_SUPABASE_ANON_KEY`	Yes	Supabase anonymous key
`SUPABASE_SERVICE_ROLE_KEY`	Yes	Supabase service role key
`OPENAI_API_KEY`	Yes	OpenAI API key for embeddings and chat
`NOTION_CLIENT_ID`	No	Notion OAuth client ID
`NOTION_CLIENT_SECRET`	No	Notion OAuth client secret
`NOTION_REDIRECT_URI`	No	Notion OAuth redirect URI
`STRIPE_SECRET_KEY`	No	Stripe secret key for billing
`STRIPE_WEBHOOK_SECRET`	No	Stripe webhook signing secret
`CRON_SECRET`	No	Secret for authenticating cron job requests

Docker Deployment

Build the Image

docker build -t vectorbase .

Run the Container

docker run -p 3000:3000 \
  -e DATABASE_URL="postgresql://..." \
  -e DIRECT_URL="postgresql://..." \
  -e NEXT_PUBLIC_APP_NAME="VectorBase" \
  -e NEXT_PUBLIC_APP_URL="https://your-domain.com" \
  -e NEXT_PUBLIC_SELF_HOSTED="true" \
  -e NEXT_PUBLIC_SUPABASE_URL="https://..." \
  -e NEXT_PUBLIC_SUPABASE_ANON_KEY="..." \
  -e SUPABASE_SERVICE_ROLE_KEY="..." \
  -e OPENAI_API_KEY="sk-..." \
  vectorbase

Docker Compose Example

version: "3.8"
services:
  vectorbase:
    build: .
    ports:
      - "3000:3000"
    environment:
      - DATABASE_URL=${DATABASE_URL}
      - DIRECT_URL=${DIRECT_URL}
      - NEXT_PUBLIC_APP_NAME=VectorBase
      - NEXT_PUBLIC_APP_URL=http://localhost:3000
      - NEXT_PUBLIC_SELF_HOSTED=true
      - NEXT_PUBLIC_SUPABASE_URL=${SUPABASE_URL}
      - NEXT_PUBLIC_SUPABASE_ANON_KEY=${SUPABASE_ANON_KEY}
      - SUPABASE_SERVICE_ROLE_KEY=${SUPABASE_SERVICE_KEY}
      - OPENAI_API_KEY=${OPENAI_API_KEY}

Development Scripts

Command	Description
`bun install`	Install dependencies
`bun run dev`	Start development server
`bun run build`	Build for production
`bun run start`	Start production server
`bun run db:push`	Push schema changes to database
`bun run db:migrate`	Run database migrations
`bun run db:seed`	Seed database with initial data
`bun run db:studio`	Open Prisma Studio
`bun run lint`	Run ESLint

Contributing

Contributions are welcome! Please follow these steps:

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Please ensure your code:

Follows the existing code style
Includes appropriate tests
Updates documentation as needed

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

Documentation: docs.vectorbase.dev
Issues: GitHub Issues
Discord: Join our community

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
.github		.github
prisma		prisma
public		public
scripts		scripts
src		src
stuff		stuff
.dockerignore		.dockerignore
.env.example		.env.example
.gitignore		.gitignore
CONTRIBUTING.md		CONTRIBUTING.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
bun.lock		bun.lock
components.json		components.json
eslint.config.mjs		eslint.config.mjs
next.config.ts		next.config.ts
package.json		package.json
postcss.config.mjs		postcss.config.mjs
prisma.config.ts		prisma.config.ts
tsconfig.json		tsconfig.json
vercel.json		vercel.json

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VectorBase

Overview

Features

Quick Start

Requirements

Installation

Environment Setup

Database Setup

Running

Self-Hosted vs Cloud

API Documentation

Rate Limiting

POST /api/v1/query

POST /api/v1/chat

GET /api/v1/sources

POST /api/v1/sources

GET /api/v1/sources/{sourceId}

POST /api/v1/sources/{sourceId}

DELETE /api/v1/sources/{sourceId}

Tech Stack

Project Structure

Environment Variables

Docker Deployment

Build the Image

Run the Container

Docker Compose Example

Development Scripts

Contributing

License

Support

About

Uh oh!

Releases

Languages

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codextde/vectorbase-ai-knowledgebase

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VectorBase

Overview

Features

Quick Start

Requirements

Installation

Environment Setup

Database Setup

Running

Self-Hosted vs Cloud

API Documentation

Rate Limiting

POST /api/v1/query

POST /api/v1/chat

GET /api/v1/sources

POST /api/v1/sources

GET /api/v1/sources/{sourceId}

POST /api/v1/sources/{sourceId}

DELETE /api/v1/sources/{sourceId}

Tech Stack

Project Structure

Environment Variables

Docker Deployment

Build the Image

Run the Container

Docker Compose Example

Development Scripts

Contributing

License

Support

About

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License

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