What it is
LobeHub is a work-and-lifestyle space for finding, building, and collaborating with AI agent teammates, treating agents as the unit of work. It offers an Agent Builder, Agent Groups, scheduled runs, Pages, Projects, Workspaces, and a white-box Personal Memory. It can be self-hosted via Vercel, Zeabur, Sealos, Alibaba Cloud, or Docker, and supports plugins to extend function calling.
Who it's for
- Developers and users who want a playground for managing multiple AI agents in one place
- Teams wanting shared agent workspaces with scheduling and project organization
- Self-hosters who want to deploy their own chatbot instance
- Plugin developers extending function calling capabilities
Requirements
Requirements
- An OpenAI API Key (OPENAI_API_KEY is required for the one-click deployment)
- Docker and Docker Compose for the Docker deployment path
- pnpm for local development installation (bun is used for the dev:spa script)
- A GitHub account for the Vercel one-click deploy
Setup
Create a storage folder
Create a folder for storage files and enter it.
fish$ mkdir lobehub-db && cd lobehub-dbInitialize the LobeHub infrastructure
Run the setup script to init the infrastructure.
fishbash <(curl -fsSL https://lobe.li/setup.sh)Start the service
Start the LobeHub service with Docker Compose.
fishdocker compose up -dLocal development
Clone the repo, install dependencies, and run the dev servers (full-stack, or SPA frontend only on port 9876).
fish$ git clone https://github.com/lobehub/lobehub.git $ cd lobehub $ pnpm install $ pnpm dev # Full-stack (Next.js + Vite SPA) $ bun run dev:spa # SPA frontend only (port 9876)
Examples
Docker self-hosting
fish$ mkdir lobehub-db && cd lobehub-db
bash <(curl -fsSL https://lobe.li/setup.sh)
docker compose up -dWhat it does: The three documented steps to deploy LobeHub on a private device with Docker.
Customize the model list
textOPENAI_MODEL_LIST=qwen-7b-chat,+glm-6b,-gpt-3.5-turboWhat it does: Uses + to add a model, - to hide a model, and model_name=display_name to rename; the value format follows the README's example.
Override the OpenAI base URL
textOPENAI_PROXY_URL=https://api.chatanywhere.cnWhat it does: Overrides the default OpenAI API base URL (https://api.openai.com/v1) when using a proxy; example value taken from the README.
Pros & cons
Pros
- Pro:Multiple deployment options: Vercel, Zeabur, Sealos, Alibaba Cloud, RepoCloud, and Docker
- Pro:Agent Groups, scheduling, and shared Workspaces support team-style multi-agent work
- Pro:White-box, editable Personal Memory gives users control over what agents remember
- Pro:Extensible via a plugin system with SDK, template, and gateway, plus a library of 10,000+ skills and MCP-compatible plugins
Cons
- Con:README states the project is under active development, so issues may be encountered
- Con:One-click deployment requires an OpenAI API key; obtaining one may involve third-party proxies that the project disclaims responsibility for
- Con:Vercel one-click deploys create a new project rather than a fork, causing constant 'updates available' prompts unless redeployed per the sync guide
Images
