[opensourcedex]

LobeChat is a free, open source ai interaction & interfaces project written in TypeScript and released under a custom open-source licence. It has 82,547 GitHub stars, 15,891 forks and 922 open issues, and was last pushed 6 hours ago. On this registry it ranks #4 of 76 tracked projects in AI Interaction & Interfaces, with 5 head-to-head comparisons available. It gained 112 stars over the last 6 tracked days.

LobeChat — Manage, build, and run AI agent teams around the clock

What is LobeChat?

What it is

LobeHub is an open-source platform for managing, building, and operating AI agent teams. It functions as a Chief Agent Operator (CAO), enabling users to organize, schedule, and monitor autonomous AI agents around the clock. The project lives in the AI interaction and interfaces ecosystem, integrating with major LLM providers like OpenAI, Anthropic, DeepSeek, and Alibaba’s GLM series.

It solves the problem of fragmented, manual agent orchestration by providing a unified interface to deploy, coordinate, and report on multi-agent workflows. Instead of managing agents individually through disparate APIs or scripts, users can define agent roles, assign tasks, and observe team-level behavior in a single dashboard.

Key capabilities

  • Agent role definition and task assignment with built-in collaboration patterns
  • 7×24 automated scheduling and execution of agent workflows
  • Real-time monitoring and reporting on agent performance and outputs
  • Plugin system for extending agent behavior and tool integrations
  • Multi-model support via configurable provider backends (OpenAI, Claude, Gemini, DeepSeek, GLM)
  • Self-hosted deployment options with Docker or cloud platforms (Vercel, Zeabur, Sealos)
  • Local development support with TypeScript and Vite-based tooling

Who uses it and how

  • AI product teams deploy LobeHub to prototype and run multi-agent workflows for customer support or content generation
  • Developers use it to test agent collaboration patterns before integrating into production systems
  • Researchers run controlled experiments with agent teams using reproducible configuration files
  • Self-hosters operate it as an internal AI operations layer, replacing manual orchestration scripts

Getting started

Deploy via Docker using lobehub/lobehub image, or one-click deploy to Vercel, Zeabur, or Sealos. Local development uses npm install && npm run dev. Environment variables configure API keys and backend services.

When to use it — and when not to

Use LobeHub when you need open, transparent agent orchestration with full control over data and models, especially for teams avoiding vendor lock-in. Avoid it if you require fully managed SLAs, built-in compliance certifications, or prefer a hosted-only solution without infrastructure overhead. Self-hosting requires managing a database, storage, and optionally SMTP for notifications. It trades convenience for flexibility, mirroring open-source alternatives to commercial CAO tools.

project readme (upstream, from github) — read inline

[![][image-banner]][vercel-link]

LobeHub

LobeHub organizes your agents into 7×24 operation.

It hires, schedules, reports on your entire AI team.

You stay in charge — without staying online.

English · 简体中文 · [Official Site][official-site] · [Changelog][changelog] · [Documents][docs] · [Blog][blog] · [Feedback][github-issues-link]

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Your Chief Agent Operator

LobeHub - Your Chief Agent Operator for multi-agent work | Product Hunt lobehub%2Flobehub | Trendshift

Table of contents
TOC


👋🏻 Getting Started & Join Our Community

We are a group of e/acc design-engineers, hoping to provide modern design components and tools for AIGC. By adopting the Bootstrapping approach, we aim to provide developers and users with a more open, transparent, and user-friendly product ecosystem.

Whether for users or professional developers, LobeHub will be your AI Agent playground. Please be aware that LobeHub is currently under active development, and feedback is welcome for any [issues][issues-link] encountered.

We are live on Product Hunt! We are thrilled to bring LobeHub to the world. If you believe in a future where humans and agents co-evolve, please support our journey.
[![][discord-shield-badge]][discord-link] Join our Discord community! This is where you can connect with developers and other enthusiastic users of LobeHub.

[!IMPORTANT]

Star Us, You will receive all release notifications from GitHub without any delay ~ ⭐️

[![][image-star]][github-stars-link]

Star History

✨ Features

Today’s agents are one-off, task-driven tools. They lack context, live in isolation, and require manual hand-offs between different windows and models. While some maintain memory, it is often global, shallow, and impersonal. In this mode, users are forced to toggle between fragmented conversations, making it difficult to form structured productivity.

LobeHub changes everything.

LobeHub is a work-and-lifestyle space to find, build, and collaborate with agent teammates that grow with you. In LobeHub, we treat Agents as the unit of work, providing an infrastructure where humans and agents co-evolve.

Operator: Agents as the Unit of Work

Hires, schedules, and reports on your entire AI team.

  • More productivity. Fewer tools: Bring all your agents under one roof.
  • IM Gateway: Agents where you already chat.

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Create: Agents as the Unit of Work

Building a personalized AI team starts with the Agent Builder. You can describe what you need once, and the agent setup starts right away, applying auto-configurations so you can use it instantly.

  • Unified Intelligence: Seamlessly access any model and any modality—all under your control.
  • 10,000+ Skills: Connect your agents to the skills you use every day with a library of over 10,000 tools and MCP-compatible plugins.

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Collaborate: Scale New Forms of Collaboration Networks

LobeHub introduces Agent Groups, allowing you to work with agents like real teammates. The system assembles the right agents for the task, enabling parallel collaboration and iterative improvement.

  • Pages: Write and refine content with multiple agents in one place with a shared context.
  • Schedule: Schedule runs and let agents do the work at the right time, even while you are away.
  • Project: Organize work by project to keep everything structured and easy to track.
  • Workspace: A shared space for teams to collaborate with agents, ensuring clear ownership and visibility across the organization.

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Evolve: Co-evolution of Humans and Agents

The best AI is one that understands you deeply. LobeHub features Personal Memory that builds a clear understanding of your needs.

  • Continual Learning: Your agents learn from how you work, adapting their behavior to act at the right moment.
  • White-Box Memory: We believe in transparency. Your a

readme truncated — read the full docs on github

Frequently asked questions

Is LobeChat free to use?

LobeChat is open source. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does LobeChat do?

Manage, build, and run AI agent teams around the clock

What is LobeChat written in?

LobeChat is primarily written in TypeScript. Its source is publicly available at https://github.com/lobehub/lobehub, and it has 82,547 GitHub stars.