GGitHub采集材料
Open Duet自托管AI协作团队
发布时间未知 · 北京时间
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查看原文 Open Duet自托管AI协作团队
Anil-matcha星标6,258采集时的累计值
每小时增长待观察星标 / 小时 · 观测区间平均值
最近提交10-28 14:26提交时间不是项目发布时间
发布时间:未知 · 首次发现 10-28 14:30 · 北京时间
指标采集:10-28 14:30 · 指标已取得
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摘要
Open Duet可创建带有指令、记忆和工作区的专职代理,让负责人分派任务给研究、写作或开发等代理,也能设置定时例程并审核操作。材料还举出每周项目简报的团队配置示例。
摘要由 AI 生成,请以原文为准。观测历史 · 最近 1 条 展开 / 收起
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| 采集时间 · 北京时间 | 指标 | 数值 | 来源 | 状态 |
|---|---|---|---|---|
| 10-28 14:30:25 | Star | 6,258 | GitHub 公开页面 | 已取得 |
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open-duet
Open-source, self-hosted alternative to Claude Duet: AI coworkers (named agents) with instructions, memory, routines, their own isolated …
项目说明 展开 / 收起
Open Duet Your own team of AI coworkers, running on your computer or a server you control. Open Duet is an open-source workspace for creating named AI agents, giving each one a job and a place to work, and chatting with them over time. Let a lead agent hand work to specialists, keep useful context between conversations, or set a routine to run later. Choose how much freedom an agent has, and review the actions it takes. You choose where the app runs and which engine gets your prompts. Open Duet does not include a model or a model subscription. Project on GitHub · Desktop app · Web app (invite-only) · Watch the demo · Quick start · Run it on your server · Guides Status: Active development. The desktop app, self-hosted server, agent computers, and newer team features are still evolving. See known limitations before relying on them for important work. What you can do Create a roster of agents. Give each one a name, instructions, model, workspace, memory, and approval settings. Use different agents for research, planning, writing, support, or development. Work as a team. Set a lead and specialists, let the lead delegate tasks, and follow the results in chat. You can also bring agents together in shared rooms. Team leads can use Claude or Codex. See teams and delegated work. Keep useful context. Agents can keep notes, recall relevant notes and earlier conversations, and search their own history. You can review and edit what they remember. See memory. Set work to run later. Create routines that run on a schedule, when another service triggers them, or when you press Run now. Follow each run and respond if it needs your approval. Routines do not need Boat. See routines. Stay in control. Choose Ask first, Accept edits, or Plan only. Review tool activity and approval decisions in the app. Agents can also be given an isolated Docker computer; computer and browser access are experimental and off until you enable them. Keep track of work. Search conversations, attach text files and images, browse or download workspace files, and review reported token use and cost. Plan tasks and deadlines. Keep work on a board, assign an agent or team, and review deadlines alongside routine occurrences in a week or month calendar. Start an agent from a card, schedule a one-time run, and review its conversation and attempt history. See tasks and calendar. Example: prepare a weekly project briefing Create a lead agent and a couple of specialists, such as a researcher and an editor. Give them the same project workspace, and set the lead's engine to Claude or Codex. Then ask the lead to prepare a briefing from the notes and reports in that folder. The lead can split the request into smaller tasks and hand them to the specialists. Their work runs in its own conversations; when the results are ready, they return to the lead, which can put the briefing together. You can open the chats to follow along, and approve actions when the approval settings require it. Once the task is useful, make it a weekly routine and review each run from the app. What stays on your machine or server Open Duet stores conversations, agent notes, routines, and settings in the local data folder or server database for the instance you run. Workspace files stay in the folders you assign to agents. API keys saved through Open Duet are encrypted there; command-line sign-ins remain with the engine installed on that machine. When an agent answers, the selected engine receives the prompt and the context needed for that turn. That can include text you attach, relevant notes, and workspace content the engine reads. If the engine is a hosted service, that information is handled under that provider's terms. Open Duet does not include a hosted model or a model subscription. Choose an engine Connect an engine you already use: Claude Code or Codex CLI, Gemini CLI or Cursor, another command-line agent using the Agent Client Protocol (ACP), OpenRouter, or an OpenAI-compatible API such as Ollama or LM Studio. Available tools vary by engine; for example, image input and agent computers are not supported by every engine. See engine setup and capabilities. You bring the provider account, CLI sign-in, or API key; model usage may cost money. Ways to run Open Duet Desktop on your computer Server you control Development checkout Good for Trying a personal, local workspace Keeping agents and routines available while your computer is off Contributing or changing Open Duet Where data lives The desktop app's local data folder Your server Your development machine or configured database You'll need Node.js 22+, uv, and an engine on your computer A Linux server, a domain with HTTPS, Docker or Node.js and uv, and an engine on the server Node.js, uv, and Docker if you use PostgreSQL Start here Quick start Self-hosting guide Development setup Status Experimental Experimental; single owner Quick start The desktop app runs from a source checkout. It needs Node.js 22 or newer, uv, and at least one engine available on the same computer. For a CLI engine, install it and sign in before opening Open Duet. You can also configure an API-based engine in Settings → Engines. You do not need Docker for ordinary chat; Docker is only needed for the optional isolated agent computers. git clone https://github.com/Anil-matcha/open-duet.git cd open-duet/desktop npm run app On first launch, the setup screen checks your engines, helps you choose a workspace and approval mode, and can create a starter agent. Then: Open Settings → Engines and confirm that an engine is ready. Create an agent with a name, a clear job, and the workspace it should use. Start a chat. Choose Ask first if you want the agent to pause for approval before actions that need it. Add teammates or a routine when you want to split up work or repeat it later. As of 2026-10-28, the Releases page has a Windows x64 installer and macOS arm64 DMG for v0.5.0 (listed as a pre-release, so it is not under "latest"). Both are experimental and uns