Andrew Ng發佈OpenWorker助手

2026年7月24日 00:00

重點摘要

Issues welcome. AI that gets your everyday tasks done. OpenWorker is an open-source AI coworker that lives on yo。

站內 AI 整理稿

Issues welcome.AI that gets your everyday tasks done.OpenWorker is an open-source AI coworker that lives on your desktop and delivers finished work, not just chat: a polished document, a Slack reply with the numbers, an updated calendar, a triaged inbox.

It runs on your machine and doesn't lock you into any model: bring your own API key for OpenAI, Anthropic, Google, or an open-weight provider, or run fully local with Ollama.Your data leaves your machine only through the model and integrations you choose.

Download ⬇ macOS (Apple Silicon) macOS 12+ · signed & notarized · auto-updates ⬇ Windows 10/11 (x64) builds are not yet code-signed, so SmartScreen will warn; signing is in progress Open the app, add a model key (or point it at Ollama), and ask for something real.

How it works Tell OpenWorker the outcome you want - "prepare a customer brief," "untangle my calendar," "draft a report," "check where the release stands across Jira and GitHub." It breaks the task into steps and works across your desktop, files, and connected apps.

Before anything consequential - sending a message, changing a calendar, running a command - it checks in and you approve or redirect.You get the finished deliverable, not a to-do list.

Under the hood: ┌────────────────────────────────────────────────┐ │ OpenWorker desktop app │ native shell + GUI ├────────────────────────────────────────────────┤ │ local agent server (Python) │ engine · tools · connectors - built on aisuite ├───────────────┬────────────────┬───────────────┤ │ your files │ your tools │ your model │ everything runs with your keys, │ & terminal │ 25+ connectors │ any provider │ on your machine └───────────────┴────────────────┴───────────────┘ What it can do Produce real deliverables - documents, spreadsheets, reports, and web pages land as files you can open and share.

Work from Slack - mention @OpenWorker in a channel; a session opens on your desktop, the work happens with your tools, and the answer comes back as a thread reply.Use your everyday tools - 25+ integrations including GitHub, Slack, Jira, Notion, Linear, HubSpot, Outlook, monday.

com, Gmail, and Google Calendar, plus your terminal and local files.Any tool reachable over MCP plugs in too, with per-tool control.Run on a schedule - automations for recurring work: a morning brief, a weekly report, a standing watch over a channel.Runs land in the app with full transcripts.

Ask before acting - writes, sends, and shell commands are approval-gated.Unattended runs park their asks in an inbox instead of acting on their own.Bring your own model Model access is yours: pick a provider, paste your key, switch anytime.

Supported out of the box: OpenAI · Anthropic · Google Gemini · Inkling (Thinking Machines) · GLM (Z.ai) · DeepSeek · Kimi (Moonshot) · Qwen · MiniMax · Mistral · Grok (xAI) - plus open-weight models via Together and Fireworks, and fully local models via Ollama.

A curated model list marks what we've verified for tool-calling work.Adding any model string works at your own risk.Privacy OpenWorker is local-first.Everything lives on your machine: the agent loop, your conversations, connector tokens, and model keys - all in the app's local secret store.

The only cloud piece is a small service that brokers OAuth handshakes for connectors.You can always use the App without signing-in - use the connectors via manually-created credentials/API-keys.Run from source Prerequisites: Python 3.

10+, Node 20+, and (for the desktop shell) the Rust toolchain via rustup.git clone https://github.com/andrewyng/openworker cd openworker # 1.One-time bootstrap - creates the Python venv at .venv # (on Windows, run from Git Bash or WSL) bash packaging/setup_dev_env.sh # 2.

Start the local agent server .venv/bin/openworker-server --cwd ~/some/project --port 8765 # (Windows: .venv\Scripts\openworker-server.exe) # 3.

In a second terminal, start the UI cd surfaces/gui npm install npm run dev # browser UI on the Vite dev port To run the full desktop app instead of the browser UI, replace step 3 with npm run tauri dev (from surfaces/gui/) - the Tauri shell launches the window and supervises the server itself.

Tests: .venv/bin/pytest (server), npm test and npm run e2e in surfaces/gui (GUI unit + hermetic end-to-end).Desktop bundles are built with packaging/build_dmg.sh / packaging/build_windows.ps1.

Repository layout Directory What's in it coworker/ Python backend - agent engine, model providers, connectors, MCP client, memory, automations surfaces/gui/ Desktop app - React UI + Tauri shell that supervises the server stt/ Speech-to-text sidecar (Rust) for voice input packaging/ Installer builds (macOS DMG, Windows), auto-update manifest, dev bootstrap docs/ Design specs and decision logs tests/ Backend test suite Built on aisuite OpenWorker's engine is built on aisuite, a lightweight Python library providing a unified chat-completions API across LLM providers and an agents layer with tools, toolkits, and MCP support.

If you want to build your own agent harness rather than use ours, start there; this repo is a working reference for what aisuite can carry.OpenWorker was originally developed inside the aisuite repository before moving to its own home here; thanks to the aisuite contributors whose work it builds on.

Contributing Contributions and bug reports are welcome - open an issue or a pull request.The app updates itself, so fixes reach installs quickly.For any PR, please attach screenshots of what was broken and how it is fixed now.We will shortly add features that you can contribute to.

Please note that we are actively developing based off a internal list and goal, so we may not approve PRs that add features that are already under-development or deviates from our vision.License MIT - see LICENSE.AboutNo description, website, or topics provided.

ResourcesReadmeMIT licenseActivityStars1.5k starsWatchers15 watchingForks222 forksReport repositoryReleasesPackagesContributorsLanguages

Related

相關文章

秋招信息戰打不動?我們測了千問的新功能,讓Agent全程陪跑

阿里巴巴旗下大模型「千問」近日推出全新功能,針對秋季招聘季中求職者面臨的海量資訊與繁複流程,打造「Agent 全程陪跑」服務。根據官方測試,這項功能能協助使用者自動篩選職缺、整理企業資訊,甚至模擬面試問答,大幅減輕求職者自行蒐集與比對資訊的負擔。 在實際體驗中,用戶只需輸入自身學經歷與目標產業,Agent 便會自動爬取最新的秋招公告,並按職位匹配度、截止日期等條件排序,同時附上企業背景與筆面試經驗摘要。

剛剛

AI寫的PR堆成山,Rust已忍無可忍

Rust 語言社群近期強烈反彈大量由 AI 生成的公關稿與行銷文淹沒官方討論區,這些內容缺乏深度且帶有商業目的,讓資深貢獻者不堪其擾。社群管理團隊正研擬加強審查機制與提高發文門檻,但同時也擔心誤傷真正的新手使用者。這場爭議凸顯開源專案在 AI 時代面臨資訊過濾成本攀升的困境。

2 小時前