ИИ-агенты
OSWorld
OSWorld — benchmark multimodal agents on open-ended tasks in real computer environments.
★ 3,2 тыс. звёздApache-2.0
Смотреть руководство →OSWorld-V2 — проект с открытым исходным кодом из категории «ИИ-агенты» от xlang-ai (xlang-ai/OSWorld-V2 на GitHub). У него 353 звезды на GitHub и 53 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 1 октября 2026.
Benchmark computer-use agents on long, real-world desktop tasks.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Actual desktops, not mocks.
Dozens of steps, like real work.
Clicks, typing, navigation.
The software people actually use.
Standardized tasks and scoring.
Purpose-built for CUAs.
Download the source and move into the project folder.
git clone https://github.com/xlang-ai/OSWorld-V2.git
cd OSWorld-V2Isolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m osworld_v2 # check README for the exact commandIt is an open-source project at xlang-ai/OSWorld-V2 with 53 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — Apache 2.0 allows commercial use and modification. Keep the license and notice files, and note it includes a patent grant.
Tasks spanning dozens of steps across real applications — not single-turn Q&A.
Virtualized OS environments per the setup docs; it's heavier than a chat benchmark.
Clone the repo and follow the README quickstart — the docs at https://osworld-v2.xlang.ai walk through setup.
OSWorld — benchmark multimodal agents on open-ended tasks in real computer environments.
Reliable computer use for any agent: drive real apps through accessibility trees, not pixel guessing.
A benchmark testing whether agents can solve long-horizon coding tasks.
ESP32 iPhone Agent — let an AI model use a real iPhone with a $7 ESP32: AirPlay eyes, USB HID hands, no computer, no jailbreak
A benchmark for tool-agent-user interaction in real-world domains.
An open benchmark for browser AI agents on everyday tasks.
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если OSWorld-V2 вам не подходит.
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DeepSeek's plugin-based agent harness where everything is a plugin.
Соседние проекты из категории «ИИ-агенты» в каталоге, ближайшие по числу звёзд к OSWorld-V2 — продолжайте изучать полку по обе стороны от него.
Agentic memory for LLM agents, from a published research project.
WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.
Safety testing for agents, right in pytest.
A complete evaluation toolkit for AI agents.
The tougher, more robust successor to the MMLU benchmark.
An MCP-native AI coding agent and runtime in a single binary.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.