ИИ-агенты
agent-qa
A self-improving QA agent that writes tests in plain English.
★ 902 звездыNOASSERTION
Смотреть руководство →PhyAgentOS-core — проект с открытым исходным кодом из категории «ИИ-агенты» от PhyAgentOS (PhyAgentOS/PhyAgentOS-core на GitHub). У него 2 776 звёзд на GitHub и 128 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 8 октября 2026.
Recursive self-improving physical agent OS — verified, evidence-based execution for robots and simulators
Define an embodied task with a visible goal and success criteria — PAOS verification modes (audit, enforce, recovery) are built around explicit criteria.
Clone the repo and install it in editable mode; install Dora CLI v0.4.1 only if you will run managed Forge Skill profiles.
Run paos onboard, then edit ~/.PhyAgentOS/config.json with your model provider (e.g. OpenRouter) and Forge/verification settings, and install the Forge Skills you need.
Start an installed Skill Runtime, then paos agent -m "..." with a task, and check the verdict and evidence afterwards.
Robot actions enter only through the versioned Forge Gateway Tool API (Query/Action/Session) — the agent never reaches directly into a simulator or hardware SDK.
Validated images and optional robot state are captured around actions with source, sequence, time and SHA-256 digest metadata.
The verifier judges goal, criteria, constraints, execution facts and evidence — with off, audit, enforce and recovery modes.
A recovery verdict appends a bounded PlanRevision to the same task; unknown effects are reconciled, never blindly retried.
SQLite WAL transactions persist AgentTask, PlanRevision, Query records and Gateway invocation references.
Verified tasks produce reusable workflow Skills and clustered Lessons, loaded only with the matching Skill, with guarded promotion.
Clone PhyAgentOS-core and install it editable, exactly as the 5-minute quick start shows.
git clone https://github.com/PhyAgentOS/PhyAgentOS-core.git
cd PhyAgentOS-coreOnboard to create ~/.PhyAgentOS/config.json and the default workspace, then add your provider API key to the config.
paos onboardRun the interactive CLI (or paos gateway for channels/Cron/Heartbeat) and give it a verifiable task.
paos agent
# one-shot: paos agent -m "Inspect Forge capabilities, then place the object in the target area and verify the visible result."The PhyAgentOS project team maintains it; the project's site is phy-agent-os.x-era.com.
Yes, it is MIT-licensed. You supply your own model provider and any robot/simulator hardware or software.
The config example uses a provider such as OpenRouter with your API key, so model costs depend on your provider and model choice.
General frameworks plan and call tools. PAOS adds a single governed execution gateway for physical actions, captured evidence, a separate verifier, and experience that only comes from verified tasks.
pip install -e . from a clone, run paos onboard, configure a provider in config.json, install a Forge Skill, and run paos agent.
A self-improving QA agent that writes tests in plain English.
A self-improving agent for coding workflows and long-running autonomous tasks
Self-improving memory layer that works across AI agent harnesses.
AI agent framework for plan-first development workflows with approval-based execution. Multi-language support (TypeScript, Python, Go, Rust) with automatic t…
WebArena-Verified: the audited, deterministically scored release of the WebArena web-agent benchmark.
An open-source multimodal retrieval engine for agent pipelines.
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если PhyAgentOS-core вам не подходит.
A personal AI that really does things — on any OS, with your data staying yours.
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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 PhyAgentOS-core — продолжайте изучать полку по обе стороны от него.
Turn papers, text, or topics into editable research figures and slides.
MCP server, CLI and skills for searching and downloading academic papers from arXiv, PubMed and 20+ sources
Model-agnostic marketplace of agent skills with a harness-free canonical layer.
Terminal security that stops malicious prompts, URLs, and payloads before they run.
Open-source observability for AI agents: trace, evaluate, guard, and improve.
Rebuild Claude Code’s core in ~5,000 lines: an 11-chapter coding-agent masterclass.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.