Tools/agentscope-ai/QwenPaw

QwenPaw

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

33.7kgrowthPythonApache License 2.0trending

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Jun 2026

QwenPaw is a personal AI assistant you run yourself instead of renting from OpenAI. It ships with a local runtime so it works with no API key out of the box, and it also plugs into Ollama, LM Studio, and a dozen-plus cloud providers if you want bigger models. The hook is reach: it talks to you through Discord, Telegram, Lark, WeChat, DingTalk, even iMessage, and you extend what it can do with skills. It is open source under Apache-2.0, built by the team behind AgentScope, Alibaba's multi-agent framework.

Self-hosting is the default here, not an afterthought. There is Docker support and a one-click path to deploy on Alibaba Cloud if you would rather not run it at home, in which case you pay for the cloud, not the software. It takes its own security seriously for a personal tool: a kernel-level sandbox, a Tool Guard, and a File Guard sit between the model and your machine, which matters once an assistant can run code and touch your files.

For a solo developer or a tinkerer who wants an assistant that lives in their own chat apps and on their own hardware, this is one of the more complete self-hosted options going, and it costs nothing. Small teams can share an instance. There is no real large-team story here; it is a personal workstation, not a company-wide deployment, and that is fine.

The catch is gravity. It is deep in the Alibaba and Qwen ecosystem, the docs are heavily multi-language, and a lot of the built-in channels (WeChat, DingTalk, Lark) point at a Chinese user base. None of that is a flaw, but if you expected a Western-defaults, English-first assistant, calibrate before you install.

Free vs Self-Hosted vs Paid

fully free

Free: Apache-2.0, the whole thing. Local runtime (no API key needed), all the chat-channel integrations, the skills system, the sandbox.

Self-hosted: The primary way to run it. Docker locally, or one-click to Alibaba Cloud where you pay infrastructure costs, not a license.

Paid: None for the software. Your only costs are optional: cloud hosting if you do not self-host, or API fees if you point it at paid model providers instead of the local runtime.

Free and open source under Apache-2.0. You only pay if you choose cloud hosting or paid model APIs.

What to do by team size

Solo
free
Small team
free
Larger team
free
Self-hosting ops:moderate

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Score
92/100 · A+
Adoption27/30
Maintenance25/25
Community15/20
License15/15
Analysis10/10

A low score is not a verdict on quality. Young and niche tools start low by design. How we calculate scores

Trust Signals

High adoption: 20,316 starsActive community: 2,703 forksCommunity discussions enabledOrganization account (20 public repos)Notable author: 2,970 followersAuthor also built: agentscope-ai/AgentTeams (4,952 stars)

License: Apache License 2.0

Use freely. Patent grant included.

Commercial use: ✓ Yes

About

Owner
AgentScope-AI (Organization)
Stars
33,745
Forks
2,986

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