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agentscope-ai/qwenpaw

16,617PythonAudience · developerComplexity · 4/5LicenseSetup · hard

TLDR

QwenPaw is a self-hosted personal AI assistant you run on your own machine or server, it remembers you over time, connects to chat apps like Telegram, Discord, and WeChat, and can be extended with custom skills.

Mindmap

mindmap
  root((repo))
    What it does
      Personal AI assistant
      Persistent memory
      Acts on your behalf
    Skills
      Built-in skills
      Custom skills
      Security scanning
    Chat channels
      Telegram and Discord
      WeChat
      DingTalk and Feishu
    Self-hosting
      Data stays local
      No third-party upload
      Python 3.10 plus
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Code map

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Things people build with this

USE CASE 1

Build a private assistant that summarises your email and calendar each morning and delivers a digest to your Telegram.

USE CASE 2

Set up a multi-agent pipeline where one agent researches topics overnight and another drafts a written report by morning.

USE CASE 3

Write a custom skill that watches a folder for new PDF files, reads them, and sends you a summary on Discord.

USE CASE 4

Connect the same assistant to WeChat, DingTalk, and Feishu so you can chat with it from any app without duplicating config.

Tech stack

PythonAgentScope

Getting it running

Difficulty · hard Time to first run · 1h+

Requires Python 3.10, 3.13, a self-managed server or local machine, and API credentials for each chat channel you want to connect.

Apache 2.0, use freely in any project, personal or commercial, as long as you keep the copyright and license notices.

In plain English

QwenPaw is a personal AI assistant that you can install on your own computer or on a cloud server you control, instead of using a chat product hosted by someone else. The pitch in the README is "works for you, grows with you", the assistant is meant to remember things about you, learn from the conversations you have with it, and act on your behalf over time. Because you deploy it yourself, your data and memory stay on your own machine or on a server you choose, with no third-party hosting and no data upload to an outside vendor. The assistant is built around the idea of skills, which are the individual capabilities that decide what it can actually do. It ships with built-in skills like scheduling, reading and processing PDF and office documents, and producing news digests, and you can add your own custom skills that get loaded automatically. It also supports multi-agent collaboration: you can create several agents with different roles and let them talk to each other to handle more complex tasks. A multi-layer security system (a tool guard, file access control, and skill security scanning) is included to keep things from going wrong when an agent is acting on your behalf. A key practical feature is that QwenPaw can connect to many chat channels, DingTalk, Feishu, WeChat, Discord, Telegram and others, so you can talk to the same assistant from whichever app you prefer. Example uses listed in the README include daily social-media digests, email and calendar summarisation, prototype generation while you sleep, tracking tech and AI news, and organising or searching local files. Someone would use this if they want a private, programmable AI assistant they fully control. It is a Python project (3.10 up to but not including 3.14), licensed under Apache 2.0, was recently renamed from CoPaw to QwenPaw, and is being actively developed. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
I want to create a custom QwenPaw skill (agentscope-ai/qwenpaw) that monitors a folder for new PDF files and sends a one-paragraph summary to Telegram. Show me the Python skill class skeleton and the YAML config entry I need.
Prompt 2
Walk me through connecting QwenPaw to my Discord server as a bot. What credentials do I need to collect and where exactly do I put them in the config file?
Prompt 3
Write a QwenPaw skill that fetches the top 5 Hacker News stories every morning at 8 AM and posts them as bullet points to my Feishu channel.
Prompt 4
How do I configure multi-agent collaboration in QwenPaw so a research agent finds information and hands it to a writing agent? Give me the config plus enough Python to run a quick test.
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