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QwenPaw

agentscope-ai/QwenPaw

Your Personal AI Assistant

GraphCanon updated 2d · GitHub synced 2d · 31 views this month

34k stars3.0k forksLast push 3d Python Apache-2.0

Decision brief

QwenPaw is an easy-to-install personal AI assistant, offering support for multiple chat apps with extensible capabilities.

Good fit when

  • - When you need to deploy a personal AI assistant on your local machine or the cloud without complex setup.
  • - If you are looking for a solution that supports various popular chat apps including DingTalk, Lark, WeChat, etc., and needs easily extendable functionalities.

Avoid when

  • - In environments with strict security policies or restricted network access where installing scripts automatically may not be possible due to corporate firewalls or constrained language mode in some,
  • - If your Python version is below 3.11 or equal to or above 3.14 as the tool requires a specific range of Python versions (>= 3.11, < 3.14) to operate correctly.
Pricing:
freemium - QwenPaw operates under an open-source model with the Apache-2.0 license but it may have additional services that could require subscription or payment in future iterations.
Requirements:
- A Python environment in version 3.11 to less than 3.14 is mandatory.; - Script installation may require manual configuration in specific Windows environments (Windows LTSC, constrained language mode).

Observed Jul 11, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Very active (0d since push)
As of 2d
Provenance
Not a fork · Organization account
As of 2d
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Backing

Company context for AgentScope. Display-only - separate from trust and ranking.

Company
AgentScope-AI·GitHub org profile·1mo
Commercial model
Pure OSS·GitHub org profile (public repos)·1mo

Install

pip install QwenPaw
PyPI

How it fits your stack(16)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Integrates

Related

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Easy to install and deploy personal AI assistant that supports multiple chat apps with extensible capabilities.

Capability facts

Deploy
Self-host

Source: dockerfile:docker-compose.yml · Aug 19, 2026

Docker
Dockerfile present

Source: dockerfile:docker-compose.yml · Aug 19, 2026

CLI
CLI entrypoint

Source: pyproject.toml:[project.scripts] · Aug 19, 2026

Languages
python

Source: github.language+pyproject.toml · Aug 19, 2026

Categories

Graph entities

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Node.js runtimeNode.js

Source: README excerpt (regex_v1, Aug 19, 2026)

ate a virtual environment, and install QwenPaw with all dependencies (including Node.js and frontend assets). Note: May not work in restricted network environments or
Source link
Python runtimePython

Source: README excerpt (regex_v1, Aug 19, 2026)

If you prefer managing Python yourself (requires Python >= 3.11, < 3.14):
Source link

Tags

README

Option 1: Pip Install

If you prefer managing Python yourself (requires Python >= 3.11, < 3.14):

pip install qwenpaw
qwenpaw init --defaults
qwenpaw app

Then open the Console in your browser at http://127.0.0.1:8088/ to configure your model. To chat in DingTalk, Lark, WeChat, etc., see the Channel setup documentation.



Option 2: Script Install

No Python setup required, one command installs everything. The script will automatically download uv (Python package manager), create a virtual environment, and install QwenPaw with all dependencies (including Node.js and frontend assets). Note: May not work in restricted network environments or corporate firewalls.

macOS / Linux:

curl -fsSL https://qwenpaw.agentscope.io/install.sh | bash

Windows (CMD):

curl -fsSL https://qwenpaw.agentscope.io/install.bat -o install.bat && install.bat

Windows (PowerShell):

irm https://qwenpaw.agentscope.io/install.ps1 | iex

Note: The installer will automatically check the status of uv. If it is not installed, it will attempt to download and configure it automatically. If the automatic installation fails, please follow the on-screen prompts or execute python -m pip install -U uv, then rerun the installer.

⚠️ Special Notice for Windows Enterprise LTSC Users

If you are using Windows LTSC or an enterprise environment governed by strict security policies, PowerShell may run in Constrained Language Mode, potentially causing the following issue:

  1. If using CMD (.bat): Script executes successfully but fails to write to Path

    The script completes file installation. Due to Constrained Language Mode, it cannot automatically update environment variables. Manually configure as follows:

    • Locate the installation directory:
      • Check if uv is available: Enter uv --version in CMD. If a version number appears, only configure the QwenPaw path. If you receive the prompt 'uv' is not recognized as an internal or external command, operable program or batch file, configure both paths.
      • uv path (choose one based on installation location; use if uv fails): Typically %USERPROFILE%\.local\bin, %USERPROFILE%\AppData\Local\uv, or the Scripts folder within your Python installation directory
      • QwenPaw path: Typically located at %USERPROFILE%\.qwenpaw\bin.
    • Manually add to the system's Path environment variable:
      • Press Win + R, type sysdm.cpl and press Enter to open System Properties.
      • Click “Advanced” -> “Environment Variables”.
      • Under “System variables”, locate and select Path, then click “Edit”.
      • Click “New”, enter both directory paths sequentially, then click OK to save.
  2. If using PowerShell (.ps1): Script execution interrupted

Due to Constrained Language Mode, the script may fail to automatically download uv.

  • Manually install uv: Refer to the GitHub Release to download uv.exe and place it in %USERPROFILE%\.local\bin or %USERPROFILE%\AppData\Local\uv; or ensure Python is installed and run python -m pip install -U uv.
  • Configure uv environment variables: Add the uv directory and %USERPROFILE%\.qwenpaw\bin to your system's Path variable.
  • Re-run the installation: Open a new terminal and execute the installation script again to complete the QwenPaw installation.
  • Configure the QwenPaw environment variable: Add %USERPROFILE%\.qwenpaw\bin to your system's Path variable.

Once installed, open a new terminal and run:

qwenpaw init --defaults   # or: qwenpaw init (interactive)
qwenpaw app
Install options

macOS / Linux:


---

# Install a specific version
curl -fsSL ... | bash -s -- --version 1.1.0

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# Install from source (

For agents

This page has a .md twin and JSON over the API.

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