6097d7ab63 ci: auto-minimize comments from org-blocked users (#7899)
* ci: auto-minimize comments from org-blocked users

Adds a scheduled workflow that runs every hour to scan recent
issue/PR comments and minimize any from users blocked at the org
level. This cleans up spam comments that were posted before a
block was applied.

The workflow:
1. Fetches the org's blocked-user list via REST API
2. Queries recent comments (last 2h) via GraphQL
3. Matches comment authors against the blocked list
4. Minimizes unmatched comments as OFF_TOPIC via GraphQL

Also triggerable manually via workflow_dispatch with a configurable
lookback window.

* ci: use repo blocklist file instead of org blocked-users API

The org blocked-users API requires admin:org scope which the CI
bot PAT doesn't have. Switch to a plain-text blocklist file at
.github/spam-blocklist.txt — one username per line, case-insensitive,
# for comments. No special scopes needed.

Also adds danialzivehdadr as the first entry.

* ci: make auto-minimize-spam failures visible, handle empty blocklist

* fix(ci): address review feedback on auto-minimize-spam workflow (#7899)

- Change hours input type from string to number (project convention)
- Extract duplicated step-summary writes into write_summary() function
- Capture gh stderr (2>&1) and include it in failure warnings
- Document coverage limits in header comment

* fix(ci): quote auto-minimize-spam expressions to pass yamllint (#7899)

* test(ci): add regression guards for auto-minimize-spam workflow invariants (#7899)

---------

Co-authored-by: qwen-code-dev-bot <[email protected]>
Co-authored-by: Shaojin Wen <[email protected]>
Co-authored-by: qwen-code-ci-bot <[email protected]>
2026-07-29 23:37:42 +00:00
2025-07-22 23:26:01 +08:00
2025-07-22 23:26:01 +08:00
2025-08-08 20:45:54 +08:00
2025-07-22 23:26:01 +08:00
2026-07-29 00:25:30 +00:00
2025-10-23 09:27:04 +08:00
2025-12-22 21:11:33 +08:00

npm version License Node.js Version Downloads

QwenLM%2Fqwen-code | Trendshift

The open-source AI coding agent that lives in your terminal.

中文 | Deutsch | français | 日本語 | Русский | Português (Brasil)

Why Qwen Code?

  • Agentic out of the box — Auto-Memory, Auto-Skills, SubAgents, Agent Teams, and MCP. Dynamic workflows, zero setup.
  • Open-source, inside and out — The framework and the Qwen models are open-source. They evolve together. No vendor lock-in.
  • Multi-protocol — Supports OpenAI, Anthropic, Gemini, and Qwen APIs. Any third-party provider or local model (Ollama / vLLM). Switch at runtime.
  • Beyond the terminal — IDE plugins, Desktop app, daemon mode, SDKs, and IM bots (Telegram / DingTalk / WeChat / Feishu).

Tip

Qwen Code is actively iterating on itself — using its own agent and models to file issues, submit PRs, review code, and run tests. Powered by the community, driven by AI.

Installation

Linux / macOS:

curl -fsSL https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.sh | bash

Windows:

irm https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen-standalone.ps1 | iex

Restart your terminal after installation to ensure environment variables take effect.

NPM / Homebrew

NPM (requires Node.js 22+):

npm install -g @qwen-code/qwen-code@latest

Homebrew (macOS / Linux):

brew install qwen-code

Quick Start

qwen          # Launch interactive terminal UI
# Inside the session:
/auth         # Configure your provider and API key

See the Authentication Guide and Settings Reference for detailed setup.

Qwen Code

How to Use Qwen Code

Mode Command Use Case
Interactive qwen Terminal UI with rich rendering, @file references, slash commands
Headless qwen -p "..." Scripts, CI/CD, batch processing — no UI
IDE — VS Code, Zed, JetBrains
Desktop — Qwen Code Desktop — GUI for macOS, Windows, Linux
Daemon qwen serve Shared agent session over HTTP+SSE (ACP). Multiple clients, one agent. (experimental) Docs
SDK — TypeScript, Python, Java
IM Bot qwen channel Connect to Telegram, DingTalk, WeChat, or Feishu
SDK example (Python)
import asyncio

from qwen_code_sdk import is_sdk_result_message, query


async def main() -> None:
    result = query(
        "Summarize the repository layout.",
        {
            "cwd": "/path/to/project",
            "path_to_qwen_executable": "qwen",
        },
    )

    async for message in result:
        if is_sdk_result_message(message):
            print(message["result"])


asyncio.run(main())

Capabilities

If you know Claude Code, you already know Qwen Code — and then some. We've put significant effort into bringing Qwen Code to feature parity with Claude Code, improving both breadth and reliability across the board.

Feature Qwen Code Claude Code
SubAgents, Agent Teams, Dynamic Workflows ✓ ✓
Auto-Memory, Auto-Skills, Hooks ✓ ✓
Built-in Skills (/review, /batch, /loop, /bugfix…) ✓ ✓
MCP, Plan Mode, LSP Integration ✓ ✓
Auto Mode, Sandbox, Git Worktrees ✓ ✓
Computer Use (desktop automation) ✓ ✓
IDE Plugins (VS Code / JetBrains / Zed) ✓ ✓
SDK ✓ ✓
Headless Mode, Session Management ✓ ✓
Open-source — model and framework ✓ —
Multi-protocol (OpenAI / Anthropic / Gemini / Qwen + any provider) ✓ —
Agent Arena (multi-model head-to-head on same task) ✓ —
Daemon Mode — qwen serve (multi-client shared agent) ✓ —
IM Channels (Telegram / DingTalk / WeChat / Feishu) ✓ —

Ecosystem

  • Qwen Code Desktop — Official desktop app for macOS, Windows, and Linux

  • AionUi — A modern GUI for command-line AI tools including Qwen Code

  • Gemini CLI Desktop — A cross-platform desktop/web/mobile UI for Qwen Code

  • 🦞 Qwen Code Claw — Let other agents (Claude, Codex, etc.) delegate coding tasks to Qwen Code via ACP. Paste this prompt into your agent:

Use Qwen Code as a coding agent. First, fetch and read this skill reference:
https://raw.githubusercontent.com/QwenLM/qwen-code/refs/heads/main/.qwen/skills/qwen-code-claw/SKILL.md
Then follow the instructions inside to install, authenticate, and use Qwen Code via acpx for all coding tasks.

Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

Acknowledgments

This project was originally based on Google Gemini CLI v0.8.2. We gratefully acknowledge the Gemini CLI team's excellent work. Starting from Qwen Code v0.1, we stopped syncing with upstream and began independent development as a multi-protocol, multi-platform agent framework with deep integrations for Qwen models and beyond.

Languages
TypeScript 76.5%
Java 11.5%
JavaScript 5.4%
Rust 5%
Python 0.5%
Other 0.9%