易良andQwen-Coder e596a410bb feat(web-shell): publish the package with the cli release (#12178)
* feat(web-shell): publish the package with the cli release

The release workflow published the cli and the channel packages but never
@qwen-code/web-shell, so the npm artifact only moved when someone published
it by hand.

Add the package to the release step and record its repository so npm accepts
the provenance attestation the workflow requests.

* fix(release): probe @qwen-code/web-shell in the push-time version guard

publish_package 'packages/web-shell' made the package CI-published, but
PUBLISHED_PACKAGES — the sole input to assertVersionUnreleased — still
listed only twelve names. A release shipped only as @qwen-code/web-shell
therefore read as unshipped: the version-collision bump never fired and
the force-push guard could proceed over an already-published version.

Widen the guard list, its pin in get-release-version.test.js, and
generalise "keeps the publish allowlist and the guard package set in
step" so every bare publish_package '<dir>' target is resolved through
the package.json it publishes. The channel-loop comparison alone could
not see this addition, which is how it shipped unguarded.

Co-authored-by: Qwen-Coder <[email protected]>
Patrol-Run: qwen-pr-closeout/jmu6tb0j73c

* test(release): simplify publish guard coverage

* fix(release): publish web-shell after the channels

Review on #12178 (R1-3): the step runs under `set -eo pipefail` and every
publish_package call is bare, so inserting the newest name ahead of the
channel packages makes a failure of its first CI publish strand all of
them. Publish it last instead.

Also append the new entry to PUBLISHED_PACKAGES rather than inserting it
after audio-capture: the version-guard tests read that array by index, so
its position is load-bearing. Record that in the pinned assertion.

---------

Co-authored-by: Qwen-Coder <[email protected]>
2026-09-18 12:17:07 +00:00
2025-07-22 23:26:01 +08:00
2025-08-08 20:45:54 +08:00
2025-07-22 23:26:01 +08:00
2026-09-16 13:31:06 +00:00
2025-10-23 09:27:04 +08:00
2025-12-22 21:11:33 +08:00

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QwenLM%2Fqwen-code | Trendshift

The open-source AI coding agent for your terminal, editor, desktop, browser, and chat.

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Qwen Code in the terminal, desktop app, browser, editor, and chat, with VS Code, Zed, JetBrains, Telegram, DingTalk, WeChat, and Feishu integrations

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, Web UI, SDKs, and chat integrations (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

Open a terminal in your project and start Qwen Code:

cd /path/to/your-project
qwen

Inside the session, run /auth to configure your provider and API key. Then try:

Explain this repository and show me where to start.

See the Authentication Guide and Settings Reference for detailed setup.

See the terminal interface

Qwen Code terminal interface

How to Use Qwen Code

Choose the interface that fits your workflow:

Interface Get started
Terminal Run qwen in your project — see Quick Start.
Desktop Download Qwen Code Desktop for macOS, Windows, and Linux.
Web Run qwen serve --open to open the Web UI in your browser. (experimental)
Editor Set up VS Code, Zed, or JetBrains.
Chat Connect Telegram, DingTalk, WeChat, or Feishu, then run qwen channel start.

For automation and custom integrations:

  • Headless — Run qwen -p "..." in scripts, CI/CD, or batch jobs.
  • SDKs — Build with TypeScript, Python, or Java.
  • Daemon — Run qwen serve to connect clients over HTTP + SSE (ACP). (experimental) Daemon guide.
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) ✓ —

Qwen Code Evaluation

Evaluation Configuration

Configuration Value
Dataset princeton-nlp/SWE-bench_Verified, 500 cases
Runs 3 trials per version, 1,500 jobs per version; 7 Qwen Code versions
Model Qwen 3.7 Max
Sampling temperature=1, top_p=0.95
Thinking / Reasoning interleaved_thinking=true, thinking_type=adaptive, reasoning_effort=high
Context / Output Limits context_1m=true, model_context_length=1,000,000, max_tokens=64,000, model_max_tokens=65,535
Harness Limits max_iterations=500, runtime_timeout_sec=7,200, agent_timeout_multiplier=3.0

Scores by Qwen Code Version

Version Avg Score Pass Rate pass@3 pass^3
0.0.14 77.80% 84.6% 84.6% 69.2%
0.1.0 76.73% 84.6% 84.6% 68.0%
0.5.0 76.60% 83.0% 83.0% 68.4%
0.10.0 76.47% 84.4% 84.4% 67.4%
0.15.0 77.67% 84.6% 84.6% 68.6%
0.19.0 76.40% 85.0% 85.0% 65.8%
0.22.0 77.33% 84.4% 84.4% 68.0%

Avg Score Trend

Qwen Code version Avg Score trend

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.
  • Aliyun Model Studio CLI — Official CLI for Aliyun's AI platform (bailian-cli). Extends Qwen Code with image/video generation, knowledge retrieval, app orchestration, and model deployment

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%