易良andQwen-Coder c1903b8bb2 fix(serve): fan out never-started process probes (#14303)
* fix(serve): fan out never-started process probes

Co-authored-by: Qwen-Coder <[email protected]>

* fix(serve): let each never-started probe carry its own binding

Address the two non-blocking review items on #14303. The fan-out
settlement loop paired probe results back to bindings by array index,
an invariant the committed suite did not pin (a positional mutant
survived all 219 tool-turn tests in sandbox verification). Each probe
now carries its own binding through the Promise, removing the index
entirely; a new mixed-outcome regression test proves that with two
probed bindings — one row present, one row absent — only the absent
binding settles.

rejectionDetail also fell through to 'no status' for the DOMException
that AbortSignal.timeout rejects fetch with, which is the literal the
issue asked to eliminate for this PR's exact failure mode; its name is
now reported like an Error name, and the probe table pins TimeoutError.

Co-authored-by: Qwen-Coder <[email protected]>

* fix(serve): drop unreachable DOMException arm, pin grant-proof diagnostic

R1-2: `DOMException.prototype`'s prototype *is* `Error.prototype` on every
Node this repo supports, so the `cause instanceof Error` arm seven lines
above always returned first with the identical `error ${cause.name}`. The
branch was inert and its comment asserted a false premise. Both deleted;
the surviving comment keeps only the load-bearing half (a DOMException's
legacy numeric `code` cannot pass the string route-code check). The existing
DOMException table row still resolves through the Error arm: 26/26 pass.

R1-3: the `processProven` gate had no test distinguishing false from true -
`if (processProven)` -> `if (true)` kept all 229 tests green, so every
grant-owner-proven settlement could have claimed a process-ledger proof it
never consulted. Added a negative stderr assertion to the grant-proven
settlement case; that single mutant now fails exactly that test.

Co-authored-by: Qwen-Coder <[email protected]>
Patrol-Run: qwen-pr-closeout/jmvb02cj89w

---------

Co-authored-by: Qwen-Coder <[email protected]>
2026-10-16 23:06:31 +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
2026-10-16 01:12:18 +08:00
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 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

On SWE-bench Verified, seven Qwen Code versions scored 76.40%–77.80% on average using the same Qwen 3.7 Max model (500 tasks, three trials per version).

Average SWE-bench Verified scores by Qwen Code version: 0.0.14, 77.80%; 0.1.0, 76.73%; 0.5.0, 76.60%; 0.10.0, 76.47%; 0.15.0, 77.67%; 0.19.0, 76.40%; 0.22.0, 77.33%.

Full results and evaluation configuration →

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-audio-agent — Realtime full-duplex voice frontend for Qwen Code over ACP — talk hands-free with barge-in and a local wake word

  • 🦞 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

Privacy

See the Terms of Service and Privacy Notice, including Chrome extension and Browser Use data handling.

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%