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ChiGaoandgary.gq
e4a6ccd449
* fix(cli): scope the ACP permission queue to the session The permission queue was keyed on the AgentSideConnection, but a daemon child owns exactly one connection that every session on it multiplexes onto. One unanswered question in an idle session therefore head-of-line blocks every sibling session, and with the mediator timeout disabled by default the wait is both unbounded and invisible: the blocked request is never published, so hosts report no pending interaction at all. Keep the queue -- a single session does have concurrent permission producers -- and narrow its unit of serialization to the session, which is what the bridge already models with its per-session promptQueue. * fix(cli): Remove the unused unqueued Session.requestPermission SubAgentTracker receives #requestPermissionQueued from the session that constructs it, and its own default goes straight to the connection, so no caller ever reached this method. Its docstring named a caller that uses the queued path, which left an unqueued route onto the shared connection sitting beside the queue that is meant to own the boundary. * test(cli): Pin the abandoned-while-queued permission request to the floor A request whose caller aborts while it is still queued behind its session's head is dropped instead of published, because an RPC that reaches the client after its caller is gone becomes a prompt nobody can answer or cancel. That short-circuit predates the queue-scoping change and no test covered it, so a mutation that removes it leaves the suite green. Add the missing case: hold one request unanswered, queue a second, abort the queued one, then release the head and assert the client was contacted exactly once. A third request from the same session then proves dropping the abandoned one did not wedge the queue. * test(cli): Pin each session's permission settlement and share the approval fixture The cross-session test asserted only where the request went. It now also asserts that each session settles its own approval against its own run registry, so a queue that mis-scoped the receive half as well as the send half cannot pass. Verified discriminating: forcing the run id to a constant fails the test. Four of these tests had each copied the same approval fixture verbatim; one of them was added here. Hoisted into a single helper, assertions unmoved. --------- Co-authored-by: gary.gq <[email protected]>
The open-source AI coding agent for your terminal, editor, desktop, browser, and chat.
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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
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 serveto 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
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.