mirror of
https://github.com/QwenLM/qwen-code.git
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76a57154b2
* fix(core): add streaming inactivity timeout to the OpenAI pipeline The OpenAI client `timeout` only bounds connect + first response. Once a streaming request returns 200, inter-chunk inactivity is unbounded, so a provider that accepts the request then streams nothing (observed with a DashScope/Bailian endpoint returning 200 with no finish_reason) hangs indefinitely — the only existing idle timer is telemetry-only and never aborts. executeStream now wraps the raw chunk stream in an inactivity watchdog: if no chunk arrives for streamIdleTimeoutMs (default 120s, configurable via contentGenerator.streamIdleTimeoutMs; <= 0 disables), it aborts the per-request controller (freeing the socket) and throws. A user AbortError is propagated when the parent signal was cancelled; otherwise a synthetic ETIMEDOUT, which classifyRetryError treats as a retryable transport error — identical to a real socket read timeout — so the existing stream-transport retry recovers a zero-chunk (first-byte) stall and surfaces a clear error after exhaustion. The timer resets on every chunk (including thinking deltas), so active streams are never interrupted. Out of scope: surfacing a terminal turn_error to the UI on retry exhaustion (separate change); the non-streaming path is already bounded by the SDK timeout. 🤖 Generated with [Qwen Code](https://github.com/QwenLM/qwen-code) * fix(core): keep ETIMEDOUT code on stream inactivity timeout (bypass error handler) Audit found the inactivity timeout could not auto-retry: the OpenAI error handler detects code 'ETIMEDOUT' as a timeout and re-throws a generic Error WITHOUT the code, so classifyRetryError no longer saw a retryable transport error. (The original tests missed this because the mock error handler is a pass-through, not the real EnhancedErrorHandler.) Make the inactivity timeout a dedicated StreamInactivityTimeoutError that processStreamWithLogging rethrows directly — the same bypass StreamContentError already uses — so the ETIMEDOUT code survives to classifyRetryError and the stream-transport retry recovers a stalled first-byte stream. Adds a regression test with an error handler that faithfully replicates the code-stripping, asserting the code survives and the handler is bypassed. 🤖 Generated with [Qwen Code](https://github.com/QwenLM/qwen-code) * test(core): fix fake-timer deadlock in inactivity timeout tests Two tests awaited expect(consume).rejects before advancing the fake timers, so the rejection could never arrive and the tests hung to timeout. Assign the assertion promise, advance the timers, then await it. 🤖 Generated with [Qwen Code](https://github.com/QwenLM/qwen-code) * codex: address PR review feedback (#5827) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> * codex: fix PR 5827 CI lint failure Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> * codex: address PR review feedback (#5827) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> * codex: address PR review feedback (#5827) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> * codex: address PR review feedback (#5827) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> --------- Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com> |
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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.
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.