* feat(cli): cap inline shell output with configurable line limit
Long-running shell commands (npm install, find /, build logs) currently
fill the viewport with the full visible PTY buffer (up to availableHeight,
~24 lines on a typical terminal). The output dominates the screen and
pushes prior context off the top.
This caps inline ANSI shell output to a small window (default 5 lines,
matching Claude Code's ShellProgressMessage). The hidden line count is
already surfaced via the existing `+N lines` indicator in
`ShellStatsBar`, so users still know how much was elided.
The cap applies only when nothing in the existing escape-hatch set is
true:
- `forceShowResult` (errors, !-prefix user-initiated commands,
tools awaiting confirmation, agents pending confirmation)
- `isThisShellFocused` (ctrl+f focus on a running embedded PTY shell)
- `ui.shellOutputMaxLines = 0` (user opt-out)
Also adds a new `ui.shellOutputMaxLines` setting (default 5) so users
can adjust or disable the cap. The SettingsDialog renders it
automatically via the existing `type: 'number'` schema path.
Notes on scope:
- Only the `'ansi'` display branch is capped. `'string'`, `'diff'`,
`'todo'`, `'plan'`, `'task'` renderers are untouched.
- `AnsiOutputDisplay` is only produced by shell tools (`shell.ts`,
`shellCommandProcessor.ts`), so other tool outputs are unaffected.
- The `+N lines` count is bounded by the headless xterm buffer height
(~30 rows) — a pre-existing limitation of the buffer-based stats,
not introduced here.
Tests:
- 4 new ToolMessage tests cover cap default, forceShowResult bypass,
settings disable (cap=0), and custom cap value.
- The existing `MockAnsiOutputText` / `MockShellStatsBar` mocks were
extended to print `availableTerminalHeight` / `displayHeight` so
the cap behavior is asserted at the prop level.
* fix(cli): apply shell output cap to completed string display too
Initial PR caught only the streaming ANSI branch. AI shell tools emit
the final completed result through `shell.ts:returnDisplayMessage =
result.output`, which is a plain string. That string went through
`StringResultRenderer` with the unmodified `availableHeight`, so the
cap was effectively bypassed for the steady-state display the user
actually sees most of the time.
Verified manually in tmux: a `seq 1 30` invocation by the AI now
collapses to "first 26 lines hidden ... 27 28 29 30" instead of
listing all 30 rows. `!`-prefix `seq 1 30` still expands fully via
the existing `isUserInitiated → forceShowResult` bypass.
Changes:
- Detect shell tool by name (matches existing `SHELL_COMMAND_NAME` /
`SHELL_NAME` checks already used in this file)
- Rename `ansiAvailableHeight` → `shellCapHeight` since it now
governs the string branch as well
- Pass `shellCapHeight` to `StringResultRenderer`; the value
falls back to `availableHeight` for non-shell tools so other
tools' string output is unaffected
- Two new tests: shell completed string is capped; non-shell
string is not
- Two existing tests updated to use `name="Shell"` so they actually
exercise the cap path (would previously have passed by accident
since the original code didn't check tool name)
Also picks up the auto-regenerated VSCode IDE companion settings
schema entry for `ui.shellOutputMaxLines`.
* fix(cli): symmetrize ANSI/string row counts and clamp shell cap input
Addresses two non-blocking review observations on #3508.
Off-by-one between paths:
MaxSizedBox reserves one row for its overflow banner when content
exceeds maxHeight (visibleContentHeight = max - 1). The ANSI path
pre-slices to N in AnsiOutputText so MaxSizedBox sees exactly N
rows and renders all N — plus the separate ShellStatsBar line.
The string path passes the raw cap and lets MaxSizedBox handle
overflow, so it shows N-1 content rows + the banner.
Result with cap=5: ANSI showed 5+stats, string showed 4+banner.
Pass shellCapHeight + 1 to StringResultRenderer when capping so
both paths render N visible content rows. Verified in tmux: the
completed Shell tool box now reports `... first 25 lines hidden ...`
followed by lines 26-30 (was 26 + lines 27-30).
Setting validation:
Schema accepts any number; the dialog only rejects NaN. Negatives
silently disabled the cap (only 0 is documented as off) and
fractional values produced fractional slice counts. Added
Math.max(0, Math.floor(value || 0)) at the use site so:
- negatives → 0 → cap disabled (matches the documented opt-out)
- fractions → floor → whole-row cap
- non-numeric (raw settings.json edits) → 0 → cap disabled
Schema-level minimum/integer constraints aren't supported by the
current settings infrastructure (no other number setting uses
them either), so the guard lives at the use site.
Tests:
- Updated string-cap test to assert lines 26-30 visible (catches
the +1 fix; was lines 27-30 before)
- New parameterized test covers -1, 1.5, and a non-numeric value
|
||
|---|---|---|
| .github | ||
| .husky | ||
| .qwen | ||
| .vscode | ||
| docs | ||
| docs-site | ||
| eslint-rules | ||
| integration-tests | ||
| packages | ||
| scripts | ||
| .dockerignore | ||
| .editorconfig | ||
| .gitattributes | ||
| .gitignore | ||
| .npmrc | ||
| .nvmrc | ||
| .prettierignore | ||
| .prettierrc.json | ||
| .yamllint.yml | ||
| AGENTS.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| esbuild.config.js | ||
| eslint.config.js | ||
| LICENSE | ||
| Makefile | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| SECURITY.md | ||
| tsconfig.json | ||
| vitest.config.ts | ||
An open-source AI agent that lives in your terminal.
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🎉 News
-
2026-04-15: Qwen OAuth free tier has been discontinued. To continue using Qwen Code, switch to Alibaba Cloud Coding Plan, OpenRouter, Fireworks AI, or bring your own API key. Run
qwen authto configure. -
2026-04-13: Qwen OAuth free tier policy update: daily quota adjusted to 100 requests/day (from 1,000).
-
2026-04-02: Qwen3.6-Plus is now live! Get an API key from Alibaba Cloud ModelStudio to access it through the OpenAI-compatible API.
-
2026-02-16: Qwen3.5-Plus is now live!
Why Qwen Code?
Qwen Code is an open-source AI agent for the terminal, optimized for Qwen series models. It helps you understand large codebases, automate tedious work, and ship faster.
- Multi-protocol, flexible providers: use OpenAI / Anthropic / Gemini-compatible APIs, Alibaba Cloud Coding Plan, OpenRouter, Fireworks AI, or bring your own API key.
- Open-source, co-evolving: both the framework and the Qwen3-Coder model are open-source—and they ship and evolve together.
- Agentic workflow, feature-rich: rich built-in tools (Skills, SubAgents) for a full agentic workflow and a Claude Code-like experience.
- Terminal-first, IDE-friendly: built for developers who live in the command line, with optional integration for VS Code, Zed, and JetBrains IDEs.
Installation
Quick Install (Recommended)
Linux / macOS
bash -c "$(curl -fsSL https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen.sh)"
Windows (Run as Administrator)
Works in both Command Prompt and PowerShell:
powershell -Command "Invoke-WebRequest 'https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen.bat' -OutFile (Join-Path $env:TEMP 'install-qwen.bat'); & (Join-Path $env:TEMP 'install-qwen.bat')"
Note
: It's recommended to restart your terminal after installation to ensure environment variables take effect.
Manual Installation
Prerequisites
Make sure you have Node.js 20 or later installed. Download it from nodejs.org.
NPM
npm install -g @qwen-code/qwen-code@latest
Homebrew (macOS, Linux)
brew install qwen-code
Quick Start
# Start Qwen Code (interactive)
qwen
# Then, in the session:
/help
/auth
On first use, you'll be prompted to sign in. You can run /auth anytime to switch authentication methods.
Example prompts:
What does this project do?
Explain the codebase structure.
Help me refactor this function.
Generate unit tests for this module.
Click to watch a demo video
🦞 Use Qwen Code for Coding Tasks in Claw
Copy the prompt below and paste it 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.
Authentication
Qwen Code supports the following authentication methods:
- API Key (recommended): use an API key from Alibaba Cloud Model Studio (Beijing / intl) or any supported provider (OpenAI, Anthropic, Google GenAI, and other compatible endpoints).
- Coding Plan: subscribe to the Alibaba Cloud Coding Plan (Beijing / intl) for a fixed monthly fee with higher quotas.
⚠️ Qwen OAuth was discontinued on April 15, 2026. If you were previously using Qwen OAuth, please switch to one of the methods above. Run
qwenand then/authto reconfigure.
API Key (recommended)
Use an API key to connect to Alibaba Cloud Model Studio or any supported provider. Supports multiple protocols:
- OpenAI-compatible: Alibaba Cloud ModelStudio, ModelScope, OpenAI, OpenRouter, and other OpenAI-compatible providers
- Anthropic: Claude models
- Google GenAI: Gemini models
The recommended way to configure models and providers is by editing ~/.qwen/settings.json (create it if it doesn't exist). This file lets you define all available models, API keys, and default settings in one place.
Quick Setup in 3 Steps
Step 1: Create or edit ~/.qwen/settings.json
Here is a complete example:
{
"modelProviders": {
"openai": [
{
"id": "qwen3.6-plus",
"name": "qwen3.6-plus",
"baseUrl": "https://dashscope.aliyuncs.com/compatible-mode/v1",
"description": "Qwen3-Coder via Dashscope",
"envKey": "DASHSCOPE_API_KEY"
}
]
},
"env": {
"DASHSCOPE_API_KEY": "sk-xxxxxxxxxxxxx"
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "qwen3.6-plus"
}
}
Step 2: Understand each field
| Field | What it does |
|---|---|
modelProviders |
Declares which models are available and how to connect to them. Keys like openai, anthropic, gemini represent the API protocol. |
modelProviders[].id |
The model ID sent to the API (e.g. qwen3.6-plus, gpt-4o). |
modelProviders[].envKey |
The name of the environment variable that holds your API key. |
modelProviders[].baseUrl |
The API endpoint URL (required for non-default endpoints). |
env |
A fallback place to store API keys (lowest priority; prefer .env files or export for sensitive keys). |
security.auth.selectedType |
The protocol to use on startup (openai, anthropic, gemini, vertex-ai). |
model.name |
The default model to use when Qwen Code starts. |
Step 3: Start Qwen Code — your configuration takes effect automatically:
qwen
Use the /model command at any time to switch between all configured models.
More Examples
Coding Plan (Alibaba Cloud ModelStudio) — fixed monthly fee, higher quotas
{
"modelProviders": {
"openai": [
{
"id": "qwen3.6-plus",
"name": "qwen3.6-plus (Coding Plan)",
"baseUrl": "https://coding.dashscope.aliyuncs.com/v1",
"description": "qwen3.6-plus from ModelStudio Coding Plan",
"envKey": "BAILIAN_CODING_PLAN_API_KEY"
},
{
"id": "qwen3.5-plus",
"name": "qwen3.5-plus (Coding Plan)",
"baseUrl": "https://coding.dashscope.aliyuncs.com/v1",
"description": "qwen3.5-plus with thinking enabled from ModelStudio Coding Plan",
"envKey": "BAILIAN_CODING_PLAN_API_KEY",
"generationConfig": {
"extra_body": {
"enable_thinking": true
}
}
},
{
"id": "glm-4.7",
"name": "glm-4.7 (Coding Plan)",
"baseUrl": "https://coding.dashscope.aliyuncs.com/v1",
"description": "glm-4.7 with thinking enabled from ModelStudio Coding Plan",
"envKey": "BAILIAN_CODING_PLAN_API_KEY",
"generationConfig": {
"extra_body": {
"enable_thinking": true
}
}
},
{
"id": "kimi-k2.5",
"name": "kimi-k2.5 (Coding Plan)",
"baseUrl": "https://coding.dashscope.aliyuncs.com/v1",
"description": "kimi-k2.5 with thinking enabled from ModelStudio Coding Plan",
"envKey": "BAILIAN_CODING_PLAN_API_KEY",
"generationConfig": {
"extra_body": {
"enable_thinking": true
}
}
}
]
},
"env": {
"BAILIAN_CODING_PLAN_API_KEY": "sk-xxxxxxxxxxxxx"
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "qwen3.6-plus"
}
}
Subscribe to the Coding Plan and get your API key at Alibaba Cloud ModelStudio(Beijing) or Alibaba Cloud ModelStudio(intl).
Multiple providers (OpenAI + Anthropic + Gemini)
{
"modelProviders": {
"openai": [
{
"id": "gpt-4o",
"name": "GPT-4o",
"envKey": "OPENAI_API_KEY",
"baseUrl": "https://api.openai.com/v1"
}
],
"anthropic": [
{
"id": "claude-sonnet-4-20250514",
"name": "Claude Sonnet 4",
"envKey": "ANTHROPIC_API_KEY"
}
],
"gemini": [
{
"id": "gemini-2.5-pro",
"name": "Gemini 2.5 Pro",
"envKey": "GEMINI_API_KEY"
}
]
},
"env": {
"OPENAI_API_KEY": "sk-xxxxxxxxxxxxx",
"ANTHROPIC_API_KEY": "sk-ant-xxxxxxxxxxxxx",
"GEMINI_API_KEY": "AIzaxxxxxxxxxxxxx"
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "gpt-4o"
}
}
Enable thinking mode (for supported models like qwen3.5-plus)
{
"modelProviders": {
"openai": [
{
"id": "qwen3.5-plus",
"name": "qwen3.5-plus (thinking)",
"envKey": "DASHSCOPE_API_KEY",
"baseUrl": "https://dashscope.aliyuncs.com/compatible-mode/v1",
"generationConfig": {
"extra_body": {
"enable_thinking": true
}
}
}
]
},
"env": {
"DASHSCOPE_API_KEY": "sk-xxxxxxxxxxxxx"
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "qwen3.5-plus"
}
}
Tip: You can also set API keys via
exportin your shell or.envfiles, which take higher priority thansettings.json→env. See the authentication guide for full details.
Security note: Never commit API keys to version control. The
~/.qwen/settings.jsonfile is in your home directory and should stay private.
Local Model Setup (Ollama / vLLM)
You can also run models locally — no API key or cloud account needed. This is not an authentication method; instead, configure your local model endpoint in ~/.qwen/settings.json using the modelProviders field.
Ollama setup
- Install Ollama from ollama.com
- Pull a model:
ollama pull qwen3:32b - Configure
~/.qwen/settings.json:
{
"modelProviders": {
"openai": [
{
"id": "qwen3:32b",
"name": "Qwen3 32B (Ollama)",
"baseUrl": "http://localhost:11434/v1",
"description": "Qwen3 32B running locally via Ollama"
}
]
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "qwen3:32b"
}
}
vLLM setup
- Install vLLM:
pip install vllm - Start the server:
vllm serve Qwen/Qwen3-32B - Configure
~/.qwen/settings.json:
{
"modelProviders": {
"openai": [
{
"id": "Qwen/Qwen3-32B",
"name": "Qwen3 32B (vLLM)",
"baseUrl": "http://localhost:8000/v1",
"description": "Qwen3 32B running locally via vLLM"
}
]
},
"security": {
"auth": {
"selectedType": "openai"
}
},
"model": {
"name": "Qwen/Qwen3-32B"
}
}
Usage
As an open-source terminal agent, you can use Qwen Code in four primary ways:
- Interactive mode (terminal UI)
- Headless mode (scripts, CI)
- IDE integration (VS Code, Zed)
- TypeScript SDK
Interactive mode
cd your-project/
qwen
Run qwen in your project folder to launch the interactive terminal UI. Use @ to reference local files (for example @src/main.ts).
Headless mode
cd your-project/
qwen -p "your question"
Use -p to run Qwen Code without the interactive UI—ideal for scripts, automation, and CI/CD. Learn more: Headless mode.
IDE integration
Use Qwen Code inside your editor (VS Code, Zed, and JetBrains IDEs):
TypeScript SDK
Build on top of Qwen Code with the TypeScript SDK:
Commands & Shortcuts
Session Commands
/help- Display available commands/clear- Clear conversation history/compress- Compress history to save tokens/stats- Show current session information/bug- Submit a bug report/exitor/quit- Exit Qwen Code
Keyboard Shortcuts
Ctrl+C- Cancel current operationCtrl+D- Exit (on empty line)Up/Down- Navigate command history
Learn more about Commands
Tip: In YOLO mode (
--yolo), vision switching happens automatically without prompts when images are detected. Learn more about Approval Mode
Configuration
Qwen Code can be configured via settings.json, environment variables, and CLI flags.
| File | Scope | Description |
|---|---|---|
~/.qwen/settings.json |
User (global) | Applies to all your Qwen Code sessions. Recommended for modelProviders and env. |
.qwen/settings.json |
Project | Applies only when running Qwen Code in this project. Overrides user settings. |
The most commonly used top-level fields in settings.json:
| Field | Description |
|---|---|
modelProviders |
Define available models per protocol (openai, anthropic, gemini, vertex-ai). |
env |
Fallback environment variables (e.g. API keys). Lower priority than shell export and .env files. |
security.auth.selectedType |
The protocol to use on startup (e.g. openai). |
model.name |
The default model to use when Qwen Code starts. |
See the Authentication section above for complete
settings.jsonexamples, and the settings reference for all available options.
Benchmark Results
Terminal-Bench Performance
| Agent | Model | Accuracy |
|---|---|---|
| Qwen Code | Qwen3-Coder-480A35 | 37.5% |
| Qwen Code | Qwen3-Coder-30BA3B | 31.3% |
Ecosystem
Looking for a graphical interface?
- 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
Troubleshooting
If you encounter issues, check the troubleshooting guide.
Common issues:
Qwen OAuth free tier was discontinued on 2026-04-15: Qwen OAuth is no longer available. Runqwen→/authand switch to API Key or Coding Plan. See the Authentication section above for setup instructions.
To report a bug from within the CLI, run /bug and include a short title and repro steps.
Connect with Us
- Discord: https://discord.gg/RN7tqZCeDK
- Dingtalk: https://qr.dingtalk.com/action/joingroup?code=v1,k1,+FX6Gf/ZDlTahTIRi8AEQhIaBlqykA0j+eBKKdhLeAE=&_dt_no_comment=1&origin=1
Acknowledgments
This project is based on Google Gemini CLI. We acknowledge and appreciate the excellent work of the Gemini CLI team. Our main contribution focuses on parser-level adaptations to better support Qwen-Coder models.
