Find a file
zhangxy-zju ae424e004b
feat(acp): LLM-based message rewrite middleware with custom prompts (#3191)
* feat(acp): LLM-based message rewrite middleware

Add MessageRewriteMiddleware that intercepts ACP messages and appends
LLM-rewritten versions with _meta.rewritten=true at turn boundaries.

Original messages pass through unmodified. At the end of each turn
(before tool calls or at response end), accumulated thought/message
chunks are sent to LLM for rewriting into business-friendly text.

- TurnBuffer: accumulates chunks per turn
- LlmRewriter: calls LLM with configurable prompt
- MessageRewriteMiddleware: orchestrates intercept → buffer → rewrite → emit
- BaseEmitter.sendUpdate: routes through middleware when configured
- Session: initializes middleware from settings.messageRewrite config

Enable via settings.json:
{
  "messageRewrite": {
    "enabled": true,
    "target": "both",
    "prompt": "custom system prompt for rewriter"
  }
}

Rewritten messages carry _meta.rewritten=true for frontend to
prioritize display. Original messages remain for debugging.

* fix: TypeScript 编译错误修复 + 优化默认改写 prompt(参考竞品风格)

* fix: 从 user/workspace originalSettings 读取 messageRewrite 配置(绕过 schema 校验)

* feat: 非交互 CLI 模式也支持 message rewrite(eval 可用)

* fix: 禁用 rewriter LLM 的 thinking,过滤 thought 部分只取纯文本输出

* fix: cron 路径补齐 message rewrite flush + 代码质量优化

- Session.ts cron 路径添加 messageRewriter.flushTurn() 调用
- nonInteractiveCli.ts cron 路径添加 turnBuffer 累积 + flush + rewrite
- 提取 loadRewriteConfig() 共享函数,消除两处重复配置读取
- 主路径和 cron 路径添加 turnBuffer.markToolCall()
- rewrite 调用添加 30s 超时保护(AbortSignal.timeout)
- 修复 import 语句被 const 声明分割的问题

* feat: rewrite 支持 async/sync 模式(默认 async,不增加执行时间)

* feat: rewrite prompt 通用化 + 上下文连贯 + promptFile + async 修复

- 默认 prompt 改为通用英文版(适配任意 coding agent,不绑定数据分析场景)
- 支持 promptFile 配置项,从文件加载自定义 prompt(优先于 inline prompt)
- 上下文连贯性:lastOutput 记录上一轮改写结果,拼接到下一轮输入,
  避免连续 turn 间信息重复
- 修复 CLI 非交互模式 async rewrite 丢失:void doRewrite() 改为
  pendingRewrites 数组 + emitResult 前 Promise.allSettled
- 增加 debug logging:REWRITE INPUT/OUTPUT 完整内容 + prev_output 长度

* refactor: remove sync rewrite mode, always use async (non-blocking) rewrite

- Remove `async` field from MessageRewriteConfig
- MessageRewriteMiddleware.flushTurn() always fires in background
- nonInteractiveCli.ts main & cron paths always push to pendingRewrites
- No user-facing latency from rewrite calls

* fix: address review feedback — trust check, timeout, history replay

1. loadRewriteConfig: skip workspace settings when !isTrusted, preventing
   untrusted repos from enabling rewriter with a custom prompt
2. MessageRewriteMiddleware.flushTurn: always enforce 30s timeout internally,
   even when caller provides no AbortSignal (interactive path)
3. Install rewriter AFTER history replay completes (Session.installRewriter),
   so historical messages are never rewritten on session load

* fix: address second round review — target filter, timeout, rewrite queue

1. nonInteractiveCli: apply rewriteConfig.target filter to accumulation
   (main path and cron path), matching MessageRewriteMiddleware behavior
2. nonInteractiveCli: add 30s AbortSignal.timeout to rewrite calls in
   both main and cron paths
3. MessageRewriteMiddleware: replace single pendingRewrite slot with
   pendingRewrites array + Promise.allSettled, ensuring all rewrites
   complete before session exits

* test: add unit tests for TurnBuffer, loadRewriteConfig, MessageRewriteMiddleware

- TurnBuffer: flush, reset, isEmpty, markToolCall, whitespace filtering (12 tests)
- loadRewriteConfig: isTrusted gating, workspace/user precedence (5 tests)
- MessageRewriteMiddleware: target filtering, tool_call boundary flush,
  pendingRewrites queue, rewrite metadata (9 tests)

* fix: config.test.ts use unknown cast for LoadedSettings stub (fix tsc --build)

* fix: filter LLM literal "empty string" responses in rewriter output

LLM sometimes outputs "(空字符串)" or similar text instead of actual
empty string when instructed to "return empty string". Add regex patterns
to catch common variants and treat them as null (skip rewrite output).

* revert: remove LLM empty-string pattern defense, rely on prompt fix instead

* fix: prevent async rewrite from corrupting adapter state + honor config.model

1. nonInteractiveCli: rewrite promises now return data only, adapter
   emission happens synchronously via emitSettledRewrites() at safe
   boundaries (before next turn starts, before cron next turn, before
   final result). Prevents concurrent startAssistantMessage corruption.
2. LlmRewriter: use rewriteConfig.model when set, fallback to
   config.getModel(). Previously model field was defined but ignored.

* docs: add messageRewrite configuration guide to settings.md

* Revert "docs: add messageRewrite configuration guide to settings.md"

This reverts commit ecd57e2d5a.

* feat: add contextTurns config for rewrite history context

Allow configuring how many previous rewrite outputs are included as
context when rewriting a new turn:
- contextTurns: 1 (default) = last rewrite only
- contextTurns: 0 = no context
- contextTurns: N = last N rewrites
- contextTurns: "all" = all previous rewrites

* refactor: rename target 'both' to 'all' + add LlmRewriter unit tests

- Rename target value 'both' → 'all' for future extensibility (e.g. 'tool')
- Add LlmRewriter tests: contextTurns (0/1/N/all), model override, filtering
- Total: 35 tests across 4 test files

* refactor: remove message rewrite from non-interactive CLI mode

Non-interactive mode (qwen -p "..." --output-format json) consumers are
scripts/programs that don't need user-friendly rewrites. Additionally,
the JSON output adapter doesn't support _meta fields, so rewritten text
was silently mixed into normal assistant messages without any marker.

Rewrite middleware is now ACP-only (Session path).

* revert: restore package-lock.json and nonInteractiveCli.ts to main state

* docs: add README for message rewrite middleware

Explain the feature purpose (business-oriented output customization),
mark it as a temporary solution, and reference the hook-based
alternative (#3266) for future discussion.

* docs: move temporary-solution notice to top of README

* docs: simplify temporary-solution notice in rewrite README
2026-04-15 14:53:24 +08:00
.github ci(release): parallelize release validation (#3132) 2026-04-13 17:16:53 +08:00
.husky Sync upstream Gemini-CLI v0.8.2 (#838) 2025-10-23 09:27:04 +08:00
.qwen docs: update quota exceeded alternatives to OpenRouter and Fireworks (#3217) 2026-04-13 21:45:38 +08:00
.vscode Merge branch 'main' into feat/sandbox-config-improvements 2026-03-06 14:38:39 +08:00
docs feat(core): implement fork subagent for context sharing (#2936) 2026-04-14 14:27:38 +08:00
docs-site feat: update docs 2025-12-15 09:47:03 +08:00
eslint-rules pre-release commit 2025-07-22 23:26:01 +08:00
integration-tests feat: add bugfix workflow, test-engineer agent, and debugging skills 2026-04-04 18:30:09 +08:00
packages feat(acp): LLM-based message rewrite middleware with custom prompts (#3191) 2026-04-15 14:53:24 +08:00
scripts refactor: merge test-utils package into core (#3200) 2026-04-13 17:11:03 +08:00
.dockerignore fix(cli): skip stdin read for ACP mode 2026-03-27 11:47:01 +00:00
.editorconfig pre-release commit 2025-07-22 23:26:01 +08:00
.gitattributes pre-release commit 2025-07-22 23:26:01 +08:00
.gitignore feat: add bugfix workflow, test-engineer agent, and debugging skills 2026-04-04 18:30:09 +08:00
.npmrc chore: remove google registry 2025-08-08 20:45:54 +08:00
.nvmrc chore: Expand node version test matrix (#2700) 2025-07-21 16:33:54 -07:00
.prettierignore Merge branch 'main' into feat/add-vscode-settings-json-schema 2026-03-03 11:21:57 +08:00
.prettierrc.json pre-release commit 2025-07-22 23:26:01 +08:00
.yamllint.yml Sync upstream Gemini-CLI v0.8.2 (#838) 2025-10-23 09:27:04 +08:00
AGENTS.md feat: add bugfix workflow, test-engineer agent, and debugging skills 2026-04-04 18:30:09 +08:00
CONTRIBUTING.md docs: add Screenshots/Video Demo section to PR template 2026-03-20 16:59:53 +08:00
Dockerfile refactor: Extract web-templates package and unify build/pack workflow 2026-02-26 21:02:46 +08:00
esbuild.config.js feat: add wasm build config (#2985) 2026-04-09 14:21:00 +08:00
eslint.config.js feat: add bugfix workflow, test-engineer agent, and debugging skills 2026-04-04 18:30:09 +08:00
LICENSE Sync upstream Gemini-CLI v0.8.2 (#838) 2025-10-23 09:27:04 +08:00
Makefile feat: update docs 2025-12-22 21:11:33 +08:00
package-lock.json chore: bump version to 0.14.4 (#3209) 2026-04-13 18:15:54 +08:00
package.json chore: bump version to 0.14.4 (#3209) 2026-04-13 18:15:54 +08:00
README.md docs: update quota exceeded alternatives to OpenRouter and Fireworks (#3217) 2026-04-13 21:45:38 +08:00
SECURITY.md fix: update security vulnerability reporting channel 2026-02-24 14:22:47 +08:00
tsconfig.json # 🚀 Sync Gemini CLI v0.2.1 - Major Feature Update (#483) 2025-09-01 14:48:55 +08:00
vitest.config.ts test(channels): add comprehensive test suites for channel adapters 2026-03-27 15:26:39 +00:00

npm version License Node.js Version Downloads

QwenLM%2Fqwen-code | Trendshift

An open-source AI agent that lives in your terminal.

中文 | Deutsch | français | 日本語 | Русский | Português (Brasil)

🎉 News

  • 2026-04-13: Qwen OAuth free tier policy update: daily quota adjusted to 100 requests/day (from 1,000). The free tier will be discontinued on 2026-04-15. Consider using OpenRouter, Fireworks AI, or Alibaba Cloud ModelStudio as alternatives.

  • 2026-04-02: Qwen3.6-Plus is now live! Sign in via Qwen OAuth to use it directly, or 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, OAuth free tier: use OpenAI / Anthropic / Gemini-compatible APIs, or sign in with Qwen OAuth for 100 free requests/day (free tier ending 2026-04-15). After that, switch to OpenRouter, Fireworks AI, or Alibaba Cloud ModelStudio.
  • 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

Linux / macOS

bash -c "$(curl -fsSL https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen.sh)"

Windows (Run as Administrator CMD)

curl -fsSL -o %TEMP%\install-qwen.bat https://qwen-code-assets.oss-cn-hangzhou.aliyuncs.com/installation/install-qwen.bat && %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 two authentication methods:

  • Qwen OAuth (recommended & free): sign in with your qwen.ai account in a browser.
  • API-KEY: use an API key to connect to any supported provider (OpenAI, Anthropic, Google GenAI, Alibaba Cloud ModelStudio, and other compatible endpoints).

Start qwen, then run:

/auth

Choose Qwen OAuth and complete the browser flow. Your credentials are cached locally so you usually won't need to log in again.

Note: In non-interactive or headless environments (e.g., CI, SSH, containers), you typically cannot complete the OAuth browser login flow. In these cases, please use the API-KEY authentication method.

API-KEY (flexible)

Use this if you want more flexibility over which provider and model to use. 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 export in your shell or .env files, which take higher priority than settings.jsonenv. See the authentication guide for full details.

Security note: Never commit API keys to version control. The ~/.qwen/settings.json file is in your home directory and should stay private.

Usage

As an open-source terminal agent, you can use Qwen Code in four primary ways:

  1. Interactive mode (terminal UI)
  2. Headless mode (scripts, CI)
  3. IDE integration (VS Code, Zed)
  4. 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
  • /exit or /quit - Exit Qwen Code

Keyboard Shortcuts

  • Ctrl+C - Cancel current operation
  • Ctrl+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.json examples, 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.

To report a bug from within the CLI, run /bug and include a short title and repro steps.

Connect with Us

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.