Qwen Code Configuration

Configuration layers

Configuration is applied in the following order of precedence (lower numbers are overridden by higher numbers):

Settings files

Qwen Code uses JSON settings files for persistent configuration. There are four locations for these files:

The .qwen directory in your project

In addition to a project settings file, a project’s .qwen directory can contain other project-specific files related to Qwen Code’s operation, such as:

• Custom sandbox profiles (e.g. .qwen/sandbox-macos-custom.sb, .qwen/sandbox.Dockerfile).

Available settings in settings.json

Settings are organized into categories. All settings should be placed within their corresponding top-level category object in your settings.json file.

general

output

ui

ide

privacy

model

Example model.generationConfig:

{
  "model": {
    "generationConfig": {
      "timeout": 60000,
      "disableCacheControl": false,
      "samplingParams": {
        "temperature": 0.2,
        "top_p": 0.8,
        "max_tokens": 1024
      }
    }
  }
}

model.openAILoggingDir examples:

• "~/qwen-logs" - Logs to ~/qwen-logs directory
• "./custom-logs" - Logs to ./custom-logs relative to current directory
• "/tmp/openai-logs" - Logs to absolute path /tmp/openai-logs

context

Troubleshooting File Search Performance

If you are experiencing performance issues with file searching (e.g., with @ completions), especially in projects with a very large number of files, here are a few things you can try in order of recommendation:

1. Use .qwenignore: Create a .qwenignore file in your project root to exclude directories that contain a large number of files that you don’t need to reference (e.g., build artifacts, logs, node_modules). Reducing the total number of files crawled is the most effective way to improve performance.
2. Disable Fuzzy Search: If ignoring files is not enough, you can disable fuzzy search by setting disableFuzzySearch to true in your settings.json file. This will use a simpler, non-fuzzy matching algorithm, which can be faster.
3. Disable Recursive File Search: As a last resort, you can disable recursive file search entirely by setting enableRecursiveFileSearch to false. This will be the fastest option as it avoids a recursive crawl of your project. However, it means you will need to type the full path to files when using @ completions.

tools

mcp

security

advanced

mcpServers

Configures connections to one or more Model-Context Protocol (MCP) servers for discovering and using custom tools. Qwen Code attempts to connect to each configured MCP server to discover available tools. If multiple MCP servers expose a tool with the same name, the tool names will be prefixed with the server alias you defined in the configuration (e.g., serverAlias__actualToolName) to avoid conflicts. Note that the system might strip certain schema properties from MCP tool definitions for compatibility. At least one of command, url, or httpUrl must be provided. If multiple are specified, the order of precedence is httpUrl, then url, then command.

telemetry

Configures logging and metrics collection for Qwen Code. For more information, see telemetry.

Example settings.json

Here is an example of a settings.json file with the nested structure, new as of v0.3.0:

{
  "general": {
    "vimMode": true,
    "preferredEditor": "code"
  },
  "ui": {
    "theme": "GitHub",
    "hideBanner": true,
    "hideTips": false,
    "customWittyPhrases": [
      "You forget a thousand things every day. Make sure this is one of 'em",
      "Connecting to AGI"
    ]
  },
  "tools": {
    "approvalMode": "yolo",
    "sandbox": "docker",
    "discoveryCommand": "bin/get_tools",
    "callCommand": "bin/call_tool",
    "exclude": ["write_file"]
  },
  "mcpServers": {
    "mainServer": {
      "command": "bin/mcp_server.py"
    },
    "anotherServer": {
      "command": "node",
      "args": ["mcp_server.js", "--verbose"]
    }
  },
  "telemetry": {
    "enabled": true,
    "target": "local",
    "otlpEndpoint": "http://localhost:4317",
    "logPrompts": true
  },
  "privacy": {
    "usageStatisticsEnabled": true
  },
  "model": {
    "name": "qwen3-coder-plus",
    "maxSessionTurns": 10,
    "enableOpenAILogging": false,
    "openAILoggingDir": "~/qwen-logs",
    "summarizeToolOutput": {
      "run_shell_command": {
        "tokenBudget": 100
      }
    }
  },
  "context": {
    "fileName": ["CONTEXT.md", "QWEN.md"],
    "includeDirectories": ["path/to/dir1", "~/path/to/dir2", "../path/to/dir3"],
    "loadFromIncludeDirectories": true,
    "fileFiltering": {
      "respectGitIgnore": false
    }
  },
  "advanced": {
    "excludedEnvVars": ["DEBUG", "DEBUG_MODE", "NODE_ENV"]
  }
}

Shell History

The CLI keeps a history of shell commands you run. To avoid conflicts between different projects, this history is stored in a project-specific directory within your user’s home folder.

• Location: ~/.qwen/tmp/<project_hash>/shell_history
  • <project_hash> is a unique identifier generated from your project’s root path.
  • The history is stored in a file named shell_history.

Environment Variables & .env Files

Environment variables are a common way to configure applications, especially for sensitive information (like tokens) or for settings that might change between environments.

Qwen Code can automatically load environment variables from .env files. For authentication-related variables (like OPENAI_*) and the recommended .qwen/.env approach, see Authentication.

Environment Variables Table

Command-Line Arguments

Arguments passed directly when running the CLI can override other configurations for that specific session.

Command-Line Arguments Table

Context Files (Hierarchical Instructional Context)

While not strictly configuration for the CLI’s behavior, context files (defaulting to QWEN.md but configurable via the context.fileName setting) are crucial for configuring the instructional context (also referred to as “memory”). This powerful feature allows you to give project-specific instructions, coding style guides, or any relevant background information to the AI, making its responses more tailored and accurate to your needs. The CLI includes UI elements, such as an indicator in the footer showing the number of loaded context files, to keep you informed about the active context.

• Purpose: These Markdown files contain instructions, guidelines, or context that you want the Qwen model to be aware of during your interactions. The system is designed to manage this instructional context hierarchically.

Example Context File Content (e.g. QWEN.md)

Here’s a conceptual example of what a context file at the root of a TypeScript project might contain:

# Project: My Awesome TypeScript Library

## General Instructions:
- When generating new TypeScript code, please follow the existing coding style.
- Ensure all new functions and classes have JSDoc comments.
- Prefer functional programming paradigms where appropriate.
- All code should be compatible with TypeScript 5.0 and Node.js 20+.

## Coding Style:
- Use 2 spaces for indentation.
- Interface names should be prefixed with `I` (e.g., `IUserService`).
- Private class members should be prefixed with an underscore (`_`).
- Always use strict equality (`===` and `!==`).

## Specific Component: `src/api/client.ts`
- This file handles all outbound API requests.
- When adding new API call functions, ensure they include robust error handling and logging.
- Use the existing `fetchWithRetry` utility for all GET requests.

## Regarding Dependencies:
- Avoid introducing new external dependencies unless absolutely necessary.
- If a new dependency is required, please state the reason.

This example demonstrates how you can provide general project context, specific coding conventions, and even notes about particular files or components. The more relevant and precise your context files are, the better the AI can assist you. Project-specific context files are highly encouraged to establish conventions and context.

• Hierarchical Loading and Precedence: The CLI implements a sophisticated hierarchical memory system by loading context files (e.g., QWEN.md) from several locations. Content from files lower in this list (more specific) typically overrides or supplements content from files higher up (more general). The exact concatenation order and final context can be inspected using the /memory show command. The typical loading order is:
  1. Global Context File:
     • Location: ~/.qwen/<configured-context-filename> (e.g., ~/.qwen/QWEN.md in your user home directory).
     • Scope: Provides default instructions for all your projects.
  2. Project Root & Ancestors Context Files:
     • Location: The CLI searches for the configured context file in the current working directory and then in each parent directory up to either the project root (identified by a .git folder) or your home directory.
     • Scope: Provides context relevant to the entire project or a significant portion of it.
  3. Sub-directory Context Files (Contextual/Local):
     • Location: The CLI also scans for the configured context file in subdirectories below the current working directory (respecting common ignore patterns like node_modules, .git, etc.). The breadth of this search is limited to 200 directories by default, but can be configured with the context.discoveryMaxDirs setting in your settings.json file.
     • Scope: Allows for highly specific instructions relevant to a particular component, module, or subsection of your project.
• Concatenation & UI Indication: The contents of all found context files are concatenated (with separators indicating their origin and path) and provided as part of the system prompt. The CLI footer displays the count of loaded context files, giving you a quick visual cue about the active instructional context.
• Importing Content: You can modularize your context files by importing other Markdown files using the @path/to/file.md syntax. For more details, see the Memory Import Processor documentation.
• Commands for Memory Management:
  • Use /memory refresh to force a re-scan and reload of all context files from all configured locations. This updates the AI’s instructional context.
  • Use /memory show to display the combined instructional context currently loaded, allowing you to verify the hierarchy and content being used by the AI.
  • See the Commands documentation for full details on the /memory command and its sub-commands (show and refresh).

By understanding and utilizing these configuration layers and the hierarchical nature of context files, you can effectively manage the AI’s memory and tailor Qwen Code’s responses to your specific needs and projects.

Sandbox

Qwen Code can execute potentially unsafe operations (like shell commands and file modifications) within a sandboxed environment to protect your system.

Sandbox is disabled by default, but you can enable it in a few ways:

• Using --sandbox or -s flag.
• Setting GEMINI_SANDBOX environment variable.
• Sandbox is enabled when using --yolo or --approval-mode=yolo by default.

By default, it uses a pre-built qwen-code-sandbox Docker image.

For project-specific sandboxing needs, you can create a custom Dockerfile at .qwen/sandbox.Dockerfile in your project’s root directory. This Dockerfile can be based on the base sandbox image:

FROM qwen-code-sandbox
# Add your custom dependencies or configurations here
# For example:
# RUN apt-get update && apt-get install -y some-package
# COPY ./my-config /app/my-config

When .qwen/sandbox.Dockerfile exists, you can use BUILD_SANDBOX environment variable when running Qwen Code to automatically build the custom sandbox image:

BUILD_SANDBOX=1 qwen -s

Usage Statistics

To help us improve Qwen Code, we collect anonymized usage statistics. This data helps us understand how the CLI is used, identify common issues, and prioritize new features.

What we collect:

• Tool Calls: We log the names of the tools that are called, whether they succeed or fail, and how long they take to execute. We do not collect the arguments passed to the tools or any data returned by them.
• API Requests: We log the model used for each request, the duration of the request, and whether it was successful. We do not collect the content of the prompts or responses.
• Session Information: We collect information about the configuration of the CLI, such as the enabled tools and the approval mode.

What we DON’T collect:

• Personally Identifiable Information (PII): We do not collect any personal information, such as your name, email address, or API keys.
• Prompt and Response Content: We do not log the content of your prompts or the responses from the model.
• File Content: We do not log the content of any files that are read or written by the CLI.

How to opt out:

You can opt out of usage statistics collection at any time by setting the usageStatisticsEnabled property to false under the privacy category in your settings.json file:

{
  "privacy": {
    "usageStatisticsEnabled": false
  }
}