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# Authentication Setup
The Qwen Code CLI supports multiple authentication methods. On initial startup you'll need to configure **one** of the following authentication methods:
1. **Login with Google (Gemini Code Assist):**
- Use this option to log in with your google account.
- During initial startup, Gemini CLI will direct you to a webpage for authentication. Once authenticated, your credentials will be cached locally so the web login can be skipped on subsequent runs.
- Note that the web login must be done in a browser that can communicate with the machine Gemini CLI is being run from. (Specifically, the browser will be redirected to a localhost url that Gemini CLI will be listening on).
- <a id="workspace-gca">Users may have to specify a GOOGLE_CLOUD_PROJECT if:</a>
1. You have a Google Workspace account. Google Workspace is a paid service for businesses and organizations that provides a suite of productivity tools, including a custom email domain (e.g. your-name@your-company.com), enhanced security features, and administrative controls. These accounts are often managed by an employer or school.
1. You have received a free Code Assist license through the [Google Developer Program](https://developers.google.com/program/plans-and-pricing) (including qualified Google Developer Experts)
1. You have been assigned a license to a current Gemini Code Assist standard or enterprise subscription.
1. You are using the product outside the [supported regions](https://developers.google.com/gemini-code-assist/resources/available-locations) for free individual usage.
1. You are a Google account holder under the age of 18
- If you fall into one of these categories, you must first configure a Google Cloud Project Id to use, [enable the Gemini for Cloud API](https://cloud.google.com/gemini/docs/discover/set-up-gemini#enable-api) and [configure access permissions](https://cloud.google.com/gemini/docs/discover/set-up-gemini#grant-iam).
You can temporarily set the environment variable in your current shell session using the following command:
```bash
export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"
```
- For repeated use, you can add the environment variable to your [.env file](#persisting-environment-variables-with-env-files) or your shell's configuration file (like `~/.bashrc`, `~/.zshrc`, or `~/.profile`). For example, the following command adds the environment variable to a `~/.bashrc` file:
```bash
echo 'export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"' >> ~/.bashrc
source ~/.bashrc
```
2. **<a id="gemini-api-key"></a>Gemini API key:**
- Obtain your API key from Google AI Studio: [https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey)
- Set the `GEMINI_API_KEY` environment variable. In the following methods, replace `YOUR_GEMINI_API_KEY` with the API key you obtained from Google AI Studio:
- You can temporarily set the environment variable in your current shell session using the following command:
```bash
export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"
```
- For repeated use, you can add the environment variable to your [.env file](#persisting-environment-variables-with-env-files) or your shell's configuration file (like `~/.bashrc`, `~/.zshrc`, or `~/.profile`). For example, the following command adds the environment variable to a `~/.bashrc` file:
```bash
echo 'export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"' >> ~/.bashrc
source ~/.bashrc
```
3. **Vertex AI:**
- Obtain your Google Cloud API key: [Get an API Key](https://cloud.google.com/vertex-ai/generative-ai/docs/start/api-keys?usertype=newuser)
- Set the `GOOGLE_API_KEY` environment variable. In the following methods, replace `YOUR_GOOGLE_API_KEY` with your Vertex AI API key:
- You can temporarily set these environment variables in your current shell session using the following commands:
```bash
export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"
```
- For repeated use, you can add the environment variables to your [.env file](#persisting-environment-variables-with-env-files) or your shell's configuration file (like `~/.bashrc`, `~/.zshrc`, or `~/.profile`). For example, the following commands add the environment variables to a `~/.bashrc` file:
```bash
echo 'export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"' >> ~/.bashrc
source ~/.bashrc
```
- To use Application Default Credentials (ADC), use the following command:
- Ensure you have a Google Cloud project and have enabled the Vertex AI API.
```bash
gcloud auth application-default login
```
For more information, see [Set up Application Default Credentials for Google Cloud](https://cloud.google.com/docs/authentication/provide-credentials-adc).
- Set the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` environment variables. In the following methods, replace `YOUR_PROJECT_ID` and `YOUR_PROJECT_LOCATION` with the relevant values for your project:
- You can temporarily set these environment variables in your current shell session using the following commands:
```bash
export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"
export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION" # e.g., us-central1
```
- For repeated use, you can add the environment variables to your [.env file](#persisting-environment-variables-with-env-files) or your shell's configuration file (like `~/.bashrc`, `~/.zshrc`, or `~/.profile`). For example, the following commands add the environment variables to a `~/.bashrc` file:
```bash
echo 'export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"' >> ~/.bashrc
echo 'export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION"' >> ~/.bashrc
source ~/.bashrc
```
4. **Cloud Shell:**
- This option is only available when running in a Google Cloud Shell environment.
- It automatically uses the credentials of the logged-in user in the Cloud Shell environment.
- This is the default authentication method when running in Cloud Shell and no other method is configured.
### Persisting Environment Variables with `.env` Files
You can create a **`.qwen/.env`** file in your project directory or in your home directory. Creating a plain **`.env`** file also works, but `.qwen/.env` is recommended to keep Gemini variables isolated from other tools.
Gemini CLI automatically loads environment variables from the **first** `.env` file it finds, using the following search order:
1. Starting in the **current directory** and moving upward toward `/`, for each directory it checks:
1. `.qwen/.env`
2. `.env`
2. If no file is found, it falls back to your **home directory**:
- `~/.qwen/.env`
- `~/.env`
> **Important:** The search stops at the **first** file encountered—variables are **not merged** across multiple files.
#### Examples
**Project-specific overrides** (take precedence when you are inside the project):
```bash
mkdir -p .gemini
echo 'GOOGLE_CLOUD_PROJECT="your-project-id"' >> .qwen/.env
```
**User-wide settings** (available in every directory):
```bash
mkdir -p ~/.gemini
cat >> ~/.qwen/.env <<'EOF'
GOOGLE_CLOUD_PROJECT="your-project-id"
GEMINI_API_KEY="your-gemini-api-key"
EOF
```
5. **OpenAI Authentication:**
- Use OpenAI models instead of Google's Gemini models
- For detailed setup instructions, see [OpenAI Authentication](./openai-auth.md)
- Supports interactive setup, command line arguments, and environment variables

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# CLI Commands
Gemini CLI supports several built-in commands to help you manage your session, customize the interface, and control its behavior. These commands are prefixed with a forward slash (`/`), an at symbol (`@`), or an exclamation mark (`!`).
## Slash commands (`/`)
Slash commands provide meta-level control over the CLI itself.
- **`/bug`**
- **Description:** File an issue about Gemini CLI. By default, the issue is filed within the GitHub repository for Gemini CLI. The string you enter after `/bug` will become the headline for the bug being filed. The default `/bug` behavior can be modified using the `bugCommand` setting in your `.qwen/settings.json` files.
- **`/chat`**
- **Description:** Save and resume conversation history for branching conversation state interactively, or resuming a previous state from a later session.
- **Sub-commands:**
- **`save`**
- **Description:** Saves the current conversation history. You must add a `<tag>` for identifying the conversation state.
- **Usage:** `/chat save <tag>`
- **`resume`**
- **Description:** Resumes a conversation from a previous save.
- **Usage:** `/chat resume <tag>`
- **`list`**
- **Description:** Lists available tags for chat state resumption.
- **`/clear`**
- **Description:** Clear the terminal screen, including the visible session history and scrollback within the CLI. The underlying session data (for history recall) might be preserved depending on the exact implementation, but the visual display is cleared.
- **Keyboard shortcut:** Press **Ctrl+L** at any time to perform a clear action.
- **`/compress`**
- **Description:** Replace the entire chat context with a summary. This saves on tokens used for future tasks while retaining a high level summary of what has happened.
- **`/editor`**
- **Description:** Open a dialog for selecting supported editors.
- **`/extensions`**
- **Description:** Lists all active extensions in the current Gemini CLI session. See [Gemini CLI Extensions](../extension.md).
- **`/help`** (or **`/?`**)
- **Description:** Display help information about the Gemini CLI, including available commands and their usage.
- **`/mcp`**
- **Description:** List configured Model Context Protocol (MCP) servers, their connection status, server details, and available tools.
- **Sub-commands:**
- **`desc`** or **`descriptions`**:
- **Description:** Show detailed descriptions for MCP servers and tools.
- **`nodesc`** or **`nodescriptions`**:
- **Description:** Hide tool descriptions, showing only the tool names.
- **`schema`**:
- **Description:** Show the full JSON schema for the tool's configured parameters.
- **Keyboard Shortcut:** Press **Ctrl+T** at any time to toggle between showing and hiding tool descriptions.
- **`/memory`**
- **Description:** Manage the AI's instructional context (hierarchical memory loaded from `GEMINI.md` files).
- **Sub-commands:**
- **`add`**:
- **Description:** Adds the following text to the AI's memory. Usage: `/memory add <text to remember>`
- **`show`**:
- **Description:** Display the full, concatenated content of the current hierarchical memory that has been loaded from all `GEMINI.md` files. This lets you inspect the instructional context being provided to the Gemini model.
- **`refresh`**:
- **Description:** Reload the hierarchical instructional memory from all `GEMINI.md` files found in the configured locations (global, project/ancestors, and sub-directories). This command updates the model with the latest `GEMINI.md` content.
- **Note:** For more details on how `GEMINI.md` files contribute to hierarchical memory, see the [CLI Configuration documentation](./configuration.md#4-geminimd-files-hierarchical-instructional-context).
- **`/restore`**
- **Description:** Restores the project files to the state they were in just before a tool was executed. This is particularly useful for undoing file edits made by a tool. If run without a tool call ID, it will list available checkpoints to restore from.
- **Usage:** `/restore [tool_call_id]`
- **Note:** Only available if the CLI is invoked with the `--checkpointing` option or configured via [settings](./configuration.md). See [Checkpointing documentation](../checkpointing.md) for more details.
- **`/stats`**
- **Description:** Display detailed statistics for the current Gemini CLI session, including token usage, cached token savings (when available), and session duration. Note: Cached token information is only displayed when cached tokens are being used, which occurs with API key authentication but not with OAuth authentication at this time.
- [**`/theme`**](./themes.md)
- **Description:** Open a dialog that lets you change the visual theme of Gemini CLI.
- **`/auth`**
- **Description:** Open a dialog that lets you change the authentication method.
- **`/about`**
- **Description:** Show version info. Please share this information when filing issues.
- [**`/tools`**](../tools/index.md)
- **Description:** Display a list of tools that are currently available within Gemini CLI.
- **Sub-commands:**
- **`desc`** or **`descriptions`**:
- **Description:** Show detailed descriptions of each tool, including each tool's name with its full description as provided to the model.
- **`nodesc`** or **`nodescriptions`**:
- **Description:** Hide tool descriptions, showing only the tool names.
- **`/privacy`**
- **Description:** Display the Privacy Notice and allow users to select whether they consent to the collection of their data for service improvement purposes.
- **`/quit`** (or **`/exit`**)
- **Description:** Exit Gemini CLI.
## At commands (`@`)
At commands are used to include the content of files or directories as part of your prompt to Gemini. These commands include git-aware filtering.
- **`@<path_to_file_or_directory>`**
- **Description:** Inject the content of the specified file or files into your current prompt. This is useful for asking questions about specific code, text, or collections of files.
- **Examples:**
- `@path/to/your/file.txt Explain this text.`
- `@src/my_project/ Summarize the code in this directory.`
- `What is this file about? @README.md`
- **Details:**
- If a path to a single file is provided, the content of that file is read.
- If a path to a directory is provided, the command attempts to read the content of files within that directory and any subdirectories.
- Spaces in paths should be escaped with a backslash (e.g., `@My\ Documents/file.txt`).
- The command uses the `read_many_files` tool internally. The content is fetched and then inserted into your query before being sent to the Gemini model.
- **Git-aware filtering:** By default, git-ignored files (like `node_modules/`, `dist/`, `.env`, `.git/`) are excluded. This behavior can be changed via the `fileFiltering` settings.
- **File types:** The command is intended for text-based files. While it might attempt to read any file, binary files or very large files might be skipped or truncated by the underlying `read_many_files` tool to ensure performance and relevance. The tool indicates if files were skipped.
- **Output:** The CLI will show a tool call message indicating that `read_many_files` was used, along with a message detailing the status and the path(s) that were processed.
- **`@` (Lone at symbol)**
- **Description:** If you type a lone `@` symbol without a path, the query is passed as-is to the Gemini model. This might be useful if you are specifically talking _about_ the `@` symbol in your prompt.
### Error handling for `@` commands
- If the path specified after `@` is not found or is invalid, an error message will be displayed, and the query might not be sent to the Gemini model, or it will be sent without the file content.
- If the `read_many_files` tool encounters an error (e.g., permission issues), this will also be reported.
## Shell mode & passthrough commands (`!`)
The `!` prefix lets you interact with your system's shell directly from within Gemini CLI.
- **`!<shell_command>`**
- **Description:** Execute the given `<shell_command>` in your system's default shell. Any output or errors from the command are displayed in the terminal.
- **Examples:**
- `!ls -la` (executes `ls -la` and returns to Gemini CLI)
- `!git status` (executes `git status` and returns to Gemini CLI)
- **`!` (Toggle shell mode)**
- **Description:** Typing `!` on its own toggles shell mode.
- **Entering shell mode:**
- When active, shell mode uses a different coloring and a "Shell Mode Indicator".
- While in shell mode, text you type is interpreted directly as a shell command.
- **Exiting shell mode:**
- When exited, the UI reverts to its standard appearance and normal Gemini CLI behavior resumes.
- **Caution for all `!` usage:** Commands you execute in shell mode have the same permissions and impact as if you ran them directly in your terminal.

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# Gemini CLI Configuration
Gemini CLI offers several ways to configure its behavior, including environment variables, command-line arguments, and settings files. This document outlines the different configuration methods and available settings.
## Configuration layers
Configuration is applied in the following order of precedence (lower numbers are overridden by higher numbers):
1. **Default values:** Hardcoded defaults within the application.
2. **User settings file:** Global settings for the current user.
3. **Project settings file:** Project-specific settings.
4. **System settings file:** System-wide settings.
5. **Environment variables:** System-wide or session-specific variables, potentially loaded from `.env` files.
6. **Command-line arguments:** Values passed when launching the CLI.
## Settings files
Gemini CLI uses `settings.json` files for persistent configuration. There are three locations for these files:
- **User settings file:**
- **Location:** `~/.qwen/settings.json` (where `~` is your home directory).
- **Scope:** Applies to all Gemini CLI sessions for the current user.
- **Project settings file:**
- **Location:** `.qwen/settings.json` within your project's root directory.
- **Scope:** Applies only when running Gemini CLI from that specific project. Project settings override user settings.
- **System settings file:**
- **Location:** `/etc/gemini-cli/settings.json` (Linux), `C:\ProgramData\gemini-cli\settings.json` (Windows) or `/Library/Application Support/GeminiCli/settings.json` (macOS).
- **Scope:** Applies to all Gemini CLI sessions on the system, for all users. System settings override user and project settings. May be useful for system administrators at enterprises to have controls over users' Gemini CLI setups.
**Note on environment variables in settings:** String values within your `settings.json` files can reference environment variables using either `$VAR_NAME` or `${VAR_NAME}` syntax. These variables will be automatically resolved when the settings are loaded. For example, if you have an environment variable `MY_API_TOKEN`, you could use it in `settings.json` like this: `"apiKey": "$MY_API_TOKEN"`.
### The `.gemini` directory in your project
In addition to a project settings file, a project's `.gemini` directory can contain other project-specific files related to Gemini CLI's operation, such as:
- [Custom sandbox profiles](#sandboxing) (e.g., `.qwen/sandbox-macos-custom.sb`, `.qwen/sandbox.Dockerfile`).
### Available settings in `settings.json`:
- **`contextFileName`** (string or array of strings):
- **Description:** Specifies the filename for context files (e.g., `GEMINI.md`, `AGENTS.md`). Can be a single filename or a list of accepted filenames.
- **Default:** `GEMINI.md`
- **Example:** `"contextFileName": "AGENTS.md"`
- **`bugCommand`** (object):
- **Description:** Overrides the default URL for the `/bug` command.
- **Default:** `"urlTemplate": "https://github.com/google-gemini/gemini-cli/issues/new?template=bug_report.yml&title={title}&info={info}"`
- **Properties:**
- **`urlTemplate`** (string): A URL that can contain `{title}` and `{info}` placeholders.
- **Example:**
```json
"bugCommand": {
"urlTemplate": "https://bug.example.com/new?title={title}&info={info}"
}
```
- **`fileFiltering`** (object):
- **Description:** Controls git-aware file filtering behavior for @ commands and file discovery tools.
- **Default:** `"respectGitIgnore": true, "enableRecursiveFileSearch": true`
- **Properties:**
- **`respectGitIgnore`** (boolean): Whether to respect .gitignore patterns when discovering files. When set to `true`, git-ignored files (like `node_modules/`, `dist/`, `.env`) are automatically excluded from @ commands and file listing operations.
- **`enableRecursiveFileSearch`** (boolean): Whether to enable searching recursively for filenames under the current tree when completing @ prefixes in the prompt.
- **Example:**
```json
"fileFiltering": {
"respectGitIgnore": true,
"enableRecursiveFileSearch": false
}
```
- **`coreTools`** (array of strings):
- **Description:** Allows you to specify a list of core tool names that should be made available to the model. This can be used to restrict the set of built-in tools. See [Built-in Tools](../core/tools-api.md#built-in-tools) for a list of core tools. You can also specify command-specific restrictions for tools that support it, like the `ShellTool`. For example, `"coreTools": ["ShellTool(ls -l)"]` will only allow the `ls -l` command to be executed.
- **Default:** All tools available for use by the Gemini model.
- **Example:** `"coreTools": ["ReadFileTool", "GlobTool", "ShellTool(ls)"]`.
- **`excludeTools`** (array of strings):
- **Description:** Allows you to specify a list of core tool names that should be excluded from the model. A tool listed in both `excludeTools` and `coreTools` is excluded. You can also specify command-specific restrictions for tools that support it, like the `ShellTool`. For example, `"excludeTools": ["ShellTool(rm -rf)"]` will block the `rm -rf` command.
- **Default**: No tools excluded.
- **Example:** `"excludeTools": ["run_shell_command", "findFiles"]`.
- **Security Note:** Command-specific restrictions in
`excludeTools` for `run_shell_command` are based on simple string matching and can be easily bypassed. This feature is **not a security mechanism** and should not be relied upon to safely execute untrusted code. It is recommended to use `coreTools` to explicitly select commands
that can be executed.
- **`autoAccept`** (boolean):
- **Description:** Controls whether the CLI automatically accepts and executes tool calls that are considered safe (e.g., read-only operations) without explicit user confirmation. If set to `true`, the CLI will bypass the confirmation prompt for tools deemed safe.
- **Default:** `false`
- **Example:** `"autoAccept": true`
- **`theme`** (string):
- **Description:** Sets the visual [theme](./themes.md) for Gemini CLI.
- **Default:** `"Default"`
- **Example:** `"theme": "GitHub"`
- **`sandbox`** (boolean or string):
- **Description:** Controls whether and how to use sandboxing for tool execution. If set to `true`, Gemini CLI uses a pre-built `gemini-cli-sandbox` Docker image. For more information, see [Sandboxing](#sandboxing).
- **Default:** `false`
- **Example:** `"sandbox": "docker"`
- **`toolDiscoveryCommand`** (string):
- **Description:** Defines a custom shell command for discovering tools from your project. The shell command must return on `stdout` a JSON array of [function declarations](https://ai.google.dev/gemini-api/docs/function-calling#function-declarations). Tool wrappers are optional.
- **Default:** Empty
- **Example:** `"toolDiscoveryCommand": "bin/get_tools"`
- **`toolCallCommand`** (string):
- **Description:** Defines a custom shell command for calling a specific tool that was discovered using `toolDiscoveryCommand`. The shell command must meet the following criteria:
- It must take function `name` (exactly as in [function declaration](https://ai.google.dev/gemini-api/docs/function-calling#function-declarations)) as first command line argument.
- It must read function arguments as JSON on `stdin`, analogous to [`functionCall.args`](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#functioncall).
- It must return function output as JSON on `stdout`, analogous to [`functionResponse.response.content`](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#functionresponse).
- **Default:** Empty
- **Example:** `"toolCallCommand": "bin/call_tool"`
- **`mcpServers`** (object):
- **Description:** Configures connections to one or more Model-Context Protocol (MCP) servers for discovering and using custom tools. Gemini CLI 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.
- **Default:** Empty
- **Properties:**
- **`<SERVER_NAME>`** (object): The server parameters for the named server.
- `command` (string, required): The command to execute to start the MCP server.
- `args` (array of strings, optional): Arguments to pass to the command.
- `env` (object, optional): Environment variables to set for the server process.
- `cwd` (string, optional): The working directory in which to start the server.
- `timeout` (number, optional): Timeout in milliseconds for requests to this MCP server.
- `trust` (boolean, optional): Trust this server and bypass all tool call confirmations.
- **Example:**
```json
"mcpServers": {
"myPythonServer": {
"command": "python",
"args": ["mcp_server.py", "--port", "8080"],
"cwd": "./mcp_tools/python",
"timeout": 5000
},
"myNodeServer": {
"command": "node",
"args": ["mcp_server.js"],
"cwd": "./mcp_tools/node"
},
"myDockerServer": {
"command": "docker",
"args": ["run", "-i", "--rm", "-e", "API_KEY", "ghcr.io/foo/bar"],
"env": {
"API_KEY": "$MY_API_TOKEN"
}
}
}
```
- **`checkpointing`** (object):
- **Description:** Configures the checkpointing feature, which allows you to save and restore conversation and file states. See the [Checkpointing documentation](../checkpointing.md) for more details.
- **Default:** `{"enabled": false}`
- **Properties:**
- **`enabled`** (boolean): When `true`, the `/restore` command is available.
- **`preferredEditor`** (string):
- **Description:** Specifies the preferred editor to use for viewing diffs.
- **Default:** `vscode`
- **Example:** `"preferredEditor": "vscode"`
- **`telemetry`** (object)
- **Description:** Configures logging and metrics collection for Gemini CLI. For more information, see [Telemetry](../telemetry.md).
- **Default:** `{"enabled": false, "target": "local", "otlpEndpoint": "http://localhost:4317", "logPrompts": true}`
- **Properties:**
- **`enabled`** (boolean): Whether or not telemetry is enabled.
- **`target`** (string): The destination for collected telemetry. Supported values are `local` and `gcp`.
- **`otlpEndpoint`** (string): The endpoint for the OTLP Exporter.
- **`logPrompts`** (boolean): Whether or not to include the content of user prompts in the logs.
- **Example:**
```json
"telemetry": {
"enabled": true,
"target": "local",
"otlpEndpoint": "http://localhost:16686",
"logPrompts": false
}
```
- **`usageStatisticsEnabled`** (boolean):
- **Description:** Enables or disables the collection of usage statistics. See [Usage Statistics](#usage-statistics) for more information.
- **Default:** `true`
- **Example:**
```json
"usageStatisticsEnabled": false
```
- **`hideTips`** (boolean):
- **Description:** Enables or disables helpful tips in the CLI interface.
- **Default:** `false`
- **Example:**
```json
"hideTips": true
```
- **`hideBanner`** (boolean):
- **Description:** Enables or disables the startup banner (ASCII art logo) in the CLI interface.
- **Default:** `false`
- **Example:**
```json
"hideBanner": true
```
- **`maxSessionTurns`** (number):
- **Description:** Sets the maximum number of turns for a session. If the session exceeds this limit, the CLI will stop processing and start a new chat.
- **Default:** `-1` (unlimited)
- **Example:**
```json
"maxSessionTurns": 10
```
- **`enableOpenAILogging`** (boolean):
- **Description:** Enables or disables logging of OpenAI API calls for debugging and analysis. When enabled, all requests and responses to the OpenAI API are logged to files in the `~/.qwen/logs/` directory.
- **Default:** `false`
- **Example:**
```json
"enableOpenAILogging": true
```
### Example `settings.json`:
```json
{
"theme": "GitHub",
"sandbox": "docker",
"toolDiscoveryCommand": "bin/get_tools",
"toolCallCommand": "bin/call_tool",
"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
},
"usageStatisticsEnabled": true,
"hideTips": false,
"hideBanner": false,
"maxSessionTurns": 10,
"enableOpenAILogging": true
}
```
## 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 API keys or for settings that might change between environments.
The CLI automatically loads environment variables from an `.env` file. The loading order is:
1. `.env` file in the current working directory.
2. If not found, it searches upwards in parent directories until it finds an `.env` file or reaches the project root (identified by a `.git` folder) or the home directory.
3. If still not found, it looks for `~/.env` (in the user's home directory).
- **`GEMINI_API_KEY`** (Required):
- Your API key for the Gemini API.
- **Crucial for operation.** The CLI will not function without it.
- Set this in your shell profile (e.g., `~/.bashrc`, `~/.zshrc`) or an `.env` file.
- **`GEMINI_MODEL`**:
- Specifies the default Gemini model to use.
- Overrides the hardcoded default
- Example: `export GEMINI_MODEL="gemini-2.5-flash"`
- **`GOOGLE_API_KEY`**:
- Your Google Cloud API key.
- Required for using Vertex AI in express mode.
- Ensure you have the necessary permissions.
- Example: `export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"`.
- **`GOOGLE_CLOUD_PROJECT`**:
- Your Google Cloud Project ID.
- Required for using Code Assist or Vertex AI.
- If using Vertex AI, ensure you have the necessary permissions in this project.
- **Cloud Shell Note:** When running in a Cloud Shell environment, this variable defaults to a special project allocated for Cloud Shell users. If you have `GOOGLE_CLOUD_PROJECT` set in your global environment in Cloud Shell, it will be overridden by this default. To use a different project in Cloud Shell, you must define `GOOGLE_CLOUD_PROJECT` in a `.env` file.
- Example: `export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"`.
- **`GOOGLE_APPLICATION_CREDENTIALS`** (string):
- **Description:** The path to your Google Application Credentials JSON file.
- **Example:** `export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/credentials.json"`
- **`OTLP_GOOGLE_CLOUD_PROJECT`**:
- Your Google Cloud Project ID for Telemetry in Google Cloud
- Example: `export OTLP_GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"`.
- **`GOOGLE_CLOUD_LOCATION`**:
- Your Google Cloud Project Location (e.g., us-central1).
- Required for using Vertex AI in non express mode.
- Example: `export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION"`.
- **`GEMINI_SANDBOX`**:
- Alternative to the `sandbox` setting in `settings.json`.
- Accepts `true`, `false`, `docker`, `podman`, or a custom command string.
- **`SEATBELT_PROFILE`** (macOS specific):
- Switches the Seatbelt (`sandbox-exec`) profile on macOS.
- `permissive-open`: (Default) Restricts writes to the project folder (and a few other folders, see `packages/cli/src/utils/sandbox-macos-permissive-open.sb`) but allows other operations.
- `strict`: Uses a strict profile that declines operations by default.
- `<profile_name>`: Uses a custom profile. To define a custom profile, create a file named `sandbox-macos-<profile_name>.sb` in your project's `.qwen/` directory (e.g., `my-project/.qwen/sandbox-macos-custom.sb`).
- **`DEBUG` or `DEBUG_MODE`** (often used by underlying libraries or the CLI itself):
- Set to `true` or `1` to enable verbose debug logging, which can be helpful for troubleshooting.
- **`NO_COLOR`**:
- Set to any value to disable all color output in the CLI.
- **`CLI_TITLE`**:
- Set to a string to customize the title of the CLI.
- **`CODE_ASSIST_ENDPOINT`**:
- Specifies the endpoint for the code assist server.
- This is useful for development and testing.
## Command-Line Arguments
Arguments passed directly when running the CLI can override other configurations for that specific session.
- **`--model <model_name>`** (**`-m <model_name>`**):
- Specifies the Gemini model to use for this session.
- Example: `npm start -- --model gemini-1.5-pro-latest`
- **`--prompt <your_prompt>`** (**`-p <your_prompt>`**):
- Used to pass a prompt directly to the command. This invokes Gemini CLI in a non-interactive mode.
- **`--sandbox`** (**`-s`**):
- Enables sandbox mode for this session.
- **`--sandbox-image`**:
- Sets the sandbox image URI.
- **`--debug`** (**`-d`**):
- Enables debug mode for this session, providing more verbose output.
- **`--all-files`** (**`-a`**):
- If set, recursively includes all files within the current directory as context for the prompt.
- **`--help`** (or **`-h`**):
- Displays help information about command-line arguments.
- **`--show-memory-usage`**:
- Displays the current memory usage.
- **`--yolo`**:
- Enables YOLO mode, which automatically approves all tool calls.
- **`--telemetry`**:
- Enables [telemetry](../telemetry.md).
- **`--telemetry-target`**:
- Sets the telemetry target. See [telemetry](../telemetry.md) for more information.
- **`--telemetry-otlp-endpoint`**:
- Sets the OTLP endpoint for telemetry. See [telemetry](../telemetry.md) for more information.
- **`--telemetry-log-prompts`**:
- Enables logging of prompts for telemetry. See [telemetry](../telemetry.md) for more information.
- **`--checkpointing`**:
- Enables [checkpointing](./commands.md#checkpointing-commands).
- **`--extensions <extension_name ...>`** (**`-e <extension_name ...>`**):
- Specifies a list of extensions to use for the session. If not provided, all available extensions are used.
- Use the special term `gemini -e none` to disable all extensions.
- Example: `gemini -e my-extension -e my-other-extension`
- **`--list-extensions`** (**`-l`**):
- Lists all available extensions and exits.
- **`--version`**:
- Displays the version of the CLI.
- **`--openai-logging`**:
- Enables logging of OpenAI API calls for debugging and analysis. This flag overrides the `enableOpenAILogging` setting in `settings.json`.
## Context Files (Hierarchical Instructional Context)
While not strictly configuration for the CLI's _behavior_, context files (defaulting to `GEMINI.md` but configurable via the `contextFileName` setting) are crucial for configuring the _instructional context_ (also referred to as "memory") provided to the Gemini model. 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 Gemini model to be aware of during your interactions. The system is designed to manage this instructional context hierarchically.
### Example Context File Content (e.g., `GEMINI.md`)
Here's a conceptual example of what a context file at the root of a TypeScript project might contain:
```markdown
# 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., `GEMINI.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/<contextFileName>` (e.g., `~/.qwen/GEMINI.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.).
- 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 to the Gemini model. The CLI footer displays the count of loaded context files, giving you a quick visual cue about the active instructional context.
- **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](./commands.md#memory) 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 the Gemini CLI's responses to your specific needs and projects.
## Sandboxing
The Gemini CLI can execute potentially unsafe operations (like shell commands and file modifications) within a sandboxed environment to protect your system.
Sandboxing 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 in `--yolo` mode by default.
By default, it uses a pre-built `gemini-cli-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:
```dockerfile
FROM gemini-cli-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 Gemini CLI to automatically build the custom sandbox image:
```bash
BUILD_SANDBOX=1 gemini -s
```
## Usage Statistics
To help us improve the Gemini CLI, 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 Gemini 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 Gemini 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` in your `settings.json` file:
```json
{
"usageStatisticsEnabled": false
}
```

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# Gemini CLI
Within Gemini CLI, `packages/cli` is the frontend for users to send and receive prompts with the Gemini AI model and its associated tools. For a general overview of Gemini CLI, see the [main documentation page](../index.md).
## Navigating this section
- **[Authentication](./authentication.md):** A guide to setting up authentication with Google's AI services.
- **[Commands](./commands.md):** A reference for Gemini CLI commands (e.g., `/help`, `/tools`, `/theme`).
- **[Configuration](./configuration.md):** A guide to tailoring Gemini CLI behavior using configuration files.
- **[Token Caching](./token-caching.md):** Optimize API costs through token caching.
- **[Themes](./themes.md)**: A guide to customizing the CLI's appearance with different themes.
- **[Tutorials](tutorials.md)**: A tutorial showing how to use Gemini CLI to automate a development task.
## Non-interactive mode
Gemini CLI can be run in a non-interactive mode, which is useful for scripting and automation. In this mode, you pipe input to the CLI, it executes the command, and then it exits.
The following example pipes a command to Gemini CLI from your terminal:
```bash
echo "What is fine tuning?" | gemini
```
Gemini CLI executes the command and prints the output to your terminal. Note that you can achieve the same behavior by using the `--prompt` or `-p` flag. For example:
```bash
gemini -p "What is fine tuning?"
```

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# OpenAI Authentication
Qwen Code CLI supports OpenAI authentication for users who want to use OpenAI models instead of Google's Gemini models.
## Authentication Methods
### 1. Interactive Authentication (Recommended)
When you first run the CLI and select OpenAI as your authentication method, you'll be prompted to enter:
- **API Key**: Your OpenAI API key from [https://platform.openai.com/api-keys](https://platform.openai.com/api-keys)
- **Base URL**: The base URL for OpenAI API (defaults to `https://api.openai.com/v1`)
- **Model**: The OpenAI model to use (defaults to `gpt-4o`)
The CLI will guide you through each field:
1. Enter your API key and press Enter
2. Review/modify the base URL and press Enter
3. Review/modify the model name and press Enter
**Note**: You can paste your API key directly - the CLI supports paste functionality and will display the full key for verification.
### 2. Command Line Arguments
You can also provide the OpenAI credentials via command line arguments:
```bash
# Basic usage with API key
qwen-code --openai-api-key "your-api-key-here"
# With custom base URL
qwen-code --openai-api-key "your-api-key-here" --openai-base-url "https://your-custom-endpoint.com/v1"
# With custom model
qwen-code --openai-api-key "your-api-key-here" --model "gpt-4-turbo"
```
### 3. Environment Variables
Set the following environment variables in your shell or `.env` file:
```bash
export OPENAI_API_KEY="your-api-key-here"
export OPENAI_BASE_URL="https://api.openai.com/v1" # Optional, defaults to this value
export OPENAI_MODEL="gpt-4o" # Optional, defaults to gpt-4o
```
## Supported Models
The CLI supports all OpenAI models that are available through the OpenAI API, including:
- `gpt-4o` (default)
- `gpt-4o-mini`
- `gpt-4-turbo`
- `gpt-4`
- `gpt-3.5-turbo`
- And other available models
## Custom Endpoints
You can use custom endpoints by setting the `OPENAI_BASE_URL` environment variable or using the `--openai-base-url` command line argument. This is useful for:
- Using Azure OpenAI
- Using other OpenAI-compatible APIs
- Using local OpenAI-compatible servers
## Switching Authentication Methods
To switch between authentication methods, use the `/auth` command in the CLI interface.
## Security Notes
- API keys are stored in memory during the session
- For persistent storage, use environment variables or `.env` files
- Never commit API keys to version control
- The CLI displays API keys in plain text for verification - ensure your terminal is secure

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# Themes
Gemini CLI supports a variety of themes to customize its color scheme and appearance. You can change the theme to suit your preferences via the `/theme` command or `"theme":` configuration setting.
## Available Themes
Gemini CLI comes with a selection of pre-defined themes, which you can list using the `/theme` command within Gemini CLI:
- **Dark Themes:**
- `ANSI`
- `Atom One`
- `Ayu`
- `Default`
- `Dracula`
- `GitHub`
- **Light Themes:**
- `ANSI Light`
- `Ayu Light`
- `Default Light`
- `GitHub Light`
- `Google Code`
- `Xcode`
### Changing Themes
1. Enter `/theme` into Gemini CLI.
2. A dialog or selection prompt appears, listing the available themes.
3. Using the arrow keys, select a theme. Some interfaces might offer a live preview or highlight as you select.
4. Confirm your selection to apply the theme.
### Theme Persistence
Selected themes are saved in Gemini CLI's [configuration](./configuration.md) so your preference is remembered across sessions.
## Dark Themes
### ANSI
<img src="../assets/theme-ansi.png" alt="ANSI theme" width="600" />
### Atom OneDark
<img src="../assets/theme-atom-one.png" alt="Atom One theme" width="600">
### Ayu
<img src="../assets/theme-ayu.png" alt="Ayu theme" width="600">
### Default
<img src="../assets/theme-default.png" alt="Default theme" width="600">
### Dracula
<img src="../assets/theme-dracula.png" alt="Dracula theme" width="600">
### GitHub
<img src="../assets/theme-github.png" alt="GitHub theme" width="600">
## Light Themes
### ANSI Light
<img src="../assets/theme-ansi-light.png" alt="ANSI Light theme" width="600">
### Ayu Light
<img src="../assets/theme-ayu-light.png" alt="Ayu Light theme" width="600">
### Default Light
<img src="../assets/theme-default-light.png" alt="Default Light theme" width="600">
### GitHub Light
<img src="../assets/theme-github-light.png" alt="GitHub Light theme" width="600">
### Google Code
<img src="../assets/theme-google-light.png" alt="Google Code theme" width="600">
### Xcode
<img src="../assets/theme-xcode-light.png" alt="Xcode Light theme" width="600">

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# Token Caching and Cost Optimization
Gemini CLI automatically optimizes API costs through token caching when using API key authentication (Gemini API key or Vertex AI). This feature reuses previous system instructions and context to reduce the number of tokens processed in subsequent requests.
**Token caching is available for:**
- API key users (Gemini API key)
- Vertex AI users (with project and location setup)
**Token caching is not available for:**
- OAuth users (Google Personal/Enterprise accounts) - the Code Assist API does not support cached content creation at this time
You can view your token usage and cached token savings using the `/stats` command. When cached tokens are available, they will be displayed in the stats output.

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# Tutorials
This page contains tutorials for interacting with Gemini CLI.
## Setting up a Model Context Protocol (MCP) server
> [!CAUTION]
> Before using a third-party MCP server, ensure you trust its source and understand the tools it provides. Your use of third-party servers is at your own risk.
This tutorial demonstrates how to set up a MCP server, using the [GitHub MCP server](https://github.com/github/github-mcp-server) as an example. The GitHub MCP server provides tools for interacting with GitHub repositories, such as creating issues and commenting on pull requests.
### Prerequisites
Before you begin, ensure you have the following installed and configured:
- **Docker:** Install and run [Docker].
- **GitHub Personal Access Token (PAT):** Create a new [classic] or [fine-grained] PAT with the necessary scopes.
[Docker]: https://www.docker.com/
[classic]: https://github.com/settings/tokens/new
[fine-grained]: https://github.com/settings/personal-access-tokens/new
### Guide
#### Configure the MCP server in `settings.json`
In your project's root directory, create or open the [`.qwen/settings.json` file](./configuration.md). Within the file, add the `mcpServers` configuration block, which provides instructions for how to launch the GitHub MCP server.
```json
{
"mcpServers": {
"github": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITHUB_PERSONAL_ACCESS_TOKEN",
"ghcr.io/github/github-mcp-server"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_PERSONAL_ACCESS_TOKEN}"
}
}
}
}
```
#### Set your GitHub token
> [!CAUTION]
> Using a broadly scoped personal access token that has access to personal and private repositories can lead to information from the private repository being leaked into the public repository. We recommend using a fine-grained access token that doesn't share access to both public and private repositories.
Use an environment variable to store your GitHub PAT:
```bash
GITHUB_PERSONAL_ACCESS_TOKEN="pat_YourActualGitHubTokenHere"
```
Gemini CLI uses this value in the `mcpServers` configuration that you defined in the `settings.json` file.
#### Launch Gemini CLI and verify the connection
When you launch Gemini CLI, it automatically reads your configuration and launches the GitHub MCP server in the background. You can then use natural language prompts to ask Gemini CLI to perform GitHub actions. For example:
```bash
"get all open issues assigned to me in the 'foo/bar' repo and prioritize them"
```