Get started with Gemini CLI

Welcome to Gemini CLI! This guide will help you install, configure, and start using the Gemini CLI to enhance your workflow right from your terminal.

Gemini CLI brings the power of advanced language models directly to your command line interface. As an AI-powered assistant, Gemini CLI can help you with a variety of tasks, from understanding and generating code to reviewing and editing documents.

The standard method to install and run Gemini CLI uses npm:

npm install -g @google/gemini-cli

Once Gemini CLI is installed, run Gemini CLI from your command line:

gemini

For more installation options, see Gemini CLI Installation.

To begin using Gemini CLI, you must authenticate with a Google service. In most cases, you can log in with your existing Google account:

1. Run Gemini CLI after installation:

   gemini

2. When asked “How would you like to authenticate for this project?” select 1. Sign in with Google.

3. Select your Google account.

4. Click on Sign in.

Certain account types may require you to configure a Google Cloud project. For more information, including other authentication methods, see Gemini CLI Authentication Setup.

Gemini CLI offers several ways to configure its behavior, including environment variables, command-line arguments, and settings files.

To explore your configuration options, see Gemini CLI Configuration.

Once installed and authenticated, you can start using Gemini CLI by issuing commands and prompts in your terminal. Ask it to generate code, explain files, and more.

You can use Gemini CLI to automate file management tasks that require visual analysis. In this example, Gemini CLI renames images based on their actual subject matter.

Scenario: You have a folder containing the following files:

photos/photo1.png
photos/photo2.png
photos/photo3.png

Give Gemini the following prompt:

Rename the photos in my "photos" directory based on their contents.

Result: Gemini asks for permission to rename your files.

Select Allow once and your files are renamed:

photos/yellow_flowers.png
photos/antique_dresser.png
photos/green_android_robot.png

Gemini CLI is effective for rapid codebase exploration. The following example shows how to ask Gemini CLI to fetch, analyze, and summarize a remote project.

Scenario: You want to understand how a popular open-source utility works by inspecting its code, not just its README.

Give Gemini CLI the following prompt:

Clone the 'chalk' repository from https://github.com/chalk/chalk, read its key source files, and explain how it works.

Result: Gemini performs a sequence of actions to answer your request.

1. First, it asks for permission to run git clone to download the repository.
2. Next, it finds the important source files and asks for permission to read them.
3. Finally, after analyzing the code, it provides a summary.

Gemini CLI returns an explanation based on the actual source code:

The `chalk` library is a popular npm package for styling terminal output with
colors. After analyzing the source code, here's how it works:

- **Core functionality:** The main file sets up a chainable API. Each color or
  modifier (like `bold` or `italic`) is a getter that appends the corresponding
  ANSI escape code to an internal stack.

- **Chainable API:** When you call `chalk.red.bold('Hello')`, you are accessing
  getters. The `red` getter adds the red color code, and the `bold` getter adds
  the bold code.

- **Output generation:** When the chain is treated as a string (e.g., in
  `console.log`), a final `toString()` method is called. This method joins all
  the stored ANSI codes, wraps them around the input string ('Hello'), and adds
  a reset code at the end. This produces the final, styled string that the
  terminal can render.

Gemini CLI can process and transform data across multiple files. Use this capability to merge reports or reformat data sets without manual copying.

Scenario: You have two .csv files: Revenue - 2023.csv and Revenue - 2024.csv. Each file contains monthly revenue figures.

Give Gemini CLI the following prompt:

Combine the two .csv files into a single .csv file, with each year a different column.

Result: Gemini CLI reads each file and then asks for permission to write a new file. Provide your permission and Gemini CLI provides the combined data:

Month,2023,2024
January,0,1000
February,0,1200
March,0,2400
April,900,500
May,1000,800
June,1000,900
July,1200,1000
August,1800,400
September,2000,2000
October,2400,3400
November,3400,1800
December,2100,9000

Gemini CLI can generate boilerplate code and tests based on your existing implementation. This example demonstrates how to request code coverage for a JavaScript component.

Scenario: You’ve written a simple login page. You wish to write unit tests to ensure that your login page has code coverage.

Give Gemini CLI the following prompt:

Write unit tests for Login.js.

Result: Gemini CLI asks for permission to write a new file and creates a test for your login page.

You can check your current token usage and quota information using the /stats model command. This command provides a snapshot of your current session’s token usage, as well as your overall quota and usage for the supported models.

For more information on the /stats command and its subcommands, see the Command Reference.

• Follow the File management guide to start working with your codebase.
• See Shell commands to learn about terminal integration.