Gemini CLI

This repository contains the Gemini CLI, a command-line AI workflow tool that connects to your tools, understands your code and accelerates your workflows.

With the Gemini CLI you can:

• Query and edit large codebases in and beyond Gemini's 1M token context window.
• Generate new apps from PDFs or sketches, using Gemini's multimodal capabilities.
• Automate operational tasks, like querying pull requests or handling complex rebases.
• Use tools and MCP servers to connect new capabilities, including media generation with Imagen, Veo or Lyria.
• Ground your queries with the Google Search tool, built in to Gemini.

Quickstart

1. Install Node 20+.
2. Get an API key from Google AI Studio.
3. Set the API key in your shell using the following command, replacing YOUR_API_KEY with the API key you obtained: export GEMINI_API_KEY="YOUR_API_KEY".
4. Run the Gemini CLI from your shell using the following command: npx https://github.com/google-gemini/gemini-cli#early-access
5. Enjoy!

Examples

Once the CLI is running, you can start interacting with Gemini from your shell.

You can start a project from a new directory:

$ cd new-project/
$ gemini
> Write me a Gemini Discord bot that answers questions using a FAQ.md file I will provide

Or work with an existing project:

$ git clone https://github.com/google-gemini/gemini-cli
$ cd gemini-cli
$ gemini
> Give me a summary of all of the changes that went in yesterday

API Key Setup

The Gemini CLI requires you to authenticate with Google's AI services. You'll need to configure one of the following authentication methods:

1. Gemini Code Assist:

   • To enable this mode you only need set the GEMINI_CODE_ASSIST environment variable to true.
   • Enterprise users must also provide a GOOGLE_CLOUD_PROJECT environment variable specifying their Google Cloud project. In the following methods, replace GOOGLE_CLOUD_PROJECT with the relevant values for your project:
     • You can temporarily set the environment variable in your current shell session using the following command:

       export GEMINI_CODE_ASSIST="true"
       export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID" // Enterprise users only.

     • For repeated use, you can add the environment variable to your .env file (located in the project directory or user home directory) or your shell's configuration file (like ~/.bashrc, ~/.zshrc, or ~/.profile). For example, the following command adds the environment variable to a ~/.bashrc file:

       echo 'export GEMINI_CODE_ASSIST="true"' >> ~/.bashrc
       echo 'export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"' >> ~/.bashrc # Enterprise users only.
       source ~/.bashrc

2. Gemini API key:

   • Obtain your API key from Google AI Studio: 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:

       export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"

     • For repeated use, you can add the environment variable to your .env file (located in the project directory or user home directory) or your shell's configuration file (like ~/.bashrc, ~/.zshrc, or ~/.profile). For example, the following command adds the environment variable to a ~/.bashrc file:

       echo 'export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"' >> ~/.bashrc
       source ~/.bashrc

3. Google API Key (Vertex AI Express Mode):

   • You can use a general Google Cloud API key if it has been enabled for the Gemini API or Vertex AI.
   • Set the GOOGLE_API_KEY and GOOGLE_GENAI_USE_VERTEXAI environment variables. In the following methods, replace YOUR_GEMINI_API_KEY with your Google Cloud API key:
     • You can temporarily set these environment variables in your current shell session using the following commands:

       export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"
       export GOOGLE_GENAI_USE_VERTEXAI=true

     • For repeated use, you can add the environment variables to your .env file (located in the project directory or user home directory) or your shell's configuration file (like ~/.bashrc, ~/.zshrc, or ~/.profile). For example, the following commands adds the environment variables to a ~/.bashrc file:

       echo 'export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"' >> ~/.bashrc
       echo 'export GOOGLE_GENAI_USE_VERTEXAI=true' >> ~/.bashrc
       source ~/.bashrc

4. Vertex AI (Project and Location):

   • Ensure you have a Google Cloud project and have enabled the Vertex AI API.
   • Set up Application Default Credentials (ADC), using the following command:

     gcloud auth application-default login

     For more information, see Set up Application Default Credentials for Google Cloud.
   • Set the GOOGLE_CLOUD_PROJECT, GOOGLE_CLOUD_LOCATION, and GOOGLE_GENAI_USE_VERTEXAI 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:

       export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"
       export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION" # e.g., us-central1
       export GOOGLE_GENAI_USE_VERTEXAI=true

     • For repeated use, you can add the environment variables to your .env file (located in the project directory or user home directory) or your shell's configuration file (like ~/.bashrc, ~/.zshrc, or ~/.profile). For example, the following commands adds the environment variables to a ~/.bashrc file:

       echo 'export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID"' >> ~/.bashrc
       echo 'export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION"' >> ~/.bashrc
       echo 'export GOOGLE_GENAI_USE_VERTEXAI=true' >> ~/.bashrc
       source ~/.bashrc

Next Steps

• Learn how to contribute to or build from the source.
• Explore the available CLI Commands.
• If you encounter any issues, review the Troubleshooting guide.
• For more comprehensive documentation, see the full documentation.

Gemini APIs

This project leverages the Gemini APIs to provide AI capabilities. For details on the terms of service governing the Gemini API, please refer to the Gemini API Terms of Service.