This project provides a command-line interface (CLI) for interacting with Google's Gemini AI models, enabling users to query and edit large codebases, generate applications from various inputs, and automate operational tasks directly from their terminal. It targets developers and power users seeking to integrate advanced AI capabilities into their existing workflows and development processes.

How It Works

The Gemini CLI acts as a bridge between the user's terminal environment and the Gemini AI models. It leverages multimodal capabilities to process diverse inputs like PDFs and sketches, and can interact with external tools and services (e.g., Imagen, Veo, Lyria, Google Search) to extend its functionality. The CLI supports integration with GitHub via a dedicated GitHub Action for automated code reviews and issue management.

Quick Start & Requirements

• Installation:
  • Via npx: npx https://github.com/google-gemini/gemini-cli
  • Via npm: npm install -g @google/gemini-cli
  • Via Homebrew: brew install gemini-cli
• Prerequisites: Node.js v20+ (for npm install).
• Authentication: Requires signing in with a Google account or setting GEMINI_API_KEY (Google AI Studio) or GOOGLE_API_KEY with GOOGLE_GENAI_USE_VERTEXAI=true (Google Cloud).
• Resources: Free tier offers 60 requests/min and 1000 requests/day with personal Google account; Gemini API offers 100 requests/day free tier.
• Documentation: Full Documentation

Highlighted Details

• Query and edit large codebases beyond Gemini's 1M token context window.
• Generate new apps from PDFs or sketches using multimodal capabilities.
• Automate operational tasks like querying pull requests or handling complex rebases.
• Integrates with GitHub Actions for automated PR reviews and issue triage.

Maintenance & Community

• Official roadmap available.
• Security advisories managed on GitHub.

Licensing & Compatibility

• The repository does not explicitly state a license in the provided README.

Limitations & Caveats

• The README does not specify the project's license, which is crucial for understanding usage rights and compatibility, especially for commercial or closed-source applications.