Core Viewpoint - Gemini CLI is an AI workflow tool developed by Google that integrates the Gemini model directly into the command line, enabling users to perform coding, debugging, content generation, research, and task management through natural language commands. Group 1: Features and Capabilities - Gemini CLI has received over 50.1k stars, indicating significant interest and adoption in the developer community [2]. - It allows users to write code and solve problems directly in the terminal, eliminating the need to switch between different tools like IDEs or web browsers [3]. - The tool supports a large context window of 1 million tokens, making it capable of handling extensive codebases and documents [3]. - It offers a wide range of functionalities, including writing copy, researching, managing pipelines, and generating media content, effectively serving as a versatile AI assistant within the terminal [3]. - The free usage tier is generous, allowing personal Google accounts to make approximately 60 requests per minute and 1,000 requests per day, which is considered one of the most accommodating preview plans in the industry [3]. - Gemini CLI is fully open-source under the Apache 2.0 license, promoting community contributions and audits [3]. Group 2: Installation and Setup - To use Gemini CLI, users need to ensure that Node.js (version 18 or higher) is installed [7]. - Installation can be done via terminal commands, either using npx or npm, and once installed, users can start the interactive CLI by typing "gemini" [8]. - Users must log in with their Google account to access the free request limit of 1,000 requests per day [12]. - Alternatively, users can authorize using a Gemini API Key, which can be obtained from Google AI Studio [13]. Group 3: Troubleshooting and Configuration - If users encounter issues logging in with their Google account, they can set temporary proxy environment variables to connect to Google login services [14]. - For users facing login errors related to Google Workspace accounts or project configuration, they need to create a project in the Google Cloud Console and set the project ID as an environment variable [15]. - The setup process includes configuring proxy settings for both Windows and macOS/Linux environments to ensure proper connectivity [19].