Introducing Gemini CLI
4 sections
- 0:00Claude Code has expanded significantly since its initial release, becoming more versatile and widely used.
- “Claude Code has been out for quite a while now and it has really grown quite a lot.”0:00
- 0:09Users, including the speaker, have integrated command-line usage into their workflows, enhancing productivity.
- “I've used and gotten used to actually using a command line to use an LLM to get it to update things in a folder.”0:09
- 0:20The tool can quickly generate high costs, which many developers, including the speaker, find problematic.
- “My only complaint has been how much you can run up a bill very quickly.”0:20
- 0:31A new development or update related to Claude Code has just been announced, generating interest.
- 0:39Google releases a command line interface for Gemini, inspired by Claude code, enhancing how large language models are used with tools.
- “Form factor is such a killer way to use large language models, prompting them with tools and MCPs.”0:50
- 1:32The Gemini CLI code is made available to developers, initially private but expected to become open, enabling broad participation.
- 1:58Users can access Gemini 2 with a free license using their Google account, with high request limits (1 million context window, 60 requests/min).
- “All code is available via an open repo, so developers can download, set up, and start experimenting.”1:58
- “You can get a free Gemini Code Assist license with your Google account, enabling high request limits.”2:16
- 3:01The CLI allows grounding prompts in Google Search, use of MCPs (multi-choice prompts), and options to connect with Vertex AI or Gemini AI Studio for higher rate limits.
- 3:30The transcript demonstrates installing the CLI, logging in, and generating code snippets for web development using Tailwind CSS and JavaScript.
- “We run the CLI, choose our AI account, and then ask it to generate HTML and JS code with Tailwind.”3:30
- 5:40AI tools can create complete landing pages, including content, images, and menus, saving time and effort in website building.
- “Build me a landing page with a cat cafe in San Francisco.”5:40
- 6:32Users can easily modify AI-generated content, such as adding menu items or fixing pages, through simple prompts, enabling dynamic updates.
- “Added in please add some cat treats to the menu and also an about us page.”6:32
- 6:53Managing project information with Gemini MD files and context windows helps organize data and enhances AI responsiveness as projects grow.
- “We need pictures of Mun cats to complete the page.”7:35
- “The Gemini MD file provides a comprehensive overview of the project.”8:34
- 8:39Tools like Gemini MD and memory modules allow saving facts, generating backends like Flask, and maintaining a persistent, coherent workflow.
- “Using the memory tool, I can save facts and information for the AI to use later.”9:25
- 10:10Creates a virtual environment, activates it, and installs necessary packages for AI development.
- “We can see that the virtual environment is created, activated, and packages are installed, ready for deployment.”10:20
- 10:30Activates the virtual environment to run apps and verify installation success.
- 10:40Pushes the application to cloud and monitors token usage, including input, output, and total tokens.
- “After pushing to cloud, token usage is tracked, showing input, output, and total tokens processed.”10:40
- 11:18Installs MCPS, adds Hugging Face MCP server, and explores features like model search and image generation.
- “Installing MCPS and integrating Hugging Face MCP server unlocks model search, image generation, and dataset access.”11:18
- 12:23Uses MCP to find models, papers, and datasets, retrieving specific items like the Easy Gibli space.
- “Using MCP, I can find specific models, papers, and datasets easily, like the Easy Gibli space.”12:23
- 13:12References extensive docs on commands, themes, tutorials, and usage examples for MCPS.
- “Extensive documentation exists for commands, themes, tutorials, and best practices for MCPS.”13:12