Show HN: Gemma Gem – AI model embedded in a browser – no API keys, no cloud

Summary

Your personal AI assistant living right inside the browser. Gemma Gem runs Google's Gemma 4 model entirely on-device via WebGPU — no API keys, no cloud, no data leaving your machine. It can read pages, click buttons, fill forms, run JavaScript, and answer questions about any site you visit. Chrome with WebGPU support ~500MB disk for model download (cached after first run) Load the extension in chrome://extensions (developer mode) from .output/chrome-mv3-dev/. Navigate to any page Click the gem icon (bottom-right corner) to open the chat Wait for model to load (progress shown on icon + chat) Ask questions about the page or request actions Offscreen Document Service Worker Content Script (Gemma 4 + Agent Loop) <-> (Message Router) <-> (Chat UI + DOM Tools) | | WebGPU inference Screenshot capture Token streaming JS execution Offscreen document: Hosts the model via @huggingface/transformers + WebGPU. Runs the agent loop. Service worker: Routes messages between content scripts and offscreen document. Handles take_screenshot and run_javascript. Content script: Injects gem icon + shadow DOM chat overlay. Executes DOM tools (read_page_content, click_element, type_text, scroll_page). Tool Description Runs in read_page_content Read text/HTML of the page or a CSS selector Content script take_screenshot Capture visible page as PNG Service worker click_element Click an element by CSS selector Content script type_text Type into an input by CSS selector Content script scroll_page Scroll up/down by pixel amount Content script run_javascript Execute JS in the page context with full DOM access Service worker Click the gear icon in the chat header: Thinking: Toggle native Gemma 4 chain-of-thought reasoning Max iterations: Cap on tool call loops per request Clear context: Reset conversation history for the current page Disable on this site: Disable the extension per-hostname (persisted) pnpm build # Development build (with logging, source maps) pnpm build:prod # Production build (loggi...