Gemma Gem

Gemma Gem is an open-source Chrome extension that brings a personal AI assistant directly into your browser, powered by Google's Gemma 4 model running entirely on-device via WebGPU. There are no API keys, no cloud calls, and no data leaving your machine — all inference happens locally using your GPU. The extension injects a chat overlay into any page, allowing you to ask questions about content or instruct the agent to interact with the page on your behalf. It supports two model sizes (E2B ~500MB and E4B ~1.5GB), both cached locally after the first download.

• On-device inference — Uses @huggingface/transformers with WebGPU for fully local Gemma 4 model execution; no internet connection required after model download.
• Page reading — The read_page_content tool extracts text or HTML from the full page or a specific CSS selector, letting the model understand any site you visit.
• Element interaction — click_element and type_text tools allow the agent to click buttons and fill forms by CSS selector, enabling true browser automation.
• Screenshot capture — take_screenshot captures the visible page as a PNG, giving the model visual context alongside text.
• JavaScript execution — run_javascript runs arbitrary JS in the page context with full DOM access via the service worker.
• Scrolling — scroll_page scrolls up or down by a specified pixel amount for navigating long pages.
• Model switching — Toggle between Gemma 4 E2B and E4B models in settings; selection persists across sessions.
• Native thinking toggle — Enable or disable Gemma 4's native thinking mode directly from the chat settings panel.
• Per-site disable — Suppress the extension on specific hostnames, persisted across browser sessions.
• Zero-dependency agent core — The agent/ directory defines clean ModelBackend and ToolExecutor interfaces with no external dependencies, making it extractable as a standalone library.
• Developer-friendly build — Built with WXT (Vite-based Chrome extension framework); supports development builds with full logging and production builds with minification.