n4ze3m/page-assist

Use your locally running AI models to assist you in your web browsing

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Summary Information

Updated 60 minutes ago
Added to GitGenius on September 8th, 2026
Created on April 9th, 2023
Open Issues & Pull Requests: 360 (+0)
GitHub issues: Enabled
Number of forks: 786
Total Stargazers: 8,206 (+0)
Total Subscribers: 54 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.7 hours
Mean response time: 9.9 days
90th percentile: 5.7 days
Tracked items: 378

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 69% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 7% of issues opened in the past year have been closed. Three people close 68% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 305
New in 7 days: 3
Closed in 7 days: 0
Avg open age: 484 days
Stale 30+ days: 297
Stale 90+ days: 284

Recent activity

Opened in 7 days: 3
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (229)
  • bug (153)
  • question (6)
  • documentation (3)

Detailed Description

Page Assist is a browser extension that provides a sidebar and web UI for interacting with locally running AI models while browsing the web.

The tool solves the problem of integrating AI assistance into your browsing workflow without relying on cloud services. It works by connecting to local AI models through Ollama or OpenAI API-compatible endpoints like LM Studio and llamafile. The extension adds a sidebar accessible via keyboard shortcut to any webpage, allowing you to query your model directly. It also includes a dedicated web UI that functions like a chat interface and supports querying the content of the current webpage.

Page Assist suits developers and users who want AI assistance while browsing but prefer to keep their models and data local rather than sending requests to external services. It works with Chromium-based browsers including Chrome, Brave, and Edge, as well as Firefox. The project is open-source and can be installed manually by cloning the repository and building it with Bun or npm, then loading the extension through your browser's developer mode.

Development activity shows consistent engagement with the community through active Discord and Twitter channels. The project maintains documentation and accepts feature requests through GitHub issues. Manual installation requires standard development tools and setup steps are clearly documented for both Chrome and Firefox.