AIskNet

This project aims to develop a browser extension that runs AI models locally on the browser to answer questions about the content of the page the user is visiting.

Installation

The extension is available for Chrome, Firefox and Edge. You can install it from the following links:

• Google Chrome
• Mozilla Firefox
• Microsoft Edge

Usage

Upon installation, the extension downloads the models, after its done you can start using it by clicking on the extension icon or by pressing Alt+A. A popup will appear with a text input where you can write your question. After writing your question, press Enter or click on the Sumbmit button to get the answer.

A few settings can be changed after pressing the Settings button. These are the following:

• Embeddings model: the embeddings model to use to embed the text extracted from the websites into vector embeddings. The default is multi-qa-MiniLM-L6-cos-v1-quantized.
• Main generative model: the generative model used to generate an answer given a context. The default is LaMini-Flan-T5-248M-quantized.
• Secondary generative model: the generative model used to generate a temporary answer without context, useful to find more relevant embeddings. The default is LaMini-Flan-T5-77M-quantized.
• Chunk size: the number of characters to use when splitting up the text extracted from the websites to be saved into embeddings. The default is 280.
• Results number: the number of embeddings to return from the similarity search to be used as a context to answer the question. The default is 5.

Environment Setup

Install Node.js through fnm and pnpm.

curl -fsSL https://fnm.vercel.app/install | bash
curl -fsSL https://get.pnpm.io/install.sh | sh -
fnm use
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Install the project dependencies:

pnpm install
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Developing

Start a development server:

pnpm dev
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Open your browser and load the appropriate development build. For example, if you are developing for the chrome browser, using manifest v3, use: build/chrome-mv3-dev.

Building

To create a production version of the extension, run the following:

pnpm build
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This should create a production bundle for the extension, ready to be zipped and published to the stores. The builds can be packaged into zip files with pnpm package.

Authors

• Alberto García ([email protected])