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Site RAG
Site RAG
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Site RAG
AI searchKnowledge Management#Chrome Extension#Natural Language Processing#RAG#Privacy Protection#Local ExecutionStandard PicksOpen Source
Overview :
Site RAG is a Chrome extension designed to assist users in quickly obtaining answers to questions while browsing the web, using natural language processing technology. It supports querying with the current page content as context and allows the indexing of entire website content into a vector database for subsequent retrieval-enhanced generation (RAG). The product runs entirely in the local browser, ensuring user data security, and supports connection to a locally running Ollama instance for inference. It primarily targets users who need to rapidly extract information from web content, such as developers, researchers, and students. This product is currently offered for free, making it suitable for those seeking immediate assistance while browsing the web.
Target Users :
This product is ideal for users who need to quickly extract information from web content, such as developers, researchers, and students. It helps users swiftly find answers to their questions while browsing the web, thereby enhancing work efficiency. For users who need to index and query a large volume of web content, Site RAG provides robust functional support.
Total Visits： 492.1M
Top Region： US(19.34%)
Website Views ： 61.0K
Use Cases
A user quickly queries a specific technical question in the documentation while browsing using Site RAG.
A researcher indexes the content of an entire academic website using Site RAG for in-depth study.
A student utilizes Site RAG to index web pages related to their courses, aiding their review and searches.
Features
Perform one-time queries on the current page to quickly obtain answers to questions.
Index the current page content into vector storage for RAG queries later.
Support indexing of entire websites, allowing for persistent document storage for future queries.
Run completely locally, with all data stored in the browser to ensure privacy and security.
Support connection to a locally running Ollama instance for local LLM inference.
How to Use
1. Clone the repository: `git clone https://github.com/bracesproul/site-rag.git`
2. Navigate to the project directory: `cd site-rag`
3. Install dependencies: `yarn install`
4. Build the project: `yarn build`
5. Load the extension in Chrome: Go to chrome://extensions/, click 'Load unpacked', and select the `dist` directory.
6. Open the extension and go to the settings page to add the API key and other configurations.
7. Return to the chat view, enter your question, and get answers.
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