gpt-open / rag-gpt-h5

An HTML5 interface for Smart QA Service designed for easy integration into websites via iframe, providing users direct access to a tailored knowledge base without leaving the site, enhancing functionality and immediate query resolution.

Smart QA Service: An Intelligent Knowledge Base

The Smart QA Service harnesses the power of advanced technologies like Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) to learn from user-customized knowledge bases. It is designed to deliver contextually relevant answers across a broad spectrum of inquiries, ensuring rapid and precise information retrieval. This capability not only enhances user experience but also supports a more efficient knowledge management process.

This project introduces an HTML5 (h5) interface for the Smart QA Service, crafted for seamless integration into your website. By embedding the service as an iframe, you can offer your users direct access to this intelligent knowledge base without navigating away from your site. This integration enriches your website's functionality, providing immediate answers to user questions based on the tailored knowledge base.

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Quick Start Guide

1. clone project

git clone https://github.com/open-kf/smart-qa-h5.git

2. install dependencies

cd smart-qa-h5
npm install

3. update environment variables

To ensure seamless communication between your client application and the backend service, especially when the server isn't running in the default environment or is configured to use a custom port, you need to specify the base URL of the Smart QA Service API server. This is done by setting the VITE_BASE_URL variable within the .env file to the URL where the server's API is accessible.

# Example: Setting the Smart QA Service API base URL
VITE_BASE_URL=https://smart-qa-service.com

This step is crucial for directing your application to the correct server location, ensuring that all API requests are routed to the appropriate endpoint.

4. start the project

npm run dev

open the browser and visit http://localhost:5177

5. build the project

npm run build

6. deploy

You can deploy the built application to any hosting service that supports static file hosting, such as Vercel, Netlify, or GitHub Pages. Simply upload the contents of the dist directory to your chosen hosting provider, and your application will be live and accessible to users.

rag-gpt-h5's Issues

feat: get response with stream

get response with stream