Spaces:
Running
Frontend Application
This frontend project aims to enhance the user experience of GPT-Researcher, providing an intuitive and efficient interface for automated research. It offers two deployment options to suit different needs and environments.
Option 1: Static Frontend (FastAPI)
A lightweight solution using FastAPI to serve static files.
Prerequisites
- Python 3.11+
- pip
Setup and Running
Install required packages:
pip install -r requirements.txt
Start the server:
python -m uvicorn main:app
Access at
http://localhost:8000
Demo
https://github.com/assafelovic/gpt-researcher/assets/13554167/dd6cf08f-b31e-40c6-9907-1915f52a7110
Option 2: NextJS Frontend
A more robust solution with enhanced features and performance.
Prerequisites
- Node.js (v18.17.0 recommended)
- npm
Setup and Running
Navigate to NextJS directory:
cd nextjs
Set up Node.js:
nvm install 18.17.0 nvm use v18.17.0
Install dependencies:
npm install --legacy-peer-deps
Start development server:
npm run dev
Access at
http://localhost:3000
Note: Requires backend server on localhost:8000
as detailed in option 1.
Demo
https://github.com/user-attachments/assets/092e9e71-7e27-475d-8c4f-9dddd28934a3
Choosing an Option
- Static Frontend: Quick setup, lightweight deployment.
- NextJS Frontend: Feature-rich, scalable, better performance and SEO.
For production, NextJS is recommended.
Frontend Features
Our frontend enhances GPT-Researcher by providing:
- Intuitive Research Interface: Streamlined input for research queries.
- Real-time Progress Tracking: Visual feedback on ongoing research tasks.
- Interactive Results Display: Easy-to-navigate presentation of findings.
- Customizable Settings: Adjust research parameters to suit specific needs.
- Responsive Design: Optimal experience across various devices.
These features aim to make the research process more efficient and user-friendly, complementing GPT-Researcher's powerful agent capabilities.