93527597b77f23fca0989de294ad06fb61884ee4
Deep Research Web UI
[English | 中文]
This is a web UI for https://github.com/dzhng/deep-research, with several improvements and fixes.
Features:
- 🚀 Safe & Secure: Everything (config, API requests, ...) stays in your browser locally
- 🕙 Realtime feedback: Stream AI responses and reflect on the UI in real-time
- 🌳 Search visualization: Shows the research process using a tree structure
- 📄 Export as PDF: Export the final research report as a PDF
- 🌐 Search in different languages: Useful when you want to get search results in a different language
- 🤖 Supports more models: Uses plain prompts instead of newer, less widely supported features like Structured Outputs. This ensures to work with more providers that haven't caught up with the latest OpenAI capabilities.
Currently available providers:
- AI: OpenAI compatible
- Web Search: Tavily (similar to Firecrawl, but with more free quota (1000 credits / month))
Please give a 🌟 Star if you like this project!
How to use
Live demo: https://deep-research.ataw.top
Self hosted
One-click deploy with EdgeOne Pages:
Use pre-built Docker image:
docker run -p 3000:3000 --name deep-research-web -d anotia/deep-research-web:latest
Use self-built Docker image:
git clone https://github.com/AnotiaWang/deep-research-web-ui
cd deep-research-web-ui
docker build -t deep-research-web .
docker run -p 3000:3000 --name deep-research-web -d deep-research-web
Developing
Setup
Make sure to install dependencies:
pnpm install
Development Server
Start the development server on http://localhost:3000
:
pnpm dev
Production
Build the application for production:
If you want to deploy a SSR application:
pnpm build
If you want to deploy a static, SSG application:
pnpm generate
Locally preview production build:
pnpm preview
Check out the deployment documentation for more information.
License
MIT
Description
(Supports DeepSeek R1) An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models.
Languages
Vue
53.6%
TypeScript
42.1%
JavaScript
3.5%
Dockerfile
0.5%
CSS
0.3%