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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:

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.
Readme 11 MiB
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