Deep Research Web UI

June 4, 2026 · View on GitHub

[English | 中文]

This is a web UI for https://github.com/dzhng/deep-research, with several improvements and fixes.

Features:

🚀 Safe & Secure: In Client Mode, config and API requests stay 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. Supports searching in different languages
📄 Export as PDF: Export the final research report as Markdown / PDF
🤖 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.
🐳 Docker support: Deploy in your environment in one-line command
🔧 Server Mode: Deploy with environment variables, no need for users to configure API keys

Currently available providers:

AI: OpenAI compatible, SiliconFlow, InfiniAI, DeepSeek, OpenRouter, Ollama and more
Web Search: Tavily (1000 free credits / month), Firecrawl (cloud / self-hosted), Google PSE

Please give a 🌟 Star if you like this project!

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Recent updates

25/07/24

Added: Research history management - Export/import individual history records, delete all records

25/07/23

Added: Server Mode - Deploy with environment variables, users don't need to configure API keys

25/06/26

Added: Provider 302.AI support

25/04/06

Added: Use Google PSE for web search

25/03/09

Added: InfiniAI support
Improved LLM prompts
Improved error handling
Improved: Try to fetch model list even when no API key is provided

25/02/27

Added: Citations in research report
Improved: Chinese output layout
Improved: Increased max width and breadth in the form
Fixed: Text overflow issues for web search node details
Fixed: general UI style issues

25/02/24

Added: Fullscreen mode for the search flow. This helps you to focus on the search process better.
Changed: "Export PDF" now uses the browser's native print ability. This fixes layout issues and eliminates font problems.
Fixed: "Context Size" setting are not correctly applied

25/02/22

Added: NL/Dutch translation
Added: Retry failed nodes in web search
Fixed: Web search node sometimes shows empty label and duplicated learnings
Fixed: Firecrawl now limits scrape content format to Markdown

25/02/18 - 25/02/20

Added: "advanced search" and "search topic" support for Tavily
Added: custom endpoint support for Firecrawl
Fixed: overall bug fixes, less "invalid JSON structure" errors

25/02/17

Added: set rate limits for web search
Added: set context length for AI model

25/02/16

Refactored the search visualization using VueFlow
Style & bug fixes

Older updates

25/02/15

Added AI providers DeepSeek, OpenRouter and Ollama; Added web search provider Firecrawl
Supported checking project updates
Supported regenerating reports
General fixes

25/02/14

Supported reasoning models like DeepSeek R1
Improved compatibility with more models & error handling

25/02/13

Significantly reduced bundle size
Supported searching in different languages
Added Docker support
Fixed "export as PDF" issues

How to use

Live demo: https://deep-research.ataw.top

Deployment modes

Client Mode: users enter their own API keys in the browser. This is the best fit for static deployments such as EdgeOne Pages or pnpm generate.
Server Mode: API keys are configured as server-side environment variables, so users do not need to enter keys in the UI. This requires an SSR/Nitro runtime such as the Docker image; it is not available in purely static deployments.

Self hosted

Server Mode (Recommended)

Deploy with environment variables - users don't need to configure API keys. Use this mode when you can run the Nuxt server:

Using Docker with environment variables:

docker run -p 3000:3000 \
  -e NUXT_PUBLIC_SERVER_MODE=true \
  -e NUXT_AI_API_KEY=your-ai-api-key \
  -e NUXT_WEB_SEARCH_API_KEY=your-search-api-key \
  -e NUXT_PUBLIC_AI_PROVIDER=openai-compatible \
  -e NUXT_PUBLIC_AI_MODEL=gpt-4o-mini \
  -e NUXT_PUBLIC_WEB_SEARCH_PROVIDER=tavily \
  anotia/deep-research-web:latest

Using Docker with .env file:

# Copy .env.example and update it with your configuration
cp .env.example .env
docker run -p 3000:3000 --env-file .env anotia/deep-research-web:latest

Client Mode (Traditional)

Users configure their own API keys in the browser. Use this mode for static deployments:

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

Environment Variables

Server Mode Configuration

Variable	Description	Default
`NUXT_PUBLIC_SERVER_MODE`	Enable server mode	`false`
`NUXT_AI_API_KEY`	AI provider API key	-
`NUXT_AI_API_BASE`	AI provider base URL	-
`NUXT_WEB_SEARCH_API_KEY`	Web search API key	-
`NUXT_WEB_SEARCH_API_BASE`	Web search base URL	-

Public Configuration (Server Mode)

Variable	Description	Default
`NUXT_PUBLIC_AI_PROVIDER`	AI provider type	`openai-compatible`
`NUXT_PUBLIC_AI_MODEL`	AI model name	`gpt-4o-mini`
`NUXT_PUBLIC_AI_CONTEXT_SIZE`	Context size	`128000`
`NUXT_PUBLIC_WEB_SEARCH_PROVIDER`	Search provider	`tavily`
`NUXT_PUBLIC_WEB_SEARCH_CONCURRENCY_LIMIT`	Max concurrency	`2`
`NUXT_PUBLIC_WEB_SEARCH_SEARCH_LANGUAGE`	Search language	`en`
`NUXT_PUBLIC_TAVILY_ADVANCED_SEARCH`	Use Tavily advanced search	`false`
`NUXT_PUBLIC_TAVILY_SEARCH_TOPIC`	Tavily search topic	`general`
`NUXT_PUBLIC_GOOGLE_PSE_ID`	Google PSE ID	-

Provider values

Type	Supported values
AI provider	`openai-compatible`, `siliconflow`, `302-ai`, `infiniai`, `openrouter`, `deepseek`, `ollama`
Web search provider	`tavily`, `firecrawl`, `google-pse`

Notes:

NUXT_WEB_SEARCH_API_KEY supports comma-separated keys for Tavily and Google PSE, for example key1,key2,key3.
Google PSE requires both NUXT_WEB_SEARCH_API_KEY and NUXT_PUBLIC_GOOGLE_PSE_ID.
Firecrawl self-hosted deployments can set NUXT_WEB_SEARCH_API_BASE.
Ollama uses http://localhost:11434/v1 as the default API base. When running the app inside Docker, localhost refers to the container itself, so set NUXT_AI_API_BASE to a reachable host or Docker network address if Ollama runs outside the container.