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🌟 Project Overview

SearChat is a modern AI-powered conversational search engine built with Turborepo monorepo architecture, integrating Node.js + Koa backend and Vue 3 + TypeScript frontend.

🎯 Key Features:

• 🤖 Multi-model Support - Compatible with OpenAI, Anthropic, Gemini APIs
• 🔍 Multiple Search Engines - Support for Bing, Google, SearXNG and more
• 💬 Conversational Search - Multi-turn chat-based search experience
• ⏰ Chat History - Conversation history cached in browser (IndexedDB/LocalStorage)
• 🧠 Deep Research Mode - Refactoring deep research functionality
• 🔌 MCP Support - (TODO) Support for external MCP services
• 🖼️ Image Search - (TODO) Support for image and video search
• 📂 File Parsing - (TODO) Support for document upload and content extraction

✨ Core Features

🧠 Deep Research

• Intelligent Research Mode - Deep research functionality
• Iterative Exploration - Workflow orchestration based on LangChain + LangGraph
• Comprehensive Report Generation - Automatically generate structured research reports

🤖 AI Model Support

[!IMPORTANT] To achieve the best results, the model must support Tool Call (Function Calling).

• OpenAI API compatible
• Google Gemini API compatible
• Anthropic API compatible
• Google Vertex AI compatible

🔍 Multi-Search Engine Integration

• SearXNG - Open source aggregated search, no API key required
• Bing Search - Microsoft Bing web search API
• Google Search - Google web search API
• Tavily - Tavily web search API
• Exa - Exa.ai web search API
• Bocha - BochaAI web search API
• ChatGLM Web Search - Zhipu AI free search plugin

🎨 Modern Interface Experience

• Responsive Design - Perfect adaptation for desktop and mobile
• Dark/Light Theme - Support for automatic system theme switching
• Internationalization - Multi-language interface (i18n)
• Real-time Streaming - Typewriter effect answer display
• Contextual Conversation - Support for multi-turn dialogue and history

🔬 Deep Research Mode

Deep Research mode uses AI-driven iterative search and analysis to generate comprehensive and in-depth research reports on any topic.

Key Features:

• 🔄 Iterative Research - Automatically identifies knowledge gaps and performs follow-up searches
• 📊 Structured Reports - Generates well-organized research reports with citations
• 🔗 Citation Support - Includes source references with configurable formats ([[citation:1]] or clickable URLs)
• 🎯 Multi-Engine Search - Leverages multiple search engines for comprehensive results

📹 Feature Demo

Demo

📦 Standalone Usage

If you want to integrate Deep Research capabilities into your own Node.js project:

npm install deepsearcher

Quick Example:

import { DeepResearch } from 'deepsearcher';

const deepResearch = new DeepResearch({
  searcher: async ({ query }) => {
    // Your search implementation
    return searchResults;
  },
  options: {
    type: 'openai',
    apiKey: 'your-api-key',
    enableCitationUrl: false, // Use [[citation:1]] format
  },
});

const agent = await deepResearch.compile();
const result = await agent.invoke({
  messages: [{ role: 'user', content: 'Your research question' }],
});

Citation Format Options:

• enableCitationUrl: true (default) - Outputs <sup>[[1](url)]</sup> format with clickable links
• enableCitationUrl: false - Outputs [[citation:1]] simple format

Documentation: DeepResearch NPM Package

🐳 Quick Deployment (Recommended Docker)

📋 Prerequisites

• Install Docker and Docker Compose
• Prepare AI model API keys (configure in model.json)
• Optional: Configure search engine API keys (in docker-compose.yaml)
• Ensure network access to required services (SearXNG needs Google access)

🚀 One-Click Deployment

1. Create docker-compose.yaml file

Please refer to the deploy/docker-compose.yaml file.

2. Configure Environment Variables

Edit the docker-compose.yaml file and modify the corresponding environment variables in the search_chat service:

services:
  search_chat:
    container_name: search_chat
    image: docker.cnb.cool/aigc/aisearch:v1.2.0-alpha
    environment:
      # Server Configuration
      - PORT=3000

      # Search Engine API Keys (configure as needed)
      - BING_SEARCH_KEY=your_bing_key
      - GOOGLE_SEARCH_KEY=your_google_key
      - GOOGLE_SEARCH_ID=your_google_cse_id
      - TAVILY_KEY=your_tavily_key
      - ZHIPU_KEY=your_zhipu_key
      - EXA_KEY=your_exa_key
      - BOCHA_KEY=your_bocha_key

      # Web Content Extraction (optional)
      - JINA_KEY=your_jina_key

      # SearXNG Configuration (included by default, ready to use)
      - SEARXNG_HOSTNAME=http://searxng:8080
      - SEARXNG_SAFE=0
      - SEARXNG_LANGUAGE=en
      - SEARXNG_ENGINES=bing,google
      - SEARXNG_IMAGES_ENGINES=bing,google

      # DeepResearch Configuration
      - DEEP_MAX_RESEARCH_LOOPS=3
      - DEEP_NUMBER_OF_INITIAL_QUERIES=3

      # Domain Whitelist (optional)
      - WHITELIST_DOMAINS=
    volumes:
      - ./model.json:/app/apps/server/dist/model.json
    ports:
      - "3000:3000"
    restart: always

3. Configure AI Models (Required)

Create and edit the model.json file in the same directory as docker-compose.yaml to configure AI models and API keys:

[
  {
    "provider": "openai",
    "type": "openai",
    "baseURL": "https://api.openai.com/v1",
    "apiKey": "sk-your-openai-api-key",
    "models": [
      {
        "name": "gpt-4o-mini",
        "alias": "GPT-4o Mini",
        "description": "OpenAI GPT-4o Mini model",
        "maxTokens": 262144,
        "intentAnalysis": true
      },
      {
        "name": "gpt-4o",
        "alias": "GPT-4o",
        "description": "OpenAI GPT-4o model",
        "maxTokens": 262144
      }
    ]
  },
  {
    "provider": "anthropic",
    "type": "anthropic",
    "baseURL": "https://api.anthropic.com/v1",
    "apiKey": "sk-your-anthropic-api-key",
    "models": [
      {
        "name": "claude-sonnet-4-5",
        "alias": "Claude Sonnet 4.5",
        "description": "Anthropic Claude Sonnet 4.5",
        "maxTokens": 131072
      }
    ]
  }
]

Models with intentAnalysis: true will be used for search intent analysis and query rewriting. It's recommended to set smaller models here to improve response speed.

Configuration Description:

• provider: Model provider name
• type: API type (openai/anthropic/google etc.)
• baseURL: API base URL
• apiKey: Your API key
• models: Model list with name, alias, description and max tokens

4. Start Services

docker compose up -d

5. Access Application

Open your browser and visit: http://localhost:3000

🔄 Update Deployment

# Stop services
docker compose down

# Pull latest image
docker pull docker.cnb.cool/aigc/searchchat:latest

# Restart
docker compose up -d

🔍 Search Engine Configuration

The project supports multiple search engines. Choose the appropriate search source based on your needs. SearXNG is recommended.

🆓 SearXNG (Recommended - Free & Open Source)

Advantages: Completely free, no API key required, aggregates multiple search sources, protects privacy

SearXNG is an open-source metasearch engine that aggregates results from multiple search services without tracking users. Built into Docker deployment, ready to use out of the box.

Configuration Options:

• SEARXNG_ENGINES: Set search engines (default: bing,google)
• SEARXNG_LANGUAGE: Search language (zh=Chinese, en-US=English, all=all)
• SEARXNG_SAFE: Safe search level (0=off, 1=moderate, 2=strict)

[!IMPORTANT]

Make sure to activate the json format to use the API. This can be done by adding the following line to the searxng/settings.yml file:

search:
    formats:
        - html
        - json

💻 Local Development

📋 Requirements

• Node.js >= 20
• Package Manager yarn@3.5.1
• Build Tool Turborepo

🏗️ Project Architecture

search_with_ai/
├── apps/
│   ├── server/          # Backend service (Koa + TypeScript)
│   │   ├── src/
│   │   │   ├── app.ts           # Application entry
│   │   │   ├── controller.ts    # Route controllers
│   │   │   ├── interface.ts     # Type definitions
│   │   │   └── model.json       # Model configuration
│   │   └── package.json
│   └── web/             # Frontend application (Vue 3 + TypeScript)
│       ├── src/
│       │   ├── pages/           # Page components
│       │   ├── stores/          # Pinia state management
│       │   └── components/      # Common components
│       └── package.json
├── deploy/              # Deployment configuration
│   ├── docker-compose.yaml
│   ├── .env.docker
│   └── model.json
└── package.json         # Root configuration

🚀 Development Workflow

1. Install Dependencies

# Clone project
git clone https://github.com/sear-chat/SearChat.git
cd SearChat

# Install dependencies (run in root, will install all sub-project dependencies)
yarn install

2. Configure Environment

Copy and edit server environment configuration:

# Copy environment configuration template
cp apps/server/.env apps/server/.env.local

# Edit configuration file
vim apps/server/.env.local

3. Start Development Services

# Start both frontend and backend development servers
yarn dev

# Or use Turborepo command
turbo dev

Access URLs:

• Frontend: http://localhost:5173
• Backend: http://localhost:3000

4. Build Production Version

# Build all applications
yarn build

# Or
turbo build

🔧 Development Tools

Backend Tech Stack

• Framework: Koa.js + TypeScript
• AI Integration: LangChain + LangGraph
• Search Engines: Multi-engine adapter pattern

Frontend Tech Stack

• Framework: Vue 3 + Composition API
• Build: Vite + TypeScript
• UI Library: TDesign Vue Next
• State Management: Pinia + persistence
• Styling: Tailwind CSS + Less

🤝 Contributing

Welcome to contribute to the project! Please follow these steps:

1. Fork the project to your GitHub account
2. Create a feature branch git checkout -b feature/amazing-feature
3. Commit your changes git commit -m 'Add amazing feature'
4. Push the branch git push origin feature/amazing-feature
5. Create a Pull Request

🐛 Issue Reporting

• GitHub Issues - Report bugs or feature requests
• GitHub Discussions - Technical discussions and Q&A

📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• SearXNG - Open source search engine
• LangChain - AI application development framework
• Tencent EdgeOne - CDN acceleration support

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