https://github.com/sear-chat/searchat
Search + Chat = SearChat(AI Chat with Search), Support OpenAI/Anthropic/VertexAI/Gemini, DeepResearch, SearXNG, Docker. AI对话式搜索引擎，支持DeepResearch, 支持OpenAI/Anthropic/VertexAI/Gemini接口、聚合搜索引擎SearXNG，支持Docker一键部署。
https://github.com/sear-chat/searchat
ai anthropic deepresearch gemini llm mcp openai rag search searxng vertexai
Last synced: about 1 month ago
JSON representation
Search + Chat = SearChat(AI Chat with Search), Support OpenAI/Anthropic/VertexAI/Gemini, DeepResearch, SearXNG, Docker. AI对话式搜索引擎，支持DeepResearch, 支持OpenAI/Anthropic/VertexAI/Gemini接口、聚合搜索引擎SearXNG，支持Docker一键部署。
- Host: GitHub
- URL: https://github.com/sear-chat/searchat
- Owner: sear-chat
- License: mit
- Created: 2024-03-08T12:15:29.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-12-24T06:59:12.000Z (6 months ago)
- Last Synced: 2025-12-25T19:40:46.825Z (6 months ago)
- Topics: ai, anthropic, deepresearch, gemini, llm, mcp, openai, rag, search, searxng, vertexai
- Language: TypeScript
- Homepage: https://isou.chat
- Size: 11.6 MB
- Stars: 1,033
- Watchers: 14
- Forks: 176
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-ChatGPT-repositories - SearChat - Search + Chat = SearChat(AI Chat with Search), Support OpenAI/Anthropic/VertexAI/Gemini, DeepResearch, SearXNG, Docker. AI对话式搜索引擎，支持DeepResearch, 支持OpenAI/Anthropic/VertexAI/Gemini接口、聚合搜索引擎SearXNG，支持Docker一键部署。 (The latest additions 🎉)
README
# 🔍 SearChat
**AI-powered conversational search engine**
*Multi-model integration | Real-time conversational search | Deep Research support*
**English** | [中文](./README_ZH_CN.md) | [日本語](./README_JP.md)
---
## 🌟 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**:
- [x] 🤖 **Multi-model Support** - Compatible with OpenAI, Anthropic, Gemini APIs
- [x] 🔍 **Multiple Search Engines** - Support for Bing, Google, SearXNG and more
- [x] 💬 **Conversational Search** - Multi-turn chat-based search experience
- [x] ⏰ **Chat History** - Conversation history cached in browser (IndexedDB/LocalStorage)
- [x] 🧠 **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](https://youtu.be/W_455aI14hI)
### 📦 Standalone Usage
If you want to integrate Deep Research capabilities into your own Node.js project:
```bash
npm install deepsearcher
```
[](https://www.npmjs.com/package/deepsearcher)
[](https://www.npmjs.com/package/deepsearcher)
**Quick Example**:
```typescript
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 `[[1](url)]` format with clickable links
- `enableCitationUrl: false` - Outputs `[[citation:1]]` simple format
Documentation: [DeepResearch NPM Package](https://www.npmjs.com/package/deepsearcher)
## 🐳 Quick Deployment (Recommended Docker)
### 📋 Prerequisites
- [Install Docker](https://docs.docker.com/install/) 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](./deploy/docker-compose.yaml) file
Please refer to the [deploy/docker-compose.yaml](./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:
```yaml
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](./deploy/model.json) file in the same directory as docker-compose.yaml to configure AI models and API keys:
```json
[
{
"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
```bash
docker compose up -d
```
#### 5. Access Application
Open your browser and visit: [http://localhost:3000](http://localhost:3000)
### 🔄 Update Deployment
```bash
# 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:
```yaml
search:
formats:
- html
- json
```
## 💻 Local Development
### 📋 Requirements
- **Node.js** >= 20
- **Package Manager** yarn@3.5.1
- **Build Tool** Turborepo
### 🏗️ Project Architecture
```text
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
```bash
# 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:
```bash
# Copy environment configuration template
cp apps/server/.env apps/server/.env.local
# Edit configuration file
vim apps/server/.env.local
```
#### 3. Start Development Services
```bash
# Start both frontend and backend development servers
yarn dev
# Or use Turborepo command
turbo dev
```
Access URLs:
- Frontend: [http://localhost:5173](http://localhost:5173)
- Backend: [http://localhost:3000](http://localhost:3000)
#### 4. Build Production Version
```bash
# 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](https://github.com/sear-chat/SearChat/issues) - Report bugs or feature requests
- [GitHub Discussions](https://github.com/sear-chat/SearChat/discussions) - Technical discussions and Q&A
## 📄 License
This project is licensed under the [MIT License](LICENSE).
## 🙏 Acknowledgments
- [SearXNG](https://github.com/searxng/searxng) - Open source search engine
- [LangChain](https://github.com/langchain-ai/langchain) - AI application development framework
- [Tencent EdgeOne](https://edgeone.ai/?from=github) - CDN acceleration support
---
**⭐ If this project helps you, please give it a Star!**
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