yokingma

SearChat

<a name="top"></a> <div align="center"> # 🔍 SearChat **AI-powered conversational search engine** *Multi-model integration | Real-time conversational search | Deep Research support* <p align="center"> <a href="https://github.com/sear-chat/SearChat/stargazers"><img src="https://img.shields.io/github/stars/sear-chat/SearChat" alt="Github Stars"></a> <a href="https://github.com/sear-chat/SearChat/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-purple" alt="License"></a> <a href="https://github.com/sear-chat/SearChat/issues/new"><img src="https://img.shields.io/badge/Report a bug-Github-%231F80C0" alt="Report a bug"></a> <a href="https://github.com/sear-chat/SearChat/discussions/new?category=q-a"><img src="https://img.shields.io/badge/Ask a question-Github-%231F80C0" alt="Ask a question"></a> </p> **English** | [中文](./README_ZH_CN.md) | [日本語](./README_JP.md) </div> --- ## 推荐开源AI项目 / Recommended Open Source AI Project ### [WeClaws](https://github.com/baseclaw/weclaws) WeClaws 是一个可一键部署的多用户微信 AI 助理机器人管理面板。你可以在 Web 端统一管理多个 AI 机器人，支持工具调用、Skills、MCP、子智能体、记忆、做梦、定时任务和沙盒执行等能力。 WeClaws is a one-click deployable management dashboard for multi-user WeChat AI assistant bots. It lets you manage multiple AI bots from the web and supports tool calling, Skills, MCP, sub-agents, memory, dreaming, scheduled tasks, and sandbox execution. <div align="center"> <a href="https://github.com/baseclaw/weclaws"> <img src="./assets/weclaws.jpg" alt="WeClaws AI assistant management dashboard" style="border-radius: 10px; box-shadow: 0 4px 20px rgba(0,0,0,0.1);"></img> </a> </div> --- <div align="center"> <img src="./assets/screenshot.png" alt="AI Search Chat Interface" style="border-radius: 10px; box-shadow: 0 4px 20px rgba(0,0,0,0.1);"></img> </div> ## 🌟 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 `<sup>[[1](url)]</sup>` 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", "apiMode": "openai-responses", "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 - `apiMode`: Optional for OpenAI-compatible providers. Use `openai-completions` (default) for Chat Completions, or `openai-responses` for the OpenAI Responses API. Leave it unset for OpenAI-compatible endpoints that do not support the Responses API. - `models`: Model list with name, alias, description and max tokens When `apiMode` is set on an OpenAI provider, the main chat response, search intent analysis, and DeepResearch flows use the same mode. #### 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** [email protected] - **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 --- <div align="center"> **⭐ If this project helps you, please give it a Star!** [🚀 Back to top](#top) </div>