https://github.com/divak-ar/searchagent
A chat app with web search functionality and some more features (look the README.MD file)
https://github.com/divak-ar/searchagent
flask gemini-api langchain langgraph nextjs python server-sent-events tailwindcss tavily-api typescript uvicorn web-development
Last synced: 3 months ago
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A chat app with web search functionality and some more features (look the README.MD file)
- Host: GitHub
- URL: https://github.com/divak-ar/searchagent
- Owner: Divak-ar
- Created: 2025-06-23T12:40:42.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-06-23T16:35:41.000Z (about 1 year ago)
- Last Synced: 2025-06-23T17:42:36.217Z (about 1 year ago)
- Topics: flask, gemini-api, langchain, langgraph, nextjs, python, server-sent-events, tailwindcss, tavily-api, typescript, uvicorn, web-development
- Language: Jupyter Notebook
- Homepage:
- Size: 381 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Search Agent - AI-Powered Web Search Assistant
A modern, responsive AI-powered search application that combines web search capabilities with conversational AI to provide comprehensive answers to user queries.
## ✨ Features
- 🔍 **Intelligent Web Search**: Uses Tavily API for real-time web search
- 🤖 **AI-Powered Responses**: Powered by Google Gemini 2.0 Flash model
- 💬 **Real-time Streaming**: Server-sent events for live response streaming
- 🎯 **Search Progress Tracking**: Visual indicators for search stages
- 📋 **Copy Functionality**: Easy copy-to-clipboard for AI responses
- 🔄 **Session Management**: Start fresh conversations anytime
- 🎨 **Session Context**: Custom prompt engineering for personalized AI responses
- 💡 **Interactive UI**: Modern design with smooth animations
## 📸 Screenshots
### Main Application Interface
*The main chat interface showing real-time AI responses with web search integration*
### Custom Session Context
*Session Context feature allowing users to customize AI behavior with predefined presets or custom prompts*
## 🏗️ Architecture
### Backend (Python/FastAPI)
- **FastAPI**: Modern web framework for building APIs
- **LangGraph**: State management for AI workflows
- **LangChain**: Integration with various AI models and tools
- **Tavily**: Web search API for real-time information retrieval
- **Google Gemini**: Advanced language model for responses
### Frontend (Next.js/React)
- **Next.js 15**: React framework with TypeScript
- **Tailwind CSS**: Utility-first CSS framework for responsive design
- **Server-Sent Events**: Real-time communication with backend
- **TypeScript**: Type-safe development
## 🚀 Setup Instructions
### Prerequisites
- Python 3.8+
- Node.js 18+
- API Keys for:
- Google Gemini API
- Tavily Search API
### Backend Setup
1. Navigate to the server directory:
```bash
cd server
```
2. Create and activate a virtual environment:
```bash
# Windows
python -m venv venv
venv\Scripts\activate
# macOS/Linux
python -m venv venv
source venv/bin/activate
```
```bash
python -m venv venv
venv\Scripts\activate # Windows
# or
source venv/bin/activate # Linux/Mac
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Configure environment variables in `.env`:
```env
GOOGLE_API_KEY=your_google_api_key_here
TAVILY_API_KEY=your_tavily_api_key_here
# Optional: LangSmith for debugging
LANGSMITH_TRACING=true
LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
LANGSMITH_API_KEY=your_langsmith_key
LANGSMITH_PROJECT=your_project_name
```
5. Start the backend server:
```bash
uvicorn app:app --reload --host 0.0.0.0 --port 8000
```
### Frontend Setup
1. Navigate to the client directory:
```bash
cd client
```
2. Install dependencies:
```bash
npm install
```
3. Start the development server:
```bash
npm run dev
```
The application will be available at:
- Frontend: http://localhost:3000 (or next available port)
- Backend: http://localhost:8000
- Backend Health Check: http://localhost:8000/health
## Usage
1. Open the frontend application in your browser
2. Type your question in the input field
3. Watch as the AI searches the web and compiles a response
4. Copy responses using the copy button
### Navigation
- **Home Tab**: Welcome page with project overview and "Perplexity 2.0" branding
- **Chat Tab**: Main conversational interface with AI search capabilities
- **Settings Tab**: Customize your experience (theme, search preferences, etc.)
### Session Context Feature
1. Click the large **Session Context** button (bottom-right corner)
2. Choose from **Quick Presets**:
- General Assistant
- Technical Expert
- Research Assistant
- Simple Explainer
3. Or write your own **Custom Context** to guide AI responses
4. The context applies to all messages in the current session
### Chat Features
1. **Ask Questions**: Type your question in the input field
2. **Real-time Responses**: Watch as the AI searches the web and streams responses
3. **Search Progress**: Visual indicators show search stages (searching → reading → writing)
4. **Copy Responses**: Click the copy button on any AI response
### Tips for Better Results
- Use the **Session Context** to specify your role or expertise level
- Ask specific questions for more targeted search results
- Try different contexts for the same question to get varied perspectives
## Development
### Adding New Features
1. **Backend**: Add new endpoints in `app.py` or extend the LangGraph workflow
2. **Frontend**: Add new components in `src/components/` or extend existing functionality
### Environment Variables
The application uses several environment variables:
- `GOOGLE_API_KEY`: Required for AI responses
- `TAVILY_API_KEY`: Required for web search
- `LANGSMITH_*`: Optional for debugging and monitoring
### Performance Tips
- Use specific, focused queries for better search results
- Set appropriate session context to reduce token usage
- Monitor API usage in Google AI Studio and Tavily dashboards
### Building for Production
1. **Backend Deployment**:
```bash
# Install production dependencies
pip install gunicorn
# Run with gunicorn
gunicorn app:app -w 4 -k uvicorn.workers.UvicornWorker --bind 0.0.0.0:8000
```
2. **Frontend Build**:
```bash
cd client
npm run build
npm start
```
3. **Environment Variables**: Set production API keys and endpoints
4. **Security**: Configure CORS, rate limiting, and authentication as needed
## Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request
## License
This project is for educational and development purposes.