Google Search Agent Assistant 🔍

An intelligent search assistant powered by LangChain and Streamlit that helps you find and summarize information from the web in real-time.

📸 Demo

Here's what the app looks like in action:

🌟 Features

• Real-time Web Search: Utilizes Google Search to find the most relevant information
• Dynamic Content Fetching: Automatically retrieves and processes webpage content
• Interactive UI: Built with Streamlit for a smooth user experience
• Tool Use Transparency: See exactly how the agent processes your query with an expandable tools log
• Streaming Responses: Get information as it's being processed, no need to wait for complete responses

🛠️ Technology Stack

• Frontend: Streamlit
• Backend: Python, LangChain
• AI/ML: GPT-4o-mini for natural language processing
• Tools:
  • Google Search Integration
  • Web Content Fetching
  • Real-time Response Streaming

🚀 Getting Started

1. Clone the repository

   git clone https://github.com/Xphi310302/google-search-agent-assistant.git
   cd search-agent

2. Install Poetry (if not already installed)

   pip install poetry

3. Install dependencies using Poetry

   poetry install
   source $(poetry env info --path)/bin/activate  # Activate the virtual environment

4. Set up environment variables

   # Create a .env file with your API keys
   OPENAI_API_KEY=your_openai_api_key
   GOOGLE_SEARCH_API_KEY=your_google_search_api_key
   GOOGLE_SEARCH_ENGINE_ID=your_google_search_engine_id

5. Run the application

   streamlit run main.py

💡 Usage

1. Enter your search query in the chat input
2. Watch as the agent:
   • Searches Google for relevant information
   • Fetches and processes webpage content
   • Provides a comprehensive response
3. View the Tools Use expander to see how the agent processes your query

🔄 How It Works

1. Query Processing: Your input is processed by the LangChain agent
2. Tool Selection: The agent decides which tools to use:
   • Google Search for finding relevant sources
   • Web Fetching for retrieving detailed content
3. Response Generation: Information is synthesized into a coherent response
4. Real-time Updates: See the process through the Tools Use expander

📝 Project Structure

search-agent/
├── main.py           # Main Streamlit application
├── agent/            # Agent implementation
│   ├── base.py      # Base agent class
│   └── tools/       # Tool implementations
├── config/          # Configuration files
├── utils/           # Utility functions
└── README.md        # Project documentation

📝 Todo List

• Do some experiments with some other crawler tools for more reliable results

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

Phi Nguyen Xuan

• LinkedIn: Phinx
• Website: https://phinx.vercel.app

---

Built with ❤️ using LangChain and Streamlit