Gemini Terminal Agent

A powerful terminal-based agent using Google's Gemini model with web search capabilities. This agent lets you interact with Gemini through your terminal while leveraging real-time web search for up-to-date information.

Features

🤖 Conversational AI Interface - Talk with Google's Gemini models directly from your terminal
🔍 Web Search Integration - Get real-time information from the web
💬 Conversation History - Maintain context throughout your conversation
🛠️ Advanced Search Options - Filter by domains, exclude sites, and more
📝 Clean, Modular Architecture - Well-structured codebase that's easy to extend

Installation

Prerequisites

Python 3.9+
Google API key for Gemini models
Google Custom Search Engine (CSE) API key and ID

Setup

Clone the repository:
git clone https://github.com/yourusername/gemini-terminal-agent.git cd gemini-terminal-agent
Create a virtual environment (recommended):
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
Install dependencies:
pip install -r requirements.txt
Create a .env file in the project root with your API keys:
GOOGLE_GENAI_API_KEY=your_gemini_api_key_here SEARCH_ENGINE_API_KEY=your_google_api_key_here SEARCH_ENGINE_CSE_ID=your_cse_id_here DEFAULT_MODEL=gemini-2.5-flash-preview-04-17

Setting Up Google Search Engine

To use the web search functionality, you need to set up a Google Custom Search Engine:

Get a Google API Key:
- Go to Google Cloud Console
- Create a new project or select an existing one
- Navigate to "APIs & Services" > "Library"
- Search for "Custom Search API" and enable it
- Go to "APIs & Services" > "Credentials"
- Create an API key and copy it (this will be your SEARCH_ENGINE_API_KEY)
Create a Custom Search Engine:
- Go to Programmable Search Engine
- Click "Create a Programmable Search Engine"
- Add sites to search (use *.com to search the entire web)
- Give your search engine a name
- In "Customize" > "Basics", enable "Search the entire web"
- Get your Search Engine ID from the "Setup" > "Basics" page (this will be your SEARCH_ENGINE_CSE_ID)
Get a Gemini API Key:
- Go to Google AI Studio
- Sign in with your Google account
- Go to "API Keys" and create a new API key
- Copy the API key (this will be your GOOGLE_GENAI_API_KEY)

Usage

Run the agent from the terminal:

python main.py

Commands

Type your question or prompt to interact with the agent
Type help to see available tools and commands
Type clear to clear the conversation history
Type exit, quit, or q to exit the program

Example Queries

>>> What is the capital of France?
Paris is the capital of France. It is located in the north-central part of the country on the Seine River.

>>> search for recent developments in quantum computing
Searching the web for recent developments in quantum computing...
[Agent response with up-to-date information]

>>> help
🔍 Available Tools:
  - search: Search for information online based on a query
  - advanced_search: Perform an advanced search with domain filtering and time range options

⌨️ Terminal Commands:
  - help: Show this help message
  - clear: Clear conversation history
  - exit/quit/q: Exit the program

Project Structure

gemini-terminal-agent/
│
├── main.py               # Main entry point
├── search_server.py      # Search server entry point
├── .env                  # Environment variables (not versioned)
│
├── agent/                # Agent implementation
│   ├── __init__.py
│   ├── terminal_agent.py # Core agent implementation
│   └── config.py         # Agent configuration
│
├── search/               # Search functionality
│   ├── __init__.py
│   ├── server.py         # MCP search server
│   ├── engine.py         # Search engine implementation
│   └── content.py        # Web content extraction 
│
└── utils/                # Shared utilities
    ├── __init__.py
    ├── config.py         # Global configuration
    └── logging.py        # Logging setup

Advanced Configuration

You can customize the agent's behavior by modifying settings in your .env file:

# Model settings
DEFAULT_MODEL=gemini-2.5-flash-preview-04-17
# Other models: gemini-1.5-pro, gemini-1.5-flash

# Search settings
MAX_CONCURRENT_REQUESTS=5
CONNECTION_TIMEOUT=10
CONTENT_TIMEOUT=15
MAX_CONTENT_LENGTH=5000
CACHE_TTL=3600

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

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

Acknowledgments

This project uses LangChain for the agent framework
Web search functionality powered by Google Custom Search Engine
Built with Google's Gemini models