A command-line interface for interacting with Google's Gemini AI models
Project description
Piptalk CLI (Python)
A command-line interface for interacting with Google's Gemini AI models. Chat with Gemini AI directly from your terminal!
This is the Python version of the Gemini CLI tool. For the Node.js version, see @karitkeyaranjan/talk-cli.
Installation
From PyPI (when published):
pip install piptalk-cli
From source:
git clone <repository-url>
cd gemini-cli-python
pip install -e .
Setup
- Get your Gemini API key from Google AI Studio
- Set it as an environment variable:
export GEMINI_API_KEY="your-api-key-here"
Or create a .env file in your home directory:
GEMINI_API_KEY=your-api-key-here
Note: The tool comes with a default API key, but it's recommended to use your own.
Usage
Interactive Mode
Simply run the command without any arguments:
piptalk
Command Mode
Provide a prompt directly:
piptalk "Explain quantum computing in simple terms"
Select a Model
Use the --model or -m flag to choose a specific model:
piptalk --model flash "Hello world"
piptalk -m 2.0-flash "Quick question"
piptalk -m 2.5-pro "Explain machine learning"
Available Models
flash- ⚡ Gemini 2.5 Flash (default)2.0-flash- ⚡ Gemini 2.0 Flash2.5-pro- 🟦 Gemini 2.5 Pro1.5-pro- 🟦 Gemini Pro Latestpro-latest- 🟦 Gemini Pro Latest
Help
piptalk --help
piptalk -h
Examples
# Interactive mode
piptalk
# Quick question
piptalk "What is the capital of France?"
# Use a specific model
piptalk -m 2.0-flash "Write a Python function to sort a list"
piptalk -m 2.5-pro "Explain the difference between REST and GraphQL"
# Multi-word prompts
piptalk "Explain the difference between REST and GraphQL"
Requirements
- Python >= 3.8
- A valid Gemini API key (optional, default key included)
Features
- ✨ Beautiful formatted output with syntax highlighting
- 🎨 Color-coded responses for better readability
- 📝 Code block formatting with borders
- 📋 List and header formatting
- 🔄 Support for multiple Gemini models
- 💬 Interactive and command-line modes
License
ISC
Development
To set up for development:
git clone <repository-url>
cd gemini-cli-python
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
pip install -e .
Publishing to PyPI
# Install build tools
pip install build twine
# Build the package
python -m build
# Upload to PyPI (test first with test.pypi.org)
twine upload dist/*
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