Python AI Toolkit CLI

A command-line AI toolkit that performs three text-processing tasks using an LLM API:

• Summarization
• Translation
• Sentiment Analysis

Features

• CLI interface built with argparse
• Text summarization
• Text translation
• Sentiment analysis
• Environment-based API key management with .env
• Input validation for CLI arguments
• API error handling
• Automated tests using pytest and mocking
• Dependency management with requirements.txt

Tech Stack

• Python
• Gemini API
• argparse — CLI argument parsing
• python-dotenv — environment variable management
• pytest — automated testing

Installation

1. Clone the repository

git clone <repository-url>
cd AI_toolkit

2. Create a virtual environment

python -m venv .venv

3. Activate the virtual environment

Windows:

.venv\Scripts\activate

macOS/Linux:

source .venv/bin/activate

4. Install dependencies

pip install -r requirements.txt

Environment Setup

Create a .env file in the project root directory and add your Gemini API key:

GEMINI_API_KEY=your_api_key_here

The API key is loaded from the environment using python-dotenv.

Do not commit the .env file to GitHub.

Usage

Summarize

python ai_toolkit.py summarize "I love Python"

Translate

python ai_toolkit.py translate "I love Python" --language Spanish

Sentiment Analysis

python ai_toolkit.py sentiment "I love Python"

Testing

Run the automated tests with:

pytest test_ai_toolkit.py

The test suite uses pytest and mocking to test the AI functions without making real API calls.

Project Structure

AI_toolkit/
├── ai_toolkit.py          # Main CLI application
├── test_ai_toolkit.py     # Automated tests
├── requirements.txt       # Project dependencies
├── .env                   # API key (not committed)
├── .gitignore             # Files excluded from Git
└── README.md              # Project documentation