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A command-line tool that leverages artificial intelligence to generate complete project structures, add new features to existing projects, and streamline your development workflow.

Python CLI AI Coder helps developers quickly bootstrap new projects with well-structured codebases, proper configuration files, and best practices already implemented. Save hours of setup time and focus on building your application's unique features.

• Project Generation: Create complete project structures for various frameworks and languages
• Smart Templates: Choose from multiple project types (Python, JavaScript, TypeScript, React, Express, etc.)
• Feature Selection: Customize your project with optional features (Git, Tests, GitHub Actions, Documentation)
• Interactive CLI: User-friendly command-line interface with progress tracking and visual feedback
• Feature Addition: Extend existing projects with new functionality
• Project Organization: Generate well-structured projects with proper file organization
• Documentation: Automatically create README files and other documentation

• Python
• JavaScript
• TypeScript
• React + Vite + TypeScript
• React + Vite + JavaScript
• Express + TypeScript
• Express + JavaScript
• Custom (specify your own)

python-cli-ai-coder/├── .env# Environment variables (contains API key)├── main.py# Entry point for the application├── requirements.txt# Project dependencies├── src/# Main source code directory│   ├── __init__.py# Package initialization│   ├── cli/# Command-line interface│   │   ├── __init__.py│   │   └── main.py# CLI implementation│   ├── core/# Core functionality│   │   ├── __init__.py│   │   └── project_generator.py# ProjectGenerator class│   └── utils/# Utility functions│       ├── __init__.py│       ├── command_operations.py# Command execution functions│       └── file_operations.py# File and directory management functions

1. Clone the repository:

   git clone https://github.com/infysumanta/python-cli-ai-coder.gitcd python-cli-ai-coder

2. Set up a virtual environment:

   python -m venv .venvsource .venv/bin/activate# On Unix/Mac# OR.venv\Scripts\activate# On Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Create a.env file with your API key:

   OPENAI_API_KEY=your_api_key_here

Run the project generator:

python main.py

1. Select a project type from the available options:

   • Python
   • JavaScript
   • TypeScript
   • React + Vite (TypeScript or JavaScript)
   • Express (TypeScript or JavaScript)
   • Custom (specify your own)

2. Enter a project name that will be used for the project directory and in generated files

3. Choose a directory to store the project (defaults toprojects/your_project_name)

4. Provide a project description that will be used to generate appropriate code and documentation

5. Select optional features:

   • 🔀Git Initialization: Initialize a Git repository with appropriate .gitignore
   • 🚨Testing Framework: Add testing framework with sample tests
   • 🛠️GitHub Actions: Set up CI/CD workflows
   • 📝Documentation: Create documentation structure and templates

6. Confirm and generate your project structure

7. View the summary of generated files and directories

After generating a project, you can add new features to extend its functionality:

# After project generation completes, you'll be prompted to add features# Or run the tool again and navigate to the existing project directorypython main.py

1. Select "Yes" when asked if you want to add features to the project

2. Describe the feature you want to add in natural language, for example:

   • "Add a user authentication system with login and registration"
   • "Create a database connection module with SQLAlchemy"
   • "Add a REST API endpoint for user profiles"
   • "Implement a logging system with rotating file handlers"

3. Watch as the tool analyzes your project structure and implements the feature

4. Review the changes made to your project files

5. Optionally add more features by selecting "Yes" when prompted

• Project Types: Choose from predefined templates or create custom ones
• Project Features:
  • Git: Initialize a Git repository with appropriate .gitignore
  • Tests: Add testing framework with sample tests
  • GitHub Actions: Set up CI/CD workflows
  • Documentation: Create documentation structure and templates

The Python CLI AI Coder uses a tool-based approach to generate project structures:

TheProjectGenerator class defines a set of tools that the AI model can call to manipulate files and directories:

These tools are exposed to the AI model through a function-calling interface, allowing it to manipulate the filesystem in a controlled and secure manner.

1. Initialization 🚀

   • The tool loads the OpenAI API key from the.env file
   • It initializes theProjectGenerator class with this key
   • The system prepares the available tools for AI to use

2. User Input Collection 💬

   • The CLI presents an interactive interface with colorful prompts
   • Users select project type, name, location, and description
   • Users customize project features through a visual selection interface
   • All selections are validated and confirmed before proceeding

3. Project Generation Process ⚙️

   • The system crafts detailed prompts for the AI model with project specifications
   • The AI model (GPT-4o) analyzes the requirements and plans the project structure
   • The AI makes tool calls to create directories, files, and execute commands
   • The system executes these calls and provides real-time visual feedback
   • A comprehensive project structure is built according to best practices

4. Feature Addition Capability 🔍

   • Users can request new features in natural language
   • The AI analyzes the existing project structure to understand the codebase
   • The system determines the necessary changes to implement the feature
   • Files are modified or created to add the requested functionality
   • Tests and documentation are updated to reflect the new features

• rich: Enhanced terminal output with colors and formatting
• openai: AI integration for code generation
• python-dotenv: Environment variable management
• Additional supporting libraries (see requirements.txt)

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

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

Made with ❤️ bySumanta Kabiraj