scriptmonkey 1.3.1

A Python package that generates complex Python projects and fixes errors in your code using OpenAI's GPT API.

ScriptMonkey 🐒

ScriptMonkey is an AI-powered Python package that reimagines how projects are built. It doesn’t just generate simple scripts or templates like traditional LLMs—it creates entire, multi-file, multi-directory projects with fully custom code. Complex Python projects can be generated in seconds based on your natural language descriptions, providing everything you need, from models and routes to templates and configuration files. With ScriptMonkey, you can instantly bootstrap new ideas or start complex projects without the tedious setup. And with built-in error detection and automatic fixes, ScriptMonkey keeps your development process smooth and stress-free, letting you focus on what matters most: building.

Features

• Custom Project Generation: Create entire Python projects, not just boilerplate code. ScriptMonkey generates the specific files and directories you need based on your description.
• Lightning-Fast Setup: Complex Python projects can be generated in seconds, saving you time and effort.
• Automatic Error Detection: Captures errors during runtime.
• AI-Powered Fixes: Uses OpenAI's GPT API to understand and resolve errors.
• Code Auto-Correction: Automatically updates your Python files with the fixes.
• Cross-IDE Compatibility: Works with any IDE or code editor.
• Context-Aware Q&A: Ask questions directly to ChatGPT with or without providing files for context. Get detailed answers with code examples, explanations, and best practices tailored to your needs.

🚀 Watch the Demo

Click the image above or watch the video directly on YouTube.

Installation

To install ScriptMonkey, simply run:

pip install scriptmonkey

Usage

Project Generation with scriptmonkey CLI Tool

ScriptMonkey can generate a complete, custom-coded project structure based on a description you provide. This feature helps you quickly set up new projects with the necessary files and folders.

How to Use

1. Run the following command in your terminal:

   scriptmonkey
   

2. A text editor will open (e.g., nano, vim, or notepad depending on your environment). Follow the on-screen instructions to provide a detailed description of your project.

3. Save and close the editor. ScriptMonkey will then:

   • Generate a complete project structure based on your description.
   • Create directories, code files, and templates.
   • Automatically generate a README.md with installation instructions and usage details.

Example Project Description Prompt

I need a Flask-based web application for managing a book library. The application should include:
- User authentication (login, registration, password reset).
- Models for Users, Books, and Authors using SQLAlchemy.
- A REST API with routes for adding, updating, and deleting books and authors.
- An admin dashboard for managing users and viewing statistics.
- HTML templates for user login, book list, and book detail views.
- The database should use PostgreSQL.
- Include environment-specific configurations for development and production.

ScriptMonkey will use this description to create a project structure and code files for you in a directory named generated_project.

Context-Aware Q&A with scriptmonkey --ask CLI Tool

ScriptMonkey can help answer your technical questions, whether or not you provide code files for context. This feature allows you to leverage the power of ChatGPT to ask questions about files, clarify concepts, get code reviews, or understand best practices in various programming languages.

How to Use

• Ask a question:

  scriptmonkey --ask "What are the best practices for database indexing?"
  

• Ask a question with files:

  scriptmonkey --ask "Can you help me optimize this function?" --files ./path/to/file1.py ./path/to/file2.js
  

  The --files flag allows you to provide specific files as context for your question. ScriptMonkey will include the contents of these files in its analysis, allowing it to reference the actual code or data you are working with. This is particularly useful for getting detailed feedback on specific code snippets, debugging issues, or seeking advice on how to improve certain parts of your project.

  When you use --files, ScriptMonkey will read the contents of each provided file, include them in the prompt, and tailor its response based on the combined context of your question and the file contents. This feature ensures that you get precise, context-aware answers, helping you solve code challenges or understand complex concepts more effectively.

• Ask a question with a directory tree:

  scriptmonkey --ask "How do I organize this project better?" --tree
  

  The --tree flag will include a tree representation of the current working directory (up to 6 levels deep, excluding common large folders) in the context for your question. This is particularly useful when you want to get feedback on the structure of your codebase or when your question relates to the project organization.

  ScriptMonkey will analyze your question and any provided files or the directory tree to give a detailed, markdown-formatted response with explanations and code suggestions, if applicable. This feature is great for in-depth guidance on code optimization, architecture, or general programming questions.

Error Handling with scriptmonkey.run()

ScriptMonkey doesn't just build projects; it also makes debugging a breeze.

1. Import scriptmonkey in your Python script.
2. Call scriptmonkey.run() to activate the error handler.
3. Run your code, and let ScriptMonkey handle any errors that occur.

Example

import scriptmonkey

# Enable ScriptMonkey's error handler
scriptmonkey.run()

# Intentional error for testing
def add(a, b):
    return a + b  # This will fail if b is a string

print(add(2, "3"))  # ScriptMonkey will automatically fix this error and update the file.

Once an error occurs, ScriptMonkey will:

1. Detect the error.
2. Send the error and code to OpenAI for analysis.
3. Provide a solution and automatically update the file with the corrected code.

Setting or Updating Your OpenAI API Key

If you haven't set your OpenAI API key yet or need to update it, you can do so with the following command:

python3 -m scriptmonkey --set-api-key your-api-key

This will store the API key in a config locally and use it for all future interactions with OpenAI.

Requirements

• Python 3.6 or later
• An OpenAI API key (follow the steps below if you don't have one)

Obtaining an OpenAI API Key

1. Go to the OpenAI website: OpenAI Platform
2. Sign up or log in to your account.
3. Navigate to the API keys section in your account dashboard.
4. Create a new API key and copy it.

Configuring the API Key for ScriptMonkey

• Option 1: Environment Variable
  You can set up your API key as an environment variable:

  export OPENAI_API_KEY='your-api-key'
  

• Option 2: Entering the API Key When Prompted
  If ScriptMonkey does not find an API key in your environment variables, it will prompt you to enter your key. Once entered, it will save the key to a configuration file for future use.

• Option 3: Using the --set-api-key Command
  Use the --set-api-key command as shown above to set or update your API key easily.

Let ScriptMonkey take care of your Python errors and project setup so you can focus on building!