Transform Messy Code
Into Clean Art

Your AI-powered code janitor that understands, analyzes, and refactors code automatically. Perfect for beginners and pros alike.

# Before AI Cleanup
def messy(x,y,z):
    a=x+y
    b=a*z
    if(b>100):
        return True
    else:return False

# After AI Cleanup
def calculate_profit(revenue, cost, multiplier):
    total = revenue + cost
    result = total * multiplier
    return result > 100

How CodeCleano Works

Code Analysis

Our AI parses your code structure, identifies patterns, and detects inefficiencies using advanced static analysis.

Smart Refactoring

Automatically applies best practices like variable renaming, function extraction, and complexity reduction.

Performance Boost

Optimizes algorithms, reduces complexity, and suggests faster alternatives while preserving functionality.

Build Your Own Code AI

Follow our step-by-step guide to create your own code optimization AI

Choose Your Platform

Start with Python and Jupyter Notebook for experimentation. Then move to:

Google Colab (free GPU)
VS Code with Python extension
Docker for deployment

Essential Libraries

Install these Python packages:

pip install transformers torch astor libcst pytest

We'll use HuggingFace Transformers for the AI core and AST parsing for code analysis.

Training Process

1. Collect code examples (GitHub is great)
2. Create "before/after" refactored pairs
3. Fine-tune a model like CodeT5
4. Validate with test cases

# Sample training script
from transformers import T5ForConditionalGeneration, Trainer

model = T5ForConditionalGeneration.from_pretrained("Salesforce/codet5-base")

trainer = Trainer(
    model=model,
    train_dataset=code_dataset,
    args=training_args
)

trainer.train()

# Saving the model
model.save_pretrained("code_cleaner_model")

Transform Messy Code Into Clean Art