hmnshudhmn24/Universal-Code-Refactor-32B

🚀 Universal Code Refactor 32B

Universal Code Refactor 32B is a complete AI-driven code engineering system designed to automate large-scale refactoring, bug discovery, language-to-language conversion, and code optimization.
The project includes a full toolkit: model, pipelines, refactor engine, bug detector, conversion engine, API, CLI, Gradio UI, datasets, and training scripts.

🌟 Features

🔧 1. Multi-Language Code Refactoring

Supports intelligent transformations for multiple languages:

• Python
• Java
• JavaScript

Includes:

• Automatic formatting (Black + isort)
• Unused import removal
• Inline simple functions
• Java loop modernization → for-each syntax
• JavaScript var → let transformation
• Structural code cleanup
• Rule-based + AST-based hybrid refactoring

🐞 2. Static Bug Detection

Real AST-based detection, including:

• Possible None/null dereferences
• Unused variables
• Unsafe JavaScript eval() usage
• Missing null checks in Java
• Future support for type-based reasoning

🔄 3. Multi-Language Code Conversion

Built-in conversions:

• Python → Java
• Java → Python

Supports:

• Function extraction
• Main() generation
• Basic block translation
• Extendable conversion rules

📄 4. Patch & Diff Generation

Automated patch engine creates:

• Unified diffs
• Patch previews
• Patch cleanliness scores
• Complexity reduction metrics

Useful for PR automation and CI pipelines.

🧠 5. Compact Transformer Code Model

The model includes:

• Token embedding
• Positional encoding
• Transformer encoder stack
• Code-token-aware tokenizer
• Modular upgrade path to LLaMA / CodeGen / StarCoder models

🌐 6. Deployment Ecosystem

Included ready-to-run components:

✔ FastAPI REST Server

uvicorn inference.api_server:app --reload

✔ CLI Tool

python inference/cli.py --mode refactor --file example.py

✔ Gradio Web UI

python inference/gradio_app.py

✔ Docker Container

docker build -t universal-refactor .
docker run -p 8000:8000 universal-refactor

✔ Hugging Face Spaces App

Located inside /deployment/huggingface_spaces/

📂 Project Structure

Universal-Code-Refactor-32B/
│
├── README.md
├── requirements.txt
├── MODEL_CARD.md
│
├── src/universal_refactor/
│   ├── refactor_engine.py
│   ├── bug_detector.py
│   ├── code_converter.py
│   ├── patch_generator.py
│   ├── pipelines.py
│   ├── tokenizer.py
│   ├── model.py
│   ├── long_context_manager.py
│   ├── utils.py
│   └── embeddings/
│
├── inference/
│   ├── api_server.py
│   ├── cli.py
│   └── gradio_app.py
│
├── deployment/
│   ├── Dockerfile
│   └── huggingface_spaces/
│
├── training/
│   ├── pretrain.py
│   ├── finetune_refactor.py
│   ├── finetune_bugfix.py
│   ├── tokenizer_training.py
│   ├── long_context_training.py
│   └── distributed/
│
└── datasets/
    ├── code_repo_raw/
    ├── multilingual_code_clean/
    ├── refactor_pairs/
    ├── bugfix_pairs/
    ├── conversion_pairs/
    └── metadata.json

🛠 Installation

1. Clone Repository

git clone https://github.com/YOUR_USERNAME/universal-code-refactor-32b
cd universal-code-refactor-32b

2. Install Dependencies

pip install -r requirements.txt

🚀 Usage Examples

🔧 Refactor Python Code

python inference/cli.py --mode refactor --file sample.py --lang python

🔄 Convert Java → Python

python inference/cli.py --mode convert --file MyClass.java --src java --tgt python

🌐 Run Web UI

python inference/gradio_app.py

📊 Evaluation Tools

The evaluation pipeline computes:

• Cyclomatic complexity reduction
• Patch cleanliness
• Code change metrics
• Structural improvement score

Run evaluation:

python evaluation/evaluate.py