red-ai-code-reviewer

Red AI Code Reviewer (2025)

An RedAI-powered code review tool using OpenAI GPT models to analyze and improve your code quality. developed by Ranajit Sahoo Software developer at Redintegro .

click https://huggingface.co/Ranajit1997/red-ai-code-reviewer/tree/main on this link to check the code

✨ Features

🤖 AI-Powered Analysis - Uses OpenAI's advanced language models for comprehensive code review

📊 Multi-dimensional Review - Evaluates readability, bugs, optimizations, security, and more

🔄 Code Refactoring - Suggests improved code versions with detailed explanations

🎯 Overall Scoring - Provides quantitative score (0-100) for code quality assessment

🚀 Easy Integration - Simple Python API for quick implementation

🔍 Security Scanning - Identifies potential security vulnerabilities

⚡ Performance Optimization - Suggests performance improvements

🛠 Installation

# Install required dependencies
pip install huggingface_hub openai

Load and use directly from Hugging Face Hub!

Quick Start

from huggingface_hub import snapshot_download
import sys, os

# Set OpenAI key (if not set in terminal)
os.environ["OPENAI_API_KEY"] = "sk-your-openai-key-here"

# Download repo from Hugging Face
repo_dir = snapshot_download("Ranajit1997/red-ai-code-reviewer")

# Add repo folder to Python path
package_dir = os.path.join(repo_dir, "red_ai_code_reviewer")  # folder with model.py, pipeline.py, __init__.py

sys.path.append(package_dir)

# 4️⃣ Import classes directly from files
from model import CodeReviewerModel
from pipeline import CodeReviewerPipeline

# 5️⃣ Initialize
model = CodeReviewerModel(api_key="sk-your-openai-key-here",
)
reviewer = CodeReviewerPipeline(model)

# 6️⃣ Example code
code = """
def factorial(n):
    if n == 0:
        return 1
    else:
        return n * factorial(n-1)
"""

# 7️⃣ Run review
review = reviewer(code)

# 8️⃣ Print result
print("AI Review:\n", review)

📋 Output Format

The code review returns a comprehensive analysis in the following structured format:

{
    'readability': 'Assessment of code clarity and understandability',
    'bugs': ['List of potential bugs and issues'],
    'optimizations': ['List of optimization suggestions'],
    'refactored_code': 'Improved version of the code',
    'security_issues': ['List of security vulnerabilities'],
    'overall_score': 85  # Numerical score (0-100)
}

🎯 Example Output

AI Review:
{
    'readability': 'The code is simple and easy to understand, with a clear recursive approach to calculating the factorial.',
    'bugs': [],
    'optimizations': ['Consider using an iterative approach to avoid potential stack overflow with large inputs.'],
    'refactored_code': 'def factorial(n):\n    result = 1\n    for i in range(2, n + 1):\n        result *= i\n    return result',
    'security_issues': [],
    'overall_score': 85
}

}

🔧 Configuration

API Key Setup

You need an OpenAI API key to use this tool. Get your API key from Openai Platform

# Option 1: Set environment variable
os.environ["OPENAI_API_KEY"] = "sk-your-key-here"

# Option 2: Pass directly to model
model = CodeReviewerModel(api_key="sk-your-key-here")

# Option 3: Use .env file (recommended for production)
from dotenv import load_dotenv
load_dotenv()
# Then set OPENAI_API_KEY in your .env file

Further Updates will be update soon we are working on this now