🤖 Code Review Comment Analyzer

🔗 Live App: https://code-comment-reviewer-kx5pfmcjc-ishita-kanaujias-projects.vercel.app/

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🚀 Overview

This project is a full-stack NLP-powered web application that analyzes GitHub pull request comments and classifies them into actionable categories:

• 🐞 Bug
• ❓ Question
• 💡 Suggestion
• 🎨 Style Nitpick

It helps developers and teams understand feedback patterns and improve code quality.

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🏗️ Architecture

This project follows a modern full-stack architecture:

React (Frontend) → FastAPI (Backend) → ML Model (Scikit-learn)

• Frontend (React + Vite)

  • User inputs GitHub PR URL
  • Displays summary + categorized comments

• Backend (FastAPI)

  • Fetches PR comments using GitHub API
  • Runs ML model for classification
  • Returns structured results

• ML Model

  • TF-IDF + LinearSVC
  • Trained on labeled code review comments

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🛠️ Tech Stack

Frontend

• React (Vite)
• JavaScript
• CSS

Backend

• FastAPI
• Python

Machine Learning

• Scikit-learn
• Pandas
• NLTK
• Joblib

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📊 Model Performance

• Accuracy: 93%

precision recall f1-score support

Bug 0.71 0.79 0.75 68
Question 0.67 0.52 0.59 23
Style 0.64 0.56 0.60 32
Suggestion 0.96 0.96 0.96 908

accuracy 0.93 1031

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⚙️ Features

• 🔗 Analyze real GitHub PRs
• 📊 Summary of comment categories
• 🧠 ML-based classification
• ⚡ Fast API responses
• 🎯 Clean and responsive UI

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🧪 How to Run Locally

1. Clone the repo

git clone https://github.com/your-username/code-comment-reviewer.git
cd code-comment-reviewer

Run Backend

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

Run Frontend

cd frontend
npm install
npm run dev

Create Environment Variables

Create a .env file inside frontend/:

VITE_API_URL=http://127.0.0.1:8000

Key Learnings

• Built full-stack app (React + FastAPI)
• Integrated ML model into production API
• Handled API communication & environment configs
• Designed clean UI/UX for real users