⚡ Reviewify.ai — Enterprise-Grade AI-Powered Code Reviewer

Reviewify.ai is an advanced, interactive, and premium web application designed to perform static vulnerability scanning and code reviews on the fly. Powered by the Google Gemini API (gemini-2.5-flash) and equipped with a local JavaScript sandboxed runtime, Reviewify.ai allows developers to write, inspect, scan, and refactor code inside a single glassmorphic workspace.

Key Features • Architecture • Tech Stack • Installation • API Documentation • Deployment

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🎨 Key Features and Capabilities

• 🔍 Real-Time Code Editor: A fully integrated editor built using react-simple-code-editor and prismjs supporting syntax highlighting for multiple languages:
  • JavaScript, Python, C++, Java, CSS, and HTML.
• 🤖 Dual-Engine Error Detection:
  • Programmatic Sandbox: Runs Node.js codes locally inside a custom native vm execution sandbox to isolate and format real-time JavaScript compilation issues.
  • AI Compiler Simulator: Detects syntax faults in other languages and produces high-fidelity console diagnostics.
• 🖥️ Simulated VS Code Terminal: Programmatic syntax error catcher (using a Node.js sandbox VM for JavaScript) and AI-simulated compiler output displayed in a classic dark terminal console.
• 📈 Dynamic Quality Dashboard:
  • Quality Score Gauge: A beautiful SVG-based circular indicator presenting an automated score based on findings.
  • Issues Tab: Highlights and categorizes scanned issues by severity (Critical ❌, Warnings ⚠️, Info/Safe ✔️).
  • Refactored Code: Clean tab rendering optimized code suggestions with copy-to-clipboard access.
  • Raw Markdown: Rich-text display of the full explanation from the AI reviewer.
• 📁 File Upload Support: Directly drag-and-drop or select scripts to import code, auto-detecting language formats.
• 📚 Interactive Templates & Presets: Loaded template bugs (e.g., Memory Leaks, Callback Hell, SQL Injection, Mutable Defaults, Out of Bounds, Resource Leaks) for immediate testing.
• 💾 Review History & Logs: Integrated review logs stored in a MongoDB database with a LocalStorage fallback to allow users to revisit, toggle, or clear past reviews.

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🏗️ Project Architecture

Reviewify.ai decouples frontend interactions from code analysis through an optimized Express API layer:

[ Frontend Client ] │
▼ (POST /ai/get-review)
[ Backend Express Controller ]
│
├─► [ Local VM Sandbox ] ──► (Catches JavaScript runtime & syntax errors)
│
├─► [ Gemini AI Engine ] ──► (Reviews patterns, scans security, formats fixes)
│
└─► [ MongoDB Instance ] ──► (Saves review output details & history log)

Directory Structure

Below is the directory mapping of the project's source codebase:

• Backend Server Modules:
  • server.js — Main entry point initiating database connections and hosting the Express application listener.
  • app.js — Express app configuration, Middleware definitions, and CORS configuration.
  • db.js — MongoDB client initialization using the native driver.
  • ai.routes.js — Express routers mapping REST endpoints to controllers.
  • ai.controller.js — Route controllers managing code reviews, history queries, VM sandboxing, and clear functions.
  • ai.service.js — Generative AI Service configuring system prompts and interacting with the @google/generative-ai API SDK.
• Frontend Dashboard UI:
  • App.jsx — Main dashboard component rendering templates, code editor, history panel, quality gauges, and VS Code terminal simulator.
  • App.css — Custom stylesheet providing premium glassmorphic properties, glowing tabs, and terminal font styles.
  • index.css — Root layout setup, scrolling setups, and tailwind/custom configurations.
  • main.jsx — Primary index runner rendering the App context.

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🛠️ Tech Stack

Tier	Component / Library	Purpose
Frontend	React 19 (Vite)	High-performance SPA view layer & routing
	Prism.js	Tokenizer rendering real-time editor syntax styles
	React Markdown	Formats complex AI responses containing tables and blocks
	Axios	Manages API communication and asynchronous fetches
Backend	Node.js (Express.js)	Server runtime supporting JSON payloads and API routing
	@google/generative-ai	Integrates with Google Gemini API models
	Node VM Subsystem	Executes JavaScript scripts inside clean sandbox contexts
	MongoDB Native Driver	Retains logs and query records in collection documents

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🚀 Getting Started

Follow these steps to set up and run a local instance of Reviewify.ai.

Prerequisites

• Node.js (v18.x or later recommended)
• MongoDB (local instance or MongoDB Atlas connection URI)
• Google Gemini API Key (obtain from Google AI Studio)

1. Clone and Prepare the Workspace

git clone https://github.com/NoumanAhmed01/AI-Code-Reviewer.git
cd AI-Code-Reviewer/AI-Code-Reviewer

2. Configure and Boot the Backend

1. Navigate to the backend directory:

   cd Backend

2. Install all server dependencies:

   npm install

3. Set up environment configurations: Create a .env file based on the provided template:

   cp .env.example .env

   Edit .env to include your configuration variables:

   PORT=3000MONGODB_URI=mongodb://localhost:27017/reviewifyGOOGLE_GEMINI_KEY=your_google_gemini_api_keyGEMINI_MODEL=gemini-2.5-flash

4. Run the backend server in development mode:

   npm run dev

   The server will start running on http://localhost:3000.

3. Configure and Launch the Frontend

1. Open a new terminal pane and navigate to the frontend directory:

   cd ../Frontend

2. Install client dependencies:

   npm install

3. Set up environment configurations: Create a .env file based on the provided template:

   cp .env.example .env

   Set the API URL variable:

   VITE_API_URL=http://localhost:3000

4. Run the frontend development server:

   npm run dev

   Open your browser and navigate to http://localhost:5173.

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🔌 API Specification

All endpoints are prefixed with the base /ai path.

1. Perform Code Review

• Endpoint:POST /ai/get-review
• Headers:Content-Type: application/json
• Request Body:

  {
  "code": "function checkUser(id) { const query = 'SELECT * FROM users WHERE id = ' + id; return db.execute(query); }",
  "language": "javascript"
  }

• Success Response (200 OK):

  {
  "review": "### ❌ Issues\n1. **SQL Injection Vulnerability**: Direct string interpolation...",
  "error": null
  }

2. Fetch Review Log History

• Endpoint:GET /ai/history
• Success Response (200 OK):

  [
  {
  "id": "64c8d5a1b32f41a8a25c1b5a",
  "language": "javascript",
  "code": "function checkUser(id) { ... }",
  "review": "...",
  "error": null,
  "date": "10:35 PM - Jun 25"
  }
  ]

3. Delete All Logs

• Endpoint:DELETE /ai/history
• Success Response (200 OK):

  {
  "message": "History cleared successfully"
  }

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🔒 Security & VM Sandbox Mechanics

To catch compilation and reference bugs before shipping scripts to the AI Engine, Reviewify.ai incorporates a dual validation layer:

• Native VM Sandbox: When a user requests review on a block of JavaScript code, the server passes it directly into the native Node.js vm core module:

  constvm=require("vm");newvm.Script(code);// Throws SyntaxError on malformed structures

  This catches syntactical compilation faults locally inside an isolated thread context without exposing the server environment.
• AI Compiler Simulation: In non-JS formats, system prompt boundaries force Gemini to identify reference issues and format them inside predefined tags ([TERMINAL_ERROR] ... [/TERMINAL_ERROR]). The controller intercepts these tags and maps them to the terminal console layout.

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🌍 Deployment & Configuration

Backend Deployment (Vercel, Render, or Railway)

Deploy the Backend/ subdirectory. Ensure you set the following environment variables:

• MONGODB_URI — Connection URI for database storage.
• GOOGLE_GEMINI_KEY — API credentials key.
• GEMINI_MODEL — Configured AI model version (defaults to gemini-2.5-flash).

Frontend Deployment (Vercel or Netlify)

Deploy the Frontend/ subdirectory. Set the build settings to:

• Build Command:npm run build
• Output Directory:dist
• Environment Variable:VITE_API_URL pointing to your deployed backend URL.

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🤝 Contributing

Contributions make the open-source community an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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📜 License

Distributed under the MIT License. See LICENSE for more information.

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Developed with ❤️ by the Reviewify Team using Google Gemini & React.