{"id":29647205,"url":"https://github.com/harshil748/ai-code-reviewer","last_synced_at":"2026-04-05T08:35:28.741Z","repository":{"id":305201981,"uuid":"1022213124","full_name":"harshil748/AI-Code-Reviewer","owner":"harshil748","description":"This is a full-stack web application that leverages the power of Large Language Models (LLMs) to provide instant code analysis, improvement suggestions, and documentation. Users can paste a code snippet, select the programming language, and receive an AI-generated review. 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Users can paste a code snippet, select the programming language, and receive an AI-generated review. All analyses are saved in a history log for future reference.\n\n## ✨ Features\n\n* **AI-Powered Analysis:** Get an in-depth explanation of your code, a list of actionable improvement suggestions, and a summary of potential bugs.\n\n* **Multi-Language Support:** Supports popular languages like Python, JavaScript, TypeScript, Java, and C++.\n\n* **Persistent History:** Every analysis is automatically saved to a PostgreSQL database.\n\n* **Modern Tech Stack:** Built with a professional-grade stack including Next.js, FastAPI, and Docker.\n\n* **Responsive UI:** Clean, user-friendly interface built with Tailwind CSS that works on all devices.\n\n## 🛠️ Tech Stack\n\n* **Frontend:** Next.js, React, TypeScript, Tailwind CSS\n\n* **Backend:** Python, FastAPI\n\n* **Database:** PostgreSQL\n\n* **AI Integration:** Google Gemini API\n\n* **Containerization:** Docker \u0026 Docker Compose\n\n## 🚀 Local Setup and Installation\n\nFollow these steps to get the entire application running on your local machine.\n\n### Prerequisites\n\nMake sure you have the following installed:\n\n* [Node.js](https://nodejs.org/) (v18 or later)\n\n* [Python](https://www.python.org/downloads/) (v3.8 or later)\n\n* [Docker Desktop](https://www.docker.com/products/docker-desktop/)\n\n### 1. Clone the Repository\n\n```bash\ngit clone [https://github.com/your-github-username/ai-code-reviewer.git](https://www.google.com/search?q=https://github.com/your-github-username/ai-code-reviewer.git)\ncd ai-code-reviewer\n```\n\n\n### 2. Set Up the Database\n\nThe PostgreSQL database runs in a Docker container.\n\n* Make sure Docker Desktop is running on your machine.\n\n* In the root directory of the project, run the following command to start the database in the background:\n\n```bash\ndocker-compose up -d\n```\n\nThis will start a PostgreSQL server on `localhost:5432`.\n\n### 3. Configure the Backend\n\n* Navigate to the `backend` directory:\n\n```bash\ncd backend\n```\n\n* Create and activate a Python virtual environment:\n\n\n# For macOS/Linux\n```bash\npython3 -m venv venv\nsource venv/bin/activate\n```\n\n# For Windows\n```bash\npython -m venv venv\n.\\\\venv\\\\Scripts\\\\activate\n```\n\n* Install the required Python libraries:\n\n```bash\npip install -r requirements.txt\n```\n\n* Create a `.env` file for your environment variables by copying the example file:\n\n```bash\ncp .env.example .env\n````\n\n* **Edit the `.env` file:**\n\n* Get your API key from [Google AI Studio](https://aistudio.google.com/app/apikey).\n\n* Open the `.env` file and add your key. It should look like this:\n\n  ```bash\n  # .env\n  GEMINI_API_KEY=YOUR_API_KEY_HERE\n  DATABASE_URL=\"postgresql://myuser:mypassword@localhost/ai_reviewer\"\n  ```\n\n### 4. Configure the Frontend\n\n* In a **new terminal window**, navigate to the `frontend` directory:\n\n```bash\ncd frontend\n```\n* Install the required Node.js packages:\n```\nnpm install\n```\n\n### 5. Run the Application\n\nYou need to have **two terminals** running simultaneously: one for the backend and one for the frontend.\n\n* **Terminal 1: Start the Backend**\n\n* Make sure you are in the `backend` directory with the `(venv)` activated.\n\n* Run the FastAPI server:\n\n  ```bash\n  uvicorn main:app --reload\n  ```\n\n* The backend will be running at `http://127.0.0.1:8000`.\n\n* **Terminal 2: Start the Frontend**\n\n* Make sure you are in the `frontend` directory.\n\n* Run the Next.js development server:\n\n  ```bash\n  npm run dev\n  ```\n\n* The frontend will be running at `http://localhost:3000`.\n\nYou can now open your browser and navigate to `http://localhost:3000` to use the application!\n\n## 📂 Project Structure\n\n```\n\nai-code-reviewer/\n├── backend/\n│   ├── .env                \\# Environment variables (API key, DB URL)\n│   ├── database.py         \\# Database connection setup\n│   ├── main.py             \\# FastAPI application and API endpoints\n│   ├── models.py           \\# SQLAlchemy database models\n│   └── requirements.txt    \\# Python dependencies\n│\n├── frontend/\n│   ├── src/app/\n│   │   ├── page.tsx        \\# Main React component for the UI\n│   │   └── globals.css     \\# Global styles\n│   └── package.json        \\# Node.js dependencies\n│\n├── .gitignore\n├── docker-compose.yml      \\# Docker configuration for the database\n└── README.md               \\# This file\n\n```\n\n## 📄 API Endpoints\n\n* `POST /api/analyze`: Receives code and language, returns AI analysis, and saves to history.\n\n* `GET /api/history`: Returns a list of all past analyses from the database.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshil748%2Fai-code-reviewer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharshil748%2Fai-code-reviewer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshil748%2Fai-code-reviewer/lists"}