Code Analyser

A comprehensive web application for code analysis, management, and AI-powered assistance using Google Gemini API.

Features

• Code Upload & Analysis: Upload code files and get instant AI-powered analysis
• AI Chat Assistant: Chat with an intelligent code assistant powered by Google Gemini
• RAG System: Retrieval-Augmented Generation for context-aware responses
• User Authentication: Secure login/signup system
• Code Management: Store and manage code files in SQLite database
• Real-time Analysis: Get quality assessment, bug detection, and optimization suggestions

Technology Stack

• Backend: Flask (Python)
• Database: SQLite3
• AI Integration: Google Gemini API
• Frontend: HTML5, CSS3, JavaScript, Bootstrap 5
• Authentication: Session-based authentication

Installation

1. Clone the repository

   git clone https://github.com/Samviksanjee/Code-Analysier
   cd code-analyser

2. Create a virtual environment

   python -m venv venv
   
   # On Windows
   venv\Scripts\activate
   
   # On macOS/Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Set up environment variables

   • Copy env_example.txt to .env
   • Update the API key and secret key in .env:

   GEMINI_API_KEY=your_gemini_api_key_here
   SECRET_KEY=your_secret_key_here
   

5. Run the application

   python app.py

6. Access the application

   • Open your browser and go to http://localhost:5000

Usage

Getting Started

1. Sign Up: Create a new account or login with existing credentials
2. Upload Code: Go to the Upload Code section and paste your code
3. View Analysis: Check the analysis results in your dashboard
4. Chat with Bot: Use the chat feature to ask questions about your code

Features Overview

Code Upload & Analysis

• Upload code files with filename and language specification
• Get comprehensive AI analysis including:
  • Code quality assessment
  • Bug detection and potential issues
  • Performance optimization suggestions
  • Security considerations
  • Best practices recommendations

AI Chat Assistant

• Ask questions about your uploaded code
• Get help with programming concepts
• Debugging assistance
• Code optimization suggestions
• Context-aware responses using RAG system

Dashboard

• View all uploaded code files
• Access analysis results
• Manage your code library
• Quick access to all features

API Integration

The application uses Google Gemini API for:

• Code analysis and quality assessment
• AI-powered chat responses
• RAG (Retrieval-Augmented Generation) system

Getting Gemini API Key

1. Go to Google AI Studio
2. Create a new API key
3. Add the key to your .env file

Database Schema

The application uses SQLite3 with the following tables:

• users: User authentication and profile information
• code_files: Stored code files with analysis results
• chat_history: Chat conversation history

Project Structure

code-analyser/
├── app.py                 # Main Flask application
├── requirements.txt       # Python dependencies
├── env_example.txt       # Environment variables template
├── README.md             # This file
├── templates/            # HTML templates
│   ├── base.html
│   ├── index.html
│   ├── login.html
│   ├── signup.html
│   ├── dashboard.html
│   ├── upload.html
│   ├── chat.html
│   └── analysis.html
└── static/               # Static files
    ├── style.css
    └── script.js

Security Features

• Password hashing using SHA-256
• Session-based authentication
• SQL injection protection
• Input validation and sanitization

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is licensed under the MIT License.

Support

For support and questions, please open an issue in the repository.

Future Enhancements

• File upload support (drag & drop)
• Multiple programming language support
• Code comparison features
• Export analysis reports
• Team collaboration features
• Advanced code metrics
• Integration with version control systems