MockMate 🌟

Overview

MockMate is a sophisticated, full-stack web application designed to revolutionize technical and behavioral interview preparation. Built primarily with Next.js, it simulates real-time conversations using the cutting-edge Google Gemini AI, providing instant, objective feedback on the user's content and communication style. Our mission is to transform interview anxiety into confidence, ensuring users walk into their next opportunity fully prepared.

✨ Key Features

• Serverless AI Simulation: Utilizes Next.js API Routes to securely proxy requests to the Gemini API, ensuring your API key is never exposed on the client-side.

• Real-Time Performance Analysis: Provides immediate scoring (on a scale of 1-10) and detailed feedback on technical accuracy, structure, and communication effectiveness.

• Voice and Text Interaction: Supports both spoken (via browser APIs) and typed responses for a flexible practice experience.

• Customizable Sessions: Users can select interview types (e.g., Data Science, Software Engineering), technical domains, and desired difficulty levels.

• Performance Dashboard: Tracks user progress across multiple sessions, storing data directly in a managed NoSQL or serverless database (e.g., Firebase, Supabase).

• Secure Authentication: User data and session history are protected via Firebase Authentication or NextAuth.

🛠️ Technology Stack

CategoryTechnologiesDescriptionFrameworkNext.jsReact framework for frontend and serverless API Routes.FrontendReact, TypeScriptComponent-based UI development.AI CoreGoogle Gemini APIPowers the interviewer logic, scoring, and feedback generation.**Data/AuthFirebase (or Supabase)**Provides secure, managed user sign-up/login and data storage.StylingTailwind CSSUtility-first CSS framework for rapid styling.DevOpsVercelHosting platform, perfectly integrated with Next.js.

🚀 Getting Started

Follow these steps to get a development copy of the project running on your local machine.

Prerequisites

• Node.js v18+

• A Gemini API Key from Google AI Studio.

• A Firebase Project configured for web (or a similar backend-as-a-service like Supabase).

Installation

1. Bashgit clone https://github.com/YourGitHubUsername/ai-interview-prep-buddy.gitcd ai-interview-prep-buddy

2. Bashnpm install

Configuration (Environment Variables)

Create a file named .env.local in the root directory. Replace the placeholder values with your actual credentials.

.env.local

Plain textANTLR4BashCC#CSSCoffeeScriptCMakeDartDjangoDockerEJSErlangGitGoGraphQLGroovyHTMLJavaJavaScriptJSONJSXKotlinLaTeXLessLuaMakefileMarkdownMATLABMarkupObjective-CPerlPHPPowerShell.propertiesProtocol BuffersPythonRRubySass (Sass)Sass (Scss)SchemeSQLShellSwiftSVGTSXTypeScriptWebAssemblyYAMLXML # Gemini API Key (Used ONLY in Next.js API Routes) GEMINI_API_KEY="AIzaSy...your_gemini_key...xyz" # Firebase Config (for client-side authentication and database access) NEXT_PUBLIC_FIREBASE_API_KEY="your-api-key" NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN="your-project-id.firebaseapp.com" NEXT_PUBLIC_FIREBASE_PROJECT_ID="your-project-id" NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET="your-project-id.appspot.com" # ... other Firebase/Supabase keys

Running the Application

• Bashnpm run dev

The application will now be running at http://localhost:3000.

🤝 Contributing

We actively welcome and appreciate contributions to the AI Interview Prep Buddy project!

1. Fork the repository and clone your fork.

2. Create a new feature branch (git checkout -b feature/new-behavioral-model).

3. Commit your changes with clear, descriptive messages.

4. Push your branch to your fork.

5. Open a detailed Pull Request explaining the changes and linking to any relevant issues.