AI-Powered Excel Mock Interviewer 🤖📊

This project is an AI-driven mock interviewer designed to assess a candidate's proficiency in Microsoft Excel. The system automates the technical screening process for roles in Finance, Operations, and Data Analytics, ensuring a consistent and efficient evaluation.

Key Features ✨

• Structured Interview Flow: The AI agent manages a multi-turn conversation, guiding the candidate through a series of Excel-related questions.
• Intelligent Evaluation: The system evaluates candidate responses against a predefined rubric for each question. This is the core challenge.
• Agentic Behavior: The AI maintains context and state, acting like a professional interviewer throughout the conversation.
• Constructive Feedback: At the end of the interview, the agent generates a performance summary.

Technology Stack ⚙️

• Backend:
  • FastAPI: A modern, fast (high-performance) web framework for building the API.
  • Google Gemini (gemini-2.5-flash): The LLM powering the conversational AI and evaluation logic.
  • uvicorn: The ASGI server to run the FastAPI application.
• Frontend:
  • Next.js: A React framework for building the user interface.
• Deployment:
  • Backend: Deployed on Render.
  • Frontend: Deployed on Vercel.

Getting Started 🚀

To get a local copy up and running, follow these steps.

1. Clone the repository:

git clone https://github.com/your-username/your-repo-name.git
cd your-repo-name

2. Set up the Backend:

• Navigate to the backend directory (or wherever your FastAPI code is).
• Install dependencies:

  pip install -r requirements.txt

• Create a .env file and add your Google AI API key:

  GOOGLE_API_KEY="your_api_key_here"
  

• Run the backend server:

  uvicorn main:app --reload

  The backend will run on http://localhost:8000.

3. Set up the Frontend:

• Navigate to the frontend directory (or wherever your Next.js code is).
• Install dependencies:

  npm install

• Create a .env.local file and point it to your backend URL:

  NEXT_PUBLIC_API_URL="http://localhost:8000"
  

• Run the frontend development server:

  npm run dev

  The frontend will be available at http://localhost:3000.

Deployment 🌐

The backend is deployed to Render and the frontend to Vercel.

• Backend (Render): The main.py application is configured to run on Render.
• Frontend (Vercel): The Next.js application uses the NEXT_PUBLIC_API_URL environment variable to connect to the deployed backend.