PrepAI – Intelligent Interview & Notes Assistant

PrepAI is a comprehensive AI-powered platform designed to help users prepare for interviews, generate personalized quizzes, manage study notes, and even participate in real-time mock interviews using conversational AI. It blends multiple modern technologies such as FastAPI, React, ChromaDB, PostgreSQL, Vapi, Groq, and LlamaIndex into a cohesive, production-ready system.

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🎬 Demo Video

▶ Watch the demo: https://youtu.be/WFycdZQijyA?si=aumRW2hEyBNleGGI

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🚀 Live Demo

▶ Try the project here: https://huggingface.co/spaces/aki-008/prepAI

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🚀 Overview

PrepAI enables users to:

• Conduct AI-powered mock interviews with real-time voice interaction.
• Upload PDFs and chat with notes using vector search + RAG.
• Generate MCQ quizzes from resumes or study material.
• Maintain persistent chat sessions, interview transcripts, and summaries.
• Work inside a fully containerized architecture with isolated services.

This system is ideal for interview preparation platforms, ed-tech tools, or personal study automation.

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🧩 Architecture

PrepAI is built with a modular full-stack architecture:

Backend (FastAPI)

• JWT Authentication
• Upload & process PDFs
• ChromaDB vector store integration
• Streaming LLM responses
• Vapi-powered live interview assistant
• Quiz generation using Groq/OpenAI

Frontend (React + TypeScript + Vite)

• User onboarding (Sign In / Sign Up)
• PDF upload, preview, rename, deletion
• Interactive note-chat interface
• Dashboard with metrics
• Seamless Vapi interview client

Database Layer

• PostgreSQL stores:

  • Users
  • PDFs
  • Chat sessions
  • Messages
  • Metadata

Vector Search Layer

• ChromaDB stores:

  • Chunked PDF embeddings
  • User-ingested knowledge

AI Services

• Groq/OpenAI for LLM responses
• SentenceTransformers for embeddings
• Vapi for real-time voice conversations
• LlamaIndex for PDF parsing & chunking

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📦 Directory Structure

aki-008-prepai/
├── Backend/
│   ├── app/
│   ├── Dockerfile
│   └── requirements.txt
│
├── Frontend/
│   ├── src/
│   ├── Dockerfile
│   └── vite.config.ts
│
├── docker-compose.yml
└── RUN.md

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⚙️ Installation & Setup

1. Clone the repository

git clone <repo-url>
cd aki-008-prepai

2. Create your .env file

Provide:

• PostgreSQL credentials
• Groq API key
• OpenAI key (if needed)
• VAPI_PRIVATE_KEY
• VAPI_PUBLIC_KEY
• VAPI_ASSISTANT_ID

Example:

DATABASE_URL=postgresql+asyncpg://postgres:password@db:5432/studentdb
GROQ_API_KEY=your-key
VAPI_PRIVATE_KEY=your-key
VAPI_PUBLIC_KEY=your-key
VAPI_ASSISTANT_ID=your-assistant-id

3. Run the system (Docker)

docker-compose up --build

Services started:

• Frontend → http://localhost:5173
• Backend → http://localhost:8000
• ChromaDB → http://localhost:8080
• PostgreSQL → http://localhost:5432

4. Dev mode (manual)

Backend:

cd Backend
python run.py

Frontend:

cd Frontend
npm install
npm run dev

ChromaDB:

chroma run --host 0.0.0.0 --port 8080 --path ./chroma_store

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🧪 Key Features in Detail

1. PDF Upload & Notes Chat

• PDFs are chunked using PyMuPDF + LlamaIndex.
• Embeddings generated via MiniLM.
• Chunks stored in ChromaDB.
• Users can open chats tied to each PDF with full chat history.

2. AI Interview System

• Dynamic prompt generation based on job-role, experience, difficulty.

• Real-time Vapi-based interview with:

  • Emotion recognition
  • Adjustable voice
  • Adaptive follow-ups
  • Strict 5-minute flow

• Transcripts saved automatically.

3. Quiz Generation

From resumes or notes:

• Strict rules enforced by the SYSTEM_PROMPT
• Always 10 MCQs with 4 options
• JSON-structured output
• Options + explanations

4. Authentication

• Secure hashing using Argon2
• JWT tokens
• Protected routes for all user-specific actions

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🛠️ Development Notes

Backend

• Powered by FastAPI with async SQLAlchemy.
• Auto-table creation on startup.
• Organized into clear routers: Auth, Notes, Interview, Quiz.
• Streaming responses for chat.

Frontend

• Built on React + TypeScript.
• Modern UI with Tailwind.
• Routes include: Home, Dashboard, Notes, Interview.
• ProtectedRoute ensures authentication.

Docker Setup

docker-compose.yml orchestrates:

• PostgreSQL database
• ChromaDB vector server
• Backend (Python)
• Frontend (Nginx)

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📄 Interview Transcript Storage

During every interview:

• All real-time transcripts are appended in Backend/transcripts/<call_id>.txt.
• Summary is appended at end of call.

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🚧 Roadmap

Future improvements:

• User analytics dashboard
• Multi-file knowledge merging
• Advanced scoring for interview responses
• Multi-voice model selector
• Mobile-friendly front-end layout

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🧑‍💻 Contributing

Feel free to open issues or submit pull requests. Contributions are welcome for both frontend and backend.

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📜 License

This project is licensed under your chosen license (MIT recommended).

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❤️ Thank you for using PrepAI!

If you'd like additional documentation (API reference, UML diagrams, onboarding guide), just ask!