AI Interview Assistant

An AI-powered Interview Preparation Assistant built using FastAPI, RAG (Retrieval-Augmented Generation), FAISS, and Google Gemini.

The system helps users prepare for interviews through document-based question answering, mock interviews, resume analysis, and automated answer evaluation.

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🚀 Features

• 📄 PDF Knowledge Base Processing
• 🔍 Semantic Search using FAISS
• 🤖 RAG-based Question Answering System
• 📑 Resume Parsing and Analysis
• 🎯 Mock Interview Question Generation
• 📝 AI-powered Answer Evaluation
• 📊 Interview Report Generation
• 📚 Interview History Tracking
• 🚀 FastAPI Backend with Swagger Documentation

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🛠 Tech Stack

• Python
• FastAPI
• Google Gemini API
• Sentence Transformers
• FAISS
• PyPDF
• Uvicorn

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📁 Project Structure

interview-prep-assistant/
│
├── app.py
├── requirements.txt
├── README.md
├── .env
│
├── data/
│   ├── raw/
│   └── interviews/
│
├── vectorstore/
│   ├── index.faiss
│   └── chunks.pkl
│
├── src/
│   ├── api/
│   │   └── routes.py
│   │
│   ├── components/
│   │   ├── pdf_loader.py
│   │   ├── chunker.py
│   │   ├── embedder.py
│   │   ├── vector_store.py
│   │   ├── retriever.py
│   │   ├── llm_client.py
│   │   ├── question_generator.py
│   │   ├── evaluator.py
│   │   ├── resume_parser.py
│   │   └── report_generator.py
│   │
│   └── pipeline/
│       ├── rag_pipeline.py
│       └── interview_pipeline.py
│
├── tests/
│   ├── __pycache__/
│   ├── __init__.py
│   ├── test_evaluator.py
│   ├── test_history.py
│   ├── test_interview.py
│   ├── test_llm.py
│   ├── test_question_generator.py
│   ├── test_rag.py
│   ├── test_resume_parser.py
│   └── test_retrieval.py
│
└── README.md

⚙️ Installation

Clone the repository

git clone <repository-url>
cd interview-prep-assistant

Create virtual environment

python -m venv venv

Activate environment

Windows

venv\Scripts\activate

Mac/Linux

source venv/bin/activate

Install dependencies

pip install -r requirements.txt

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🔐 Environment Variables

Create a .env file in the root directory:

GEMINI_API_KEY=your_api_key

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▶️ Run the Application

uvicorn app:app --reload

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🌐 Server Access

Local Development

• Base URL: http://127.0.0.1:8000
• Swagger Docs: http://127.0.0.1:8000/docs

Production Deployment

• Live Application: https://ai-interview-assistant-production-0a84.up.railway.app/
• Swagger Docs: https://ai-interview-assistant-production-0a84.up.railway.app/docs

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🔌 API Endpoints

Method	Endpoint	Description
GET	/	Home endpoint
POST	/ask	Ask questions from knowledge base
POST	/start-interview	Generate interview questions
POST	/evaluate-answer	Evaluate candidate answers
POST	/upload-resume	Parse resume
GET	/history	View interview history

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🔄 Workflow

PDF Documents
      ↓
Text Chunking
      ↓
Embeddings Generation
      ↓
FAISS Vector Store
      ↓
Retriever
      ↓
Google Gemini LLM
      ↓
Final Generated Response

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🔮 Future Enhancements

• User Authentication System
• PostgreSQL Database Integration
• Docker Deployment
• Resume-based Personalized Interviews
• Performance Analytics Dashboard
• Voice-based Mock Interviews

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