InterviewGraph: Interview Prep Multi-Agent System

Summary

Interview preparation process is very intimidating and daunting, particularly for candidates who are aiming for roles in highly competitive companies like big tech (MAANG). This project aims to streamline and personalize the whole process of interview preparation using advanced AI tools, with a focus on deep research, contextual relevance and realistic mock interview simulation.

Documentation

• Codelabs URL: (https://codelabs-preview.appspot.com/?file_id=1AbMe_4jxEPx0P9NO9eErGrNsStrpEOpLfezefqXEHdc#0)
• GitHub Projects URL: (https://github.com/orgs/DAMG7245-Team-2/projects/1/views/1)

Deployments

• Backend URL: (https://ig-service-642366140190.us-east4.run.app)
• Frontend URL: (interview-graph.vercel.app)
• Airflow URL: (http://34.41.132.26:8080)

Architecture

The system consists of multiple AI agents working together:

• Interview Agent: Conducts mock interviews and provides feedback
• Prep Agent: Helps with interview preparation and research
• Backend API: FastAPI-based service handling agent interactions
• Frontend: Streamlit-based user interface
• MCP: MCP service to access snowflake DB

How to Run

Prerequisites

• Python 3.12
• Poetry (Python package manager)
• Snowflake account credentials

Installation

1. Clone the repository:

git clone https://github.com/DAMG7245-Team-2/InterviewGraph.git
cd InterviewGraph

2. Set up environment variables: Create a .env file with your Snowflake credentials:

SNOWFLAKE_ACCOUNT=your_account
SNOWFLAKE_USER=your_user
SNOWFLAKE_PASSWORD=your_password
SNOWFLAKE_WAREHOUSE=your_warehouse
SNOWFLAKE_DATABASE=your_database
SNOWFLAKE_SCHEMA=your_schema
SNOWFLAKE_ROLE=your_role

OPENAI_API_KEY=your_api_key
ELEVEN_LABS_API_KEY=your_api_key
PINECONE_API_KEY=your_api_key
PINECONE_HOST=your_host_url

Running the Application

1. Start the backend API:

docker build . -t "interview-graph"
docker run -p 8000:8000 --env-file .env "interview-graph"

2. Start the frontend:

cd frontend
npm i
npm run dev

Project Structure

InterviewGraph/
├── airflow/                   # Airflow pipelines
├── backend/
│   ├── api.py                 # FastAPI application
│   ├── interview_agent/       # Interview agent implementation
│   │   ├── src/
│   │   │   └── interview_agent/
│   │   │       ├── graph.py   # Interview workflow
│   │   │       └── ...
│   ├── prep_agent/            # Prep agent implementation
│   │   ├── src/
│   │   │   └── prep_agent/
│   │   │       ├── graph.py   # Prep workflow
│   │   │       └── ...
│   └── sql_mcp.py             # MCP server
├── frontend/                  # React frontend
│
├── .github/
│   └── workflows/            # CI/CD configurations
├── pyproject.toml            # Project dependencies
└── README.md                 # This file

Team Contribution Declaration

WE ATTEST THAT WE HAVEN'T USED ANY OTHER STUDENTS' WORK IN OUR ASSIGNMENT AND ABIDE BY THE POLICIES LISTED IN THE STUDENT HANDBOOK

• Ashish Nevan: 33.3%
• Neha Devarapalli: 33.3%
• Adwaith Korapati: 33.3%