🚀 Interview Copilot

Interview Copilot is an AI-powered interview preparation platform.

The platform helps candidates prepare for technical interviews through intelligent resume analysis, mock interview sessions, and an AI-powered assistant.

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🌟 Features

📄 Resume Analyzer Agent

Upload your resume in PDF format and receive:

• Resume strengths
• Resume Weakness
• Personalized interview questions

🎤 Mock Interview Agent

Practice interviews with AI-generated questions.

• Technical interview simulation
• Topic-based interview questions
• Interactive interview preparation

💡 General AI Assistant

Ask questions related to:

• Artificial Intelligence
• Machine Learning
• Data Science
• Python
• FastAPI
• LangChain
• LangGraph
• Interview Preparation
• or Any domain

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🏗️ Architecture

Interview Copilot uses a LangGraph-based multi-agent workflow.

                    User Query
                         │
                         ▼
                  Planner Agent
                         │
      ┌──────────────────┼──────────────────┐
      │                  │                  │
      ▼                  ▼                  ▼
 Resume Agent     Mock Interview      General Agent
                        Agent
      │                  │                  │
      └──────────────────┴──────────────────┘
                         │
                         ▼
                     Response

The Planner Agent identifies the user's intent and routes requests to the appropriate specialized agent.

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🛠️ Tech Stack

AI & Agent Frameworks

• LangGraph
• LangChain

LLM

• Groq
• Llama 3.3 70B Versatile

Frontend

• Streamlit

Backend

• Python

Libraries

• PyPDF
• Requests
• Python Dotenv

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📂 Project Structure

Interview-Copilot/
│
├── app/
│   ├── agents/
│   │   ├── planner.py
│   │   ├── resume_agent.py
│   │   ├── interviewer.py
│   │   └── general_agent.py
│   │
│   ├── graph/
│   │   └── workflow.py
│   │
│   ├── schemas/
│   │   └── state.py
│   │
│   ├── tools/
│   │   └── resume_tool.py
│   │
│   └── main.py
│
├── streamlit_app.py
├── requirements.txt
├── .env
└── README.md

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⚙️ Installation

1. Clone the Repository

git clone https://github.com/mayaannkkk/Interview-Copilot

cd interview-copilot

2. Create Virtual Environment

Using UV:

uv venv

Activate Environment:

Windows

.venv\Scripts\activate

Linux/Mac

source .venv/bin/activate

3. Install Dependencies

uv sync

or

pip install -r requirements.txt

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🔑 Environment Variables

Create a .env file in the root directory:

GROQ_API_KEY=your_groq_api_key

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▶️ Running the Application

Start the Streamlit application:

streamlit run streamlit_app.py

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📖 How It Works

Resume Analysis

1. Upload a PDF resume.
2. Resume text is extracted using PyPDF.
3. The Resume Agent analyzes the content.
4. Strengths, weaknesses, and personalized interview questions are generated.

Mock Interview

1. Select Mock Interview mode.
2. Enter a topic.
3. The Interview Agent generates interview questions.
4. Practice answering technical questions.

General Assistant

1. Ask any interview or AI-related question.
2. The General Agent responds using Groq's Llama 3.3 70B model.

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🚀 Future Improvements

• Tool Calling
• Memory Support
• RAG (Retrieval-Augmented Generation)
• Interview Performance Tracking
• Personalized Learning Roadmaps
• Voice-Based Interviews
• Multi-turn Mock Interview Sessions
• Interview Scoring System

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Live Demo

https://interview-copilot-01.streamlit.app/

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🎯 Key Learnings

Through this project, I gained hands-on experience with:

• Agentic AI Workflows
• LangGraph State Management
• Multi-Agent Architectures
• LLM Integration using Groq
• PDF Processing with PyPDF
• Streamlit Deployment
• Building End-to-End AI Applications

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👨‍💻 Author

Mayank Goyal

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