Hyderabad, India Chapter - Chatbot for Interview Preparation using NLP

Table of Contents

• About
• Setup
  • Folder Structure
  • Installation
• Collaborators
• License

About

Omdena Hyderabad Local Chapter is working on a LLM based chatbot that can conduct mock interviews for aspiring candidates, evaluate the responses of job aspirants during mock HR interviews and provide quantitative, personalized feedback for each candidate along with recommendations to develop their skills to successfully navigate HR rounds of interviews.

Setup

Folder Structure

The project follows the following folder structure:

.
├── CONTRIBUTING.md                    --> Contributing Guidelines
├── README.md                          --> Project README
├── app/                               --> Streamlit App
│   └── main.py
├── data                               --> Data Directory
│   ├── README.md                      --> Data README
│   ├── final                          --> Final Data
│   └── final.dvc
├── docs/                              --> Documentation Directory
│   ├── Data.md                        --> Data Documentation
│   ├── Preprocess.md                  --> Preprocessing Documentation
│   ├── Analysis.md                    --> Analysis Documentation
│   ├── Modelling.md                   --> Modelling Documentation
│   ├── Deployment.md                  --> Deployment Documentation
│   └── assets                         --> Documentation Assets
├── lib/                               --> Library Directory
│   └── __init__.py
├── poetry.lock                       --> Poetry Lock File
├── pyproject.toml                    --> Poetry Project File
└── src/                              --> Source Directory
    ├── task-1/                       --> Task 1 Directory (Data Collection)
    │   ├── README.md                 --> Task 1 README
    │   ├── data/                     --> Task 1 Data Directory
    │   │   ├── README.md
    │   │   ├── external/             --> Task 1 External Data Directory
    │   │   ├── external.dvc
    │   │   ├── raw/                  --> Task 1 Raw Data Directory
    │   │   └── raw.dvc
    │   ├── docs/                     --> Task 1 Documentation Directory
    │   │   ├── Data.md
    │   │   └── assets/               --> Task 1 Documentation Assets
    │   ├── notebook/                 --> Task 1 Notebook Directory
    │   └── scripts/                  --> Task 1 Scripts Directory
    │       └── __init__.py
    ├── task-2/                       --> Task 2 Directory (Data Preprocessing)
    │   ├── README.md                 --> Task 2 README
    │   ├── data/                     --> Task 2 Data Directory
    │   │   ├── README.md
    │   │   ├── processed/            --> Task 2 Processed Data Directory
    │   │   └── processed.dvc
    │   ├── docs/                     --> Task 2 Documentation Directory
    │   │   ├── Preprocess.md
    │   │   └── assets/               --> Task 2 Documentation Assets
    │   ├── notebook/                 --> Task 2 Notebook Directory
    │   └── scripts/                  --> Task 2 Scripts Directory
    │       └── __init__.py
    ├── task-3/                       --> Task 3 Directory (Data Analysis)
    │   ├── README.md
    │   ├── docs
    │   │   ├── Analysis.md
    │   │   └── assets
    │   ├── notebook
    │   └── scripts
    │       └── __init__.py
    ├── task-4/                       --> Task 4 Directory (Modelling)
    │   ├── README.md                 --> Task 4 README
    │   ├── docs/                     --> Task 4 Documentation Directory
    │   │   ├── Modelling.md
    │   │   └── assets/               --> Task 4 Documentation Assets
    │   ├── lib/                      --> Task 4 Library Directory
    │   │   └── __init__.py
    │   └── notebook/                 --> Task 4 Notebook Directory
    └── task-5/                       --> Task 5 Directory (Deployment)
        ├── README.md                 --> Task 5 README
        └── docs/                     --> Task 5 Documentation Directory
            ├── Deployment.md
            └── assets/               --> Task 5 Documentation Assets

Installation

To install the project, make sure you have

• Git
• Python 3.10
• Poetry installed.

1. Clone the repository

git clone https://dagshub.com/Omdena/HyderabadIndiaChapter_ChatbotInterviewPreparation.git

2. Install Poetry and activate the virtual environment

poetry install
poetry shell

3. Setup DVC

dvc remote add origin s3://dvc
dvc remote modify origin endpointurl https://dagshub.com/Omdena/HyderabadIndiaChapter_ChatbotInterviewPreparation.s3
dvc remote modify origin --local access_key_id <your_token>
dvc remote modify origin --local secret_access_key <your_token>

4. Get the data

dvc pull

5. Setup environment variables

cp .env.example .env

Replace the values in .env with your own values.

6. Run the app

streamlit run app/main.py

Collaborators

License