Career Path Recommendation System

This project is a Career Path Recommendation System built with a React frontend and a Django backend. The system is implemented in four main steps:

1. User Registration and Quiz
2. Machine Learning Prediction
3. Sentiment Analysis (NLP)
4. Chatbot Assistant
5. Voice Assistant

Features

1. User Registration and Quiz

   • After successful registration, the user is redirected to the quiz page.
   • The user answers 19 quizzes.
   • The user is automatically redirected to the prediction page to see their career job role based on their answers.

2. Machine Learning Prediction

   • The prediction is made using a machine learning model.
   • The model suggests a career path for the user based on their quiz answers.

3. Sentiment Analysis

   • If the user is not satisfied with the prediction, they can provide feedback.
   • An NLP model predicts whether the feedback is positive or negative using the NLTK library.
   • The sentiment (positive or negative) is displayed to the user.

4. Chatbot and Voice Bot

   • The chatbot responds to custom data queries.
   • Implemented using Google Gemini API, LangChain, and FAISS as the Vector-DB.
   • Google Gemini is used for word embeddings.
   • The voice bot is implemented with the React Speech Recognition library, FAISS DB, LangChain, and Gemini.

Technologies Used

• Frontend:

  • React
  • React Speech Recognition

• Backend:

  • Django
  • DRF
  • NLTK
  • LangChain
  • FAISS
  • Google Gemini API

• Database:

  • FAISS (Vector-DB)
  • SQL

Installation

Prerequisites

• Node.js and npm
• Python 3.x and pip
• Django
• NLTK

Backend Setup

1. Clone the repository:

   git clone https://github.com/chandima2000/career-path-recommendation-system.git
   cd career-path-recommendation-system/backend

2. Create a virtual environment and activate it:

   python -m venv venv
   venv\Scripts\activate

3. Install the dependencies:

   pip install -r requirements.txt

4. Create .env file inside backend folder:

   GOOGLE_API_KEY = "YOUR_API_KEY"

5. Run the Django server:

   python manage.py migrate
   python manage.py runserver

Frontend Setup

1. Navigate to the frontend directory:

   cd ../frontend

2. Install the dependencies:

   npm install

3. Run the React development server:

   npm run dev

Usage

1. Open your browser and navigate to http://localhost:5173.
2. Register as a new user.
3. Complete the quiz to receive a career path recommendation.
4. Provide feedback on the prediction to see the sentiment analysis.
5. Use the chatbot for custom queries.
6. Interact with the voice bot for voice commands.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

"# Carrer-Recommendation-System"