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https://github.com/chandima2000/career-path-recommendation-system

AI powered career path recommendation system
https://github.com/chandima2000/career-path-recommendation-system

ai django faiss gemini langchain machine-learning nlp reactjs

Last synced: 2 days ago
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AI powered career path recommendation system

Host: GitHub
URL: https://github.com/chandima2000/career-path-recommendation-system
Owner: chandima2000
Created: 2024-07-27T18:05:36.000Z (4 months ago)
Default Branch: main
Last Pushed: 2024-10-30T16:02:33.000Z (20 days ago)
Last Synced: 2024-10-30T17:17:05.844Z (20 days ago)
Topics: ai, django, faiss, gemini, langchain, machine-learning, nlp, reactjs
Language: Jupyter Notebook
Homepage:
Size: 16.5 MB
Stars: 1
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

README

# 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:
```bash
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:
```bash
python -m venv venv
venv\Scripts\activate
```

3. Install the dependencies:
```bash
pip install -r requirements.txt
```
4. Create .env file inside backend folder:

GOOGLE_API_KEY = "YOUR_API_KEY"

5. Run the Django server:
```bash
python manage.py migrate
python manage.py runserver
```

### Frontend Setup

1. Navigate to the frontend directory:
```bash
cd ../frontend
```

2. Install the dependencies:
```bash
npm install
```

3. Run the React development server:
```bash
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.