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: 9 months 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 (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-14T20:51:58.000Z (over 1 year ago)
- Last Synced: 2025-04-09T10:52:26.020Z (about 1 year ago)
- Topics: ai, django, faiss, gemini, langchain, machine-learning, nlp, reactjs
- Language: Jupyter Notebook
- Homepage:
- Size: 16.5 MB
- Stars: 7
- Watchers: 1
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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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.
"# Carrer-Recommendation-System"