Hybrid Model for Multilingual Chatbot

This project builds a hybrid text classification model combining Sentence Transformers and Logistic Regression to power a multilingual chatbot interface.

🔍 Features

• Combines semantic embeddings (SBERT) with a traditional ML classifier (Logistic Regression)
• High performance on multilingual emotion/sentiment classification
• Future-ready chatbot UI with Bootstrap + Flask API integration

📁 Project Structure

Hybrid-Model-for-Multilingual-Chatbot/ ├── sbert_lr_model.pkl # Trained classifier

├── label_encoder.pkl # Label encoder

├── hybrid_model_training.ipynb # Model training notebook

├── README.md

Project documentation

💡 Model Info

• Embeddings: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
• Classifier: Logistic Regression
• Input: User queries/messages
• Output: Predicted label (emotion/sentiment)

🚀 Upcoming

• Chatbot UI (Bootstrap + Flask)
• Real-time text + voice chat support
• Deployment on Render / Vercel

📌 How to Use

1. Clone this repository:

git clone https://github.com/YOUR_USERNAME/Hybrid-Model-for-Multilingual-Chatbot.git



## 💡 Model Info

- **Embeddings**: `sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2`
- **Classifier**: Logistic Regression
- **Input**: User queries/messages
- **Output**: Predicted label (emotion/sentiment)

## 🚀 Upcoming

- [ ] Chatbot UI (Bootstrap + Flask)
- [ ] Real-time text + voice chat support
- [ ] Deployment on Render / Vercel

## 📌 How to Use

1. Clone this repository:
```bash
git clone https://github.com/YOUR_USERNAME/Hybrid-Model-for-Multilingual-Chatbot.git



2. **Push it to GitHub**:
```bash
%cd /kaggle/working/Hybrid-Model-for-Multilingual-Chatbot

!git add README.md
!git commit -m "Add README.md with project overview"
!git push origin main