# 🌍 MultiLinguaAI

## 🚀 AI-Powered Multilingual Conversational Assistant

MultiLinguaAI is an intelligent multilingual conversational assistant developed using **FastAPI, NLP, Machine Learning, and JavaScript**. The system supports communication in multiple languages including **English, Hindi, and Marathi** with intelligent intent recognition and service-based response generation.

The project provides a modern AI chatbot interface with multilingual NLP processing, confidence scoring, service search capability, and interactive frontend UI.

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# 📌 Features

    ✅ Multilingual Support (English, Hindi, Marathi)  
    ✅ NLP-Based Intent Classification  
    ✅ FastAPI Backend API  
    ✅ Interactive Modern Chat UI  
    ✅ Confidence Score Prediction  
    ✅ Language Detection  
    ✅ Service Search System  
    ✅ Conversation Memory  
    ✅ Responsive Design  
    ✅ Real-Time Chat Interface  
    ✅ AI-Powered Virtual Assistant  

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# 🧠 AI & NLP Capabilities

    - Intent Classification
    - Language Detection
    - Response Generation
    - Service Recommendation
    - Conversation Handling
    - Multilingual Query Processing

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# 🛠️ Technologies Used

## Backend
    - Python
    - FastAPI
    - Uvicorn
    - Scikit-learn
    - NLP
    - Machine Learning

## Frontend
    - HTML5
    - CSS3
    - JavaScript

## AI/NLP
    - TF-IDF Vectorization
    - Logistic Regression
    - Intent Prediction
    - Language Detection

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# 📂 Project Structure

```bash
MultiLinguaAI/
│
├── backend/
│   ├── app.py
│   ├── nlu.py
│   ├── service_search.py
│
├── frontend/
│   ├── index.html
│   ├── style.css
│   ├── script.js
│
├── models/
│
├── data/
│
├── requirements.txt
│
├── README.md
│
└── .gitignore

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⚙️ Installation

1️⃣ Clone Repository

git clone https://github.com/jaypalsing/multilinguaai.git

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2️⃣ Open Project

    cd multilinguaai

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3️⃣ Create Virtual Environment

    python -m venv venv

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4️⃣ Activate Environment

Windows

    venv\Scripts\activate

Linux / Mac

    source venv/bin/activate

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5️⃣ Install Dependencies

    pip install -r requirements.txt

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▶️ Run Backend Server

    uvicorn backend.app:app --reload

Backend URL:

        http://127.0.0.1:8000

Swagger API Docs:

        http://127.0.0.1:8000/docs

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🌐 Run Frontend

Open:

    frontend/index.html

OR use VS Code Live Server.

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💬 Example Queries

English

* Hello
* Help me
* Show hospitals
* Bank near me

Hindi

* नमस्ते
* अस्पताल दिखाइए
* मदद चाहिए

Marathi

* नमस्कार
* हॉस्पिटल दाखवा
* मदत करा

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📊 API Example

Request

{
  "message": "Hello"
}

Response

{
    "message": "Hello",
    "language": "English",
    "intent": "greeting",
    "confidence": 0.95,
    "reply": "Hello! Welcome to MultiLinguaAI."
}

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🧪 Current Features

| Feature               | Status |
| --------------------- | ------ |
| Multilingual NLP      | ✅      |
| Intent Classification | ✅      |
| Service Search        | ✅      |
| FastAPI API           | ✅      |
| Responsive UI         | ✅      |
| Confidence Prediction | ✅      |
| Conversation Memory   | ✅      |

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🚀 Future Improvements

* Voice Assistant
* Speech-to-Text
* Text-to-Speech
* OpenAI/Gemini Integration
* LLM Support
* RAG System
* Database Integration
* User Authentication
* Chat History
* Docker Deployment
* Cloud Hosting

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📸 Screenshots

Main Dashboard

(Add screenshot here)

Chat Interface

(Add screenshot here)

Swagger API

(Add screenshot here)

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👨‍💻 Developer

Dr. Jaypalsing N. Kayte

PhD in Computer Science

AI Researcher | NLP Engineer | Machine Learning Developer | FastAPI Developer

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📜 License

This project is developed for educational, research, and AI application development purposes.

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⭐ GitHub

If you like this project, give it a ⭐ on GitHub.