# RAG Bot

## Overview
The RAG Bot is a dialogue system capable of engaging in coherent Urdu conversations. It integrates natural language processing, a Speech-to-Text (STT) module for understanding spoken language, and a Text-to-Speech (TTS) module for synthesized voice output.

## Table of Contents
1. [Requirements](#requirements)
2. [Setup](#setup)
3. [Running the Bot](#running-the-bot)
4. [Interacting with the Bot](#interacting-with-the-bot)
5. [Models and Datasets](#models-and-datasets)
6. [Customization](#customization)
7. [Evaluation](#evaluation)
8. [Report](#report)
9. [Contributing](#contributing)
10. [License](#license)

## Requirements
- Python 3.6 or higher
- Pip package manager
- Internet connection for model downloads

## Setup
1. Clone the repository:
   ```bash
   git clone https://github.com/azharali9/rag-bot.git
   cd rag-bot
   ```

2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```

3. Download models:
   ```bash
   sh models/download.sh
   ```

## Running the Bot
Execute the following command:
   ```bash
   python app.py
   ```

## Interacting with the Bot
- Open a web browser and go to [http://localhost:5000/](http://localhost:5000/).
- Type queries or use the microphone icon for speech input.

## Models and Datasets
- RAG Model: "facebook/rag-sequence-nq"
- STT Model: "facebook/hf-seamless-m4t-medium"
- TTS Model: "facebook/hf-seamless-m4t-medium"
- Urdu Dataset: [urdu_stories.csv](datasets/urdu_stories.csv)

## Customization
- Modify the code in `app.py` for custom behavior.
- Explore additional models from Hugging Face for diverse functionality.

## Evaluation
The evaluation results and approach are documented in the [evaluation report](evaluation_report.pdf).

## Report
Refer to the [documentation report](documentation_report.pdf) for a detailed explanation of the system's approach, challenges faced, and results.

## Contributing
Feel free to contribute by submitting issues or pull requests.