Agri Chatbot: Chat-Bot-using-LLM

This project is an agriculture chatbot designed to assist farmers with their queries using a large language model. The chatbot is built with Flask for the backend and uses a pre-trained model from Hugging Face for generating responses.

Features

Chat Interface: Interact with the chatbot through a user-friendly chat interface.
Text-to-Speech: Converts the chatbot's responses to audio.
Responsive Design: Ensures the interface looks good on all devices using Bootstrap.

Getting Started

Prerequisites

Python 3.7+
Pip (Python package installer)
Git (for cloning the repository)
PyTorch

Installation

Clone the repository:

git clone https://github.com/FaisalAhmedBijoy/Chat-Bot-using-LLM-with-Gradio

Install the dependencies:
```
pip install -r requirements.txt
```
Download the model:

Download the Qwen/Qwen2-7B-Instruct model from Hugging Face and place it in a directory (e.g., models).
```
python download_model.py
```

Running the Application

Run the Flask application:
```
python app.py
```
Open your browser and go to:
```
http://127.0.0.1:5000
```

Project Structure

agri-chatbot/
│
├── static/
│   ├── audio/
│   ├── images/
│
├── templates/
│   └── index.html
│
├── .env
├── app.py
├── download_model.py
├── requirements.txt
└── README.md

Demo

Usage

Type your query in the input box and press Send.
The bot will respond with a text message and an audio message.

Acknowledgments

The chatbot uses the Qwen2-7B-Instruct model from Hugging Face.
Flask is used for the web framework.
Bootstrap is used for styling the web interface.

hm-badhon/Chat-Bot-using-LLM-with-Gradio