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https://github.com/faisalahmedbijoy/chat-bot-using-llm-with-gradio
Chat Bot using LLM with Gradio
https://github.com/faisalahmedbijoy/chat-bot-using-llm-with-gradio
Last synced: about 4 hours ago
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Chat Bot using LLM with Gradio
- Host: GitHub
- URL: https://github.com/faisalahmedbijoy/chat-bot-using-llm-with-gradio
- Owner: FaisalAhmedBijoy
- Created: 2024-08-01T14:48:16.000Z (4 months ago)
- Default Branch: master
- Last Pushed: 2024-08-01T16:34:58.000Z (4 months ago)
- Last Synced: 2024-08-02T17:51:38.287Z (4 months ago)
- Language: HTML
- Size: 271 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 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
1. **Clone the repository:**
```sh
git clone https://github.com/FaisalAhmedBijoy/Chat-Bot-using-LLM-with-Gradio
```
2. **Install the dependencies:**
```sh
pip install -r requirements.txt
```
3. **Download the model:**
Download the `Qwen/Qwen2-7B-Instruct` model from Hugging Face and place it in a directory (e.g., `models`).
```sh
python download_model.py
```
### Running the Application
1. **Run the Flask application:**
```sh
python app.py
```
2. **Open your browser and go to:**
```
http://127.0.0.1:5000
```
## Project Structure
```bash
agri-chatbot/
│
├── static/
│ ├── audio/
│ ├── images/
│
├── templates/
│ └── index.html
│
├── .env
├── app.py
├── download_model.py
├── requirements.txt
└── README.md
```
## Demo
## Usage
1. Type your query in the input box and press `Send`.
2. The bot will respond with a text message and an audio message.
## Acknowledgments
- The chatbot uses the [Qwen2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct) model from Hugging Face.
- Flask is used for the web framework.
- Bootstrap is used for styling the web interface.
## Contributors
- [Faisal Ahmed](https://www.linkedin.com/in/faisal-ahmed-2a71581b1/)
- [H.M. Mehedi Hasan](https://www.linkedin.com/in/h-m-mehedi-hasan-badhon/)