TalkToEBM

Welcome to the TalkToEBM project! This repository contains code and resources for creating an interactive conversational AI tool using EBM (Explainable Boosting Machine).

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License

Introduction

The TalkToEBM project aims to facilitate a user-friendly interface to interact with Explainable Boosting Machines, enabling users to obtain insights from machine learning models and making predictions in a conversational manner.

Features

• Interactive Chat Interface: Engage with the model through a chatbot-style interface.
• Model Explanation: Users can ask for explanations of model predictions in a human-readable format.
• Customizable: Modify the underlying model and interaction logic to suit specific applications.

Installation

To get started, clone this repository to your local machine:

git clone https://github.com/apkirana/project_learn_TalkToEBM.git
cd project_learn_TalkToEBM

Requirements

Ensure you have Python installed (preferably Python 3.6 or later). Then, install the necessary packages:

pip install -r requirements.txt

Usage

To run the application, execute the main script:

python main.py

You will then be able to interact with the model via the provided chat interface.

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue if you have suggestions or improvements. Fork the repository. Create a new branch (git checkout -b feature/YourFeature). Make your changes. Commit your changes (git commit -m 'Add some feature'). Push to the branch (git push origin feature/YourFeature). Open a pull request. License This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

EBM (Explainable Boosting Machine) - for making machine learning more interpretable. Chatbot frameworks and libraries that inspired the development of this project.

important ins

Create virtual env (if not already done)

python -m venv venv source venv/bin/activate # Linux/Mac

Generate requirements.txt from installed packages

pip freeze > requirements.txt

create env first

python3 -m venv .venv #activate source .venv/bin/activate #sync toml sync

#if you want to run requirement uv pip install -r requirements.txt

#if you want to add new lyb uv add pandas uv add seaborn

%update python pip install --upgrade pip

pip install tomli tomli-w 


conda env list
conda activate vlmtask
conda env export > environment.yml