This project is a personalized customer engagement chatbot built using Streamlit and Hugging Face's GPT-Neo model. The chatbot generates personalized engagement messages based on customer data and interaction history. It is designed to provide a seamless and personalized customer experience by utilizing state-of-the-art natural language processing models.

Personalized Engagement: The chatbot generates responses based on individual customer preferences and interaction history.

Easily manage and engage with multiple customers by selecting from a list.

A minimalistic and user-friendly interface built with Streamlit.

Easily add or update customer data.

Python 3.7 or higher

Run the Streamlit Application:

Open the local Streamlit URL provided in the terminal. Select a customer from the dropdown. Enter an engagement query in the text input field. Click "Generate Response" to receive a personalized message.

This project is licensed under the MIT License.