Problem

As a book club organizer, we wanted to create a platform that would allow our members to chat with a virtual assistant about the books they were reading. We needed a solution that would be easy to use and provide personalized recommendations based on each member's reading history.

We decided to use OpenAI, Streamlit, and Neo4j for this project. However, we faced several challenges in integrating these technologies and creating an intuitive user interface.

Solution

To address these challenges, we created a chatbot using OpenAI's GPT-3 language model. We used Streamlit to build the front-end of the application and Neo4j as the database to store information about each member's reading history.

We also implemented natural language processing (NLP) techniques to ensure that the chatbot could understand and respond appropriately to user input. This involved training the model on a large corpus of text data related to books and literature.

Impact

Increased engagement among book club members by X%
Generated personalized book recommendations for each member based on their reading history

"Quote of how incredible of an impact this had."

Team

Team Member #1 - Software Engineer
- Oversaw the integration of OpenAI, Streamlit, and Neo4j technologies
- Built the back-end infrastructure for storing member data in Neo4j
Team Member #2 - Data Scientist
- Trained the NLP model on a large corpus of text data related to books and literature
- Implemented the chatbot using OpenAI's GPT-3 language model

Learn more about our project here.

Meet-up Club - Use of AI in your Domain