PrismaTech Chatbot

The accompanying blogpost

This repo is an example of how one can implement guardrails by fine-tuning BERT.

There are two modules here:

• bert -- the notebook and the dataset used for fine-tuning. The data is generated using Claude.
• server -- the actual chatbot implemented with streamlit and OpenAI API

Fine-tuning

• Load the notebook in Colab
• Upload the data in the Colab storage
• Run the notebook
• The resulting weights can then be put into the server folder

Running the server

• poetry install && poetry shell to set up the environment
• streamlit run server/app.py to start the server

The following environment variables MUST be set before running:

• OPENAI_API_KEY
• PASSPHRASE
• PARTY_DATE
• PARTY_LOCATION
• PARTY_THEME
• PARTY_DRESSCODE
• PARTY_MENU