Millions are using ChatGPT, but its knowledge is limited to pre-2021 data and lacks awareness of recent or private data. This blog post provides a tutorial for setting up a customized version of ChatGPT using a specific data corpus, with an accompanying GitHub repository for reference. The process involves two main components: data ingestion and creating a chatbot interface. Data ingestion includes loading data from various sources, chunking it into manageable pieces, embedding those chunks, and storing them in a vectorstore for efficient querying. The chatbot setup involves combining chat history with new questions to form standalone queries, using these to fetch relevant documents, and generating responses using a language model. The tutorial discusses customization options, such as altering prompts and selecting different language models, and offers guidance on deployment, including using a simple terminal interface or deploying via Gradio and Hugging Face spaces.