Create your own AI that answers questions based on your custom knowledge base using open AI API and GPT 3 model.
Learn how to create your own AI that can answer questions based on your custom knowledge base, as opposed to relying on general knowledge from the internet.
We use open AI API with GPT 3 model and break our knowledge database into small chunks to find relevant context and give only necessary information to our AI.
Use the open source library GPT index, which utilizes the GPT3 API, to create an index of your data by uploading it to a folder named "context data" and following a simple tutorial in Google notebook.
The speaker created a custom knowledge base using a fake user research data and a script generated by GPT-2 for a small use case, but the data is not insightful and cannot be shared.
Learn how to set parameters for a language model and use the GPT index Library to query an AI model with user input and context information.
The lecture discusses setting parameters for a large language model, including maximum length, temperature, and model name, using the Open AI API documentation to ask questions and receive answers.
The lecture explains how to use the GPT index Library to define a path, load data, create and save an index in Json format, and query an AI model with user input and context information.
Our AI uses information from interviews about cooking and domestic appliances to answer questions and can also break down the data into clusters and brainstorm ideas based on the information.