Summaries Artificial Intelligence and Technology Create Your Own AI Chatbot with Custom Knowledge Base using OpenAI API and GPT 3

This is a summary of a YouTube video "Build AI chatbot with custom knowledge base using OpenAI API and GPT Index" by Irina Nik!

4.3 (45 votes)

The video teaches how to create your own AI that answers questions based on your custom knowledge base using open AI API and GPT 3 model.

• 🤖
  00:00

  Create your own AI that answers questions based on your custom knowledge base using open AI API and GPT 3 model.
• 📈
  02:38

  The GPT index, powered by GPT3 API, can help create an index of data by uploading it to a folder named "context data" and following a tutorial in Google notebook.
• 📊
  04:03

  The speaker used GPT-2 to create a custom knowledge base, but the fake user research data is not insightful and cannot be shared.
• 🔍
  05:43

  Created functions to analyze interview data using GPT index and line channel libraries.
• 📚
  07:17

  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.
• 🔑
  10:20

  Sign up for openai API, construct an index, and ask questions to access data.
• 🤖
  12:15

  Our AI uses cooking and appliance data to answer questions and generate ideas.
• 🤖
  13:53

  Create your own AI with a custom knowledge base by defining functions, installing dependencies, and running functions.

Key insights

• 🤔 Creating a custom AI allows for answering specific knowledge-based questions that cannot be accessed by general AI models like GPT.
• 📚 The GPT index library, which utilizes the GPT-3 API, can be used to create an index from data, simplifying the process of building an AI chatbot with a custom knowledge base.
• 💡 The use of AI-powered chatbots has the potential to streamline information retrieval and display, as demonstrated by the ability to query the AI with context information and display the results in markdown format.
• 💰 Using the OpenAI API for experiments is relatively cheap, with the speaker mentioning that they have only spent 14 cents for all their experiments.
• 💡 Using AI to analyze interviews and break down information into clusters can make it easier to extract valuable insights and patterns from the data.

Detailed summary

• 🤖
  00:00

  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.
• 📈
  02:38

  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.
• 📊
  04:03

  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.
• 🔍
  05:43

  Install GPT index and line channel libraries, create two functions (construct index and search index) to analyze interview data.
• 📚
  07:17

  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.
• 🔑
  10:20

  To use openai API, sign up on their website to get an API key, construct an index with the data path, and start asking questions.
• 🤖
  12:15

  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.
• 🤖
  13:53

  Define functions, install dependencies, and run functions to create your own AI with a custom knowledge base.

Q&A

• How can I create my own AI that answers questions based on my custom knowledge base?

  You can create your own AI by using the open AI API with the GPT 3 model and breaking your knowledge database into small chunks to find relevant context and provide necessary information to the AI.

• What is the GPT index library used for?

  The GPT index library is used to create an index of your data by uploading it to a folder named "context data" and following a tutorial in Google notebook. It utilizes the GPT3 API.

• How do I set parameters for a large language model?

  You can set parameters such as maximum length, temperature, and model name using the Open AI API documentation. These parameters help in asking questions and receiving answers.

• How do I use the GPT index library to query an AI model?

  To use the GPT index library, you need to define a path, load data, create and save an index in Json format, and then query the AI model with user input and context information.

• How do I use the openai API to ask questions?

  To use the openai API, you need to sign up on their website to get an API key, construct an index with the data path, and start asking questions.