Code Lab: Simple Chatbot using Llama Index

https://michael-ai.com

https://github.com/msuliot/simple_ai

Welcome to Michael AI's guide on creating a chatbot for digesting PDF files effectively. In this video, we tackle the challenge of making PDF documents on a website more easily accessible and searchable. The solution proposed is a chatbot that can scour through the contents of these documents and provide information as required.

In the first part, we establish the problem and discuss our ideal solution: a chatbot capable of parsing multiple PDF files and delivering information from them. This solution aims to enhance customer service, allowing users to look up information 24/7 while freeing customer service representatives for more complex queries.

In the following sections, we walk you through setting up our framework, 'Simple AI,' using Python 3. We begin by cloning our repository from GitHub and setting up our working directory in an editor of choice (VS Code in this example). We demonstrate how to pull the necessary data from our repository, run the pip commands, and secure an OpenAI key.

Next, we detail how to run the export command and hard code our OpenAI key into the environment variables. We also provide guidance on how to clear out placeholder files and move the necessary PDF files into our data directory.

Subsequently, we demonstrate the usage of Llama Index, a versatile tool that offers a variety of file readers. This utility is employed to import the contents of our PDF files into our chatbot.

Towards the end of the video, we run the Python script 'data import' to index the contents of the PDF files and store the vectors. We also highlight the importance of persisting this information for future use by the chatbot.

In the final part of the video, we showcase how to interact with our chatbot, asking it questions related to the information contained in the imported PDF files. This demonstrates the effectiveness of the bot, its ability to pull out relevant information, and the ease of interaction.

Join Michael AI for this comprehensive tutorial and learn how to create an efficient, information-retrieving chatbot that leverages the power of AI.