GPT extrae y responde a datos de cualquier sitio (con Chromadb y Trafilatura)

Table of Contents

1. Introduction
2. Building a GPT-Powered Q&A Board
3. Collecting Data with Phila Tour Web Reader
4. Storing Embeddings with Chroma DB
5. Creating the Q&A Board
6. Querying the Website and Getting Answers
7. Results and Analysis
8. Conclusion

Introduction

In this video, we will explore the concept of large language models and how they can be utilized to build a powerful Q&A board. We will be specifically using GPT (Generative Pre-trained Transformer), a popular language model, to Interact with websites and retrieve information directly from them. The demo will be conducted using the website of supertype.ai as an example, but You can Apply the same principles to any website you have permission to scrape data from.

Building a GPT-Powered Q&A Board

To begin, we need to install the necessary tools for this project. We will be using Llama, Index, and Chroma, which are powerful libraries for working with large language models and embeddings. Make sure to have these dependencies installed before proceeding.

Collecting Data with Phila Tour Web Reader

Next, we will use Phila Tour Web Reader, a library that helps us extract text from websites. By using this tool, we will Collect the necessary data from the website we want to interact with. In our case, this includes information about the services provided by supertype.ai and details about the team members. We will store this data in our index for later use.

Storing Embeddings with Chroma DB

To store the embeddings retrieved from the website, we will utilize Chroma DB. Chroma DB acts as an embedding store or database, allowing us to efficiently store and retrieve embeddings. We will Create a Helper function to initialize our Chroma DB and create a collection to store the embeddings.

Creating the Q&A Board

Now that we have collected the data and set up our embedding store, we can proceed to create our Q&A board. We will define a function to query a specific page and retrieve answers to our questions. In this function, we will use the Phila Tour Web Reader to load data from the provided URLs and then build an index using the GPT Chroma Index. This index will be Based on the collected documents.

Querying the Website and Getting Answers

With our Q&A board set up, we can now start querying the website and getting answers to our questions. We will define a list of questions that we want to ask, such as the team members of supertype.ai or the problems they are trying to solve. We will use the index to perform a query for each question and retrieve the corresponding answers. These answers will be printed out, allowing us to see the results of our Q&A board in action.

Results and Analysis

After querying the website and getting the answers, we can analyze the results. We will examine the accuracy and relevance of the answers provided by the Q&A board. Additionally, we will discuss any limitations or potential improvements that could be made to enhance the performance of the system.

Conclusion

In conclusion, building a GPT-powered Q&A board is an exciting and powerful way to interact with websites and retrieve information from them. By leveraging large language models and embedding stores, we can create a system that can answer questions based on the data collected from a website. This opens up numerous possibilities for automation, chatbots, and customer support systems. Whether you are looking to build a Q&A board for your own website or explore the capabilities of large language models, this tutorial provides a solid starting point.