Hey everybody, how’s it going? Alex here. Today, we’re going to take a look at the functions in ChatGPT and how they can be used to automate text extraction and generate structured responses.
In the previous video, we explored how to talk to PDFs, but in this one, we’re going to focus more on how to take any text and extract structured responses from chat completion using functions.
To set up the process, we’ll be using Airtable to store the extracted data. The first step is to create a function that defines the structure of the data we want to extract. This function will include properties such as the business model, projected revenue, contact email, and CEO.
Once the function is set up, we can make a call to ChatGPT using the function as a parameter. We’ll use the ChatGPT API to send a POST request with the function and the text we want to extract from.
The response from ChatGPT will be in JSON format. We can parse the JSON and extract the relevant information using filters. For example, if the business model exists in the response, we can populate our Airtable database with that information.
We can repeat this process for other properties like projected revenue, contact email, and CEO. Each property will have its own filter to extract the relevant data.
By using functions in ChatGPT, we can automate the extraction of structured data from text and store it in a database. This allows us to easily access and analyze the information.
In conclusion, functions in ChatGPT provide a powerful tool for automating text extraction and generating structured responses. By defining the properties we want to extract and using filters to parse the response, we can easily populate a database with the extracted data. This opens up possibilities for various applications in data analysis and automation.
Thank you for watching this tutorial on how to use functions in ChatGPT. If you have any ideas for future tutorials, feel free to leave a comment below. Have a great rest of the week!
