Feb 21, 202303:09 AM - edited Feb 21, 202303:54 AM
I'm looking to use Slack + Airtable + Chat GPT to do the following:
When a post is written in a travel slack channel in natural language, e.g. John Johnson writes "I will be in Genoa with Steve Marshall on 23rd/24th Feb and travel to Singapore on the 26th to 4th March."
That is sent to airtable (easy enough) but as structured data. Where Chat GPT is acting as the tool for structuring the data into columns such as "Location" "Date" "Client" "Other people visiting (that isn't the author)".
I just wondered if anyone had any ideas how I might be able to do that? Thanks!
Hi Bill_French, really interesting architecture that you built there.
I was wondering whether you could assist me with something similar. I currently have a typeform that is used to gather information on families that want to register on our platform. These information dive straight into our Airtable and I would like to use the learnings from these inputs to feed a LLM model on chatgpt in order to automatically generate a description of these families based on their answers and have it standardised (as you know people are usually very lazy when it comes to writing text in a survey). I would like to have this data come back to the airtable but I am not really sure how to structure it.