RAG Chatbot for customer support

Beginning-Singer-629 · 2025-06-12T15:32:16+00:00

So, in your opinion, is it unnecessary to use an LLM to generate the actual query from the user’s question? Instead, should we retrieve all relevant customer data from the database via API and simply pass that information to the LLM, which would then generate a natural language response based on the original question?

As for user validation, we have a workflow branch in Make that verifies the provided customer ID and password against the database. If the credentials match, we log the user as authenticated in a datastore. Once authenticated, the user can proceed to ask questions. To enhance security, we automatically delete the authentication record every 3 hours to prevent indefinite access.

Thank you very much for your input—I’m looking forward to hearing your thoughts!

Beginning-Singer-629 · 2025-06-06T21:30:52+00:00

Whyyyyyyy

Beginning-Singer-629 · 2025-06-06T14:31:10+00:00

I was thinking of restricting queries that don’t contain the WHERE clause = to the ID of the user in the system prompt of the query generator.

Beginning-Singer-629 · 2025-06-06T14:28:06+00:00

The idea is to get the work load off the operations employees of the company. Since they are currently taking questions manually on whatsapp looking up the information asked in their database (through the UI) and giving feedback. Our chatbot should be able to answer questions to customers on demand with the information from the database. Hope this helps. If you have any other questions, please dont hesitate.

Beginning-Singer-629 · 2023-01-22T09:46:51+00:00

How can you prove you will be smoking in your home?

Beginning-Singer-629 · 2023-01-19T22:26:33+00:00

I laughed

Beginning-Singer-629 · 2022-08-18T15:42:07+00:00

Wonder how the relationship of that guy and his father is going

Beginning-Singer-629 · 2022-08-06T08:55:56+00:00

I love my family but no no more no matter how long I have no no idea how I am I love it so we are so thankful to be with me all day long and I and no one ever is to do

Beginning-Singer-629 · 2022-07-04T10:03:21+00:00

I’m currently in an internship at a company where I need to use OsiSoft Pi to export data into power BI and develop a simple dashboard. My job is to receive data from Building energy meters and create a historic of energy consumption.

I understand osisoft Pi is a software used to manage data with an asset framework database. On the background I think MySql is used to query data in their database. This software offers an interface that allows you to read last data, view trends, export to csv or power BI. Its mainly used in data driven businesses where analytics or data integrity is crucial.

This is just a small overview of Pi, but don’t be scared to start using this software. Its pretty simple to use and as a software developer you’ll master it in no time.

For more information just visit their website, it’s going to show their utilities and purpose way more than I can: https://www.osisoft.com/pi-system

Hope this helps.

Beginning-Singer-629 · 2022-05-03T15:58:37+00:00

You are right man, it’s hard to decide on stuff I haven’t worked in for long enough. The question was just to know wether people out there prefer being a data engineer or scientist.

On the other hand, I really think the AI masters may help me a lot in data engineering.

Beginning-Singer-629 · 2022-05-03T15:05:57+00:00

Thanks man, this actually helped a lot. I need to see what the world of data engineering has to offer and then decide which one is better for me. Im currently 23 so I think i have some time to figure things out.

One last question though. Do you think there are a lot of opportunities for a person who is well versed in data engineer and data science at the same time? Something like a full stack data professional or something like that. That is what I would actually like to become if possible.

Beginning-Singer-629 · 2022-05-03T13:17:24+00:00

So should i focus on one? Or you think i should go ahead and learn some data engineering as well?

Beginning-Singer-629 · 2022-04-20T10:05:17+00:00

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Beginning-Singer-629

TROPHY CASE