Chat with Your SQL Data Using ChatGPT

In this video, we will use Open AI to chat with our SQL/Tabular data without writing any SQL query. We can ask any question about our database using conversation and the results will be retrieved and explained again without any coding.

Part 1 – Chat With Your Data:

Part 2 – Chat With Your Data:

Open AI+ Azure = Revolutionize the Way You Do Business

ChatGPT Came To Azure:

Repo used in this video:

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[funkedelic_bob]

Really cool to see MG. However, I was hoping this was going to be more of an expansion on Part 2 and showing how to hook up a SQL server to Azure Cognitive Search. Would love to see a video on that :)

[blahblahblahblah]

This is gonna change the whole job of a data analyst to another LEVEL... Will try this and get back with doubts...👍 cool video

[dvenkatnath]

Hey bro !, Amazing video and very clear explanation. Very clear and comprehensive. I tried and understood the works. Thank you.

[tgrtusi]

This is amazing content MG. Thanks alot for sharing this!

[jtndhqi]

Thanks MG for making such high quality content!

[Elvee]

That’s exactly what I was looking for thanks so much

[maciejgowacki]

Hi "MG", it would be good to see a film about basic Azure ML configurations. The problem I see is that Azure ML provides so many possibilities for teams working on a business solution that it can be confusing for beginners. Basically, Microsoft does not introduce a "standard"; you can use everything that is available in any way, for example, Databricks cluster, MLflow, bamboolib - a GUI for pandas - here you go, GitLab plus Databricks - no problem, ONNX, Feast, OpenAI - why not. In my opinion, this is a big drawback because at the "start, " I have to choose tools myself (know the pros and cons of these solutions), and I have to have a solution architecture established. For example, should I use the Run class and methods (log, log_accuracy_table, log_list, log_predictions) or maybe MLflow?

[ChristianGUIDIBI]

This I great thanks for sharing. Will try it and see if I can have it generate sql query to build complex report joining those tables

[sunnysohom]

Excellent video MG. Love the content. Only one query. If the data inside the table changes while we are conversing with ChatGPT, does the change reflect in the model's output ?

[creneemugo]

You can run a stored procedure that brings back only the data you want and just place the data in a collections object.

[swetareddy]

Hi MG! The video was really helpful. Can I know in details about the same scenario if we have the column's content of the data table in the jsonb that is "key-value pair" format?

[vijayakannanr]

Great Video, Is there a way to implement CRUD operations in the DB using Langchain and GPT? If the user types "I want to add a new artist", then the app should ask for the necessary details. Once the user enters the necessary details, it should create a new record in the Artist table.

[avicool]

wow, this is really cool which will really help many of our scenario. Please share more of these kind of videos. Here you've linked with local SQLite, is there a way we can connect to external source in SQL Serverless in Synapse? (which has like GBs of data)

[AnuragKhareOracle]

Hi MG, wondering if you have tested sequence of prompts (sql) one feed to others as part of analysis.

[somilmehta]

Hi MG, Can you please make a tutorial on how to connect it with SQL server as well.

[yusufkemaldemir]

@MG, how can you connect to existing server? Having SSMS, server name and lots of database in it. Without using/creating sqlite, can i directly connect langchain to existing SSMS? Thanks

[nachopascual]

Excellent video!!! Is it possible to add memory to the agent so that it remembers the questions and reduce the number of tokens used in them?

[Denver]

I think I'm echoing what others are asking for: I have SQL 2016, 2019 servers with multiple DBs. I would like an interface application similar to what you're using, I think. That interface can process the schemas of the databases and then help me form new queries and retune existing queries as required.
As I see it, your python interface application is producing a local .db file as source material for your questions. I'm hoping the interface can leave the data in place -due to its size. I imagine with the schemas, ChatGPT or some other AI engine can loosely understand the goals and produce, test, refine queries for me to QA and work with.
Perhaps this is not possible yet?
I suppose another issue is privacy and how I can use the engine without exposing my private data.

[micaelakulesz]

Hi! How can I retrain the model as to reduce the error in the translation natural language to query? Retraining is I guess almost absurd, but would you have any suggestion on how to correct these queries? For instance, I sometimes ask for an average and the query doesn't add a GROUP BY cluase.

[farexBaby-urns]

missing something..is there a sql agent loaded locally that you interact with which in turn accesses db?
Do conv go outside local, to openai servers or are all this local
(if not I dont like chatgpt learning my data and database structure)