Integrating Azure ML and Power BI 

Unfortunately, I have bad news and slightly less bad news. The bad news is that the 502 Bad Gateway response you're getting is (most likely) because the response to the Power BI gateway is too large, above 8MB. Here's a similar issue regarding Application Insights data: stackoverflow.com/questions/41869170/query-from-powerbi-to-ai-suddenly-fails-with-502-bad-gateway To fix this, there are three options I can see. One is, like you mentioned, reducing the amount of data you send (and receive) as part of the Power BI to Azure ML connection. Because that's not a desirable option for you, a second alternative would be to feed the data to Azure ML using a separate process, store the results, and then load that into Power BI. You lose the benefit of the AML-PBI direct integration and may have some level of delay in scoring data, but would not run into this issue. The third alternative would be something like a hybrid approach. Have a back-end process call your scoring endpoint for data, storing that someplace you can access it later. Then, in Power BI, have two Power Query tables: one with the scored results and one without (for records that you ingested after the last time your back-end scoring process ran). The one without, you'd perform just-in-time scoring. Then, union the two tables together and the output looks normal again. Some enterprising mind might know of a good fourth way, but I'm not aware of one.

I'm not particularly familiar with Tableau, but I'll at least add this to my list to check out and see if I can create a video.

Hmm, that's interesting. I do see azureml-inference-server-http available in pip, so the package hasn't been removed. If there's a typo, that could explain things, though I didn't see any typos based on the error message you have. One thing you could try is running the container locally to see if you get any additional information. I have some instructions at github.com/feaselkl/AzureML-Local-Deployment/tree/master and a video at ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-bue85m7lbjQ.html. If you can successfully run the container locally, that would indicate an issue somewhere in Azure ML.

As of today, the answer is kind of complicated. You can use Azure OpenAI within Power Query to enrich data: techcommunity.microsoft.com/t5/educator-developer-blog/how-to-use-azure-open-ai-to-enhance-your-data-analysis-in-power/ba-p/4041036 And there is Copilot for Power BI within Microsoft Fabric but it requires Microsoft Fabric and at least an F64 SKU: learn.microsoft.com/en-us/power-bi/create-reports/copilot-introduction There is at least one third-party custom component that might do what you want in AI Lens for Power BI, though there will likely be additional costs for licensing it: www.lensvisual.io/

@@KevinFeasel thanks kevin for detail answer, but instead of openai or copilot i want to use other open source model from huggingface. Is it feasible?

@@muhammadtalmeez3276 Probably not without a significant amount of development work on your end. Just spitballing an answer, you'd probably need to host your model via API and then create a custom component to send the user prompt plus data to that API and get the response back. It's the "plus data" that would make this a real challenge, especially if you intended to use it with sliders and to view data on charts. It's not something I've done before, though I suppose it is technically possible, just a major endeavor.

@@KevinFeasel thank you so much kevin. I am struggling this from last 3 days. Your answer is very helpful to conclude my research.