azure-search-openai-demo VS xTuring

Hi all, Im not an expert at full-stack deployments and need help with a sample code from github to which I want to make changes. (Code: https://github.com/Azure-Samples/azure-search-openai-demo) If your suggestion works, I am willing to tip 15$ (please provide link). This Github code is used as frontend for our application. We pretty much want to keep it like it is but make one minor adjustment. If you chat with the model, it gives you citations: (Link). Then on the right side of the page a Analysis Bar opens and it shows the one page that this citation refers to. HERE: We need to show the WHOLE document for each citation instead of just one page. I think it has to do with an url or something that needs to be changed. Could you tell me the script names and changes (before and after) so I can overwrite it? Thanks a lot. Best

There's at least two more. There's also https://github.com/Azure-Samples/azure-search-openai-demo

And you can deploy a chat bot from within the Azure playground which runs on another codebase.

You can see region availability here for Azure OpenAI:

https://learn.microsoft.com/en-us/azure/cognitive-services/o...

It's definitely limited, but there's currently more than one region available.

(I happen to be working at the moment on a location-related fix to our most popular Azure OpenAI sample, https://github.com/Azure-Samples/azure-search-openai-demo )

Hello everyone, I am an electrical engineer working at a company, since I’ve been coding for a few months they asked me to implement Ai services in their workflow and I did it following the tutorial by azure to chat with entreprise data provided by Microsoft (https://github.com/Azure-Samples/azure-search-openai-demo) the problem is in only a few days the pricing was indicated to be about 70$ going in too much higher prévision for the rest of the month in the azure cost analysis tool which is too high for us. When I saw that I deleted the ressource group that was created following the tutorial but now I can’t access it to see azure stopped billing us and I’m a little worried. If the ressource group including the cognitive search was deleted the billing stop right (it was cognitive search that costed like 95%) if not how can i see a deleted ressource group and how can I stop the billing?

I recently deployed https://github.com/Azure-Samples/azure-search-openai-demo

You may also want to browse through this sample code base on GitHub https://github.com/Azure-Samples/azure-search-openai-demo. This sounds like what you want to achieve. https://github.com/Azure-Samples/azure-search-openai-demo

You can also use a GPT model combined with a search service to provide a QnA chatbot https://github.com/Azure-Samples/azure-search-openai-demo

Explore the project on GitHub here.

If you're curious, I encourage you to: - Dive deeper with the LLaMA 2 tutorial here. - Explore the project on GitHub here. - Connect with our community on Discord here.

If you want best performance, you need to do both RAG and fine-tuning very well. There are plenty of resources on doing fine-tuning thought. I'm one of the contributors to https://github.com/stochasticai/xturing project focused on fine-tuning LLMs. You can find help in the discord channel listed on the GitHub.

What tools do you use and achieved great results ? … For me i have tried xturing and SFTTrainer and they got me a semi okay results.

Code: https://github.com/stochasticai/xTuring/blob/main/examples/llama/llama_lora_int8.py Colab: https://colab.research.google.com/drive/1SQUXq1AMZPSLD4mk3A3swUIc6Y2dclme?usp=sharing

We are a group of researchers out of Harvard working on open-source library called xTuring, focused on fine-tuning LLMs: https://github.com/stochasticai/xturing.

Fine tuning I was thinking about using this (low GPU memory footprint): https://github.com/stochasticai/xturing/blob/main/examples/int4_finetuning/README.md

I can't speak for QLORA, as I haven't had a chance to get an implementation working, but I've had success with StochasticAI's Xturing. It's by far the most streamlined method of finetuning I've come across, and they offer int8 and int4 fintuning (but only for llama-7B).