I like how you are so comprehensive in covering the different branches of scenarios and possibilities, going over the trade-offs. All these delivered so systematically and articulately as well. Well done. I RARELY subscribe to tutorial channels but yours is an instant subscribe after 2 videos.
Well deserved compliments in the comments, you have explained the greatest ability of LLMs very clear. Let's chat at the next Amsterdam AI Builders Meetup!
This is really wonderful tutorial! I hope this video becomes popular soon. Could you share such more tutorial talking about how to make LLM application output consistent responses with production grade solution that will scale!
@@daveebbelaar I have a follow up question. If you want to "prompt" the LLM to output AI generated emails in a specific format (e.g. intro paragraph/hook of 30 words max, main body of e.g. 50 words max and a CTA of 15 words max) what would be your suggested approach? The traditional way of just giving an example when prompting is very unreliable in this regard but wondering which of your discussed approaches would be best.
@@daveebbelaar They certainly can! I was wondering, do you know of a way to make a RAG using something like Flowise AI work with tools? Eg, have a RAG chatbot that is able to call on functions (POST to a webhook), for example when it sees fit to? I have attempted to configure this in Flowise, but always get stuck at merging the RAG and the tool together... I suspect something like the solutions you cover in this video could work for that sort of requirement... 🙏
You are great Dave, helping us a lot. Thank you for your effort here. Does Instructor library also work with Assistant API of Open AI instead of Chat completion API? I mean instead of client.chat.completions.create, using client.beta.threads.runs.create format. Does this work with Instructor as well? One another question is, are you really using Chat Completion API for your project with your real world client that you mention in the video? If so, why don't you use assistant API? Is not that easier? Is there any drawbacks of Asisstant API over Chat Completion API?
Hey there new to channel and pretty new to AI still in learning process :) tbh I think this video is soo advanced for me to grasp the idea :) but I have some insights on it can you correct me if Iam wrong :) My insight: "You are building a software for responses depending on pretrained LLM models " ?
Is there an example of the content filtering for JavaScript? I can see instructor has a JavaScript version but can’t see any information or examples on content filtering. Would appreciate any help!
@daveebbelaar, if I'm not mistaken, I think "max_retries=1" means retries are allowed once. If you don't want to allow any retries, it needs to be "max_retries=0", correct?
Hmm, while that would make sense, I am not sure. I tried many examples with max_retries=1, and they all failed. I can't see anything in the docs about this. It would require further testing and looking at the API calls.
Great Stuff there. Really like the use case as it is not new, message classification, but how to do this with an LLM instead of a local ML model and do it reliably!
Creator of instructor here! Thanks so much for this video
Appreciate the comment Jason 🙌🏻
Please keep on making unique content like this that solves pains of gen AI developers for which solutions aren't that straightforward.
I like how you are so comprehensive in covering the different branches of scenarios and possibilities, going over the trade-offs. All these delivered so systematically and articulately as well. Well done. I RARELY subscribe to tutorial channels but yours is an instant subscribe after 2 videos.
This is gold. Thanks for sharing Dave!
Glad you enjoyed it!
Great walkthrough and thank you for pointing out Instructor - a great library!
Well deserved compliments in the comments, you have explained the greatest ability of LLMs very clear. Let's chat at the next Amsterdam AI Builders Meetup!
This is really wonderful tutorial! I hope this video becomes popular soon. Could you share such more tutorial talking about how to make LLM application output consistent responses with production grade solution that will scale!
I had been wondering about these problems for a while. This video is 100% gold!
Wow! Knowledge bomb.
Please make more videos like this.
More to come!
Great content. The progressive approach of explaining the problem and narrowing down the solutions is perfect 👌
Very helpful thank you David
The exact video i needed with Pydantic and Instructor - Thank you Dave!
Dave.. your content is so specific for us GenAI devs. I LOVE it. Please keep it up!
More to come!
@@daveebbelaar I have a follow up question. If you want to "prompt" the LLM to output AI generated emails in a specific format (e.g. intro paragraph/hook of 30 words max, main body of e.g. 50 words max and a CTA of 15 words max) what would be your suggested approach? The traditional way of just giving an example when prompting is very unreliable in this regard but wondering which of your discussed approaches would be best.
Really helpful video Dave, thank you for sharing this information!
man, you're a really good teacher!
I appreciate that!
thanks for this awesome video
This was great, thanks. I've had questions about this previously
Thanks! The different methods can definitely be confusing at first.
@@daveebbelaar They certainly can!
I was wondering, do you know of a way to make a RAG using something like Flowise AI work with tools? Eg, have a RAG chatbot that is able to call on functions (POST to a webhook), for example when it sees fit to? I have attempted to configure this in Flowise, but always get stuck at merging the RAG and the tool together...
I suspect something like the solutions you cover in this video could work for that sort of requirement... 🙏
THANK YOU!
Love this!
Thanks Dave, love ur content and channel
Absolutely fantastic! Thanks for sharing @daveebballar! Can we make this work with a local llm - e.g. ollama?
Great content - thank you for sharing:)
Insane content. Thank you.
This content is awesome !!!!!
Very helpful!
please how do you use the interactive python execution in vs code??
You are great Dave, helping us a lot. Thank you for your effort here.
Does Instructor library also work with Assistant API of Open AI instead of Chat completion API? I mean instead of client.chat.completions.create, using client.beta.threads.runs.create format. Does this work with Instructor as well? One another question is, are you really using Chat Completion API for your project with your real world client that you mention in the video? If so, why don't you use assistant API? Is not that easier? Is there any drawbacks of Asisstant API over Chat Completion API?
yea i would like to know as well since we using threads and runs this solution does not work unless you build around chat completions
Hey there new to channel and pretty new to AI still in learning process :) tbh I think this video is soo advanced for me to grasp the idea :) but I have some insights on it can you correct me if Iam wrong :)
My insight: "You are building a software for responses depending on pretrained LLM models " ?
yea. He is basically building a wrapper around chat-gpt that does really specific task with more accuracy an efficiency .
Hi Dave does your company also make apps for math education. Where can we find details of your company
Won't it be same if I simply pass schema inside the system message rather than using instructorGPT/function calling thing?
Is there an example of the content filtering for JavaScript? I can see instructor has a JavaScript version but can’t see any information or examples on content filtering. Would appreciate any help!
@daveebbelaar, if I'm not mistaken, I think "max_retries=1" means retries are allowed once. If you don't want to allow any retries, it needs to be "max_retries=0", correct?
Hmm, while that would make sense, I am not sure. I tried many examples with max_retries=1, and they all failed. I can't see anything in the docs about this. It would require further testing and looking at the API calls.
can we use it with runs as well
Hi, thanks for this tutorial. But the Git repo is not available. It shows 404 error. Thanks
Ah, it was still set to private. It's fixed now - thanks!
@@daveebbelaar Yeah, its working now. Thanks 👍
Great Stuff there. Really like the use case as it is not new, message classification, but how to do this with an LLM instead of a local ML model and do it reliably!
is it just me or is it just always returning a confidence score of .9?
Prompt it to be more specific E.g., give conditions on makes it a 0.5 or 0.9