Extract Topics From Video/Audio With LLMs (Topic Modeling w/ LangChain)

0:00 - Intro
1:13 - Code Intro
2:46 - LLMs and Set Up
4:43 - Extracting Topic Titles
8:29 - Creating Structured Data
9:47 - Expanding on Topics
15:00 - Bonus: Add timestamps to topics

[changmianwang]

Thank you for the thorough introduction and sharing of your research.

[sullygoes]

I love your videos, just subbed. I've been watching your videos for a few months now and all of your content is gold. I've been in tech for ages and writing python like about 8 years, and I'm just so blown away by how much power LLM's have put into our hands with a simple API call. I'm using GPT all over the place in my personal tools right now, which is in turn helping me write even more, better code. I've been doing a hobby project where I have GPT doing virtual Tarot Readings in Streamlit app and with just a few nights and weekends of work it is capable of things that, without an LLM I doubt I could have EVER made happen in any amount of time. I haven't started using langchain yet because I've wanted to work directly with the prompts and responses for a while to get a good feel for how the models work, but I can already tell it's an amazing framework. Thanks for making this content!

[_ptoni_]

This is gem. Ty. Very well structed topic extraction.

[ednavas]

Such a good video. You do an incredible job of balancing the technical breakdown, the code itself and how it relates to the real world. Nice job!

[chaower]

Thank you for an awsome walk thru video very much. Every bits are informtive. 😊

[maya-akim]

This is great content, thank you so much! I learn so much from you every time I watch your videos

[hansenmarc]

Thank you for the great information! I hope you’ll consider doing a tutorial on how to use a GUI like flowise ai with langchain.

[OliNorwell]

That's amazing, great walkthrough, very easy to follow. I guess one improvement would be to look at the final timestamps, and remove any that are within say 30 seconds of the previous topic. At 12:32 in the example timestamps you have two topics. I guess you could either do this manually, or in Python. Perhaps given that it might only take 30 seconds to do so perhaps human tweaking right at the end is the way to go there.

[AliAliOxenFree]

I deleted my last comment because i was wrong and i feel like a moron. Anyways, these videos are invaluable and I hope you keep posting. Not only is the content cutting edge and already in high demand, but your style of presentation/explanation is top notch.

[Norfeldt]

Great content. Wouldn't abbreviating the names in the transcript help reducing the token size or is it the same? Likewise converting the timestamps to base64..?

[rhwcjlh]

Hi Greg. Thanks for your amazing video😃

What I want to know is that there are several methods to convert context into structured data using LLM, such as the Schema you used in the video or the Pydantic method provided in the LangChain official documentation.

Now I would like to ask, in terms of output stability, which method would you recommend? Because for me, using Schema to define the output of LLM seems more intuitive and straightforward than Pydantic.

Thank you for your response.

[xiaomiwu]

Great video, thanks! I ran into a problem this afternoon with the reference code. I can't import Pinecone. Any suggestion? Thanks!

[KhaledMohamed-ysgr]

I am a new in this channel, I will start with you but I have a question, Is playlist complete? and will explanation LangChain?
thank you very much.
and another question sir
Are there any requirements to understand this content other than Python?

[calebsuh]

Hi Greg, for your transcript txt files, did you manually copy/paste them from youtube? Or did you use something like Whisper to generate them?

I don't believe the youtube api provides timestamps when fetching transcripts...

[photon]

how do you obtain the GPT-4 API? is it not given to only a select few people? Btw, love your content!

[msmmpts]

Hi,

Thanks for this.

Is it possible to make a tutorial on product recommendation through LangChain & OpenAI?

[wiama]

sorry in this exercise how did you get the transcription with timestamp in the first place?

[densonsmith]

When I run this on longer text I get time out errors with gpt-4-0613 but no problems with gpt-3.5-turbo-0613 when I call load_summarize_chain. Is there some maximum time limit?

[michaelabrams]

Do you know if I can get structured data using a gemini model? Seems like langchain only supports interfacing with OpenAI for this specific approach. Not sure if I am missing something

[arslanabid]

can you make a video on how to upload image as well as pdf and text prompts in LangChain ?