ChatGPT for YOUR OWN PDF files with LangChain

If you're looking to harness the power of large language models for your data, this is the video for you. In this tutorial, you'll discover how to utilize LangChain to extract valuable information from your PDFs, utilizing OpenAI Text Embeddings. Step-by-step, we'll guide you through setting up LangChain to communicate with your PDF files, enabling you to conduct efficient and effective information retrieval. By the end of this video, you'll have the skills you need to leverage advanced language processing technology and elevate your data analysis.

▬▬▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

Links:

#LargeLanguageModel #LangChain #InformationRetrieval #PDF #OpenAITextEmbeddings #StepbyStep #DataAnalysis #LanguageProcessingTechnology #AI #MachineLearning #NaturalLanguageProcessing #NLP #Tutorial #HowTo

[besarthysniu]

Very clear, thorough, well paced and learner-centered. What an amazing educator!

[nickstaresinic]

Well, done. You filled in several important holes in my understanding of how to code something like this for my domain.

[ricksegalCanada]

Excellent video. In three minutes, I learned more about how AI works in general than 100s of other videos. Well done, sir.

[martynas-al]

A very clear explanation. Before this video, I was confused about the purpose of embeddings and how the actual answers are produced and the video explained it very well.

[calabisan]

Great work! Thanks! Works out of the box. Shorter and clearer impossible 🙂

[oryxchannel]

OMG someone took the time to talk about usage costs. No one has yet herded up usage case scenarios in relation to cost from major AI vendors. Thanks for your consideration in this area.

[jrs]

Really interesting and helpful! Thanks for taking the time to put this video together.

[helterK]

Nice work - very clearly explained and you addressed the code fragments really well - look forward to more vids!!

[arthur...barros]

Excellent educator. loved the well paced video. Thanks for sharing your knowledge and findings

[ianabrahams]

Thanks for a very instructive video and learned quite a bit from your step by step guide. Much appreciate the effort you put in & you have inspired me to keep expanding my knowledge in this area. Thank you.

[gybeturkey]

Very well laid out and all answered. Thank you.

[lynnqi]

Your explanation is very clear! Love it! Thank you very much!

[tchrapko]

At this point it doesn't get any easier than that! I was able to drop in a technical document that makes my eyes bleed when I read it and just start asking questions of it instead. Great job! If someone would bundle this up into a nice little application and let me aim it at directories full of documents I think they could make a boatload of money.

[andresmontoya]

Mindblowing! Very clear and your explanation is excellent! Thanks ;)

[AIEinstein]

AWESOME Video! This kind of apps are really good :)) the workflow gets improved too much

[peterthegreat]

Super useful, this is what I have been looking for, ❤ love it!

[port]

It was a very helpful guide. Thanks! Great that I was able to test it quickly thanks to your notebook link.

[JavArButt]

Very nice content - thank you for that introduction

[VastIllumination]

I love you. thank you for making this so easy!

[rolandowise]

Thanks so much, this was very helpful! You mentioned doing a version that can take in multiple files within a folder, what are the changes required? Will the embeddings retain a correlation to the rest of their respective file (e.g. if i ask who are the authors of a particular quote somewhere in the middle of a paper, how will it know that it relates to the names right at the beginning if there are multiple different papers embedded?)