I'm just a product manager who knows only a little bit about writing codes, but this video made it really easy to understand the high level concept and get the hang of lang chain. Big shoutout from Japan🍣
Thank you for this really helpful tutorial! It has helped me discover many things to which I was previously unaware of. No more doing things in an amateur way haha!😄
You Good sir are not a Guy who talks the talk. I learnt more about Langchain from you in this half hour than anybody else I have listened to on the last 3months. The veritable quarter to be exact. You are a Guy who walks the walk 🫡
Yesterday I finally had a breakthrough and am beginning to understand the things that I see and read. I just hope that I don't have to use API keys as I want EVERYTHING local until I want to access the 'net for more information. I am building a fairly comprehensive application that not only will order groceries but will also perform local actions. What a time to be alive.
Thanks again, Greg! This video on LangChain concepts was really helpful after watching your LangChain intro. Learning about schemas, models, prompts, etc. is giving me a much better understanding of how LangChain works. Onward to the next video in your playlist!
I've watched 4 of your videos now, and the "set" and video quality have incrementally improved. I appreciate you putting in the effort to make your videos better. I look forward to watching and learning from your future videos!
this is awesome. as someone who fails with some silly error everytime they try coding, this is the first time i've been able to fluently follow through a tutorial without hiccups. big kudos to you and great work with your explanations. excited to work through your series
Very nice intro, thank you Greg. A good starting point to dig in deeper. Now looking forward to the second part with some use cases and then stop watching videos and get the hands on it. But rest assured, I will sure come back for more videos later. Love your work, please keep it going. Greetings and be well, sir.
I will write the comment on this video but thanks too much for ALL the videos, code and your explanations. Keep going please, you have talent for this! waiting for new lessons sir!
I guess we can run it through your cookbook too right? If yes, how would integrating it into my website work? Can we also copy it's code exactly for our initial templates?
@@DataIndependent Hi Greg, I'm a web developer. Recently I tried openai's whisper to do subtitles and I'm amazed by its accuracy. I've also been curious about what Langchain is and how it can used. you offered a great explanation. 🙏
Took me a while to realize the parsing is done by the llm and all you're doing is giving it instructions on how to parse. In hindsight, it's obvious that's what would be done but I'm still amazed and surprised all at once.
It has become very difficult to keep up with the ML/DL/AI scene as of lately, so I decided to go with Lang ⛓️, and your video has been the best I've seen so far. Thank you for your effort.
Amazing job explaining the core concepts, this video + the cook book are THE fast references to understand more and memorize less and practice and develop even more. Thanks a million sir
This is really helpful. With the order that those concepts are introduced with the great examples, I found everything in the langchain documentation become much easier to follow now. I now know what to look at for each of the ideas I have. Thank you!
Thank you so much for making this so easy to follow and understand. As someone who has been out of the coding game for 15 years, I really struggled with some of the content from others where the assumed knowledge and terminology is so much higher. Keep up the good work :)
@@DataIndependent An app that helps users draft a specific type form of words. I'd like to use an agent that will follow a general process to gather information, then evaluate whether it has enough to draft the text against specific criteria, and ask for more if not. Once it thinks it has enough, it will draft the form of words. Evaluation seems tricky though!
Thank you for this amazingly helpful overview! Lucky to have this as my intro to GPT world. I have a question regarding splitters and embeddings. I'm working on an application that stores chat history of coaches with their clients and allows quickly find the references from the previous conversations with the user. Let's say he mentioned his dog, so instead of scrolling the chart and trying to find his dog's name and type, I can simply ask GPT and get the name. Would you rather save each message as a different doc/embedding or the whole conversation as one doc?
Not everyone needed it, it's a tough balance to know what set up steps to include or not. Ex: Do I include a link to jupyter notebook installation too?
If I may make a suggestion, for complete noobs tell them how to or where they can get info on how to run the Python Notebook, that took me a while to figure out, the rest of your stuff was spot on, well done!
You explain stuff very well and your voice is quite pleasant. Investing in learning LangChain right now seems to be a wise move for many. It may become something like Docker or Ansible for AI in the future.
Excellent, clear video, inspired me to check out more of your content - cheers! On an aside, anyone ever mentioned that you kinda look like Dennis from Always Sunny? 😅
Hi in the past few weeks I realized that Langchain is the way to go, I am very encouraged to follow you and I have just subbed from your channel. The question is how do I apply this to try?
Excellent instruction! You've made what could be a complex topic, very simple. Hope you can do a video on embedding and the various use cases. Thank you for the excellent presentation in this video.
Thanks for great overview. Even as a dev myself I find the docs are dooing a poor job of explaining what is for what and why. You did incredible job at this. Thanks!
Hey there! These are amazing, I've been intrigued with Langchain but didn't know how to start, so really grateful for your videos! One question regarding the chat history around 7:30. If you send in chat history so the AI has memory (human: "says this", AI: "says that"), wouldn't each additional "human say, AI say" prompt line increase the amount of tokens and cost? If I had a 2 hour long convo with an AI, each response would be thousands of tokens and really expensive. Is there a workaround for AI memory that's more scalable and efficient?
I need this answered as well. That said, I can't imagine anyone having two hour long chats with an AI with messages flying back and forth throughout (unless it is a therapy session, maybe?). If your AI agent can't answer something quickly, maybe something needs to change in how you have set everything up.
Thanks a lot for making this! I love that you just went through the notebook, giving us clear and concise overviews of each step.
Wow this is so cool! Love the tip, I hardly get them.
Thank you!
As usual, very lucid and high quality content. I think I should embed the youtube transcripts and prompt gpt to 'explain it like data independent'. 😂
Nice! That's fun thank you
This should be a college lecture for all CS students since 2023.
Wow that is an awesome compliment thank you
Okay beta
there won't be a need for a CS degree by 2025...
even in the data science field...
Huh? What's college?
@@greendsnowvery true I didn’t get a degree and I’m working in the CS field. Not easy though
Thank you, I learned so much reading your Cookbook.
Oh heck ya! This is my 2nd tip ever. Love it.
Reach out if you have any questions
I'm just a product manager who knows only a little bit about writing codes, but this video made it really easy to understand the high level concept and get the hang of lang chain.
Big shoutout from Japan🍣
Where has this channel been all this while? This is gold. Thanks for the great video!
Thank you for this really helpful tutorial! It has helped me discover many things to which I was previously unaware of. No more doing things in an amateur way haha!😄
Nice! This notebook needs updating forsure
Great, correct, incisive, ultimate pragmatic video explanation, completely zero-based social science students eager to listen
Nice! Thanks
What is abundantly evident is that you, @DataIndependent, are an excellent teacher🙏.
nice! thank you Krbabu that's nice
I can't appreciate this video or this playlist more. This work is a masterpiece. Thank you!!
I have started using Langchain. The video is what I need. Thank you.
You Good sir are not a Guy who talks the talk. I learnt more about Langchain from you in this half hour than anybody else I have listened to on the last 3months. The veritable quarter to be exact. You are a Guy who walks the walk 🫡
Yesterday I finally had a breakthrough and am beginning to understand the things that I see and read. I just hope that I don't have to use API keys as I want EVERYTHING local until I want to access the 'net for more information. I am building a fairly comprehensive application that not only will order groceries but will also perform local actions. What a time to be alive.
Thanks again, Greg! This video on LangChain concepts was really helpful after watching your LangChain intro. Learning about schemas, models, prompts, etc. is giving me a much better understanding of how LangChain works. Onward to the next video in your playlist!
This is super high-quality content. Well done man!
Glad you enjoy it!
I've watched 4 of your videos now, and the "set" and video quality have incrementally improved. I appreciate you putting in the effort to make your videos better. I look forward to watching and learning from your future videos!
I’m amazed how dense and well indexed this video and document is
Nice! Thank you
In just a few minutes, I became a really big fan! Thank you for your videos!
Nice! Thank you Gabriel
Best langchain explanation I have seen so far. Fast paced. Brilliant.
this is awesome. as someone who fails with some silly error everytime they try coding, this is the first time i've been able to fluently follow through a tutorial without hiccups. big kudos to you and great work with your explanations. excited to work through your series
You used the colab notebook to follow the code?
Very nice intro, thank you Greg. A good starting point to dig in deeper. Now looking forward to the second part with some use cases and then stop watching videos and get the hands on it. But rest assured, I will sure come back for more videos later. Love your work, please keep it going. Greetings and be well, sir.
I love the support! Thank you Markus
I had zero knowledge about it and was struggle to understand it. now I have fairly good idea that Langchain is and what it can do with. thanks a lot.
I will write the comment on this video but thanks too much for ALL the videos, code and your explanations. Keep going please, you have talent for this! waiting for new lessons sir!
Awesome, thanks you Rocio
One of the best and concise summary on the core concepts of LangChain. I highly recommend it. Thank you.
Literally amazed at how easily you went through such complex concepts.
Nice and inspiring examples, good job!
With this attitude your channel will be a start in the upcoming months/years.Keep up the great work..
Nice thank you!
I am amazed at how well you explained these concepts 🤯Keen to read your newsletters!
Love it! Thank you!
Finally found the clear and intuitive lecture on how to smart use of LLMs by langchain and other search tools. Thank you so much.
Nice! Thank you
Wow. The power and possibilities are endless! I hooked already.
Dude finding this video was one of the best things that happened to me in life
I guess we can run it through your cookbook too right? If yes, how would integrating it into my website work? Can we also copy it's code exactly for our initial templates?
Best video I followed all way long. Thanks Greg. This is Quality content!
Glad you enjoyed it! What're you building
The best explanation I have found on TH-cam , thank you!
Awesome thanks Hoyin - what're you working on?
@@DataIndependent Hi Greg, I'm a web developer. Recently I tried openai's whisper to do subtitles and I'm amazed by its accuracy.
I've also been curious about what Langchain is and how it can used. you offered a great explanation. 🙏
Took me a while to realize the parsing is done by the llm and all you're doing is giving it instructions on how to parse. In hindsight, it's obvious that's what would be done but I'm still amazed and surprised all at once.
Thank you - I am a development editor, and I built a little tool to help ask questions of the first draft text I am sent from what I learnt from you.
Nice!
Hello Rob. Do you have a demo reel of your project?
It has become very difficult to keep up with the ML/DL/AI scene as of lately, so I decided to go with Lang ⛓️, and your video has been the best I've seen so far. Thank you for your effort.
High level/big picture explanations like this are very useful to some of us. Thank you
Nice! Glad it worked out
Fantastic video. I learned a ton in 60 minutes, by watching this video
Looking forward to watch the rest as well
Nice! Glad to hear it Prasanna!
Your way of explaining is just flawless. Really helpful material, provided in a perfect manner. Congrats!
Nice! Thank you and glad to hear it
This is indeed a Cookbook, very good job, eagerly waiting for the use cases video, thank you!
Glad you liked it!
Thanks a lot Greg Kamradt for this video, It made me understand very clearly LangChain's coponents.
Loving the new look bro! Great upgrade and as usual great conent
Nice! Thank you very much. It was time to take AI more seriously.
I'm about to rebrand data indy to my personal brand as well.
Greg, thanks for so generously sharing your knowledge! I like the new navy paint on the walls in your room. 👍🏻
Thank you! it was time for an upgrade
Too relaxing to learn with you!! The way you communicate is very nice and clear, thank you
Thanks for the kind comments!
All of a sudden, I liked this course. Great content.
Amazing job explaining the core concepts, this video + the cook book are THE fast references to understand more and memorize less and practice and develop even more. Thanks a million sir
Awesome explanation. So clear! I loved that you just went step by step through the notebook.
I am gonna set this up to ask questions about langchain to keep me updated with langchain :D
Greg, thanks for another great video. I've come back to this one a few times to clear my head :)
Good stuff. Even as a developer the concepts of AI are some completely new so thanks for breaking the concepts down into simple language
Thank you for this video! You did an amazing job, learning from which we will also do amazing jobs!
U just blew my mind!!!, jumping into your langchaing guided tour to figure out ways to tame OpenAI 💥
Nice! Thank you
Useful contributions. Thanks your helping the community, Bro!
Nice! Thanks Tim
Great coverage and explanation of Langchain Greg. Thanks for this!
Awesome thank you! What’re you building?
thanks greg, this was very very easy to understand and insightful
Kudos to you reffort on doing this. Very helpful. Thank you
Thank you for your work Greg! Regards from Belgium :)
Great overview Greg! Really enjoyed the examples and the way you broke down the concepts.
Nice!! Thanks man
This is really helpful. With the order that those concepts are introduced with the great examples, I found everything in the langchain documentation become much easier to follow now. I now know what to look at for each of the ideas I have. Thank you!
Nice! glad to hear it.
Amazing and great explanation, Ill try out the cookbook in Git. Thank you
Brilliant! Would love to see you do one on building a personal assistent with LangChain!
Awesome introduction about LangChain, great job!
Dude. Epic💪🏾💪🏾💪🏾💪🏾💪🏾
👏🏾thanks for this Masterclass!
Thank you so much for making this so easy to follow and understand. As someone who has been out of the coding game for 15 years, I really struggled with some of the content from others where the assumed knowledge and terminology is so much higher. Keep up the good work :)
Awesome! Thank you very much - what projects are you working on building?
@@DataIndependent An app that helps users draft a specific type form of words. I'd like to use an agent that will follow a general process to gather information, then evaluate whether it has enough to draft the text against specific criteria, and ask for more if not. Once it thinks it has enough, it will draft the form of words. Evaluation seems tricky though!
Thank you for this amazingly helpful overview! Lucky to have this as my intro to GPT world.
I have a question regarding splitters and embeddings. I'm working on an application that stores chat history of coaches with their clients and allows quickly find the references from the previous conversations with the user. Let's say he mentioned his dog, so instead of scrolling the chart and trying to find his dog's name and type, I can simply ask GPT and get the name. Would you rather save each message as a different doc/embedding or the whole conversation as one doc?
That was a brilliant video. So well described with logical, easily understood examples. Thank you!
Glad it was helpful!
Why not include a cell in the notebook to install langchain and openAI?
Not everyone needed it, it's a tough balance to know what set up steps to include or not. Ex: Do I include a link to jupyter notebook installation too?
Thank you for the great Cookbook!
Nice! Hope it's fun
Just Awesome .. Thanks a lot for making and sharing this video ..
You aced the topic man!. Thanks.
If I may make a suggestion, for complete noobs tell them how to or where they can get info on how to run the Python Notebook, that took me a while to figure out, the rest of your stuff was spot on, well done!
This is awesome !!! Please keep up ! All my support
What an amazing video to walk you through the concepts, as well as practical examples. I recommended my friend to watch it too. 😊
Thank you! I’m going to be doing an update soon. Too much code is out of date.
Yes! Only tutorial that makes any sense. Great job thank you!!
Awesome! Thanks Mel!
amazing playlist...watching it completely for sure
Very impressive communication skills!
Well crafted overview with concrete examples. I'm very experienced in the field, and this taught me quite a bit.
Great thank you George.
What’re you working on or building?
Fantastic tutorial. One of the best I found. Great job! Subscribed
Nice! Thank you
Insanely high quality video. Thanks so much!
Glad you enjoyed it!
awesome video. the concepts are explained clearly!
Love it thank you Vers.
Awesome vid! When can we expect #2?
You explain stuff very well and your voice is quite pleasant. Investing in learning LangChain right now seems to be a wise move for many. It may become something like Docker or Ansible for AI in the future.
Thank you Terry. Yes, learning the frameworks that are being put on top of LLMs will be a good investment.
Excellent, clear video, inspired me to check out more of your content - cheers!
On an aside, anyone ever mentioned that you kinda look like Dennis from Always Sunny? 😅
Extremely concise and no hype and straigh to the point. I LOVE IT!
BRAVO! Clear, concise, and to the point. Thank you.
Hi in the past few weeks I realized that Langchain is the way to go, I am very encouraged to follow you and I have just subbed from your channel. The question is how do I apply this to try?
Excellent instruction! You've made what could be a complex topic, very simple. Hope you can do a video on embedding and the various use cases. Thank you for the excellent presentation in this video.
Awesome thank you!
For embeddings, what is the real world use case you want to explore more?
This is a great presentation. You have a great way of teaching.
Fantastic presentation! This is incredibly useful. Thank you!
Awesome! Thank you
Thanks, this really helped a lot to briefly get an idea what Langchain can do👍
Thanks for great overview. Even as a dev myself I find the docs are dooing a poor job of explaining what is for what and why. You did incredible job at this. Thanks!
Thank you for the guide cookbook! 谢谢你精彩的cookbook！
Awesome! Glad it worked
Spectacular video. Thank you.
Glad you enjoyed it!
Hey there! These are amazing, I've been intrigued with Langchain but didn't know how to start, so really grateful for your videos! One question regarding the chat history around 7:30. If you send in chat history so the AI has memory (human: "says this", AI: "says that"), wouldn't each additional "human say, AI say" prompt line increase the amount of tokens and cost? If I had a 2 hour long convo with an AI, each response would be thousands of tokens and really expensive. Is there a workaround for AI memory that's more scalable and efficient?
I need this answered as well. That said, I can't imagine anyone having two hour long chats with an AI with messages flying back and forth throughout (unless it is a therapy session, maybe?). If your AI agent can't answer something quickly, maybe something needs to change in how you have set everything up.
Yes I would say so. Thats why you should consider using the WindowMemory, or ways to summarise the previous messages.
@DataIndependent I want to know this too, please answer
I just f***** love LangChain it is soooo fun
Nice!! What're you building?
The best overview ever!!
Awesome, thank you!
Thank you very much! This is super helpful for a Langchain Beginner LOL. Looking forward to your use cases!
Thanks Heqing - Working on it
great video! I feel like I have a good understanding of langchain after this and this is my first video ive watched on it :))
Happy to hear that!
Amazing video and 99% of it is still holding up despite OpenAI and LangChain APis evolution
nice! Yes that is good - it's due for an update
This video was a really great beginner overview. Thanks a lot for putting it together. I'm looking forward to part 2.
He got a whole playlist ( 16 episodes ), this one is the 3rd one, you can check it out if you haven't
Big thanks for publishing such great content.