The LangChain Cookbook - Beginner Guide To 7 Essential Concepts
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Cookbook Part 2: • The LangChain Cookbook...
Wild Belle - Keep You: open.spotify.com/track/1eREJI...
LangChain Cookbook: github.com/gkamradt/langchain...
LangChain Conceptual Docs: docs.langchain.com/docs/categ...
Python Docs: python.langchain.com/en/latest/
JS/TS Docs: js.langchain.com/docs/
0:00 - Introduction
1:12 - Conceptual Docs
1:54 - Cookbook introduction
2:27 - What is LangChain?
5:10 - Schema (Text, Messages, Documents)
8:54 - Models (Language, Chat, Embeddings)
12:03 - Prompts (Template, Examples, Output Parse)
20:45 - Indexes (Loaders, Splitters, Retrievers, Vectorstores)
26:39 - Memory (Chat History)
28:12 - Chains (Simple, Summarize)
32:52 - Agents (Toolkits, Agents)
Music by lofigenerator.com / CC BY
This is exactly i wanted. Short tutorial which covers all important features of Langchain
Awesome explanation. So clear! I loved that you just went step by step through the notebook.
BRAVO! Clear, concise, and to the point. Thank you.
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 super high-quality content. Well done man!
Glad you enjoy it!
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
One of the best and concise summary on the core concepts of LangChain. I highly recommend it. Thank you.
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!
Beautiful summary! Thanks a lot for sharing it. I'll definitely check out all the documentation but you gave us a very good overview. Thanks for the ramp up!
Nice glad to hear it
That was a brilliant video. So well described with logical, easily understood examples. Thank you!
Glad it was helpful!
Your way of explaining is just flawless. Really helpful material, provided in a perfect manner. Congrats!
Nice! Thank you and glad to hear it
amazing playlist...watching it completely for sure
Great overview Greg! Really enjoyed the examples and the way you broke down the concepts.
Nice!! Thanks man
Too relaxing to learn with you!! The way you communicate is very nice and clear, thank you
Thanks for the kind comments!
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!
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
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.
I am amazed at how well you explained these concepts 🤯Keen to read your newsletters!
Love it! Thank you!
Wow. The power and possibilities are endless! I hooked already.
Literally amazed at how easily you went through such complex concepts. Nice and inspiring examples, good job!
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 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.
Thank you for this concise and understandable introduction of the concepts!
Glad it was helpful!
Thank you so much for the video. It was really very helpful. You explained the concepts very well. 🙏
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
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?
Best video I followed all way long. Thanks Greg. This is Quality content!
Glad you enjoyed it! What're you building
Brilliant! Would love to see you do one on building a personal assistent with LangChain!
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.
High level/big picture explanations like this are very useful to some of us. Thank you
Nice! Glad it worked out
This is a great presentation. You have a great way of teaching.
Thanks a lot Greg Kamradt for this video, It made me understand very clearly LangChain's coponents.
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🍣
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!
Big thanks for publishing such great content.
Useful contributions. Thanks your helping the community, Bro!
Nice! Thanks Tim
Thank you for the guide cookbook! 谢谢你精彩的cookbook!
Awesome! Glad it worked
Kudos to you reffort on doing this. Very helpful. Thank you
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
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!
Spectacular video. Thank you.
Glad you enjoyed it!
Greg, thanks for another great video. I've come back to this one a few times to clear my head :)
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.
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 have started using Langchain. The video is what I need. 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
All of a sudden, I liked this course. Great content.
What is abundantly evident is that you, @DataIndependent, are an excellent teacher🙏.
nice! thank you Krbabu that's nice
Excellent video, and thank you for sharing your wisdom from your perspective, really appreciate it.
Glad it was helpful!
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!
Awesome introduction about LangChain, great job!
Great coverage and explanation of Langchain Greg. Thanks for this!
Awesome thank you! What’re you building?
This is indeed a Cookbook, very good job, eagerly waiting for the use cases video, thank you!
Glad you liked it!
I spent the whole day watching this series. Just as I was about to run out you post this! Haha, thanks :D
Thanks man I'm glad to hear it.
Fantastic presentation! This is incredibly useful. Thank you!
Awesome! 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 :)
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!
In just a few minutes, I became a really big fan! Thank you for your videos!
Nice! Thank you Gabriel
highly appreciate your work 💖
Awesome thank you
Thank you Greg. The video was explained very well
Glad it was helpful!
Great run through. Very helpful!
Glad to hear it!
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.
Best langchain explanation I have seen so far. Fast paced. Brilliant.
Thank you for your work Greg! Regards from Belgium :)
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 awesome !!! Please keep up ! All my support
Thank you for this video! You did an amazing job, learning from which we will also do amazing jobs!
This is a really concise & cool tutorial to start with langchain! Thank you.
Glad it was helpful!
Yes! Only tutorial that makes any sense. Great job thank you!!
Awesome! Thanks Mel!
Dude. Epic💪🏾💪🏾💪🏾💪🏾💪🏾 👏🏾thanks for this Masterclass!
Excellent tutorial, thanks for sharing
The best explanation I have found on KZhead , 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. 🙏
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 tutorial! Thanks!
Awesome thank you! What’re you building or working on right now?
Thanks for sharing this amazing content with us!
You bet! Glad you liked it
Super helpful overview! Thanks
Glad it was helpful!
awesome video. the concepts are explained clearly!
Love it thank you Vers.
Great presentation
You are a great teacher!
With this attitude your channel will be a start in the upcoming months/years.Keep up the great work..
Nice thank you!
Thoroughly enjoyed this! Thank You so much :)
I’m amazed how dense and well indexed this video and document is
Nice! Thank you
Thanks, this really helped a lot to briefly get an idea what Langchain can do👍
great presentation
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
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.
Thank you for the great Cookbook!
Nice! Hope it's fun
Thank you for this, just what I needed.
Glad it was helpful!
Super interesting and thorough - thanks!
Nice! Thank you
You aced the topic man!. Thanks.
Hi Greg, your content is some of the best around the LangChain library, and I believe you’ll grow a lot in the coming months in the YT tech space. I’ve been studying a lot of this new tools in the past month or so, and experimented with a lot of small exercises. Now I’m really putting it all into test in the real world were I’m trying to create something and I would like to have your feedback on this. I'm building a chatbot that helps my users to get informations about a functionality and execute some actions via API... I was thinking to have the GPT-3.5-turbo ChatAPI as "orchestrator", and if the user wants to get informations redirect the request to a query on a vector DB for getting useful chunks of info and feed those to GPT-4 and get an appropriate response to the user question, and if instead the user wants to execute an action, redirect the request to GPT-4 and the LangChain OpenAPI Agent to execute it and return the result to the user. What do you think about this approach? Any suggestions?
I’ve been doing a similar approach in some smaller projects myself recently. I would definitely recommend trying implementing it yourself first before using langchain to see if you really need it. I made my own chatbot and agent classes that essentially do the same, but much less code. Awesome idea though!
Hey! Just seeing this now - comments got crazy for a while. I would check out LangChain's new conversational retrieval agent which should help blog.langchain.dev/conversational-retrieval-agents/ python.langchain.com/docs/use_cases/question_answering/how_to/conversational_retrieval_agents
Thank you. This was very helpful.
Wonderful
Excellent video content, thank you very much!
Thanks Qwerty
@@DataIndependent No worries, cheers!
this video is pure gold, thank you
Glad you enjoyed it!
Absolutely awesome content.
Awesome thank you!
The best overview ever!!
Awesome, thank you!
Super helpful, thank you!
Nice!! Glad to hear it - what’re you building?
Excellent summary!
Glad you liked it!
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?
Thank you so much for this tutorial