LangChain Crash Course: Build a AutoGPT app in 25 minutes! 

The pace of this video is perfect. You gave a pace that was fast enough to cover a lot of ground in a short period of time for the "watch through" understanding, but not so crazy that it is difficult to pause when you're trying to follow along with code. This was the first of your videos I watched, and it had me checking out some of your older stuff. Your older stuff definitely isn't to this same level, but it all seems like things where you've improved over time. I've subscribed, and I'm looking forward to future videos.

Nic is one of the best youtube tutors out there. i really enjoyed the video just as I like his other videos. It's always remarkable that he teaches such topics with such great ease and understandability, which speak volumes about his skills and knowledge on the subject matter. Thnx Nic

I have been fighting for weeks just for a simple script like this as my entry point to this tech. Now I can move past this obstacle and onto greater days! Thanks. I learned some coding about 30 years ago so I am learning everything as new again. Happy days!

This is super cool. Recently I read entire documentation of LangChain and I can say you literally covered important things in good details.

Amazing video and love that you provided the code. This is the furthest I've gotten beyond standard ChatGPT capabilities and since it's mostly one script done in Python instead of Google Collab or Jupter, even better for my local use case. Instant Subscribe and can't wait to see what else you do with LLMs and Langchain.

I think this is my favorite tutorial on all RU-vid. Superb work! Thank you!!

Love your teaching style! I think a quick recap at the end, going through what everything does would be beneficial.

❤Hey, Nick. Definitely, one of the best tutorials of LangChain! Better than some paid courses! 🎉 Thank you 🙏 As I’m not so versed in Python, I slowed it down to 0.75 speed😂

Seriously such an awesome video. I am glad you didn't stop when the timer did!

@nicholas it’s been over 12 years since I’ve coded. I never coded in Python but this video inspired me to get back in and I was able to build your tutorial from scratch! Thank you! 👏🏾

I spent a few hours with you this morning writing my first script. Your script, though I didn't realize you'd be chopping and changing stuff everywhere. I got it in the end and learned lots. Cheers mate

That was really interesting to see how to put the pieces together. Your vid gave me a deeper appreciation for how they come together and what they're capable of. Thank you!

Great video - as usual! It is mind blowing how python libraries are so powerful - that we can do so amazing POC applications in about 30mins where it would take week of teams work couple years ago... not even talking about NLP part... Thanks for sharing and motivating me to try it out for some weekend projects!

Thank you for the step by step tutorial, as someone who is learning to code this is a highly valuable resource. Please create more content like this relating to AI.

Thankkkkssssss !! I was looking that tool inside a lot of LLM github projects but not understanding exactly doing what!! Everything makes sense now!!

Waiting for video on indexes , superb video buddy keep bringing awesome content like this and if possible just take your time and don't rush on topics so that more people can understand well, rest upto you :-)

I'm a absolute noob in coding but you really bring light in the darkness of this world, I just join your course, thank you so much bro!!

Excellent video! Very helpful and love how it's structured. Thanks so much for making it!

Hey Nicholas, super and clear I really like your videos, and easy to understand the logic behind them. Thank you so much!

im a complete beginner with langchain and this was the perfect intro! please keep it coming! 🔥

Great work Nicolas, very clear explanation and easy to follow.

Great video! I just discovered your channel! Please continue more work like this, because you're approach is very easy to follow and extremely concise!

Amazing video, everything was well explained and the result was awesome, thank you so much!

Ive watched many of your videos now and i gotta say you are a great teacher and im so glad you do these videos :) big thank you and greetings from germany! I Learned so much valuable Information i cant thank you enough :))))

I'd love to see a video on indexes! I think thats a very powerful tool for integrating LLMs into an existing data-based application

Amazing video! Thanks you so much Nicholas.

Some constructive feedback: would love to see an example of the app in action before you dive into building the code for it. Video jumps straight to code before we really know what for. That being said, the setting a 15 minute timer and then speaking quickly to respect time is a phenomenal touch (something I’ve never seen done before). Well done man, thanks for the video

This is great, still trying to understand embeddings and indexes, so yes, please do a video on them!

Awesome crash course! Thanks so much!🙏🏾✌🏿🔥🏆

so cool, so clear! thank you a lot! looking forward to your indexes video~

Just found your videos, finding them so beneficial, I’ve subbed my friend, looking forward to diving into your content

Another great video 🙏 ! In a future video can you expand on showing how to incorporate other AI API services? You touched on this subject briefly in previous videos on how each AI system API can leverage on one each other to produce the best results. Seems like LangChain NeuralSeek would be perfect for this. Maybe a LC and NS combo vide?

Beautiful, thanks! Can you do a video on CGPT connection to outside applications, like vscode, word, excel, etc? Similar to what AutoGPT is doing

Awesome, thanks. As a beginner in python, this was super helpful.

Wonderful Tutorial! Clear and concise. Gg as always Nick 🤞. Waiting for more LLM content.

This is one of the best videos to understand Langchain, It was perfect for me, thanks.

Just found your channel. Epic content brother. Thanks for taking the time to share! Can you show how us how we would actually upload something like this to a website (as opposed to being on your localhost)?

This is really incredible. Amazing work. Super simple to follow along with! I’m going to do this tutorial after work

Fantastic video. If you decide to do a follow on video, I'd like to see the next step being using vector databases/stores and creating a ChatGPT web app that can answer questions from a collection of PDF or Microsoft Word or HTML documents. i.e. Summarize documents , rewrite documents, or answer questions based on the contents of documents.

You prompted the script chain with the prompt again rather than the output from the title chain. Very interesting stuff, thanks for the information.

Simply awesome. Thanks for making this.

Excellent job and very useful. Thank you! Liked and subscribed.

More video about langchain. You have explained the best out of everyone on RU-vid, cheers mate

Omg this was exactly what I was looking for. More please :)

Thank you for the really amazing video. I would love to see a video about indexes in LangChain too! It must be a very powerful tool right now.

Wow, this is amazing! Save tons of time and easy to understand. Well done Nicholas!

Beautiful! Thank you!🌞

Awesome content. Definitelly interested on the indexing.

You are awesome. Thank you. Love the little cuts and analogies. Well done mate.

Great video I followed step by step and it was really helpful in understanding how to develop with Langchain. Did you do a video about indexes?

Hi Nicholas, I am restarting my development journey after a decade.. Your videos are really inspirational and easy to follow, thanks for this. I had one query, how do I import the langchain documentation in VSCODE so that it auto completes python imports and code?

Damn, another video in my todo list. Awesome crash course guide!

Can you do a video on GPT index and the difference with LangChain?Or how to integrate the two frameworks.

I have no clue about programming but i learned quite a few things from this video so thank you very much!

Amazing Video as usual man, really loved to see this and understand how you can do amazing stuff with LangChain. However, the title is a little misleading as I thought it would actually be related to the AutoGPT repo and using langchain with that. Would love to see more though on langchain, especially indexes

Not sure if the pace or how well you discuss the why of things but i finally get it as a non dev person

Amazing content. Just subscribed. Best wishes from New Delhi, India

Amazing! Thank you for awesome tutorial

Wow!! Really Good Explaining, Very interested learn more about it

Thanks a lot! It's much simpler than I thought ;)

Just amazing!! Loved this video. Quick question - how would you change the code if say the prompts are in a file? Instead of having to write a prompt every time, I would like to add the prompts to a file, have the app read the prompts from the file and run in the background. How can I reuse the code to do that? Again, thanks for the great video!

Fantastic presentation, so pleased with how you spelled it out for me. I've been scratching my head a little bit with Langchain these past couple of weeks!

Hey Nick, can you make a playlist of best practices for prompt engineering?

So rad! Thank you!!

Amazing tutorial... thank you for sharing with us

excellent tutorial. Thank you!

Fantastic video as per usual!

Really great..surely need video on index

really enjoy your videos! great content =)

Would love to see indexes. Possibly larger memories like a couple of philosophy books and semantic search. Associating some context to user input and answering some cool questions. SocratesGPT?

Dope video! Thanks for keeping it quick and spicy, I learned heaps mate I'm curious about indexes but not sure the value add? I'm excited to build an app to simplify nutrition tracking using cronometer. It's a pain to type everything in all the time and figure out measurements. I'd love the leverage this to do that for me

Great work thanks for the course

As always the best crash courses ! 💪🏻

Hi Nicholas ! Can you make a video about application of deep learning on medicine ( like how to create a cure for diseases etc ) Thanks 😊

Amazing! Best 27mins

excellent. great job man

Excellent video and walk through.👍

Thank you for this great video!

Hi bro! This video is amazing! Could you create an indexes video to keep learning? Great Job!!!!

Thank you very much for your sharing, it has given me a lot of inspiration. I am currently preparing a programming assistant for a software. I have prepared 10 sample programs and stored them in a JSON file. I hope that users can ask questions using the chatbot and get relevant responses. However, I am facing several issues at the moment: 1. I am struggling with how to upload the JSON file to Vetor Store. Currently, my approach is to convert the JSON into a CSV file, but this method is not yielding satisfactory results compared to directly uploading the JSON file using relevanceai. 2. In my own setup, I am using openai's GPT3.5 along with Pinecone and openai embedding. These configurations are similar to relevanceai except for Pinecone. Should I consider switching to another vector store?

Thanks man great and practical video, nice job. Does llm transform wikipedia research somehow or it just pure text from wikipedia in the wikipedia section output?

Really nice video. Subscribed. ❤

Hi. Enjoying your presentation style but a bit over my head at this point. Couple questions. Can you recommend a learning path to get to here from a decent understanding of basic Python? 2. I would like to develop an AutoGPT (agent?) that can generate a spreadsheet with the contact information for every dementia care facility in Canada. How would you go about doing that? I'm envisioning an autoGPT agent that scrapes Google results for each zip code in Canada. Anyway, anything that can get me moving in the right direction would be great. Thanks.

Thanks for awesome tut!!!

Please do make video on the indexes as well. Thank you so much for this video too.

Fantastic presentation!

Hey, would it also be possibel to adjust the prompt to something like "create a youtube title and a fitting sctript for {input}" instead of using a sequential chain? If yes why would you still use a sequential chain, is it cheaper or more efficient or whats the point? Thanks in advance.

Hi Nicholas, this was great 😃

Curious about maintaining confidentiality though with the autogpt stuff. My main concern with using gpt for anything serious is leaving any potentially sensitive information while working on creative projects or research projects. I you could adopt this to work with more localized models, but most of us don't have machines capable of that even with these 3rd party llms.

I love the way you explain everything, Just the a question though is there a way to display full script, I have been going over this video for 2 days, the output is displayed on half, and some of them stopped in between a sentence. Is there any way to overcome this? Thanks for your help.

Hi Nicholas, this was great 😃 I am looking forward to eleminate OpenAI dependency and use llamacpp bindings for local. There are few documentation errors of langchain otherwise I am almost there.

Wow your teaching skills are amazing

Great video. Thanks.

Thanks for posting this video, was great and really liked how you iterated on concepts (from easy to more complex). I added this line and it seems to help with the script getting cut-off. llm = OpenAI(max_tokens=1024)

This is amazing ! thank you for the video ! i was wondering if this can be also a solution to create reports out of an excel file following previous reports in a form of PDF if so how ? thank you !

finally I see a video about langchain straight to the point!

How do you think we should approach combining unnecessary chains. For example, in this case title and script both could be asked in only 1 api call but it would be much messier to work with. Do you think we should go for cost efficency or deal with chain combining after we get the whole script working, or not do it at all.

Great video, langchain appears to be the solution to a LOT of the issues I'm currently facing. I definitely want to see a video with the indexes!

We got issue about information security and can't use openAI service. Can you advise some open source models to replace OpenAI but have acceptable accuracy? We tried LLaMA, Vicuna, Koala but they are not good enough

@12:22 in the script_template we define the input prompt as title. This title is the output of the title_template. But, I don't see this being defined. I mean, we haven't explicity said that the output of script_template is title. So then, how does the script_template figure that out?