CHATGPT For WEBSITES: Custom ChatBOT: LangChain Tutorial

In this video, we will create a chatbot based on GPT-3 powered Natural Question Answering BOT on any Website using LangChain. We will combine the concepts of Embedding, Information Retrieval and VectorStore to create a powerful information retrieval system for your website.

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Langchain is a powerful open-source Python (and Javascript) framework that allows you to build applications with LLMs and text embeddings. With Langchain, you can easily train GPT on your own data and create a personalized LLM that can answer questions and generate text.

In this tutorial, we will walk you through the process of building an application with Langchain using Streamlit. We will dive into Langchain and its features, including its ability to train GPT on documents and text embeddings.

We will show you how to create a Text Embedding model for your application using Langchain and how to integrate it into your project. You will also learn how to train GPT on PDF documents and fine-tune it to your specific use case.

Throughout the tutorial, we will be building a fully functional application that allows you to upload a PDF file, ask questions about it directly, and have an LLM answer for you. We will use the powerful capabilities of Langchain to create a seamless user experience and showcase the framework's many possibilities.

Langchain is a versatile framework that can be used in many applications, from chatbots to document analysis. We will show you how to leverage Langchain to create powerful applications with Streamlit that can help automate tasks and improve efficiency.

If you're looking to take your natural language processing skills to the next level, this tutorial is a must-watch. Learn how to build powerful applications with Langchain and chat with GPT about your PDF files. So, what are you waiting for? Let's get started with Langchain!

All Interesting Videos:

[saltinejones]

This was a game-changer for me. I'm pretty new to langchain and was having a hard time wrapping my head around it, but your video made everything click. Thanks for sharing your wisdom with the rest of us!

[biraescudero]

My friend, I watch most of your videos and I am learning a lot. Your explanations are CLEAR and you show complex things in a way that any one (even I) can understand without any doubt!!!
Thanks a lot for your work, your videos and patience!
Go on! You make the difference!

[roua.]

Great video, I really appreciate that you kept going back to the diagram while writing the code.

[lucarestagno]

This video explanation is just great.
I was switching between the websites of different products, like LangChain and QDrant, but I was not able to get the overall picture of such a solution.
Thanks for the explanation! It's crystal clear!

[victor-balta]

I was searching or hours for a video like this. Thanks! It's pretty straightforward, and your diagram helps a lot in understanding the concepts

[merneadanfoundation]

Wow, what a clear and concise explanation!!! Thanks for this and keep on giving us this valuable information.

[lovol]

Probably the most clear explanation of this. Thanks. Next up, some UI for it 😊

[JasonFowler]

Thank you for sharing with the world. Your work is packed with information and remains accessible.

[underdog]

Great video, a good follow-up might include how to use agents to enhance the chatbot for sites that also have dynamic content

[automanai]

It is truly amazing. Greetings from China.

[joser]

Very good content as usual, two points in case you can comment or consider for the future:
1. Just on this context of web-sites (there is many more data to consider), there is normally plenty of info in web-sites that is provided as non-text, think of diagrams or screenshots, etc, in fact some websites are strongly supported by this type of "image" support, I guess we will need multi-modal support for this at some point in time (you can also have links to documents or other type of data of course), so asking in case there is anything that could help with this part, for a more comprehensive/relevant scraping of sites.
2. Then the point with secured areas of web-sites, and with this the fact that users may have rights to access parts of a site (or not), think of Confluence web documents that are in private domains with a complex set of access rights, any recommendations as to how to possibly handle this type of data? I guess what I am saying is complex, since we would need to implement Auth access management into what embeddings can be accessed, etc

[MikeBtraveling]

Love your videos, keep up the great work!

[mallikarjunmongolla]

Hi, Thank you for this video. Your explanation is great and really helpful in understanding the concepts.

[carterjames]

Also what are the differences between openAi embedding models and other open source embedding models? Is it just faster or will I get completely different results?

[arpitjain]

How will the implementation shared in Google colab change when new contents appear on the website (like a blog). The entire embedding (training data) needs to be run again and the pickle file regenerated. Is that correct? What approach is better if I want to make a model for changing data (like a blog)

[shaifulislam]

That's really a knowledgable content.

[saatwikkaul]

I'm having a little trouble, at the very last step when the user asks a question I get the error :

InvalidRequestError: This model's maximum context length is 2049 tokens, however you requested 2893 tokens (2637 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.

How can I bypass this?

[aqashatehreem]

Great video. I have been working with langchain for some time now but still this video helped me a lot to fully understand the details. Just one question though! How can we make this work if the data on the website is constantly changing? For example, in the case of an e-commerce website. Do you have any video on that too?

[Luca-twfk]

Cool. Would be fun to make a website where the nav is entirely handled through conversation with Chatbot

[rishabh]

I need to login into the website before getting access to all the urls documents. How do I achieve that using Selenium URL Loader? Or any other way?