Langchain PDF App (GUI) | Create a ChatGPT For Your PDF in Python

In this project-based tutorial, we will use Langchain to create a ChatGPT for your PDF using Streamlit. We will build an application that allows you to ask questions about a PDF document and get answers directly from an LLM (Large Language Model), like OpenAI's ChatGPT.

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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 and PDF, 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 embeddings for your text using OpenAI's API and 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 with PDF 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!

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⏰ Timestamps
0:00 Introduction
1:48 Setup
6:30 Create GUI
9:33 Read the PDF
12:46 Process Diagram
16:45 Split PDF into chunks
21:22 Create embeddings
24:19 Finish Knowledge Base
26:11 Similarity Search
29:23 Q&A Chain from Langchain
34:37 Monitor Your Costs
38:55 Conclusion

#streamlit #langchain #python #chatgpt #openai

[oicsqys]

Incredible job. Thank you very much for this project. I have no more than 2 weeks learning python and with your help, I was able to complete this project in my free time. Keep the amazing work Sir. Much respect from the Caribbean 🌴

[blackhat]

I built something similar a while back. You should teach people how to store vectors locally. That would drastically reduce the cost.

[jamesallison]

After updating python to the latest version and updating my PyCharm installation, this tutorial ran perfectly. Alejandro is an excellent presenter. Thanks for this terrific tutorial!

[ReddSpark]

Holy smokes - the conciseness of you code given all that it's doing behind the scenes is breathtaking! Impressive!

[Anonymous-lwzy]

Fabulous job! Great use of the diagram to provide the high level view. I like that you kept the code simple and focused on the main objective, and covered each part step-by-step. I also like that you used FAISS, since it is free.

[chiefwiki]

I've watched numerous GPT for PDF YouTube tutorials, but yours stands out for its clarity, conciseness, and thorough explanations. Thanks, Alejandro! I've subscribed and eagerly await more content from you.

[andreyseas]

You are a really good teacher. Love how you explain things step by step without overwhelming. Keep it up!

[michaelcoleman]

Im learning python and i decided to follow along with you here. Amazing! I have less than a few months of experience and I was able to follow along with you. Well done lad!

[seanfeng]

I really appreciate the tiny details and explanations like "since we're using langchain you have to set the variable like this" etc. Very helpful in understanding "why" in addition to "how". Cheers

[homegrwn]

Thank you, thank you, thank you! Your video solidified everything for me. I knew the different pieces, but not how they all meshed together. Now I can finally continue with the project I was working on. Great content. Subscribed.

[newcooldiscoveries]

Never heard about you before Alejandro, but I'm glad you popped up on my Youtube feed. Got to give it to you---your a natural born teacher. Excellent job and very informative. Liked and subscribed.

[ChatGPT-efsr]

Very good content. Taking the time to explain what every component of the code is amazing. I never felt I understand code like this. I am subscribing.

[mjvbhaskar]

Perhaps the best tutorial out there. Maximum value 0 crap. Keep it like this. :)

Good job.

[alexander_adnan]

Thank you man,
I had this project in mind for a while, never had time for it.

[churruwn]

This is an incredible tutorial. I'm not very technical and I was able to follow the entire thing! Thanks for creating it.

[absenteeatom]

Great, this is what I needed to get me going. The best guide I have seen so far. I've been working on the code and can now load multiple files of pdf, docx, txt and html at the same time. I also increased the text box size to allow for follow-on questions. Next I want to integrate something like Pinecone with Chat 'memory'.

[xaviera]

Hi from France 👋
It's the best tutorial on how to create our own PDF GPT.
Thanks a lot.

[rakancon]

Thank you Alejandro for all the efforts and amazing videos you are creating A big thanks from my bottom of my heart ♥

[creeperXjacky]

Deeply appreciate for your sharing !! <333.
You deserved a lot more supports !!

[LucidGR]

One of the best tutorials on the subject! Great job!