GPT-4 Tutorial: How to Chat With Multiple PDF Files (~1000 pages of Tesla's 10-K Annual Reports)

Video Description

In this video we'll learn how to use OpenAI's new GPT-4 api to 'chat' with and analyze multiple PDF files. In this case, I use three 10-k annual reports for Tesla (~1000 PDF pages) OpenAI recently announced GPT-4 (it's most powerful AI) that can process up to 25,000 words – about eight times as many as GPT-3 – process images and handle much more nuanced instructions than GPT-3.5. You'll learn how to use LangChain (a framework that makes it easier to assemble the components to build a chatbot) and Pinecone - a 'vectorstore' to store your documents in number 'vectors'. You'll also learn how to create a frontend chat interface to display the results alongside source documents. A similar process can be applied to other usecases you want to build a chatbot for: PDF's, websites, excel, or other file formats. (Side note: Since the time of recording a newer, up to date version of the video has been recorded here: https://youtu.be/OF6SolDiEwU) Visuals & Code: 🖼 Visual guide download + github repo (this is the base template used for this demo): https://github.com/mayooear/gpt4-pdf-chatbot-langchain/tree/feat/vectordbqa (NOTE: The latest code example is here https://github.com/mayooear/ai-pdf-chatbot-langchain) Books: Learning LangChain (O'Reilly): https://www.oreilly.com/library/view/learning-langchain/9781098167271/ Twitter: https://twitter.com/mayowaoshin Send a tip to support the channel: https://ko-fi.com/mayochatdata Timestamps: 01:02 PDF demo (analysis of 1000-pages of annual reports) 06:01 Visual overview of the multiple pdf chatbot architecture 17:40 Code walkthrough pt.1 25:15 Pinecone dashboard 28:30 Code walkthrough pt.2 #gpt4 #investing #finance #stockmarket #stocks #trading #openai #langchain #chatgpt #langchainjavascript #langchaintypescript #langchaintutorial