LangChain Q&A from YouTube videos or PDF files

This article is a follow-up article to my previous article on YouTube Summarizer. Once you have the summary of the video(s) in a text file, #LangChain and #Python can help you in summarizing the article and even ask for specific details from that text file.

I've split the previous single file created by summarizing the three videos into three separate files, one each for each video. The next solutions can be used to analyze any documents such as white papers, book chapters, or text files as input. For PDF files, you can use #PyPDF2 to create the text file.

i. Summary of the video:

The text file created by analyzing the video https://www.youtube.com/watch?v=b95g5jexiks is summarized using summary_chain option from langchain.chains' AnalyzeDocumentChain functions. Here is the summary of the video:

This article discusses the growing influence of generative AI on the legal industry. It looks at the opportunities and risks associated with the technology, such as IP and bias issues, and suggests that companies should explore it and innovate. It also mentions the need for a user case and problem to be solved before working backwards towards the technology, and the importance of getting content in the right form. Finally, it advises that those who use the technology effectively will be better competitors.

I do notice some grammatical mistakes highlighted by LinkedIn editor, but I'll still post the text as it is.

ii. Asking Questions from the text:

In next example, I've used load_qa_chain from question_answering module of langchain.chains to ask a question from the text file of the video https://www.youtube.com/watch?v=VxJXPWFoYoc.

Question: What were the risks discussed?

Response: ?The risks discussed include copyright law in cultural marketplaces or spaces, free expression and accountability for communications of potentially illegal content, copyrightability of works created with the involvement of AI, potential threats to core civil liberties, control of large tech companies over freedom of expression, a clash with an even larger and more institutionalized set of rights holders, the copyright system needing to incentivize creation by humans, copyright incentives, the monkey selfie case, divine authorship, the use of AI, the use of licensed material, the use of input data, accountability for speech, copyright, authorship, liability for unprotected speech, obscenity, defamation, aiding and abetting law, the right to speak anonymously, regulation of online content, commercial use of works, political satire, copyright infringement, legal attack, commercial survival, the potential for harmful content such as monstrous images, deep fakes, child sexual abuse, and defamatory material, the use of AI models to create pictures of particular politicians or in the style of a particular named artist, reputational and dignitary harms, the potential for AI to take an artist's work and output 100,000 things just like it in no time, and the displacement of painting due to the invention of photography.

It was a long sentence with pretty much all the keywords discussed in that video. You can also create questions and answers from the text input.

Further usage of prompt engineering can generate the response in the following formats:

• Bulleted points
• Short summary
• 2, 3, or 5 paragraphs
• Tones or styles of the output can be changed
• Rhyme (why not?)
• json, csv or other formats

How can a set of similar #GenerativeAI solutions help your businesses? Contact WisdomTooths Consulting Kumar Kushal Manpreet Kaur for details.