Скачать с ютуб LangChain - Document Analysis & Question Answering with OpenAI | Mukunthan Ragavan в хорошем качестве

LangChain - Document Analysis & Question Answering with OpenAI | Mukunthan Ragavan

This video will explain about "AI-Powered Document Analysis and Question Answering with LangChain and OpenAI" Summary: In this video, we'll delve into the exciting world of document analysis and question answering using cutting-edge technologies. We'll demonstrate how to leverage LangChain, an advanced NLP framework, in conjunction with the powerful OpenAI language model. Our step-by-step guide will show you how to perform text analysis tasks, from loading and transforming documents to embedding text data and retrieving relevant information. Key Points Covered: Introduction to LangChain: We'll introduce you to LangChain, a versatile NLP framework, and its capabilities for handling text data. Document Loading: Learn how to load text documents, such as PDFs or blog posts, into your analysis pipeline. Text Transformation: Discover the importance of text transformation, including chunking and splitting, to prepare your documents for analysis. Text Embedding: Understand the concept of text embedding and witness how LangChain leverages OpenAI embeddings for enhancing document understanding. Building a Text Database: Explore how to create a text database using Chroma to efficiently store and retrieve information from your documents. Question Retrieval: Dive into the world of question retrieval as we showcase how to retrieve relevant documents based on specific queries. Question Answering: Witness the power of question-answering models as we demonstrate how LangChain's RetrievalQA module can answer questions from your text documents. Real-World Example: We'll run a live example of querying the system, asking questions like "Who is Aladdin?" and showcase the AI-generated responses. By the end of this video, you'll have a solid understanding of how to harness LangChain and OpenAI to unlock insights and information from your text documents, making it a valuable resource for researchers, students, and knowledge seekers.