Building RAG Apps: Understanding the Core AI Stack Components

Описание: This video breaks down the essential components of the AI application stack required to build robust Retrieval-Augmented Generation (RAG) applications. Learn how RAG combines Large Language Models (LLMs) with external knowledge retrieval to deliver accurate, grounded, and up-to-date answers. We'll explore each layer of the stack, including:

Large Language Models (LLMs): The core reasoning engine.
Frameworks & Model Access Layers: Simplifying prompt engineering, chaining, and memory.
Databases (Vector & Relational): Efficiently storing and retrieving context.
Data Extraction Tools: Populating your knowledge base from various sources.
Text Embeddings: Converting text into vectors for semantic search.
Discover popular tools and practical examples for each component, along with an overview of how the entire RAG stack works together in a seamless flow. Perfect for developers, AI enthusiasts, and anyone looking to build advanced generative AI applications!
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