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Learn practical strategies for optimizing Retrieval-Augmented Generation (RAG) implementations in this comprehensive webinar featuring host Angel Menendez and expert guest Mary Newhauser. Explore how RAG enhances large language models with custom knowledge through both indexing and inference phases, while understanding when RAG is the appropriate solution and recognizing its limitations. Master chunking strategies that improve retrieval effectiveness and discover how to leverage metadata for enhanced precision and filtering capabilities. Gain insights into selecting the most suitable embedding models and generative models for your specific requirements, and apply advanced prompt engineering techniques to significantly improve output quality. Build and optimize a complete RAG workflow within n8n, featuring vector search integration with Weaviate, providing hands-on experience with real-world implementation scenarios.
