Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela, 2020NeurIPS 2020DOI: 10.48550/arXiv.2005.11401 - Introduces the Retrieval-Augmented Generation (RAG) paradigm, a fundamental technique for grounding LLM responses with external knowledge, directly relevant to the Data Retrieval component.
LangChain Python Documentation, LangChain, 2024 - The official guide for LangChain, a primary framework for building LLM applications, covering prompt management, orchestration, data retrieval, and memory modules.
Prompt Engineering Guide, N/A, 2024 - A comprehensive, community-driven resource detailing various prompt engineering techniques and strategies essential for effective LLM interaction and prompt management.