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Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization , chatbots , and code analysis .
LangStream enables developers to better work with streaming data sources, using Apache Kafka technology and generative AI to help build event-driven architectures. [25] In November 2023, DataStax announced RAGStack, a simplified commercial offering for RAG (retrieval-augmented generation) based on LangChain and Astra DB vector search. [26]
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition, [2] machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.
Cognitive models of information retrieval rest on the mix of areas such as cognitive science, human-computer interaction, information retrieval, and library science.They describe the relationship between a person's cognitive model of the information sought and the organization of this information in an information system.
In information retrieval and natural language processing reification is the process by which an abstract idea about a person, place or thing, is turned into an explicit data model or other object created in a programming language, such as a feature set of demographic [1] or psychographic [2] attributes or both. By means of reification ...
Learned sparse retrieval or sparse neural search is an approach to Information Retrieval which uses a sparse vector representation of queries and documents. [1] It borrows techniques both from lexical bag-of-words and vector embedding algorithms, and is claimed to perform better than either alone.