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https://github.com/armanjscript/rag-driven-generative-ai

Generative AI has made remarkable strides in creating human-like text, images, and even code. However, traditional models like GPT rely solely on pre-trained knowledge, which can lead to outdated, inaccurate, or hallucinated responses. Retrieval-Augmented Generation (RAG) addresses these limitations. We offer various types of RAG here
https://github.com/armanjscript/rag-driven-generative-ai

cosine-similarity langchain langchain-ollama qwen2-5 spacy spacy-nlp tfidf tfidf-vectorizer wordnet

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Generative AI has made remarkable strides in creating human-like text, images, and even code. However, traditional models like GPT rely solely on pre-trained knowledge, which can lead to outdated, inaccurate, or hallucinated responses. Retrieval-Augmented Generation (RAG) addresses these limitations. We offer various types of RAG here

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