A curated list of retrieval-augmented generation (RAG) in large language models
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Updated
Mar 22, 2024
A curated list of retrieval-augmented generation (RAG) in large language models
Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.
MariHacks Challenge winning project. Linky leverages a RAG AI & a Vector DB to convert your inputted URLs into tokenized inputs allowing you to then treat Linky as a living form of your URL.
Learn how to build agents that can reason over their own documents
End-to-End solution that harnesses the power of documents to provide insightful answers and valuable knowledge to user's query.
Click the link below to checkout the website
The LARGE LANGUAGE MODEL FOR HYDROGEN STORAGE project uses advanced natural language processing to improve research efficiency. It offers concise summaries and answers questions about hydrogen storage research papers, helping users quickly understand key insights and latest advancements.
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