#python #knowledge_graph #large_language_model #logical_reasoning #multi_hop_question_answering #trustfulness
KAG (Knowledge Augmented Generation) is a powerful tool that helps computers understand and reason with complex information better. It uses large language models and a special engine to build logical reasoning and question-answering systems, especially in professional domains like medicine or finance. KAG improves upon older methods by reducing errors and noise, and it can handle multiple steps of reasoning and fact-checking.
The benefit to the user is that KAG provides more accurate and reliable answers to complex questions, integrating both structured and unstructured data. This makes it very useful for professionals who need precise information and logical reasoning in their work.
https://github.com/OpenSPG/KAG
KAG (Knowledge Augmented Generation) is a powerful tool that helps computers understand and reason with complex information better. It uses large language models and a special engine to build logical reasoning and question-answering systems, especially in professional domains like medicine or finance. KAG improves upon older methods by reducing errors and noise, and it can handle multiple steps of reasoning and fact-checking.
The benefit to the user is that KAG provides more accurate and reliable answers to complex questions, integrating both structured and unstructured data. This makes it very useful for professionals who need precise information and logical reasoning in their work.
https://github.com/OpenSPG/KAG
GitHub
GitHub - OpenSPG/KAG: KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used…
KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain kno...