FareedKhan-dev/14-rag-failures
Encountering 14 different Naive RAG fails and using KG to solve it
This project helps anyone working with large language models to overcome common reasoning challenges when trying to get accurate answers from their data. It demonstrates how to move beyond simple keyword matching and instead build a 'knowledge graph' that understands relationships, sequences, and hierarchies. The output is more reliable and nuanced answers from your AI, especially for complex questions, allowing you to build more intelligent applications.
Use this if your AI models struggle with tasks requiring complex reasoning, such as connecting multiple facts, understanding cause and effect, resolving ambiguities, or dealing with contradictory information.
Not ideal if your main goal is basic document retrieval based purely on keyword similarity, or if you prefer a solution that doesn't involve building and traversing structured knowledge graphs.
Stars
21
Forks
13
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 04, 2025
Commits (30d)
0
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