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hkevin01 / eeg-rag

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EEG-RAG is a Retrieval-Augmented Generation (RAG) system specifically designed for electroencephalography (EEG) research. It enables researchers, clinicians, and data scientists to ask natural language questions about EEG literature and receive evidence-based answers with proper citations.

gpu-computing lang-python nlp-tools status-experimental ai-ml-portfolio scope-enterprise framework-numpy framework-pandas framework-huggingface framework-pytorch framework-scikit-learn ai-ml-portfolio-rag gpu-deep-learning gpu-rag gpu-nlp gdl-bio-neuro
  • Updated May 19, 2026
  • Python

hkevin01 / vector-index-graph-memory

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This project is a graph-native memory prototype that addresses one of the main weaknesses of a flat vector index: semantic similarity is useful for recall, but it is not a reliable definition of identity. The codebase combines FastAPI, Neo4j 5 vector indexes, a deterministic local embedding service, lightweight entity extraction, and a conservative

gpu-rag
  • Updated May 25, 2026
  • Python

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