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Graph-based cognitive agent featuring persistent memory via SurrealDB, utilizing learned attention scoring and cross-encoder reranking for local, high-recall retrieval.
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While the project claims high performance on memory benchmarks (98.2% R@5) and uses a non-standard database (SurrealDB) to avoid API dependency, its age (1 day) and lack of community traction (0 stars) place it in the category of a personal experiment or fresh research release. Furthermore, persistent memory and local RAG are core targets for frontier labs (OpenAI, Google) who are natively integrating these capabilities into model APIs.
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