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AI agents with graph-based reasoning memory by Neo4j. Scaffold graph databases in seconds to give agents knowledge-graph-driven memory and reasoning capabilities.
AI agents with graph-based reasoning memory by Neo4j. Scaffold graph databases in seconds to give agents knowledge-graph-driven memory and reasoning capabilities.
A knowledge engine for AI agent memory that builds knowledge graphs and memory layers in 6 lines of code, supporting graph databases, vector stores, and more for knowledge extraction and retrieval.
A graph-native memory system for AI agents backed by Neo4j. Store conversations, build knowledge graphs, and let agents learn from their own reasoning.
An open-source graph-vector database built from scratch in Rust, combining graph database and vector retrieval capabilities to provide AI agents with unified storage for both knowledge graphs and semantic search.
NeurIPS 2024 RAG framework inspired by human long-term memory, combining knowledge graphs with personalized PageRank for continuous knowledge integration in LLMs.