A next-generation AI intelligent memory system inspired by biological cognition, integrating Neo4j graph storage, Lucene+BERT hybrid retrieval, and dynamic forgetting mechanisms with 92% retrieval accuracy, solving LLM long-term memory loss and multi-agent collaboration gaps.
Real long-term memory for AI agents with cognitive-science-inspired five-sector memory model and temporal knowledge graphs, featuring memory decay, reinforcement, and explainable retrieval.
A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
An agent memory system with biomimetic architecture that enables AI to learn from experience via reflection, featuring multi-strategy retrieval and top performance on LongMemEval benchmark, released under MIT license.
Enterprise-grade RAG Agent platform built on Java 17 + Spring Boot 3 + React 18, featuring multi-channel retrieval, intent recognition, conversation memory, model fault tolerance, and MCP tool integration.
An open-source collection of tutorials and runnable scripts for over 30 advanced Retrieval-Augmented Generation (RAG) techniques, including Graph RAG, Agentic RAG, and various retrieval optimization strategies, implemented primarily with LangChain.
A comprehensive AI engineering hub featuring 93+ production-ready projects with in-depth tutorials and implementations for LLMs, RAGs, AI Agents, and MCP, covering beginner to advanced skill levels.
A Pokémon-themed intelligent chat assistant powered by LangGraph multi-agent orchestration and GraphRAG technologies. Integrates Neo4j knowledge graph, Milvus vector search, and multi-source hybrid retrieval for precise Q&A with complex relationship reasoning. Also serves as a transferable template for domain-specific knowledge systems.
Page 1 / 1 · 8 total
Get the latest AI tools and trends delivered straight to your inbox. No spam, just intelligence.
