← Back to List
⚠
Notice:This resource is provided by a third-party author. Please review the code with AI tools or manually before use to ensure security and compatibility.
Pythonaiming-lab/SimpleMem

SimpleMem

[ICML'26] SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal

62.3/100
★ 3.8KForks: 401
View on GitHub →
Loading report...

Similar Projects

memora

79

Give your AI agents persistent, collective memory — with deduplicating absorb, supersession lineage, semantic search, and a graph UI. Speaks MCP.

Python★ 730

headroom

93

Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

Python★ 74.4K

Memori

90

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

Python★ 17.1K

opensquilla

85

OpenSquilla — Token-Efficient AI Agent with same budget, higher intelligence density

Python★ 7.1K
← Back to List