SimpleMem / EvolveMem Model Card
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SimpleMem / EvolveMem Model Card
| Field | Value |
|---|---|
| Repository | aiming-lab/SimpleMem |
| Category | Self-Evolving Agent Memory Stack |
| Stars / forks snapshot | 3400 / 347 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/aiming-lab_simplemem.md |
| Updated by | hourly public metadata update, 2026-05-24 |
1. Role in Self Evolve
SimpleMem 把文本、多模态记忆和 EvolveMem 自进化检索放入同一 Python 包，用压缩记忆、意图检索规划和 AutoResearch 式优化循环提升 agent memory 的质量与成本表现。
2. Working Principle
dialogue/media stream -> compressed memory units -> intent-aware retrieval -> EvolveMem optimize loop -> guarded config update
3. Evidence Path
web GitHub page observed MIT license, Python primary language, SimpleMem/Omni-SimpleMem/EvolveMem stack, v0.3.0 release on 2026-05-21, 3.4k stars and 347 forks. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the current snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Self-Evolving Agent Memory Stack in the raw -> classification -> project card -> site/report pipeline. The reading path is: raw capture -> classification row -> public site card -> project report -> aggregate GitHub analysis.
5. Limits
当前未克隆源码，未运行 benchmark、SDK examples、skill install flows 或 memory experiments；star/fork/commit 快照来自公开 GitHub 页面文本或可见页面片段。