RASPUTIN Memory Model Card
这是可索引项目报告证据页：它保留 RASPUTIN Memory Model Card 的源材料入口、机制线索和限制提醒；正文仍需 reader/editor 与 academic public-copy review 后才能当作最终结论引用。
RASPUTIN Memory Model Card
| Field | Value |
|---|---|
| Repository | jcartu/rasputin-memory |
| Category | Self-Hosted Agent Memory Backend |
| Stars / forks snapshot | 33 / 5 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/jcartu_rasputin-memory.md |
| Updated by | hourly public metadata update, 2026-05-25 |
1. Role in Self Evolve
RASPUTIN Memory 是面向 OpenClaw 和 Claude Code 的 self-hosted long-term memory backend，包含 fact/window/entity/event lane、hybrid search、Qwen reranker、MCP server 和 LoCoMo 评测记录。
2. Working Principle
conversation windows/facts/entities/events -> hybrid retrieval lanes -> reranker -> reflect/search API -> MCP recall
3. Evidence Path
web GitHub page observed MIT license, Python/JavaScript/Shell stack, 33 stars and 5 forks; README describes persistent conversation memory with LLM fact extraction, four-partition retrieval, Qwen3 reranker, HTTP API, MCP server, 33-question regression corpus and LoCoMo evaluation harness, while explicitly marking several future graph/temporal features as not integrated. 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-Hosted Agent Memory Backend in the raw -> classification -> project card -> site/report pipeline. The key question is whether memory/context evidence improves downstream agent behavior, or only improves retrieval on a local benchmark.
5. Limits
当前未克隆源码，未运行 benchmark、SDK examples、skill install flows、memory experiments、agent evolution loops 或 production deployments；star/fork/commit 快照来自公开 GitHub 页面文本或可见页面片段。