Memory for ModelScope agents — proposal
Hi! ViBo is a modular memory layer for AI agents (semantic memory, web-search compression, living archive, private execution). It is model-agnostic and works with any Python agent.
Measured on 100K facts:
- 50–150× less memory context (250,000 tokens → 263 per request)
- 96.2% web-search token savings, 99.7% archive savings
- Everything stays local; secrets (L1/L2/L3) never reach the LLM
We'd love to build an official integration for ModelScope agents: a vibo skill/tool that agents can call for persistent memory — vibo find before answering, vibo add after each session.
Available today: npm n8n-nodes-vibo, ClawHub @vnbochkarev-netizen/vibo-memory, GitHub: https://github.com/vnbochkarev-netizen/ViBo-memory
Would you be interested in a ModelScope integration guide or an official adapter? Happy to prepare it. Thanks!
Memory for ModelScope agents — proposal
Hi! ViBo is a modular memory layer for AI agents (semantic memory, web-search compression, living archive, private execution). It is model-agnostic and works with any Python agent.
Measured on 100K facts:
We'd love to build an official integration for ModelScope agents: a
viboskill/tool that agents can call for persistent memory —vibo findbefore answering,vibo addafter each session.Available today: npm
n8n-nodes-vibo, ClawHub@vnbochkarev-netizen/vibo-memory, GitHub: https://github.com/vnbochkarev-netizen/ViBo-memoryWould you be interested in a ModelScope integration guide or an official adapter? Happy to prepare it. Thanks!