Agent Skills
› TanStack/ai
› tanstack-ai-memory-in-memory
tanstack-ai-memory-in-memory
GitHub提供 TanStack AI 的内存适配器，适用于本地开发、测试及单进程演示。基于 Map 实现零依赖记忆存储，支持语义嵌入与提取选项，但不适用于多进程或持久化生产环境。
触发场景
需要本地开发调试记忆功能
编写单元测试或集成测试
构建无需持久化的单进程演示
安装
npx skills add TanStack/ai --skill tanstack-ai-memory-in-memory -g -y
SKILL.md
Frontmatter
{
"name": "tanstack-ai-memory-in-memory",
"description": "Use when wiring inMemory() from @tanstack\/ai-memory\/in-memory — explains setup, options (embedder, extract, topK\/minScore), when to pick it (dev\/tests\/single-process demos), and what NOT to use it for (multi-process or persistent)."
}
In-Memory Memory Adapter
Zero-dependency recall/save adapter backed by a Map. Records vanish on process
restart.
When to use it
- Local development.
- Vitest / Playwright tests.
- Single-process demos where users don't need persistence.
When NOT to use it
- Production multi-process deployments — every worker has its own
Map; users get inconsistent memory. - Anything that needs survival across restarts.
For production, use redis() (see the tanstack-ai-memory-redis skill).
Setup
import { memoryMiddleware } from '@tanstack/ai-memory'
import { inMemory } from '@tanstack/ai-memory/in-memory'
const memory = inMemory()
// A static scope is fine for dev/tests; derive it from the session in real apps.
memoryMiddleware({
adapter: memory,
scope: { threadId: 'demo-thread', userId: 'alice' },
})
Options
inMemory(options?) accepts:
topK(default 6),minScore(default 0.15),kinds— recall tuning.embedder: { embed(text): Promise<number[]> }— enable semantic scoring (bothrecallandsaveembed through it).extract(turn, scope)— return derived facts to persist alongside the raw turn (e.g. call an LLM to pull out preferences). Without it,savestores the raw user/assistant messages andrecallscores them lexically + by recency.render(hits)— replace the built-in prompt renderer.
Capacity
The adapter scans every record in a scope per recall. Fine up to ~100k records; beyond
that, switch to Redis.
版本历史
-
645757a
当前 2026-09-22 03:42
修复代码示例的类型检查问题，更新文档以匹配实际 API 暴露的选项和模型 ID。
- 05280a5 2026-07-30 23:52
