Agent SkillsTanStack/ai › tanstack-ai-memory-redis

tanstack-ai-memory-redis

GitHub

为 @tanstack/ai-memory 提供基于 Redis 的生产级记忆适配器,支持 ioredis 和 node-redis。涵盖客户端设置、存储模型(含键结构)、客户端排序逻辑及性能限制(约1万条记录),并包含故障排除指南。

packages/ai-memory/skills/tanstack-ai-memory-redis/SKILL.md TanStack/ai

Trigger Scenarios

需要持久化 AI 记忆数据到 Redis 配置 @tanstack/ai-memory 的 Redis 适配器 解决 Redis 记忆适配器的连接或排序问题

Install

npx skills add TanStack/ai --skill tanstack-ai-memory-redis -g -y
More Options

Non-standard path

npx skills add https://github.com/TanStack/ai/tree/main/packages/ai-memory/skills/tanstack-ai-memory-redis -g -y

Use without installing

npx skills use TanStack/ai@tanstack-ai-memory-redis

指定 Agent (Claude Code)

npx skills add TanStack/ai --skill tanstack-ai-memory-redis -a claude-code -g -y

安装 repo 全部 skill

npx skills add TanStack/ai --all -g -y

预览 repo 内 skill

npx skills add TanStack/ai --list

SKILL.md

Frontmatter
{
    "name": "tanstack-ai-memory-redis",
    "description": "Use when wiring redis() from @tanstack\/ai-memory\/redis in production — covers client setup (ioredis or node-redis via fromNodeRedis), the storage model, client-side ranking limits, and troubleshooting."
}

Redis Memory Adapter

Production-grade recall/save adapter backed by plain Redis (no vector index required). Ranks client-side (lexical + optional cosine + recency + importance).

Setup

Bring your own Redis client. ioredis wires in directly; redis (node-redis v4+) needs a small wrapper.

Option A: ioredis

import Redis from 'ioredis'
import { memoryMiddleware } from '@tanstack/ai-memory'
import { redis } from '@tanstack/ai-memory/redis'

const client = new Redis(process.env.REDIS_URL)
const memory = redis({ redis: client, prefix: 'myapp:memory' })

memoryMiddleware({ adapter: memory, scope })

Option B: redis (node-redis v4+)

import { createClient } from 'redis'
import { memoryMiddleware } from '@tanstack/ai-memory'
import { redis, fromNodeRedis } from '@tanstack/ai-memory/redis'

const client = createClient({ url: process.env.REDIS_URL })
await client.connect()

const memory = redis({
  redis: fromNodeRedis(client),
  prefix: 'myapp:memory',
})

memoryMiddleware({ adapter: memory, scope })

node-redis exposes a camelCase API (sAdd, mGet); fromNodeRedis translates it to the lowercase RedisLike shape. Passing a raw node-redis client without the wrapper throws client.sadd is not a function.

redis() accepts the same topK / minScore / kinds / embedder / extract options as inMemory().

Storage model

{prefix}:record:{id}                                          -> JSON record
{prefix}:index:{tenantId or _}:{userId or _}:{threadId}       -> Set<id>

save writes the record and adds it to the scope's index set; recall loads the set, scores, and renders. Scope values are escaped (:, \, and _) so a delimiter or the unset placeholder inside a dim can't collide two scopes.

Hard cut: there is no dual-read of older index layouts. If you previously wrote under a different shape (e.g. without tenantId), reindex or wipe — old keys are orphaned.

Always pass the same tenantId/userId/threadId on write and read: missing optional dims become _, so omit ≠ "match any".

Ranking limits

Ranking is client-side: recall loads every record for the scope into Node and scores it. Fine up to ~10k records per scope. Beyond that, write a vector-index-aware adapter against the same recall/save contract.

Troubleshooting

  • Records not visible across processes: ensure every process uses the same REDIS_URL and prefix.
  • Malformed JSON rows: a row whose JSON won't parse is skipped on read and left in place (never deleted) — the signal is a one-time console.warn per bad id. Fix or delete the offending {prefix}:record:{id} key to remediate.

Version History

  • 05280a5 Current 2026-07-30 23:52

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Version
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Hash
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Indexed
2026-07-30 23:52

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