tanstack-ai-memory-hindsight

# Hindsight Memory Adapter Hosted `recall`/`save` adapter backed by Hindsight. Hindsight owns extraction and ranking server-side, buckets memory into per-conversation "banks" (`{tenantId|_}__{user}__{threadId}`), and — uniquely — exposes LLM **tools** through `recall` so the model can retain/recall/reflect directly. ## Setup ```ts import { memoryMiddleware } from '@tanstack/ai-memory' import { hindsight } from '@tanstack/ai-memory/hindsight' // Build per request from the server-validated session — never from req.body. function memoryFor(session: { userId: string; threadId: string }) { const memory = hindsight({ user: session.userId }) // baseUrl defaults to HINDSIGHT_URL return memoryMiddleware({ adapter: memory, scope: { threadId: session.threadId, userId: session.userId }, }) } ``` `@vectorize-io/hindsight-client` is an **optional peer dependency**, loaded lazily on first use — install it where you use `hindsight()`. ## Options - `user` — durable user id for the bank key (falls back to `scope.userId`). - `baseUrl` — Hindsight server URL (default `HINDSIGHT_URL` or `http://localhost:8888`). - `budget` — recall budget: `'low' | 'mid' | 'high'` (default `'mid'`). - `onToolRetain` / `onToolRecall` — callbacks fired when the model uses the memory tools. **Scope fields:** bank id is `{tenantId|_}__{user}__{threadId}`. `namespace` is ignored. ## Tools `recall` returns `hindsight_retain`, `hindsight_recall`, and `hindsight_reflect` in its `tools` plus a `toolGuidance` block. `memoryMiddleware` merges them into the run so the model can manage long-term memory itself.