A pluggable memory layer for LLM agents with usage verification, contradiction resolution, and multi-tenant access control
Project description
Reconcile
A pluggable memory layer for LLM agents that fixes a gap in every major alternative (Mem0, Letta/MemGPT, Zep): none of them verify that a fact retrieved and injected into an agent's context was actually used. This does.
What it does
- Write-time contradiction resolution — a new fact about the same (tenant, subject, predicate) supersedes the old one instead of both floating in the store forever. O(1) via an index, not a linear scan.
- Hybrid retrieval — TF-IDF similarity + subject-match bonus, scoped per tenant.
- Usage verification — after a fact is injected into an agent's context, checks whether the response actually reflects it (not just whether the right words appear, but whether they're framed as current state vs. a suggestion, with an optional semantic-similarity fallback for paraphrases).
- Multi-tenant access control —
TenantScopedStoreenforces caller→tenant authorization, not just a partition key. - Rule-based extraction — a regex fallback for turning raw text into facts when no LLM is available (explicitly not a replacement for one).
- Thread-safe writes — a lock around the contradiction-check-and-write.
Status
65/65 tests passing. This is a validated prototype, not a production
system — every known limitation is documented in STRESS_TEST_SUMMARY.md,
SCALE_NOTES.md, and PARAPHRASE_CALIBRATION.md, and several tests
exist specifically to pin known gaps rather than hide them (search test
files for known_gap / known_limitation).
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