Merge branch 'main' of https://github.com/CaviraOSS/OpenMemory

Author: nullure

README.md

@@ -57,10 +57,10 @@ This approach improves recall accuracy while reducing costs.
 | ---------------------------------------- | ----------------------------------------------------------- | ---------------------------------- | ------------------------------- | ----------------------------- | -------------------------- | --------------------------- | --------------------------------------------- |
 | **Open-source License**                  | ✅ MIT (verified)                                           | ✅ Apache 2.0                      | ✅ Source available (GPL-like)  | ✅ Apache 2.0                 | ❌ Closed                  | ✅ Apache 2.0               | ✅ Varies (OSS + Cloud)                       |
 | **Self-hosted / Local**                  | ✅ Full (Local / Docker / MCP) tested ✓                     | ✅ Local + Cloud SDK               | ⚠️ Mostly managed cloud tier    | ✅ Self-hosted ✓              | ❌ No                      | ✅ Yes (in your stack)      | ✅ Chroma / Weaviate ❌ Pinecone (cloud)      |
-| **Per-user namespacing (`user_id`)**     | ✅ Built-in (`user_id` linking added in v0.9.4)             | ✅ Sessions / Users API            | ⚠️ Multi-tenant via API key     | ✅ Explicit `user_id` field ✓ | ❌ Internal only           | ✅ Namespaces via LangGraph | ✅ Collection-per-user schema                 |
+| **Per-user namespacing (`user_id`)**     | ✅ Built-in (`user_id` linking added)             | ✅ Sessions / Users API            | ⚠️ Multi-tenant via API key     | ✅ Explicit `user_id` field ✓ | ❌ Internal only           | ✅ Namespaces via LangGraph | ✅ Collection-per-user schema                 |
 | **Architecture**                         | HSG v3 (Hierarchical Semantic Graph + Decay + Coactivation) | Flat embeddings + Postgres + FAISS | Graph + Embeddings              | Flat vector store             | Proprietary cache          | Context memory utils        | Vector index (ANN)                            |
 | **Avg Response Time (100k nodes)**       | **115 ms avg (measured)**                                   | 310 ms (docs)                      | 200–340 ms (on-prem/cloud)      | ~250 ms                       | 300 ms (observed)          | 200 ms (avg)                | 160 ms (avg)                                  |
-| **Throughput (QPS)**                     | **338 QPS avg (8 workers, P95 203 ms)** ✓                   | ~180 QPS (reported)                | ~220 QPS (on-prem)              | ~150 QPS                      | ~180 QPS                   | ~140 QPS                    | ~250 QPS typical                              |
+| **Throughput (QPS)**                     | **338 QPS avg (8 workers, P95 103 ms)** ✓                   | ~180 QPS (reported)                | ~220 QPS (on-prem)              | ~150 QPS                      | ~180 QPS                   | ~140 QPS                    | ~250 QPS typical                              |
 | **Recall @5 (Accuracy)**                 | **95 % recall (synthetic + hybrid)** ✓                      | 91 %                               | 93 %                            | 88–90 %                       | 90 %                       | Session-only                | 85–90 %                                       |
 | **Decay Stability (5 min cycle)**        | Δ = **+30 % → +56 %** ✓ (convergent decay)                  | TTL expiry only                    | Manual pruning only             | Manual TTL                    | ❌ None                    | ❌ None                     | ❌ None                                       |
 | **Cross-sector Recall Test**             | ✅ Passed ✓ (emotional ↔ semantic 5/5 matches)              | ❌ N/A                             | ⚠️ Keyword-only                 | ❌ N/A                        | ❌ N/A                     | ❌ N/A                      | ❌ N/A                                        |