docs(changelog): backfill Python v2.0.18 and TypeScript v3.1.6 SDK entries (#6918)

Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>

docs/changelog/sdk.mdx

@@ -7,6 +7,16 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">
 
+<Update label="2026-08-11" description="v2.0.18">
+
+**Bug Fixes:**
+- **Core:** Percent-escape `%`, `&`, and `=` in `user_id`, `agent_id`, and `run_id` when building the session scope key for the recent-conversation buffer, so the key stays unambiguous for ids containing those characters. Ordinary ids keep their existing key; an id already containing `%`, `&`, or `=` maps to a new key, so its buffer starts empty once and refills on the next `add()`. Stored memories are unaffected ([#6892](https://github.com/mem0ai/mem0/pull/6892))
+- **Vector Stores:** Raise `ValueError` when a PGVector `in`/`nin` filter value is not a list. A string value was previously iterated character by character into the generated `= ANY(...)` array (so `{"user_id": {"in": "alice"}}` matched `a`, `l`, `i`, `c`, `e`), and a non-iterable value raised a bare `TypeError` from deep inside filter building ([#6879](https://github.com/mem0ai/mem0/pull/6879))
+- **Vector Stores:** Reject `index_accuracy=0` in the Oracle AI Vector Search config. The range check sat behind a truthiness test, so `0` skipped validation entirely and was passed through to `WITH TARGET ACCURACY 0` instead of raising ([#6848](https://github.com/mem0ai/mem0/pull/6848))
+- **Vector Stores:** Close the Oracle connection or pool that Mem0 opened when initialization fails. A client version check, a database version check, or a `create_col()` error previously propagated with the connection still open, leaking it for the life of the process. A caller-supplied `client` is left untouched ([#6839](https://github.com/mem0ai/mem0/pull/6839))
+
+</Update>
+
 <Update label="2026-08-05" description="v2.0.17">
 
 **New Features:**
@@ -1196,6 +1206,24 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
 
 <Tab title="TypeScript">
 
+<Update label="2026-08-11" description="v3.1.6">
+
+**New Features:**
+- **Vector Stores:** Add an Oracle AI Vector Search vector store (`oracledb`) to the OSS SDK, with pooled connections, `HNSW`/`IVF` indexes, an optional `indexAccuracy` target, JSON payload filtering, and six selectable distance metrics ([#6690](https://github.com/mem0ai/mem0/pull/6690))
+
+**Bug Fixes:**
+- **Core:** Percent-escape `%`, `&`, and `=` in `userId`, `agentId`, and `runId` when building the session scope key for the recent-conversation buffer, so the key stays unambiguous for ids containing those characters. Ordinary ids keep their existing key; an id already containing `%`, `&`, or `=` maps to a new key, so its buffer starts empty once and refills on the next `add()`. Stored memories are unaffected ([#6892](https://github.com/mem0ai/mem0/pull/6892))
+- **Vector Stores:** Close and clear the Oracle pool that Mem0 created when `initialize()` fails, and reset the cached init promise so the next call retries instead of replaying the rejection forever. A caller-supplied `client` is left untouched ([#6839](https://github.com/mem0ai/mem0/pull/6839))
+- **Vector Stores:** Validate Oracle `insert()` batches before touching the database: `ids` and `payloads` must match `vectors` in length, so a short array can no longer write rows with `undefined` ids or silently drop payloads ([#6839](https://github.com/mem0ai/mem0/pull/6839))
+
+**Improvements:**
+- **Vector Stores:** Cut Oracle round trips. `insert()` now sends the whole batch through one `executeMany()` with explicit `bindDefs` instead of one `INSERT` per vector, `list()` reads the total from a `COUNT(*) OVER ()` window in the same statement instead of issuing a second count query, and an unfiltered `search()` adds the `VECTOR_INDEX_TRANSFORM` hint so the vector index is used ([#6835](https://github.com/mem0ai/mem0/pull/6835))
+
+**Security:**
+- **Dependencies:** Patched 8 high and 18 medium severity dependency vulnerabilities across the pnpm workspace via `pnpm.overrides` (`undici`, `brace-expansion`, `ip-address`) ([#6847](https://github.com/mem0ai/mem0/pull/6847))
+
+</Update>
+
 <Update label="2026-08-05" description="v3.1.5">
 
 **New Features:**
@@ -2815,6 +2843,14 @@ Existing memories written by the previous versions are not rewritten. If your me
 
 <Tab title="n8n">
 
+<Update label="2026-08-05" description="n8n-nodes-mem0 v0.1.3">
+
+**Changes:**
+- **License changed to MIT:** The published `@mem0/n8n-nodes-mem0` package is now MIT (was Apache-2.0). n8n's Creator Portal requires verified community nodes to be MIT, and the failing license check was the blocker for verification. The rest of the mem0 repo stays Apache-2.0 ([#6804](https://github.com/mem0ai/mem0/pull/6804))
+- **Themed icons:** The node and credential icons now declare `{ light, dark }` variants instead of a single icon, clearing the remaining `icon-prefer-themed-variants` warnings from the Creator Portal scan. No functional changes ([#6804](https://github.com/mem0ai/mem0/pull/6804))
+
+</Update>
+
 <Update label="2026-08-04" description="n8n-nodes-mem0 v0.1.2">
 
 **Changes:**

docs/components/vectordbs/dbs/oracledb.mdx

@@ -3,6 +3,8 @@ title: "Oracle AI Vector Search"
 description: "Use Oracle Database AI Vector Search as a vector store in Mem0 for semantic and relational queries."
 ---
 
+{/* Copyright (c) 2026, Oracle and/or its affiliates. */}
+
 [Oracle AI Vector Search](https://www.oracle.com/database/ai-vector-search/) stores embeddings in an Oracle table using the native `VECTOR` data type, so you can combine semantic search over unstructured data with relational queries over business data in a single database.
 
 ### Requirements

docs/components/vectordbs/overview.mdx

@@ -10,7 +10,7 @@ Mem0 includes built-in support for various popular databases. Memory can utilize
 See the list of supported vector databases below.
 
 <Note>
-  The following vector databases are supported in the Python implementation. The TypeScript implementation currently supports Qdrant, Redis, PGVector, Supabase, LangChain, Azure AI Search, Vectorize, Amazon S3 Vectors, Milvus, Neptune Analytics, and an in-memory store.
+  The following vector databases are supported in the Python implementation. The TypeScript implementation currently supports Qdrant, Redis, PGVector, Supabase, LangChain, Oracle AI Vector Search, Azure AI Search, Vectorize, Amazon S3 Vectors, Milvus, Neptune Analytics, and an in-memory store.
 </Note>
 
 <CardGroup cols={3}>

docs/docs.json

@@ -1035,6 +1035,10 @@
       "source": "/features/graph-memory",
       "destination": "/platform/features/graph-memory"
     },
+    {
+      "source": "/open-source/features/graph-memory",
+      "destination": "/platform/features/graph-memory"
+    },
     {
       "source": "/features/:slug",
       "destination": "/platform/features/:slug"

integrations/n8n-nodes-mem0/LICENSE

@@ -1,201 +1,21 @@
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integrations/n8n-nodes-mem0/credentials/Mem0Api.credentials.ts

@@ -11,7 +11,7 @@ export class Mem0Api implements ICredentialType {
 
 	displayName = 'Mem0 API';
 
-	icon: Icon = 'file:mem0.svg';
+	icon: Icon = { light: 'file:mem0.svg', dark: 'file:mem0.svg' };
 
 	documentationUrl = 'https://docs.mem0.ai/platform/quickstart';
 

integrations/n8n-nodes-mem0/nodes/Mem0/Mem0.node.ts

@@ -21,7 +21,7 @@ export class Mem0 implements INodeType {
 	description: INodeTypeDescription = {
 		displayName: 'Mem0',
 		name: 'mem0',
-		icon: 'file:mem0.svg',
+		icon: { light: 'file:mem0.svg', dark: 'file:mem0.svg' },
 		group: ['transform'],
 		version: 1,
 		subtitle: '={{$parameter["operation"] + ": " + $parameter["resource"]}}',

integrations/n8n-nodes-mem0/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/n8n-nodes-mem0",
-  "version": "0.1.2",
+  "version": "0.1.3",
   "description": "n8n community node for Mem0 — the memory layer for AI agents. Add, search, get, update, and delete long-term memories.",
   "keywords": [
     "n8n-community-node-package",
@@ -10,7 +10,7 @@
     "agents",
     "llm"
   ],
-  "license": "Apache-2.0",
+  "license": "MIT",
   "homepage": "https://mem0.ai",
   "author": {
     "name": "Mem0",

integrations/openclaw/package.json

@@ -72,7 +72,7 @@
       "@qdrant/js-client-rest": "^1.18.0",
       "uuid@<11.1.1": ">=11.1.1",
       "esbuild": ">=0.28.1",
-      "undici@<6.27.0": ">=6.27.0 <8.0.0",
+      "undici@<7.29.0": ">=7.29.0 <8.0.0",
       "axios@<1.18.0": ">=1.18.0 <2.0.0",
       "postcss@<8.5.18": ">=8.5.18 <9.0.0",
       "mongoose@>=9.0.0 <9.7.2": ">=9.7.2 <10.0.0"

integrations/openclaw/pnpm-lock.yaml

@@ -13,7 +13,7 @@ overrides:
   '@qdrant/js-client-rest': ^1.18.0
   uuid@<11.1.1: '>=11.1.1'
   esbuild: '>=0.28.1'
-  undici@<6.27.0: '>=6.27.0 <8.0.0'
+  undici@<7.29.0: '>=7.29.0 <8.0.0'
   axios@<1.18.0: '>=1.18.0 <2.0.0'
   postcss@<8.5.18: '>=8.5.18 <9.0.0'
   mongoose@>=9.0.0 <9.7.2: '>=9.7.2 <10.0.0'
@@ -2036,8 +2036,8 @@ packages:
   undici-types@6.21.0:
     resolution: {integrity: sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ==}
 
-  undici@7.28.0:
-    resolution: {integrity: sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==}
+  undici@7.29.0:
+    resolution: {integrity: sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==}
     engines: {node: '>=20.18.1'}
 
   util-deprecate@1.0.2:
@@ -2547,7 +2547,7 @@ snapshots:
     dependencies:
       '@qdrant/openapi-typescript-fetch': 1.2.6
       typescript: 5.9.3
-      undici: 7.28.0
+      undici: 7.29.0
 
   '@qdrant/openapi-typescript-fetch@1.2.6': {}
 
@@ -4121,7 +4121,7 @@ snapshots:
 
   undici-types@6.21.0: {}
 
-  undici@7.28.0: {}
+  undici@7.29.0: {}
 
   util-deprecate@1.0.2: {}
 

integrations/openclaw/pnpm-workspace.yaml

@@ -21,7 +21,7 @@ overrides:
   "@qdrant/js-client-rest": "^1.18.0"
   "uuid@<11.1.1": ">=11.1.1"
   "esbuild": ">=0.28.1"
-  "undici@<6.27.0": ">=6.27.0 <8.0.0"
+  "undici@<7.29.0": ">=7.29.0 <8.0.0"
   "axios@<1.18.0": ">=1.18.0 <2.0.0"
   "postcss@<8.5.18": ">=8.5.18 <9.0.0"
   "mongoose@>=9.0.0 <9.7.2": ">=9.7.2 <10.0.0"

integrations/pi-agent-plugin/package.json

@@ -73,8 +73,8 @@
       "form-data@<4.0.6": ">=4.0.6",
       "uuid@<11.1.1": ">=11.1.1",
       "esbuild": ">=0.28.1",
-      "undici@<6.27.0": ">=6.27.0 <8.0.0",
-      "undici@>=8.0.0 <8.5.0": ">=8.5.0",
+      "undici@<7.29.0": ">=7.29.0 <8.0.0",
+      "undici@>=8.0.0 <8.9.0": ">=8.9.0 <9.0.0",
       "axios@<1.18.0": ">=1.18.0 <2.0.0",
       "brace-expansion@>=3.0.0 <5.0.8": ">=5.0.8 <6.0.0",
       "postcss@<8.5.18": ">=8.5.18 <9.0.0",

integrations/pi-agent-plugin/pnpm-lock.yaml

@@ -8,8 +8,8 @@ overrides:
   form-data@<4.0.6: '>=4.0.6'
   uuid@<11.1.1: '>=11.1.1'
   esbuild: '>=0.28.1'
-  undici@<6.27.0: '>=6.27.0 <8.0.0'
-  undici@>=8.0.0 <8.5.0: '>=8.5.0'
+  undici@<7.29.0: '>=7.29.0 <8.0.0'
+  undici@>=8.0.0 <8.9.0: '>=8.9.0 <9.0.0'
   axios@<1.18.0: '>=1.18.0 <2.0.0'
   brace-expansion@>=3.0.0 <5.0.8: '>=5.0.8 <6.0.0'
   postcss@<8.5.18: '>=8.5.18 <9.0.0'
@@ -2354,12 +2354,12 @@ packages:
   undici-types@7.24.6:
     resolution: {integrity: sha512-WRNW+sJgj5OBN4/0JpHFqtqzhpbnV0GuB+OozA9gCL7a993SmU+1JBZCzLNxYsbMfIeDL+lTsphD5jN5N+n0zg==}
 
-  undici@7.28.0:
-    resolution: {integrity: sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==}
+  undici@7.29.0:
+    resolution: {integrity: sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==}
     engines: {node: '>=20.18.1'}
 
-  undici@8.5.0:
-    resolution: {integrity: sha512-xamtWoB1EshgjpmlXd7GGm2VfdDtw1+rD8uhry8pSNW3If6S8E0m2T2+orSKeZXEn/aPJMviCpDBA65WJt8zhg==}
+  undici@8.10.0:
+    resolution: {integrity: sha512-HvltHd7avK13QIw/oLe4qoOLyoVSoafqJ2jYOrtMRBkbYT31eiBQ8O0ehRKZiEZCMEyLFQNIADpgCWC5fALvYQ==}
     engines: {node: '>=22.19.0'}
 
   util-deprecate@1.0.2:
@@ -2942,7 +2942,7 @@ snapshots:
       minimatch: 10.2.5
       proper-lockfile: 4.1.2
       typebox: 1.1.38
-      undici: 8.5.0
+      undici: 8.10.0
       yaml: 2.9.0
     optionalDependencies:
       '@mariozechner/clipboard': 0.3.9
@@ -3203,7 +3203,7 @@ snapshots:
     dependencies:
       '@qdrant/openapi-typescript-fetch': 1.2.6
       typescript: 6.0.3
-      undici: 7.28.0
+      undici: 7.29.0
 
   '@qdrant/openapi-typescript-fetch@1.2.6': {}
 
@@ -4895,9 +4895,9 @@ snapshots:
 
   undici-types@7.24.6: {}
 
-  undici@7.28.0: {}
+  undici@7.29.0: {}
 
-  undici@8.5.0: {}
+  undici@8.10.0: {}
 
   util-deprecate@1.0.2: {}
 

integrations/pi-agent-plugin/pnpm-workspace.yaml

@@ -5,8 +5,8 @@ overrides:
   "form-data@<4.0.6": ">=4.0.6"
   "uuid@<11.1.1": ">=11.1.1"
   "esbuild": ">=0.28.1"
-  "undici@<6.27.0": ">=6.27.0 <8.0.0"
-  "undici@>=8.0.0 <8.5.0": ">=8.5.0"
+  "undici@<7.29.0": ">=7.29.0 <8.0.0"
+  "undici@>=8.0.0 <8.9.0": ">=8.9.0 <9.0.0"
   "axios@<1.18.0": ">=1.18.0 <2.0.0"
   "brace-expansion@>=3.0.0 <5.0.8": ">=5.0.8 <6.0.0"
   "postcss@<8.5.18": ">=8.5.18 <9.0.0"

integrations/zapier-mem0/package.json

@@ -41,10 +41,17 @@
   ],
   "jest": {
     "testEnvironment": "node",
-    "testMatch": ["**/test/**/*.test.ts"],
-    "setupFiles": ["<rootDir>/test/setup.ts"],
+    "testMatch": [
+      "**/test/**/*.test.ts"
+    ],
+    "setupFiles": [
+      "<rootDir>/test/setup.ts"
+    ],
     "transform": {
-      "^.+\\.tsx?$": ["ts-jest", {}]
+      "^.+\\.tsx?$": [
+        "ts-jest",
+        {}
+      ]
     }
   },
   "dependencies": {
@@ -62,8 +69,9 @@
       "form-data@<4.0.6": ">=4.0.6",
       "uuid@<11.1.1": ">=11.1.1",
       "esbuild": ">=0.28.1",
-      "undici@<6.27.0": ">=6.27.0 <8.0.0",
-      "undici@>=8.0.0 <8.5.0": ">=8.5.0"
+      "undici@<7.29.0": ">=7.29.0 <8.0.0",
+      "undici@>=8.0.0 <8.9.0": ">=8.9.0 <9.0.0",
+      "brace-expansion@<1.1.16": ">=1.1.16 <2.0.0"
     }
   }
 }

integrations/zapier-mem0/pnpm-lock.yaml

@@ -8,8 +8,9 @@ overrides:
   form-data@<4.0.6: '>=4.0.6'
   uuid@<11.1.1: '>=11.1.1'
   esbuild: '>=0.28.1'
-  undici@<6.27.0: '>=6.27.0 <8.0.0'
-  undici@>=8.0.0 <8.5.0: '>=8.5.0'
+  undici@<7.29.0: '>=7.29.0 <8.0.0'
+  undici@>=8.0.0 <8.9.0: '>=8.9.0 <9.0.0'
+  brace-expansion@<1.1.16: '>=1.1.16 <2.0.0'
 
 importers:
 
@@ -413,8 +414,8 @@ packages:
     engines: {node: '>=6.0.0'}
     hasBin: true
 
-  brace-expansion@1.1.15:
-    resolution: {integrity: sha512-EwOCDEex4quD37XhqM3omwtMoJjr//isUZz1JopUNWms+4Z2ViyM/k1YIRePpoVNnQhENnxtFjLaxNHrT7xIUg==}
+  brace-expansion@1.1.18:
+    resolution: {integrity: sha512-Edep/X9fGqVNmzKBVsDYIOtD+z1tuezV70LBjdCst9Tqu76lsnvRiZ6oTic1n+/BIwX6QDGAO94PN4N2SADvtw==}
 
   braces@3.0.3:
     resolution: {integrity: sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==}
@@ -530,6 +531,7 @@ packages:
 
   crypto-js@4.2.0:
     resolution: {integrity: sha512-KALDyEYgpY+Rlob/iriUtjV6d5Eq+Y191A5g4UqLAi8CyGP9N1+FdVbkc1SxKc2r4YAYqG8JzO2KGL+AizD70Q==}
+    deprecated: Active development of CryptoJS has been discontinued. This library is no longer maintained.
 
   debug@4.4.3:
     resolution: {integrity: sha512-RGwwWnwQvkVfavKVt22FGLw+xYSdzARwm0ru6DhTVA3umU5hZc28V3kO4stgYryrTlLpuvgI9GiijltAjNbcqA==}
@@ -1995,7 +1997,7 @@ snapshots:
 
   baseline-browser-mapping@2.10.41: {}
 
-  brace-expansion@1.1.15:
+  brace-expansion@1.1.18:
     dependencies:
       balanced-match: 1.0.2
       concat-map: 0.0.1
@@ -2792,7 +2794,7 @@ snapshots:
 
   minimatch@3.1.5:
     dependencies:
-      brace-expansion: 1.1.15
+      brace-expansion: 1.1.18
 
   minimist@1.2.8: {}
 

integrations/zapier-mem0/pnpm-workspace.yaml

@@ -5,5 +5,6 @@ overrides:
   "form-data@<4.0.6": ">=4.0.6"
   "uuid@<11.1.1": ">=11.1.1"
   "esbuild": ">=0.28.1"
-  "undici@<6.27.0": ">=6.27.0 <8.0.0"
-  "undici@>=8.0.0 <8.5.0": ">=8.5.0"
+  "undici@<7.29.0": ">=7.29.0 <8.0.0"
+  "undici@>=8.0.0 <8.9.0": ">=8.9.0 <9.0.0"
+  "brace-expansion@<1.1.16": ">=1.1.16 <2.0.0"

mem0-ts/package.json

@@ -1,6 +1,6 @@
 {
   "name": "mem0ai",
-  "version": "3.1.5",
+  "version": "3.1.6",
   "description": "The Memory Layer For Your AI Apps",
   "main": "./dist/index.js",
   "module": "./dist/index.mjs",
@@ -292,18 +292,19 @@
       "glob@>=10.2.0 <10.5.0": "^10.5.0",
       "@modelcontextprotocol/sdk": "^1.25.4",
       "esbuild": ">=0.28.1",
-      "undici@<6.27.0": ">=6.27.0 <8.0.0",
+      "undici@<7.29.0": ">=7.29.0 <8.0.0",
       "@aws-sdk/client-bedrock-runtime": "3.967.0",
       "@aws-sdk/client-neptune-graph": "3.966.0",
       "axios@<1.18.0": ">=1.18.0 <2.0.0",
       "brace-expansion@<1.1.16": ">=1.1.16 <2.0.0",
-      "brace-expansion@>=2.0.0 <2.1.2": ">=2.1.2 <3.0.0",
+      "brace-expansion@>=2.0.0 <2.1.4": ">=2.1.4 <3.0.0",
       "brace-expansion@>=3.0.0 <5.0.8": ">=5.0.8 <6.0.0",
       "fast-xml-parser@>=5.0.0 <5.10.1": ">=5.10.1 <6.0.0",
       "tar@>=7.0.0 <7.5.21": ">=7.5.21 <8.0.0",
       "thrift@<0.23.0": "^0.23.0",
       "mongoose@>=9.0.0 <9.7.2": ">=9.7.2 <10.0.0",
-      "protobufjs@<7.6.5": ">=7.6.5 <8.0.0"
+      "protobufjs@<7.6.5": ">=7.6.5 <8.0.0",
+      "ip-address@<10.3.1": ">=10.3.1 <11.0.0"
     }
   }
 }

mem0-ts/pnpm-lock.yaml

@@ -25,18 +25,19 @@ overrides:
   glob@>=10.2.0 <10.5.0: ^10.5.0
   '@modelcontextprotocol/sdk': ^1.25.4
   esbuild: '>=0.28.1'
-  undici@<6.27.0: '>=6.27.0 <8.0.0'
+  undici@<7.29.0: '>=7.29.0 <8.0.0'
   '@aws-sdk/client-bedrock-runtime': 3.967.0
   '@aws-sdk/client-neptune-graph': 3.966.0
   axios@<1.18.0: '>=1.18.0 <2.0.0'
   brace-expansion@<1.1.16: '>=1.1.16 <2.0.0'
-  brace-expansion@>=2.0.0 <2.1.2: '>=2.1.2 <3.0.0'
+  brace-expansion@>=2.0.0 <2.1.4: '>=2.1.4 <3.0.0'
   brace-expansion@>=3.0.0 <5.0.8: '>=5.0.8 <6.0.0'
   fast-xml-parser@>=5.0.0 <5.10.1: '>=5.10.1 <6.0.0'
   tar@>=7.0.0 <7.5.21: '>=7.5.21 <8.0.0'
   thrift@<0.23.0: ^0.23.0
   mongoose@>=9.0.0 <9.7.2: '>=9.7.2 <10.0.0'
   protobufjs@<7.6.5: '>=7.6.5 <8.0.0'
+  ip-address@<10.3.1: '>=10.3.1 <11.0.0'
 
 importers:
 
@@ -2165,8 +2166,8 @@ packages:
   brace-expansion@1.1.16:
     resolution: {integrity: sha512-IDw48K2/2kRkg9LdJxurvq3lV3aBgq0REY89duEqFRthjlPdXHKMj7EnQOXVckxzgisinf3nHfrcE2FufFLXMw==}
 
-  brace-expansion@2.1.2:
-    resolution: {integrity: sha512-w5JZcKgdhDOgOwm8H+KgbosopHMuGcl6qbulwjtz3SM7I7P3yW1eAjzMPLrIE+NQ9vjgANKHWeMHnrT0OXW1oA==}
+  brace-expansion@2.1.4:
+    resolution: {integrity: sha512-hGfVzPxthbf3+2yjg/RBs60cB0FhqBS/zvdV/4wn4/BmN0bNMMHPc4V/BbFieqf1TKAGGAHnY4eSjajCl0f2Xg==}
 
   brace-expansion@5.0.8:
     resolution: {integrity: sha512-JZyDyq3D4AUifKTPOB7DELf6XsB3WdPuNxCtob1vFXPsSXhdAiHBWJ/tJ8HAc9aH84BK+5JFZLNkJKx3G9kzQg==}
@@ -3027,8 +3028,8 @@ packages:
     resolution: {integrity: sha512-4rTJX6Q5wTYEvxboXi8DsEiUo+OvqJGtLYOSGm37KpdRXsG5XJjbVtYKGJpPSWP+QT7rWscA4vsrdmzbEbenpw==}
     engines: {node: '>=18.12.0'}
 
-  ip-address@10.2.0:
-    resolution: {integrity: sha512-/+S6j4E9AHvW9SWMSEY9Xfy66O5PWvVEJ08O0y5JGyEKQpojb0K0GKpz/v5HJ/G0vi3D2sjGK78119oXZeE0qA==}
+  ip-address@10.4.0:
+    resolution: {integrity: sha512-oSK96Grm3aP6OrS263xVxbNDGVL7rzBtYdpGqlDG8iQdoenDoTs/nkki+DflYbAEE8Xl6o5YxhxlrKvI3nqKXQ==}
     engines: {node: '>= 12'}
 
   is-arrayish@0.2.1:
@@ -4626,8 +4627,8 @@ packages:
   undici-types@7.24.6:
     resolution: {integrity: sha512-WRNW+sJgj5OBN4/0JpHFqtqzhpbnV0GuB+OozA9gCL7a993SmU+1JBZCzLNxYsbMfIeDL+lTsphD5jN5N+n0zg==}
 
-  undici@7.28.0:
-    resolution: {integrity: sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==}
+  undici@7.29.0:
+    resolution: {integrity: sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==}
     engines: {node: '>=20.18.1'}
 
   update-browserslist-db@1.2.3:
@@ -6155,7 +6156,7 @@ snapshots:
       ms: 2.1.3
       secure-json-parse: 4.1.0
       tslib: 2.8.1
-      undici: 7.28.0
+      undici: 7.29.0
     transitivePeerDependencies:
       - supports-color
 
@@ -6711,7 +6712,7 @@ snapshots:
     dependencies:
       '@qdrant/openapi-typescript-fetch': 1.2.6
       typescript: 5.5.4
-      undici: 7.28.0
+      undici: 7.29.0
 
   '@qdrant/openapi-typescript-fetch@1.2.6': {}
 
@@ -7183,7 +7184,7 @@ snapshots:
   '@turbopuffer/turbopuffer@2.5.0':
     dependencies:
       pako: 2.2.0
-      undici: 7.28.0
+      undici: 7.29.0
 
   '@types/babel__core@7.20.5':
     dependencies:
@@ -7542,7 +7543,7 @@ snapshots:
       balanced-match: 1.0.2
       concat-map: 0.0.1
 
-  brace-expansion@2.1.2:
+  brace-expansion@2.1.4:
     dependencies:
       balanced-match: 1.0.2
 
@@ -8448,7 +8449,7 @@ snapshots:
     transitivePeerDependencies:
       - supports-color
 
-  ip-address@10.2.0: {}
+  ip-address@10.4.0: {}
 
   is-arrayish@0.2.1: {}
 
@@ -9076,7 +9077,7 @@ snapshots:
 
   minimatch@9.0.9:
     dependencies:
-      brace-expansion: 2.1.2
+      brace-expansion: 2.1.4
 
   minimist@1.2.8: {}
 
@@ -9886,7 +9887,7 @@ snapshots:
 
   socks@2.8.9:
     dependencies:
-      ip-address: 10.2.0
+      ip-address: 10.4.0
       smart-buffer: 4.2.0
 
   source-map-support@0.5.13:
@@ -10232,7 +10233,7 @@ snapshots:
 
   undici-types@7.24.6: {}
 
-  undici@7.28.0: {}
+  undici@7.29.0: {}
 
   update-browserslist-db@1.2.3(browserslist@4.28.2):
     dependencies:

mem0-ts/pnpm-workspace.yaml

@@ -25,13 +25,14 @@ overrides:
   "glob@>=10.2.0 <10.5.0": "^10.5.0"
   "@modelcontextprotocol/sdk": "^1.25.4"
   "esbuild": ">=0.28.1"
-  "undici@<6.27.0": ">=6.27.0 <8.0.0"
+  "undici@<7.29.0": ">=7.29.0 <8.0.0"
   "axios@<1.18.0": ">=1.18.0 <2.0.0"
   "brace-expansion@<1.1.16": ">=1.1.16 <2.0.0"
-  "brace-expansion@>=2.0.0 <2.1.2": ">=2.1.2 <3.0.0"
+  "brace-expansion@>=2.0.0 <2.1.4": ">=2.1.4 <3.0.0"
   "brace-expansion@>=3.0.0 <5.0.8": ">=5.0.8 <6.0.0"
   "fast-xml-parser@>=5.0.0 <5.10.1": ">=5.10.1 <6.0.0"
   "tar@>=7.0.0 <7.5.21": ">=7.5.21 <8.0.0"
   "thrift@<0.23.0": "^0.23.0"
   "mongoose@>=9.0.0 <9.7.2": ">=9.7.2 <10.0.0"
   "protobufjs@<7.6.5": ">=7.6.5 <8.0.0"
+  "ip-address@<10.3.1": ">=10.3.1 <11.0.0"

mem0-ts/src/oss/src/memory/index.ts

@@ -556,11 +556,18 @@ export class Memory {
     }
   }
 
+  private escapeScopeValue(val: unknown): string {
+    return String(val)
+      .replace(/%/g, "%25")
+      .replace(/&/g, "%26")
+      .replace(/=/g, "%3D");
+  }
+
   private buildSessionScope(filters: SearchFilters): string {
     const parts: string[] = [];
     for (const key of ["agent_id", "run_id", "user_id"].sort()) {
       const val = (filters as any)[key];
-      if (val) parts.push(`${key}=${val}`);
+      if (val) parts.push(`${key}=${this.escapeScopeValue(val)}`);
     }
     return parts.join("&");
   }

mem0-ts/src/oss/src/vector_stores/oracledb.ts

@@ -1,4 +1,4 @@
-import type { Connection, Pool } from "oracledb";
+import type { BindParameters, Connection, Pool } from "oracledb";
 import { v4 as uuidv4 } from "uuid";
 import { VectorStore } from "./base";
 import { SearchFilters, VectorStoreConfig, VectorStoreResult } from "../types";
@@ -401,7 +401,15 @@ export class OracleAIVectorSearch implements VectorStore {
 
   async initialize(): Promise<void> {
     if (!this._initPromise) {
-      this._initPromise = this._doInitialize();
+      this._initPromise = this._doInitialize().catch(async (error) => {
+        if (this.ownsClient && this.client) {
+          await Promise.resolve(this.client.close()).catch(() => {});
+          this.client = undefined;
+          this.ownsClient = false;
+        }
+        this._initPromise = undefined;
+        throw error;
+      });
     }
     return this._initPromise;
   }
@@ -565,19 +573,33 @@ export class OracleAIVectorSearch implements VectorStore {
     ids: string[],
     payloads: Record<string, any>[],
   ): Promise<void> {
+    if (ids.length !== vectors.length) {
+      throw new Error("ids and vectors must have the same length");
+    }
+    if (payloads.length !== vectors.length) {
+      throw new Error("payloads and vectors must have the same length");
+    }
+
+    if (vectors.length === 0) return;
+
     await this.initialize();
 
     await this.withConnection(async (connection) => {
-      for (let i = 0; i < vectors.length; i++) {
-        await connection.execute(
-          `INSERT INTO ${this.collectionName} (id, vector, payload) VALUES (:id, :vector, :payload)`,
-          {
-            id: ids[i],
-            vector: this.vectorBind(vectors[i]),
-            payload: this.payloadBind(payloads[i] ?? {}),
+      await connection.executeMany(
+        `INSERT INTO ${this.collectionName} (id, vector, payload) VALUES (:id, :vector, :payload)`,
+        vectors.map((vector, i) => ({
+          id: ids[i],
+          vector: new Float32Array(vector),
+          payload: payloads[i] ?? {},
+        })) as BindParameters[],
+        {
+          bindDefs: {
+            id: { type: this.oracledb.DB_TYPE_VARCHAR, maxSize: 36 },
+            vector: { type: this.oracledb.DB_TYPE_VECTOR },
+            payload: { type: this.oracledb.DB_TYPE_JSON },
           },
-        );
-      }
+        },
+      );
     }, true);
   }
 
@@ -589,8 +611,12 @@ export class OracleAIVectorSearch implements VectorStore {
     await this.initialize();
 
     const [whereClause, filterBinds] = buildWhereClause(filters);
+    const hasFilter = whereClause.length > 0;
+    const selectClause = hasFilter
+      ? "SELECT"
+      : `SELECT /*+ VECTOR_INDEX_TRANSFORM(${this.collectionName}) */`;
     const sql =
-      `SELECT id, payload, VECTOR_DISTANCE(vector, :query_vec, ${this.distanceMetric}) distance ` +
+      `${selectClause} id, payload, VECTOR_DISTANCE(vector, :query_vec, ${this.distanceMetric}) distance ` +
       `FROM ${this.collectionName} ${whereClause} ORDER BY distance FETCH APPROX FIRST :max_rows ROWS ONLY`;
 
     const rows = await this.withConnection(async (connection) => {
@@ -687,20 +713,17 @@ export class OracleAIVectorSearch implements VectorStore {
 
     return this.withConnection(async (connection) => {
       const listResult = await connection.execute<any[]>(
-        `SELECT id, payload FROM ${this.collectionName} ${whereClause} FETCH FIRST :max_rows ROWS ONLY`,
+        `SELECT id, payload, COUNT(*) OVER () total FROM ${this.collectionName} ${whereClause} FETCH FIRST :max_rows ROWS ONLY`,
         { ...filterBinds, max_rows: topK },
       );
-      const countResult = await connection.execute<any[]>(
-        `SELECT COUNT(*) FROM ${this.collectionName} ${whereClause}`,
-        filterBinds,
-      );
 
-      const results = (listResult.rows ?? []).map((row) => ({
+      const rows = listResult.rows ?? [];
+      const results = rows.map((row) => ({
         id: row[0],
         payload: this.loadPayload(row[1]),
       }));
 
-      return [results, Number(countResult.rows?.[0]?.[0] ?? 0)];
+      return [results, Number(rows[0]?.[2] ?? 0)];
     });
   }
 

mem0-ts/src/oss/tests/oracledb.unit.test.ts

@@ -2,10 +2,21 @@
 /** Oracle AI Vector Search filter, config and SQL tests. The driver is mocked, so no database is needed. */
 const DB_TYPE_VECTOR = { name: "DB_TYPE_VECTOR" };
 const DB_TYPE_JSON = { name: "DB_TYPE_JSON" };
+const DB_TYPE_VARCHAR = { name: "DB_TYPE_VARCHAR" };
 
-jest.mock("oracledb", () => ({ thin: true, DB_TYPE_VECTOR, DB_TYPE_JSON }), {
-  virtual: true,
-});
+const mockCreatePool = jest.fn();
+
+jest.mock(
+  "oracledb",
+  () => ({
+    thin: true,
+    DB_TYPE_VECTOR,
+    DB_TYPE_JSON,
+    DB_TYPE_VARCHAR,
+    createPool: mockCreatePool,
+  }),
+  { virtual: true },
+);
 
 import {
   OracleAIVectorSearch,
@@ -13,7 +24,7 @@ import {
   quoteIdentifier,
 } from "../src/vector_stores/oracledb";
 
-type Call = { sql: string; binds: any };
+type Call = { sql: string; binds: any; options?: any };
 
 function fakeConnection(calls: Call[], resultsBySql: Array<any[][]>) {
   let selectIndex = 0;
@@ -26,6 +37,10 @@ function fakeConnection(calls: Call[], resultsBySql: Array<any[][]>) {
       }
       return { rows: [] };
     },
+    async executeMany(sql: string, binds: any[], options: any = {}) {
+      calls.push({ sql: sql.replace(/\s+/g, " ").trim(), binds, options });
+      return { rows: [] };
+    },
     async commit() {},
     async rollback() {},
     async close() {},
@@ -249,13 +264,56 @@ describe("OracleAIVectorSearch SQL", () => {
     await makeStore(calls).insert([[1, 2, 3]], ["id-1"], [{ data: "hello" }]);
 
     const insert = calls.find((c) => c.sql.startsWith("INSERT INTO"))!;
-    expect(insert.binds.id).toBe("id-1");
-    expect(insert.binds.vector.type).toBe(DB_TYPE_VECTOR);
-    expect(insert.binds.vector.val).toEqual(new Float32Array([1, 2, 3]));
-    expect(insert.binds.payload).toEqual({
-      type: DB_TYPE_JSON,
-      val: { data: "hello" },
+    expect(insert.binds).toEqual([
+      {
+        id: "id-1",
+        vector: new Float32Array([1, 2, 3]),
+        payload: { data: "hello" },
+      },
+    ]);
+    expect(insert.options.bindDefs.id).toEqual({
+      type: DB_TYPE_VARCHAR,
+      maxSize: 36,
     });
+    expect(insert.options.bindDefs.vector.type).toBe(DB_TYPE_VECTOR);
+    expect(insert.options.bindDefs.payload.type).toBe(DB_TYPE_JSON);
+  });
+
+  it("issues a single executeMany call with one bind row per vector on a multi-row insert", async () => {
+    const calls: Call[] = [];
+    await makeStore(calls).insert(
+      [
+        [1, 2, 3],
+        [4, 5, 6],
+      ],
+      ["id-1", "id-2"],
+      [{ a: 1 }, { b: 2 }],
+    );
+
+    const inserts = calls.filter((c) => c.sql.startsWith("INSERT INTO"));
+    expect(inserts).toHaveLength(1);
+    expect(inserts[0].binds).toHaveLength(2);
+    expect(inserts[0].binds[0].id).toBe("id-1");
+    expect(inserts[0].binds[1].id).toBe("id-2");
+  });
+
+  it("issues no insert statement when inserting an empty batch", async () => {
+    const calls: Call[] = [];
+    await makeStore(calls).insert([], [], []);
+    expect(calls.filter((c) => c.sql.startsWith("INSERT INTO"))).toHaveLength(
+      0,
+    );
+  });
+
+  it("rejects insert batches whose IDs or payloads do not match vectors", async () => {
+    const store = makeStore([]);
+
+    await expect(store.insert([[1, 2, 3]], [], [{}])).rejects.toThrow(
+      "ids and vectors must have the same length",
+    );
+    await expect(store.insert([[1, 2, 3]], ["id-1"], [])).rejects.toThrow(
+      "payloads and vectors must have the same length",
+    );
   });
 
   it("converts cosine distance to a similarity score", async () => {
@@ -266,7 +324,7 @@ describe("OracleAIVectorSearch SQL", () => {
     expect(results).toEqual([
       { id: "id-1", payload: { data: "hello" }, score: 0.75 },
     ]);
-    const select = calls.find((c) => c.sql.startsWith("SELECT id, payload,"))!;
+    const select = calls.find((c) => c.sql.includes("VECTOR_DISTANCE"))!;
     expect(select.sql).toContain(
       "VECTOR_DISTANCE(vector, :query_vec, COSINE) distance",
     );
@@ -282,6 +340,24 @@ describe("OracleAIVectorSearch SQL", () => {
     expect(result.score).toBeCloseTo(0.4);
   });
 
+  it("adds the VECTOR_INDEX_TRANSFORM hint when searching without filters", async () => {
+    const calls: Call[] = [];
+    const store = makeStore(calls, [[["id-1", {}, 0.1]]]);
+    await store.search([1, 2, 3], 5);
+
+    const select = calls.find((c) => c.sql.includes("VECTOR_DISTANCE"))!;
+    expect(select.sql).toContain('/*+ VECTOR_INDEX_TRANSFORM("mem0") */');
+  });
+
+  it("omits the VECTOR_INDEX_TRANSFORM hint when searching with filters", async () => {
+    const calls: Call[] = [];
+    const store = makeStore(calls, [[["id-1", {}, 0.1]]]);
+    await store.search([1, 2, 3], 5, { user_id: "alice" });
+
+    const select = calls.find((c) => c.sql.includes("VECTOR_DISTANCE"))!;
+    expect(select.sql).not.toContain("VECTOR_INDEX_TRANSFORM");
+  });
+
   it("parses a payload returned as a JSON string", async () => {
     const store = makeStore([], [[["id-1", '{"data":"hello"}']]]);
     expect(await store.get("id-1")).toEqual({
@@ -313,16 +389,87 @@ describe("OracleAIVectorSearch SQL", () => {
 
   it("returns rows and the total count from list", async () => {
     const calls: Call[] = [];
-    const store = makeStore(calls, [[["id-1", { data: "hello" }]], [[7]]]);
+    const store = makeStore(calls, [[["id-1", { data: "hello" }, 7]]]);
     const [results, count] = await store.list({ user_id: "alice" }, 10);
 
     expect(results).toEqual([{ id: "id-1", payload: { data: "hello" } }]);
     expect(count).toBe(7);
 
-    const list = calls.find((c) =>
-      c.sql.startsWith("SELECT id, payload FROM"),
-    )!;
+    const selects = calls.filter((c) => /^SELECT/i.test(c.sql));
+    expect(selects).toHaveLength(1);
+    const [list] = selects;
+    expect(list.sql).toContain(
+      "SELECT id, payload, COUNT(*) OVER () total FROM",
+    );
     expect(list.sql).toContain("WHERE JSON_EXISTS(payload,");
     expect(list.binds).toEqual({ f_0: "alice", max_rows: 10 });
   });
+
+  it("returns a total of 0 from list when no rows match", async () => {
+    const store = makeStore([], [[]]);
+    const [results, count] = await store.list();
+    expect(results).toEqual([]);
+    expect(count).toBe(0);
+  });
+});
+
+describe("OracleAIVectorSearch initialization failure", () => {
+  beforeEach(() => mockCreatePool.mockReset());
+
+  function fakePool(serverVersion: string) {
+    const connection = {
+      ...fakeConnection([], []),
+      oracleServerVersionString: serverVersion,
+    };
+    return {
+      close: jest.fn(async () => {}),
+      getConnection: jest.fn(async () => connection),
+    };
+  }
+
+  function makePoolStore() {
+    return new OracleAIVectorSearch({
+      connectionParams: { user: "u", password: "p", connectString: "d" },
+      collectionName: "mem0",
+      embeddingModelDims: 3,
+    } as any);
+  }
+
+  it("closes the pool it owns when initialization fails", async () => {
+    const pool = fakePool("23.3.0.24.05");
+    mockCreatePool.mockResolvedValue(pool);
+
+    await expect(makePoolStore().initialize()).rejects.toThrow(
+      "Oracle DB version 23.3.0.24.05 not supported",
+    );
+    expect(pool.close).toHaveBeenCalledTimes(1);
+  });
+
+  it("does not cache the rejection, so a later attempt can succeed", async () => {
+    const failing = fakePool("23.3.0.24.05");
+    const working = fakePool("23.4.0.24.05");
+    mockCreatePool
+      .mockResolvedValueOnce(failing)
+      .mockResolvedValueOnce(working);
+
+    const store = makePoolStore();
+    await expect(store.initialize()).rejects.toThrow("not supported");
+    await expect(store.initialize()).resolves.toBeUndefined();
+    expect(mockCreatePool).toHaveBeenCalledTimes(2);
+  });
+
+  it("leaves a caller-supplied client open when initialization fails", async () => {
+    const client = fakeConnection([], []);
+    client.oracleServerVersionString = "23.3.0.24.05";
+    const close = jest.spyOn(client, "close");
+
+    const store = new OracleAIVectorSearch({
+      client: client as any,
+      collectionName: "mem0",
+      embeddingModelDims: 3,
+    } as any);
+
+    await expect(store.initialize()).rejects.toThrow("not supported");
+    expect(close).not.toHaveBeenCalled();
+  });
 });

mem0-ts/src/oss/tests/session-scope.unit.test.ts

@@ -0,0 +1,152 @@
+/**
+ * Unit tests for Memory.buildSessionScope. The recent-conversation buffer key
+ * derived from user_id/agent_id/run_id must be unique per id combination.
+ */
+/// <reference types="jest" />
+jest.mock("../src/utils/factory", () => {
+  const { MemoryVectorStore } = jest.requireActual(
+    "../src/vector_stores/memory",
+  );
+  const { SQLiteManager } = jest.requireActual("../src/storage/SQLiteManager");
+  const testEmbedding = new Array(1536).fill(0.1);
+  class MockEmbedder {
+    embeddingDims = 1536;
+    async embed(): Promise<number[]> {
+      return testEmbedding;
+    }
+    async embedBatch(texts: string[]): Promise<number[][]> {
+      return texts.map(() => testEmbedding);
+    }
+  }
+  class MockLLM {
+    async generateResponse() {
+      return JSON.stringify({ memory: [] });
+    }
+  }
+  return {
+    __esModule: true,
+    EmbedderFactory: { create: jest.fn(() => new MockEmbedder()) },
+    LLMFactory: { create: jest.fn(() => new MockLLM()) },
+    VectorStoreFactory: {
+      create: jest.fn(
+        () => new MemoryVectorStore({ collectionName: "t", dimension: 1536 }),
+      ),
+    },
+    HistoryManagerFactory: {
+      create: jest.fn(() => new SQLiteManager(":memory:")),
+    },
+  };
+});
+
+import { Memory } from "../src/memory";
+import { SearchFilters } from "../src/types";
+
+function scopeOf(memory: Memory, filters: SearchFilters): string {
+  return (memory as any).buildSessionScope(filters);
+}
+
+function cartesian(values: string[], length: number): string[][] {
+  if (length === 0) return [[]];
+  const rest = cartesian(values, length - 1);
+  const result: string[][] = [];
+  for (const value of values) {
+    for (const tail of rest) {
+      result.push([value, ...tail]);
+    }
+  }
+  return result;
+}
+
+describe("Memory session scope key", () => {
+  let memory: Memory;
+
+  beforeAll(async () => {
+    memory = new Memory();
+    await (memory as any)._initPromise;
+  });
+
+  it("keeps the unchanged key format for ids without delimiter characters", () => {
+    expect(
+      scopeOf(memory, { user_id: "550e8400-e29b-41d4-a716-446655440000" }),
+    ).toBe("user_id=550e8400-e29b-41d4-a716-446655440000");
+    expect(scopeOf(memory, { agent_id: "agent.assistant:v2" })).toBe(
+      "agent_id=agent.assistant:v2",
+    );
+    expect(scopeOf(memory, { run_id: "12345" })).toBe("run_id=12345");
+    expect(
+      scopeOf(memory, { user_id: "user@example.com", agent_id: "support-bot" }),
+    ).toBe("agent_id=support-bot&user_id=user@example.com");
+  });
+
+  it("no longer collides an id embedding the join syntax with the equivalent split filters", () => {
+    const collapsedRun = scopeOf(memory, { run_id: "proj-x&user_id=u1" });
+    const splitRun = scopeOf(memory, { user_id: "u1", run_id: "proj-x" });
+    expect(collapsedRun).not.toBe(splitRun);
+
+    const collapsedAgent = scopeOf(memory, { run_id: "proj-y&agent_id=a1" });
+    const splitAgent = scopeOf(memory, { agent_id: "a1", run_id: "proj-y" });
+    expect(collapsedAgent).not.toBe(splitAgent);
+  });
+
+  it("maps every distinct filter combination of delimiter-heavy ids to a distinct key", () => {
+    const keys: string[] = ["user_id", "agent_id", "run_id"];
+    const values = [
+      "u1",
+      "r1",
+      "a1",
+      "%",
+      "&",
+      "=",
+      "a==",
+      "a1&run_id=r1",
+      "a1&user_id=u1",
+      "r1&user_id=u1",
+      "a1&run_id=r1&user_id=u1",
+    ];
+    const seen = new Map<string, SearchFilters>();
+
+    for (let mask = 1; mask < 1 << keys.length; mask++) {
+      const subset = keys.filter((_key, i) => mask & (1 << i));
+      for (const combo of cartesian(values, subset.length)) {
+        const filters: SearchFilters = {};
+        subset.forEach((key, i) => (filters[key] = combo[i]));
+        const scope = scopeOf(memory, filters);
+        if (seen.has(scope)) {
+          expect(seen.get(scope)).toEqual(filters);
+        } else {
+          seen.set(scope, filters);
+        }
+      }
+    }
+  });
+
+  it("gives ids containing delimiter characters a new key format", () => {
+    expect(scopeOf(memory, { user_id: "dXNlcl9pZDE=" })).toBe(
+      "user_id=dXNlcl9pZDE%3D",
+    );
+    expect(scopeOf(memory, { agent_id: "x&y" })).toBe("agent_id=x%26y");
+    expect(scopeOf(memory, { run_id: "50% off" })).toBe("run_id=50%25 off");
+  });
+
+  it("routes the add pipeline through the builder", async () => {
+    const db = (memory as any).db;
+    const spy = jest.spyOn(db, "getLastMessages");
+    await memory.add([{ role: "user", content: "hello" }], {
+      runId: "proj-x&user_id=u1",
+    });
+    expect(spy).toHaveBeenCalledWith("run_id=proj-x%26user_id%3Du1", 10);
+    spy.mockRestore();
+  });
+
+  it("pins the exact key strings shared with the Python test suite", () => {
+    expect(
+      scopeOf(memory, { user_id: "550e8400-e29b-41d4-a716-446655440000" }),
+    ).toBe("user_id=550e8400-e29b-41d4-a716-446655440000");
+    expect(
+      scopeOf(memory, { user_id: "u1", agent_id: "a1", run_id: "r1" }),
+    ).toBe("agent_id=a1&run_id=r1&user_id=u1");
+    expect(scopeOf(memory, { run_id: "proj-x&user_id=u1" })).toBe(
+      "run_id=proj-x%26user_id%3Du1",
+    );
+  });
+});

mem0/configs/vector_stores/oracledb.py

@@ -1,3 +1,4 @@
+# Copyright (c) 2026, Oracle and/or its affiliates.
 """Pydantic configuration for the Oracle AI Vector Search integration."""
 
 import re
@@ -91,8 +92,9 @@ class OracleAIVectorSearchConfig(BaseModel):
                 exclude_none=True,
             )
 
-        if self.index_accuracy and not (0 < self.index_accuracy <= 100):
-            raise ValueError("`index_accuracy` must be between 1 and 100")
+        if self.index_accuracy is not None:
+            if not (0 < self.index_accuracy <= 100):
+                raise ValueError("`index_accuracy` must be between 1 and 100")
 
         if not (0 < self.embedding_model_dims):
             raise ValueError("`embedding_model_dims` must be bigger than 0")

mem0/memory/main.py

@@ -404,13 +404,18 @@ def _build_filters_and_metadata(
     return base_metadata_template, effective_query_filters
 
 
+def _escape_scope_value(val: Any) -> str:
+    """Escape the structural delimiters of the session scope key."""
+    return str(val).replace("%", "%25").replace("&", "%26").replace("=", "%3D")
+
+
 def _build_session_scope(filters):
     """Build deterministic session scope string from entity IDs."""
     parts = []
     for key in sorted(["user_id", "agent_id", "run_id"]):
         val = filters.get(key)
         if val:
-            parts.append(f"{key}={val}")
+            parts.append(f"{key}={_escape_scope_value(val)}")
     return "&".join(parts)
 
 
@@ -791,6 +796,11 @@ class Memory(MemoryBase):
                 are treated as general conversational/factual memories.
             prompt (str, optional): Prompt to use for the memory creation. Defaults to None.
 
+        Note:
+            `search()` and `get_all()` scope queries via `filters={"user_id": "...", "agent_id": "...", "run_id": "..."}` —
+            they reject top-level `user_id`/`agent_id`/`run_id` arguments. `add()` accepts them top-level, but passing
+            the same arguments to `search()`/`get_all()` raises a `ValueError`; use the `filters` form there instead.
+
 
         Returns:
             dict: A dictionary containing the result of the memory addition operation, typically
@@ -2447,6 +2457,12 @@ class AsyncMemory(MemoryBase):
                                          Pass "procedural_memory" to create procedural memories.
             prompt (str, optional): Prompt to use for the memory creation. Defaults to None.
             llm (BaseChatModel, optional): LLM class to use for generating procedural memories. Defaults to None. Useful when user is using LangChain ChatModel.
+
+        Note:
+            `search()` and `get_all()` scope queries via `filters={"user_id": "...", "agent_id": "...", "run_id": "..."}` —
+            they reject top-level `user_id`/`agent_id`/`run_id` arguments. `add()` accepts them top-level, but passing
+            the same arguments to `search()`/`get_all()` raises a `ValueError`; use the `filters` form there instead.
+
         Returns:
             dict: A dictionary containing the result of the memory addition operation.
         """

mem0/vector_stores/oracledb.py

@@ -1,3 +1,4 @@
+# Copyright (c) 2026, Oracle and/or its affiliates.
 """Oracle AI Vector Search vector store integration for mem0."""
 
 import array
@@ -245,25 +246,34 @@ class OracleAIVectorSearch(VectorStoreBase):
             self.client = oracledb.connect(**self.config.connection_params)
             self._owns_client = True
 
-        if not (hasattr(self.client, "thin") and self.client.thin):
-            if oracledb.clientversion()[:2] < (23, 4):
-                raise RuntimeError(
-                    f"Oracle DB client driver version {'.'.join(map(str, oracledb.clientversion()))} "
-                    "not supported, must be >=23.4 for vector support"
+        try:
+            if not (hasattr(self.client, "thin") and self.client.thin):
+                if oracledb.clientversion()[:2] < (23, 4):
+                    raise RuntimeError(
+                        f"Oracle DB client driver version {'.'.join(map(str, oracledb.clientversion()))} "
+                        "not supported, must be >=23.4 for vector support"
+                    )
+
+            if isinstance(self.client, oracledb.Connection):
+                db_version = tuple([int(v) for v in self.client.version.split(".")])
+            else:
+                with self.client.acquire() as conn:
+                    db_version = tuple([int(v) for v in conn.version.split(".")])
+
+            if db_version < (23, 4):
+                raise ValueError(
+                    f"Oracle DB version {'.'.join(map(str, db_version))} not supported, "
+                    "must be >=23.4 for vector support"
                 )
 
-        if isinstance(self.client, oracledb.Connection):
-            db_version = tuple([int(v) for v in self.client.version.split(".")])
-        else:
-            with self.client.acquire() as conn:
-                db_version = tuple([int(v) for v in conn.version.split(".")])
-
-        if db_version < (23, 4):
-            raise ValueError(
-                f"Oracle DB version {'.'.join(map(str, db_version))} not supported, must be >=23.4 for vector support"
-            )
-
-        self.create_col()
+            self.create_col()
+        except Exception:
+            if self._owns_client:
+                try:
+                    self.client.close()
+                except Exception:
+                    pass
+            raise
 
     @contextmanager
     def _get_cursor(self, commit: bool = False):

mem0/vector_stores/pgvector.py

@@ -89,6 +89,10 @@ def _build_filter_conditions(filters):
                     raise ValueError(f"Unsupported filter operator: {op}")
                 template, is_numeric = OPERATOR_SQL_MAP[op]
                 if op in ("in", "nin"):
+                    if not isinstance(op_value, list):
+                        raise ValueError(
+                            f"Filter operator {op!r} for key {key!r} requires a list value, got {type(op_value).__name__}"
+                        )
                     str_list = [str(v) for v in op_value]
                     conditions.append(template)
                     params.extend([key, str_list])

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0ai"
-version = "2.0.17"
+version = "2.0.18"
 description = "Long-term memory for AI Agents"
 authors = [
     { name = "Mem0", email = "support@mem0.ai" }

tests/memory/test_session_scope.py

@@ -0,0 +1,131 @@
+import itertools
+
+import pytest
+
+from mem0.memory.main import Memory, _build_session_scope, _escape_scope_value
+
+DELIMITER_VALUES = [
+    "u1",
+    "r1",
+    "a1",
+    "%",
+    "&",
+    "=",
+    "%25",
+    "%26",
+    "%3D",
+    "a==",
+    "a1&run_id=r1",
+    "a1&user_id=u1",
+    "r1&user_id=u1",
+    "a1&run_id=r1&user_id=u1",
+]
+
+
+class TestBuildSessionScope:
+    """Tests that _build_session_scope produces a unique key per id combination."""
+
+    def test_ordinary_ids_produce_unchanged_scope_keys(self):
+        """Ids without delimiter characters keep producing the pre-fix key format."""
+        cases = [
+            ({"user_id": "550e8400-e29b-41d4-a716-446655440000"}, "user_id=550e8400-e29b-41d4-a716-446655440000"),
+            ({"agent_id": "agent.assistant:v2"}, "agent_id=agent.assistant:v2"),
+            ({"run_id": "12345"}, "run_id=12345"),
+            (
+                {"user_id": "user@example.com", "agent_id": "support-bot"},
+                "agent_id=support-bot&user_id=user@example.com",
+            ),
+            (
+                {"user_id": "u1", "agent_id": "a1", "run_id": "r1"},
+                "agent_id=a1&run_id=r1&user_id=u1",
+            ),
+        ]
+        for filters, expected in cases:
+            assert _build_session_scope(filters) == expected
+
+    def test_ids_containing_delimiters_do_not_collide(self):
+        """A value that embeds the join syntax no longer maps to the same key as the equivalent split filters."""
+        collapsed_run = {"run_id": "proj-x&user_id=u1"}
+        split_run = {"user_id": "u1", "run_id": "proj-x"}
+        assert _build_session_scope(collapsed_run) != _build_session_scope(split_run)
+        assert _build_session_scope(collapsed_run) == "run_id=proj-x%26user_id%3Du1"
+
+        collapsed_agent = {"run_id": "proj-y&agent_id=a1"}
+        split_agent = {"agent_id": "a1", "run_id": "proj-y"}
+        assert _build_session_scope(collapsed_agent) != _build_session_scope(split_agent)
+
+    def test_ids_containing_delimiters_get_a_new_key_format(self):
+        """Ids holding a delimiter character map to a new key, so their buffer starts empty once after upgrade."""
+        assert _build_session_scope({"user_id": "dXNlcl9pZDE="}) == "user_id=dXNlcl9pZDE%3D"
+        assert _build_session_scope({"agent_id": "x&y"}) == "agent_id=x%26y"
+        assert _build_session_scope({"run_id": "50% off"}) == "run_id=50%25 off"
+
+    def test_scope_keys_are_unique_per_filter_combination(self):
+        """Every distinct filter dict built from delimiter-heavy id values maps to a distinct scope key."""
+        keys = ["user_id", "agent_id", "run_id"]
+        seen = {}
+        for size in range(1, len(keys) + 1):
+            for key_subset in itertools.combinations(keys, size):
+                for combo in itertools.product(DELIMITER_VALUES, repeat=size):
+                    filters = dict(zip(key_subset, combo))
+                    scope = _build_session_scope(filters)
+                    if scope in seen:
+                        assert seen[scope] == filters, f"{seen[scope]} and {filters} both map to {scope!r}"
+                    else:
+                        seen[scope] = filters
+
+
+class TestEscapeScopeValue:
+    """Tests for the low-level per-value escaping helper."""
+
+    def test_non_string_input_is_stringified(self):
+        assert _escape_scope_value(42) == "42"
+
+    def test_percent_is_escaped_before_other_delimiters(self):
+        assert _escape_scope_value("%26") == "%2526"
+        assert _escape_scope_value("%26") != "%26"
+
+    def test_each_delimiter_is_escaped(self):
+        assert _escape_scope_value("%") == "%25"
+        assert _escape_scope_value("&") == "%26"
+        assert _escape_scope_value("=") == "%3D"
+
+
+class TestSessionScopeWiring:
+    """Tests that the add pipeline keys the conversation buffer through the builder."""
+
+    @pytest.fixture
+    def memory(self, mocker):
+        mocker.patch("mem0.memory.main.capture_event")
+        mock_embedder = mocker.MagicMock()
+        mock_embedder.return_value.embed.return_value = [0.1, 0.2, 0.3]
+        mocker.patch("mem0.utils.factory.EmbedderFactory.create", mock_embedder)
+        mock_vector_store = mocker.MagicMock()
+        mock_vector_store.return_value.search.return_value = []
+        mocker.patch(
+            "mem0.utils.factory.VectorStoreFactory.create",
+            side_effect=[mock_vector_store.return_value, mocker.MagicMock()],
+        )
+        mocker.patch("mem0.utils.factory.LlmFactory.create", mocker.MagicMock())
+        mocker.patch("mem0.memory.storage.SQLiteManager", mocker.MagicMock())
+
+        memory = Memory()
+        memory.config = mocker.MagicMock()
+        memory.config.custom_instructions = None
+        memory.custom_instructions = None
+        memory.api_version = "v1.1"
+        memory.db.get_last_messages = mocker.MagicMock(return_value=[])
+        memory.db.save_messages = mocker.MagicMock()
+        memory.llm.generate_response.return_value = '{"memory": []}'
+        return memory
+
+    def test_add_pipeline_uses_the_escaped_key(self, memory):
+        """The pipeline must route through the builder, not assemble the key inline."""
+        memory._add_to_vector_store(
+            messages=[{"role": "user", "content": "hello"}],
+            metadata={},
+            filters={"run_id": "proj-x&user_id=u1"},
+            infer=True,
+        )
+        assert memory.db.get_last_messages.call_args[0][0] == "run_id=proj-x%26user_id%3Du1"
+        assert memory.db.save_messages.call_args[0][1] == "run_id=proj-x%26user_id%3Du1"

tests/vector_stores/test_oracledb.py

@@ -1,3 +1,4 @@
+# Copyright (c) 2026, Oracle and/or its affiliates.
 import os
 import uuid
 from contextlib import nullcontext
@@ -267,6 +268,16 @@ def test_index_parameters_reject_non_string_keys():
         )
 
 
+def test_index_accuracy_rejects_zero():
+    with pytest.raises(ValueError, match="index_accuracy.*between 1 and 100"):
+        OracleAIVectorSearchConfig(
+            collection_name=_unique_collection_name(),
+            embedding_model_dims=DIM,
+            client=object(),
+            index_accuracy=0,
+        )
+
+
 def test_index_parameters_canonicalize_int_subclasses():
     class FormattedInt(int):
         def __format__(self, format_spec):
@@ -331,6 +342,27 @@ def test_config_rejects_none_for_non_optional_fields(field, value):
         OracleAIVectorSearchConfig(client=object(), **{field: value})
 
 
+def test_init_closes_owned_client_when_post_connect_setup_fails(monkeypatch):
+    fake_connection = MagicMock(spec=oracledb.Connection)
+    fake_connection.thin = True
+    fake_connection.version = "23.4.0.0"
+
+    monkeypatch.setattr(oracledb, "connect", MagicMock(return_value=fake_connection))
+    monkeypatch.setattr(OracleAIVectorSearch, "create_col", MagicMock(side_effect=RuntimeError("boom")))
+    monkeypatch.setattr(OracleAIVectorSearch, "__del__", lambda self: None)
+
+    with pytest.raises(RuntimeError, match="boom"):
+        OracleAIVectorSearch(
+            collection_name=_unique_collection_name(),
+            embedding_model_dims=DIM,
+            connection_params={"user": "u", "password": "p", "dsn": "d"},
+            use_connection_pool=False,
+            do_create_index=False,
+        )
+
+    fake_connection.close.assert_called_once()
+
+
 @pytest.mark.parametrize(
     ("metric", "distance", "expected_score"),
     [

tests/vector_stores/test_pgvector.py

@@ -2508,3 +2508,20 @@ class TestBuildFilterConditions(unittest.TestCase):
     def test_numeric_scalar_becomes_string(self):
         conditions, params = _build_filter_conditions({"priority": 42})
         self.assertEqual(params, ["priority", "42"])
+
+    def test_in_rejects_string_value(self):
+        """Passing a string to 'in' would iterate characters and produce a misleading ANY() clause."""
+        with self.assertRaises(ValueError, msg="Expected ValueError for non-list 'in' value"):
+            _build_filter_conditions({"user_id": {"in": "alice"}})
+
+    def test_in_rejects_dict_value(self):
+        with self.assertRaises(ValueError):
+            _build_filter_conditions({"user_id": {"in": {"$gt": 0}}})
+
+    def test_nin_rejects_string_value(self):
+        with self.assertRaises(ValueError):
+            _build_filter_conditions({"user_id": {"nin": "alice"}})
+
+    def test_in_accepts_list_value(self):
+        conditions, params = _build_filter_conditions({"user_id": {"in": ["alice", "bob"]}})
+        self.assertEqual(params, ["user_id", ["alice", "bob"]])