fix: apply pnpm overrides for HIGH severity vulnerabilities

- Add immutable >=5.1.5 override to openmemory/ui (CVE-2026-29063)
- Add langsmith >=0.6.0 override to openclaw (CVE-2026-32460)
- Add langsmith >=0.6.0 override to mem0-ts (CVE-2026-32460)

Fixes #5318, #5320

.agents/plugins/marketplace.json

@@ -8,7 +8,7 @@
       "name": "mem0",
       "source": {
         "source": "local",
-        "path": "./integrations/mem0-plugin"
+        "path": "./mem0-plugin"
       },
       "policy": {
         "installation": "AVAILABLE",

.claude-plugin/marketplace.json

@@ -10,9 +10,9 @@
   "plugins": [
     {
       "name": "mem0",
-      "source": "./integrations/mem0-plugin",
+      "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows.",
-      "version": "0.2.11"
+      "version": "0.2.8"
     }
   ]
 }

.codex-plugin/marketplace.json

@@ -8,7 +8,7 @@
       "name": "mem0",
       "source": {
         "source": "local",
-        "path": "./integrations/mem0-plugin"
+        "path": "./mem0-plugin"
       },
       "policy": {
         "installation": "AVAILABLE",

.cursor-plugin/marketplace.json

@@ -10,9 +10,9 @@
   "plugins": [
     {
       "name": "mem0",
-      "source": "./integrations/mem0-plugin",
+      "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search.",
-      "version": "0.2.11"
+      "version": "0.2.8"
     }
   ]
 }

.github/workflows/cd.yml

@@ -1,33 +1,18 @@
 name: Publish Python 🐍 distributions 📦 to PyPI and TestPyPI
 
-# Dispatched by release.yml (Release Router) when a release tagged v* is
-# published. Can also be dispatched manually to re-publish a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. v1.2.3)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Unused for PyPI (pre-releases are expressed in the version itself); accepted for router uniformity'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish Python 🐍 distributions 📦 to PyPI and TestPyPI
-    # Pure SDK version tags only (v1.2.3) — excludes package-prefixed tags
-    # like vercel-ai-v* that also start with 'v'
-    if: startsWith(inputs.tag, 'v') && !contains(inputs.tag, '-v')
+    if: startsWith(github.event.release.tag_name, 'v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
     steps:
       - uses: actions/checkout@v2
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Set up Python
         uses: actions/setup-python@v2
@@ -54,6 +39,7 @@ jobs:
       #     packages_dir: dist/
 
       - name: Publish distribution 📦 to PyPI
+        if: startsWith(github.ref, 'refs/tags/v')
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           packages_dir: dist/

.github/workflows/ci-gate.yml

@@ -1,171 +0,0 @@
-name: CI Gate
-
-# Single required status check for all PRs.
-#
-# Path-filtered CI workflows can't be marked as required in branch
-# protection: on a PR that doesn't touch their paths they never report, and
-# the required check hangs at "Expected" forever. This gate solves that. It
-# runs on every PR, detects which packages changed, calls only the relevant
-# package CI workflows (as reusable workflows), and the final "CI Gate" job
-# reports the aggregate result — success when every invoked pipeline passed
-# (skipped pipelines are fine), failure when any failed.
-#
-# Branch protection should require exactly one status check: "CI Gate".
-#
-# Package CI workflows keep their own push-to-main and workflow_dispatch
-# triggers; only their pull_request triggers moved here. To wire in a new
-# package: add a filter under the `changes` job, a call job that `uses:` the
-# package workflow, and list the call job in the gate's `needs`.
-
-on:
-  pull_request:
-
-concurrency:
-  group: ci-gate-${{ github.event.pull_request.number }}
-  cancel-in-progress: true
-
-permissions:
-  contents: read
-  pull-requests: read
-
-jobs:
-  changes:
-    name: Detect changed packages
-    runs-on: ubuntu-latest
-    outputs:
-      python_sdk: ${{ steps.filter.outputs.python_sdk }}
-      ts_sdk: ${{ steps.filter.outputs.ts_sdk }}
-      cli_python: ${{ steps.filter.outputs.cli_python }}
-      cli_node: ${{ steps.filter.outputs.cli_node }}
-      openclaw: ${{ steps.filter.outputs.openclaw }}
-      opencode_plugin: ${{ steps.filter.outputs.opencode_plugin }}
-      pi_agent_plugin: ${{ steps.filter.outputs.pi_agent_plugin }}
-      docs_llms_txt: ${{ steps.filter.outputs.docs_llms_txt }}
-    steps:
-      - uses: dorny/paths-filter@v3
-        id: filter
-        with:
-          # Each filter mirrors the package workflow's old pull_request
-          # paths, plus the package workflow file itself and this gate file
-          # (changing either must re-exercise the pipeline).
-          filters: |
-            python_sdk:
-              - 'mem0/**'
-              - 'tests/**'
-              - 'pyproject.toml'
-              - '.github/workflows/ci.yml'
-              - '.github/workflows/ci-gate.yml'
-            ts_sdk:
-              - 'mem0-ts/**'
-              - '.github/workflows/ts-sdk-ci.yml'
-              - '.github/workflows/ci-gate.yml'
-            cli_python:
-              - 'cli/python/**'
-              - '.github/workflows/cli-python-ci.yml'
-              - '.github/workflows/ci-gate.yml'
-            cli_node:
-              - 'cli/node/**'
-              - '.github/workflows/cli-node-ci.yml'
-              - '.github/workflows/ci-gate.yml'
-            openclaw:
-              - 'integrations/openclaw/**'
-              - '.github/workflows/openclaw-checks.yml'
-              - '.github/workflows/ci-gate.yml'
-            opencode_plugin:
-              - 'integrations/mem0-plugin/.opencode-plugin/**'
-              - '.github/workflows/opencode-plugin-checks.yml'
-              - '.github/workflows/ci-gate.yml'
-            pi_agent_plugin:
-              - 'integrations/pi-agent-plugin/**'
-              - '.github/workflows/pi-agent-plugin-checks.yml'
-              - '.github/workflows/ci-gate.yml'
-            docs_llms_txt:
-              - 'docs/**/*.mdx'
-              - 'docs/llms.txt'
-              - 'scripts/check-llms-txt-coverage.py'
-              - 'scripts/llms-txt-ignore.txt'
-              - '.github/workflows/docs-llms-txt-check.yml'
-              - '.github/workflows/ci-gate.yml'
-
-  python-sdk:
-    name: Python SDK
-    needs: changes
-    if: needs.changes.outputs.python_sdk == 'true'
-    uses: ./.github/workflows/ci.yml
-    secrets: inherit
-
-  ts-sdk:
-    name: TypeScript SDK
-    needs: changes
-    if: needs.changes.outputs.ts_sdk == 'true'
-    uses: ./.github/workflows/ts-sdk-ci.yml
-    secrets: inherit
-
-  cli-python:
-    name: Python CLI
-    needs: changes
-    if: needs.changes.outputs.cli_python == 'true'
-    uses: ./.github/workflows/cli-python-ci.yml
-    secrets: inherit
-
-  cli-node:
-    name: Node CLI
-    needs: changes
-    if: needs.changes.outputs.cli_node == 'true'
-    uses: ./.github/workflows/cli-node-ci.yml
-    secrets: inherit
-
-  openclaw:
-    name: OpenClaw
-    needs: changes
-    if: needs.changes.outputs.openclaw == 'true'
-    uses: ./.github/workflows/openclaw-checks.yml
-    secrets: inherit
-
-  opencode-plugin:
-    name: OpenCode Plugin
-    needs: changes
-    if: needs.changes.outputs.opencode_plugin == 'true'
-    uses: ./.github/workflows/opencode-plugin-checks.yml
-    secrets: inherit
-
-  pi-agent-plugin:
-    name: Pi Agent Plugin
-    needs: changes
-    if: needs.changes.outputs.pi_agent_plugin == 'true'
-    uses: ./.github/workflows/pi-agent-plugin-checks.yml
-    secrets: inherit
-
-  docs-llms-txt:
-    name: docs llms.txt
-    needs: changes
-    if: needs.changes.outputs.docs_llms_txt == 'true'
-    uses: ./.github/workflows/docs-llms-txt-check.yml
-    secrets: inherit
-
-  gate:
-    name: CI Gate
-    needs:
-      - changes
-      - python-sdk
-      - ts-sdk
-      - cli-python
-      - cli-node
-      - openclaw
-      - opencode-plugin
-      - pi-agent-plugin
-      - docs-llms-txt
-    if: always()
-    runs-on: ubuntu-latest
-    steps:
-      - name: Evaluate pipeline results
-        env:
-          NEEDS: ${{ toJSON(needs) }}
-        run: |
-          echo "$NEEDS" | jq -r 'to_entries[] | "\(.key): \(.value.result)"'
-          failed=$(echo "$NEEDS" | jq -r '[to_entries[] | select(.value.result == "failure" or .value.result == "cancelled") | .key] | join(", ")')
-          if [ -n "$failed" ]; then
-            echo "::error::Failing pipelines: $failed"
-            exit 1
-          fi
-          echo "All pipelines relevant to this change passed."

.github/workflows/ci.yml

@@ -1,11 +1,9 @@
 name: ci
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main runs remain standalone.
 on:
   push:
     branches: [main]
-  workflow_call:
+  pull_request:
 
 jobs:
   changelog_check:

.github/workflows/cli-node-cd.yml

@@ -1,25 +1,13 @@
 name: Publish @mem0/cli 📦 to npm
 
-# Dispatched by release.yml (Release Router) when a release tagged
-# cli-node-v* is published. Can also be dispatched manually to re-publish
-# a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. cli-node-v0.2.0)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish @mem0/cli 📦 to npm
-    if: startsWith(inputs.tag, 'cli-node-v')
+    if: startsWith(github.event.release.tag_name, 'cli-node-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
@@ -28,8 +16,6 @@ jobs:
         working-directory: cli/node
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Install pnpm
         uses: pnpm/action-setup@v4
@@ -52,7 +38,7 @@ jobs:
 
       - name: Publish to npm
         run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
             PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
             npx npm@latest publish --provenance --access public --tag "$PREID"
           else

.github/workflows/cli-node-ci.yml

@@ -1,7 +1,5 @@
 name: CLI Node CI
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main and manual runs remain standalone.
 on:
   workflow_dispatch:
   push:
@@ -9,7 +7,10 @@ on:
     paths:
       - 'cli/node/**'
       - '.github/workflows/cli-node-ci.yml'
-  workflow_call:
+  pull_request:
+    paths:
+      - 'cli/node/**'
+      - '.github/workflows/cli-node-ci.yml'
 
 jobs:
   lint:

.github/workflows/cli-python-cd.yml

@@ -1,24 +1,13 @@
 name: Publish mem0-cli 🐍 distributions 📦 to PyPI
 
-# Dispatched by release.yml (Release Router) when a release tagged cli-v* is
-# published. Can also be dispatched manually to re-publish a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. cli-v0.2.0)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Unused for PyPI (pre-releases are expressed in the version itself); accepted for router uniformity'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish mem0-cli 📦 to PyPI
-    if: startsWith(inputs.tag, 'cli-v')
+    if: startsWith(github.event.release.tag_name, 'cli-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
@@ -27,8 +16,6 @@ jobs:
         working-directory: cli/python
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Set up Python
         uses: actions/setup-python@v5

.github/workflows/cli-python-ci.yml

@@ -1,7 +1,5 @@
 name: CLI Python CI
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main and manual runs remain standalone.
 on:
   workflow_dispatch:
   push:
@@ -9,7 +7,10 @@ on:
     paths:
       - 'cli/python/**'
       - '.github/workflows/cli-python-ci.yml'
-  workflow_call:
+  pull_request:
+    paths:
+      - 'cli/python/**'
+      - '.github/workflows/cli-python-ci.yml'
 
 jobs:
   lint:

.github/workflows/docs-llms-txt-check.yml

@@ -6,10 +6,13 @@ name: docs - llms.txt check
 #   python scripts/check-llms-txt-coverage.py           # read-only
 #   python scripts/check-llms-txt-coverage.py --write   # scaffold placeholders
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# manual runs remain standalone.
 on:
-  workflow_call:
+  pull_request:
+    paths:
+      - 'docs/**/*.mdx'
+      - 'docs/llms.txt'
+      - 'scripts/check-llms-txt-coverage.py'
+      - 'scripts/llms-txt-ignore.txt'
   workflow_dispatch: {}
 
 permissions:

.github/workflows/openclaw-cd.yml

@@ -1,35 +1,21 @@
 name: Publish @mem0/openclaw-mem0 📦 to npm
 
-# Dispatched by release.yml (Release Router) when a release tagged
-# openclaw-v* is published. Can also be dispatched manually to re-publish
-# a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. openclaw-v0.5.0)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish @mem0/openclaw-mem0 📦 to npm
-    if: startsWith(inputs.tag, 'openclaw-v')
+    if: startsWith(github.event.release.tag_name, 'openclaw-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
     defaults:
       run:
-        working-directory: integrations/openclaw
+        working-directory: openclaw
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Install pnpm
         uses: pnpm/action-setup@v4
@@ -42,7 +28,7 @@ jobs:
           node-version: '22'
           registry-url: 'https://registry.npmjs.org'
           cache: 'pnpm'
-          cache-dependency-path: integrations/openclaw/pnpm-lock.yaml
+          cache-dependency-path: openclaw/pnpm-lock.yaml
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -52,7 +38,7 @@ jobs:
 
       - name: Publish to npm
         run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
             PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
             npx npm@latest publish --provenance --access public --tag "$PREID"
           else

.github/workflows/openclaw-checks.yml

@@ -1,15 +1,16 @@
 name: openclaw checks
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main and manual runs remain standalone.
 on:
   workflow_dispatch:
   push:
     branches: [main]
     paths:
-      - 'integrations/openclaw/**'
+      - 'openclaw/**'
+      - '.github/workflows/openclaw-checks.yml'
+  pull_request:
+    paths:
+      - 'openclaw/**'
       - '.github/workflows/openclaw-checks.yml'
-  workflow_call:
 
 jobs:
   lint:
@@ -27,13 +28,13 @@ jobs:
         with:
           node-version: 20
           cache: 'pnpm'
-          cache-dependency-path: integrations/openclaw/pnpm-lock.yaml
+          cache-dependency-path: openclaw/pnpm-lock.yaml
 
       - name: Install dependencies
-        run: cd integrations/openclaw && pnpm install --frozen-lockfile
+        run: cd openclaw && pnpm install --frozen-lockfile
 
       - name: Type check
-        run: cd integrations/openclaw && pnpm exec tsc --noEmit
+        run: cd openclaw && pnpm exec tsc --noEmit
 
   test:
     runs-on: ubuntu-latest
@@ -53,20 +54,20 @@ jobs:
         with:
           node-version: ${{ matrix.node-version }}
           cache: 'pnpm'
-          cache-dependency-path: integrations/openclaw/pnpm-lock.yaml
+          cache-dependency-path: openclaw/pnpm-lock.yaml
 
       - name: Install dependencies
-        run: cd integrations/openclaw && pnpm install --frozen-lockfile
+        run: cd openclaw && pnpm install --frozen-lockfile
 
       - name: Run tests with coverage
-        run: cd integrations/openclaw && pnpm exec vitest run --coverage
+        run: cd openclaw && pnpm exec vitest run --coverage
 
       - name: Upload coverage to Codecov
         if: matrix.node-version == 20
         uses: codecov/codecov-action@v4
         with:
           flags: openclaw
-          directory: integrations/openclaw/coverage
+          directory: openclaw/coverage
         env:
           CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
 
@@ -85,15 +86,15 @@ jobs:
         with:
           node-version: 20
           cache: 'pnpm'
-          cache-dependency-path: integrations/openclaw/pnpm-lock.yaml
+          cache-dependency-path: openclaw/pnpm-lock.yaml
 
       - name: Install dependencies
-        run: cd integrations/openclaw && pnpm install --frozen-lockfile
+        run: cd openclaw && pnpm install --frozen-lockfile
 
       - name: Build
-        run: cd integrations/openclaw && pnpm build
+        run: cd openclaw && pnpm build
 
       - name: Verify dist output exists
         run: |
-          test -f integrations/openclaw/dist/index.js || (echo "Build output missing: dist/index.js" && exit 1)
-          test -f integrations/openclaw/dist/index.d.ts || (echo "Build output missing: dist/index.d.ts" && exit 1)
+          test -f openclaw/dist/index.js || (echo "Build output missing: dist/index.js" && exit 1)
+          test -f openclaw/dist/index.d.ts || (echo "Build output missing: dist/index.d.ts" && exit 1)

.github/workflows/opencode-plugin-cd.yml

@@ -1,35 +1,21 @@
 name: Publish @mem0/opencode-plugin 📦 to npm
 
-# Dispatched by release.yml (Release Router) when a release tagged
-# opencode-v* is published. Can also be dispatched manually to re-publish
-# a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. opencode-v0.2.0)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish @mem0/opencode-plugin 📦 to npm
-    if: startsWith(inputs.tag, 'opencode-v')
+    if: startsWith(github.event.release.tag_name, 'opencode-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
     defaults:
       run:
-        working-directory: integrations/mem0-plugin/.opencode-plugin
+        working-directory: mem0-plugin/.opencode-plugin
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Install Bun
         uses: oven-sh/setup-bun@v2
@@ -50,7 +36,7 @@ jobs:
 
       - name: Publish to npm
         run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
             PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
             npx npm@latest publish --provenance --access public --tag "$PREID"
           else

.github/workflows/opencode-plugin-checks.yml

@@ -1,22 +1,23 @@
 name: opencode-plugin checks
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main and manual runs remain standalone.
 on:
   workflow_dispatch:
   push:
     branches: [main]
     paths:
-      - 'integrations/mem0-plugin/.opencode-plugin/**'
+      - 'mem0-plugin/.opencode-plugin/**'
+      - '.github/workflows/opencode-plugin-checks.yml'
+  pull_request:
+    paths:
+      - 'mem0-plugin/.opencode-plugin/**'
       - '.github/workflows/opencode-plugin-checks.yml'
-  workflow_call:
 
 jobs:
   build:
     runs-on: ubuntu-latest
     defaults:
       run:
-        working-directory: integrations/mem0-plugin/.opencode-plugin
+        working-directory: mem0-plugin/.opencode-plugin
     steps:
       - uses: actions/checkout@v4
 

.github/workflows/pi-agent-plugin-cd.yml

@@ -1,60 +0,0 @@
-name: Publish @mem0/pi-agent-plugin 📦 to npm
-
-# Dispatched by release.yml (Release Router) when a release tagged
-# pi-agent-v* is published. Can also be dispatched manually to re-publish
-# a tag.
-on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. pi-agent-v0.1.1)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
-
-jobs:
-  build-n-publish:
-    name: Build and publish @mem0/pi-agent-plugin 📦 to npm
-    if: startsWith(inputs.tag, 'pi-agent-v')
-    runs-on: ubuntu-latest
-    permissions:
-      id-token: write
-    defaults:
-      run:
-        working-directory: integrations/pi-agent-plugin
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
-
-      - name: Install pnpm
-        uses: pnpm/action-setup@v4
-        with:
-          version: 9
-
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: '22'
-          registry-url: 'https://registry.npmjs.org'
-          cache: 'pnpm'
-          cache-dependency-path: integrations/pi-agent-plugin/pnpm-lock.yaml
-
-      - name: Install dependencies
-        run: pnpm install --frozen-lockfile
-
-      - name: Build
-        run: pnpm build
-
-      - name: Publish to npm
-        run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
-            PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
-            npx npm@latest publish --provenance --access public --tag "$PREID"
-          else
-            npx npm@latest publish --provenance --access public
-          fi

.github/workflows/pi-agent-plugin-checks.yml

@@ -1,92 +0,0 @@
-name: pi-agent-plugin checks
-
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main and manual runs remain standalone.
-on:
-  workflow_dispatch:
-  push:
-    branches: [main]
-    paths:
-      - 'integrations/pi-agent-plugin/**'
-      - '.github/workflows/pi-agent-plugin-checks.yml'
-  workflow_call:
-
-jobs:
-  lint:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Install pnpm
-        uses: pnpm/action-setup@v4
-        with:
-          version: 9
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: 20
-          cache: 'pnpm'
-          cache-dependency-path: integrations/pi-agent-plugin/pnpm-lock.yaml
-
-      - name: Install dependencies
-        run: cd integrations/pi-agent-plugin && pnpm install --frozen-lockfile
-
-      - name: Type check
-        run: cd integrations/pi-agent-plugin && pnpm exec tsc --noEmit
-
-  test:
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        node-version: [20, 22]
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Install pnpm
-        uses: pnpm/action-setup@v4
-        with:
-          version: 9
-
-      - name: Setup Node.js ${{ matrix.node-version }}
-        uses: actions/setup-node@v4
-        with:
-          node-version: ${{ matrix.node-version }}
-          cache: 'pnpm'
-          cache-dependency-path: integrations/pi-agent-plugin/pnpm-lock.yaml
-
-      - name: Install dependencies
-        run: cd integrations/pi-agent-plugin && pnpm install --frozen-lockfile
-
-      - name: Run tests
-        run: cd integrations/pi-agent-plugin && pnpm exec vitest run
-
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Install pnpm
-        uses: pnpm/action-setup@v4
-        with:
-          version: 9
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: 20
-          cache: 'pnpm'
-          cache-dependency-path: integrations/pi-agent-plugin/pnpm-lock.yaml
-
-      - name: Install dependencies
-        run: cd integrations/pi-agent-plugin && pnpm install --frozen-lockfile
-
-      - name: Build
-        run: cd integrations/pi-agent-plugin && pnpm build
-
-      - name: Verify dist output exists
-        run: |
-          test -f integrations/pi-agent-plugin/dist/index.js || (echo "Build output missing: dist/index.js" && exit 1)
-          test -f integrations/pi-agent-plugin/dist/index.d.ts || (echo "Build output missing: dist/index.d.ts" && exit 1)
-          test -f integrations/pi-agent-plugin/dist/entry.js || (echo "Build output missing: dist/entry.js" && exit 1)
-          test -f integrations/pi-agent-plugin/dist/entry.d.ts || (echo "Build output missing: dist/entry.d.ts" && exit 1)

.github/workflows/release.yml

@@ -1,68 +0,0 @@
-name: Release Router 🚦
-
-# Single entry point for all release publishing.
-#
-# Package CD workflows no longer listen to release events themselves — this
-# router inspects the release tag and dispatches only the matching pipeline,
-# so each release produces one routed run instead of one real run plus seven
-# skipped ones.
-#
-# Re-publishing a release (e.g. after fixing registry settings) does NOT
-# require deleting and recreating it anymore — manually dispatch the
-# package's CD workflow from the tag instead:
-#
-#   gh workflow run <package>-cd.yml --ref refs/tags/<tag> -f tag=<tag>
-#
-# Note: dispatching runs the workflow file as it exists at the given ref, so
-# this router can only dispatch tags created after the workflow_dispatch
-# conversion landed on main. For older tags, dispatch manually from main.
-
-on:
-  release:
-    types: [published]
-
-permissions:
-  actions: write
-
-jobs:
-  route:
-    name: Route ${{ github.event.release.tag_name }} to its CD pipeline
-    runs-on: ubuntu-latest
-    steps:
-      - name: Match tag prefix to CD workflow
-        id: match
-        env:
-          TAG: ${{ github.event.release.tag_name }}
-        run: |
-          # Specific package prefixes first; the bare v* (Python SDK) arm
-          # must stay last so prefixed tags that also start with 'v'
-          # (vercel-ai-v*) can never be routed to the Python pipeline.
-          case "$TAG" in
-            ts-v*)        workflow="ts-sdk-cd.yml" ;;
-            cli-node-v*)  workflow="cli-node-cd.yml" ;;
-            cli-v*)       workflow="cli-python-cd.yml" ;;
-            vercel-ai-v*) workflow="vercel-ai-cd.yml" ;;
-            openclaw-v*)  workflow="openclaw-cd.yml" ;;
-            opencode-v*)  workflow="opencode-plugin-cd.yml" ;;
-            pi-agent-v*)  workflow="pi-agent-plugin-cd.yml" ;;
-            v*)           workflow="cd.yml" ;;
-            *)
-              echo "::error::Release tag '$TAG' does not match any known package prefix — nothing will be published. See the tag prefix table in AGENTS.md."
-              exit 1
-              ;;
-          esac
-          echo "workflow=$workflow" >> "$GITHUB_OUTPUT"
-          echo ":outbox_tray: Routed \`$TAG\` → \`$workflow\`" >> "$GITHUB_STEP_SUMMARY"
-
-      - name: Dispatch ${{ steps.match.outputs.workflow }}
-        env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          TAG: ${{ github.event.release.tag_name }}
-        run: |
-          # --ref points at the tag so the dispatched run builds (and signs
-          # provenance for) the exact tagged commit.
-          gh workflow run "${{ steps.match.outputs.workflow }}" \
-            --repo "$GITHUB_REPOSITORY" \
-            --ref "refs/tags/$TAG" \
-            -f tag="$TAG" \
-            -f prerelease="${{ github.event.release.prerelease }}"

.github/workflows/ts-sdk-cd.yml

@@ -1,24 +1,13 @@
 name: Publish mem0ai 📦 to npm
 
-# Dispatched by release.yml (Release Router) when a release tagged ts-v* is
-# published. Can also be dispatched manually to re-publish a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. ts-v2.1.0)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish mem0ai 📦 to npm
-    if: startsWith(inputs.tag, 'ts-v')
+    if: startsWith(github.event.release.tag_name, 'ts-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
@@ -27,8 +16,6 @@ jobs:
         working-directory: mem0-ts
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Install pnpm
         uses: pnpm/action-setup@v4
@@ -51,7 +38,7 @@ jobs:
 
       - name: Publish to npm
         run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
             PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
             npx npm@latest publish --provenance --access public --tag "$PREID"
           else

.github/workflows/ts-sdk-ci.yml

@@ -1,14 +1,14 @@
 name: TypeScript SDK CI
 
-# On PRs this is invoked by ci-gate.yml (the single required check);
-# push-to-main runs remain standalone.
 on:
   push:
     branches: [main]
     paths:
       - 'mem0-ts/**'
       - '.github/workflows/ts-sdk-ci.yml'
-  workflow_call:
+  pull_request:
+    paths:
+      - 'mem0-ts/**'
 
 jobs:
   check_changes:

.github/workflows/vercel-ai-cd.yml

@@ -1,35 +1,21 @@
 name: Publish @mem0/vercel-ai-provider 📦 to npm
 
-# Dispatched by release.yml (Release Router) when a release tagged
-# vercel-ai-v* is published. Can also be dispatched manually to re-publish
-# a tag.
 on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: 'Release tag to build and publish (e.g. vercel-ai-v2.0.7)'
-        required: true
-        type: string
-      prerelease:
-        description: 'Publish under the version preid dist-tag instead of latest'
-        required: false
-        type: boolean
-        default: false
+  release:
+    types: [published]
 
 jobs:
   build-n-publish:
     name: Build and publish @mem0/vercel-ai-provider 📦 to npm
-    if: startsWith(inputs.tag, 'vercel-ai-v')
+    if: startsWith(github.event.release.tag_name, 'vercel-ai-v')
     runs-on: ubuntu-latest
     permissions:
       id-token: write
     defaults:
       run:
-        working-directory: integrations/vercel-ai-sdk
+        working-directory: vercel-ai-sdk
     steps:
       - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.tag }}
 
       - name: Install pnpm
         uses: pnpm/action-setup@v4
@@ -42,7 +28,7 @@ jobs:
           node-version: '22'
           registry-url: 'https://registry.npmjs.org'
           cache: 'pnpm'
-          cache-dependency-path: integrations/vercel-ai-sdk/pnpm-lock.yaml
+          cache-dependency-path: vercel-ai-sdk/pnpm-lock.yaml
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -52,7 +38,7 @@ jobs:
 
       - name: Publish to npm
         run: |
-          if [ "${{ inputs.prerelease }}" = "true" ]; then
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
             PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
             npx npm@latest publish --provenance --access public --tag "$PREID"
           else

.gitignore

@@ -189,5 +189,3 @@ eval/
 qdrant_storage/
 .crossnote
 testing.ipynb
-.weave/
-

.gitmodules

@@ -1,4 +0,0 @@
-[submodule "evaluation"]
-	path = evaluation
-	url = https://github.com/mem0ai/memory-benchmarks
-	branch = main

AGENTS.md

@@ -12,7 +12,7 @@ This file provides context for AI coding assistants (Claude Code, Cursor, GitHub
 
 ## Repository Structure
 
-This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs, servers, plugins, and documentation.
+This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs, servers, plugins, documentation, and evaluation tooling.
 
 ### Key Directories
 
@@ -22,18 +22,17 @@ This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs,
 | `mem0-ts/` | TypeScript SDK (`mem0ai` on npm) — client + OSS memory |
 | `cli/python/` | Python CLI (`mem0-cli` on PyPI) — Typer-based, entry point `mem0` |
 | `cli/node/` | Node CLI (`@mem0/cli` on npm) — Commander-based, entry point `mem0` |
-| `integrations/` | **Agent & editor integrations**, one directory per integration (see "Adding a New Integration") |
-| `integrations/mem0-plugin/` | AI editor plugins (Claude Code, Cursor, Codex) — MCP server connection, lifecycle hooks, skills. Contains nested `.opencode-plugin/` (`@mem0/opencode-plugin`) |
-| `integrations/openclaw/` | `@mem0/openclaw-mem0` — OpenClaw plugin for Claude Code / AI editors |
-| `integrations/pi-agent-plugin/` | `@mem0/pi-agent-plugin` — Pi Agent plugin |
-| `integrations/vercel-ai-sdk/` | `@mem0/vercel-ai-provider` — Vercel AI SDK memory provider |
+| `vercel-ai-sdk/` | `@mem0/vercel-ai-provider` — Vercel AI SDK memory provider |
+| `openclaw/` | `@mem0/openclaw-mem0` — OpenClaw plugin for Claude Code / AI editors |
 | `server/` | FastAPI REST server for self-hosted Mem0 (Docker: FastAPI + PostgreSQL/pgvector + Neo4j) |
 | `openmemory/` | Self-hosted memory platform — `api/` (FastAPI + Alembic + MCP server) and `ui/` (Next.js 15 + React 19) |
-| `skills/` | Claude Code skill definitions. Reference skills (SDK knowledge, always-on): `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/`. Pipeline skills (run on demand): `mem0-integrate/`, `mem0-test-integration/`, `mem0-oss-to-platform/` |
+| `mem0-plugin/` | AI editor plugins (Claude Code, Cursor, Codex) — MCP server connection, lifecycle hooks, skills |
+| `skills/` | Claude Code skill definitions. Reference skills (SDK knowledge, always-on): `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/`. Pipeline skills (run on demand): `mem0-integrate/`, `mem0-test-integration/` |
 | `docs/` | Documentation site (Mintlify) |
 | `tests/` | Python SDK tests (pytest) |
-| `evaluation/` | Submodule → [`mem0ai/memory-benchmarks`](https://github.com/mem0ai/memory-benchmarks) — benchmarking (LOCOMO, LongMemEval, BEAM) lives in that repo |
-| `examples/` | Sample projects & runnable demos — apps, Chrome extension, multi-agent patterns, and Jupyter notebooks (`notebooks/`) |
+| `evaluation/` | Benchmarking framework — LOCOMO evals, experiment runner, score generation |
+| `examples/` | Sample projects — demo apps, Chrome extension, multi-agent patterns |
+| `cookbooks/` | Jupyter notebooks — customer support chatbot, AutoGen integration |
 | `pr-reviews/` | Pull request review materials |
 | `scripts/` | Repo-wide utility scripts (e.g., `check-llms-txt-coverage.py` for docs/llms.txt sync) |
 
@@ -50,8 +49,8 @@ mem0 (Python SDK)          mem0-ts (TypeScript SDK)
 
 cli/python/ ──▶ mem0ai (optional, for OSS mode)
 cli/node/   ──▶ mem0ai (npm, for API calls)
-integrations/vercel-ai-sdk/ ──▶ ai, @ai-sdk/* providers
-integrations/openclaw/ ──▶ mem0ai (npm)
+vercel-ai-sdk/ ──▶ ai, @ai-sdk/* providers
+openclaw/   ──▶ mem0ai (npm)
 ```
 
 ## Development Setup
@@ -74,8 +73,8 @@ pre-commit install                # install git hooks
 # TypeScript packages
 cd mem0-ts && pnpm install        # TS SDK
 cd cli/node && pnpm install       # Node CLI
-cd integrations/vercel-ai-sdk && pnpm install  # Vercel AI provider
-cd integrations/openclaw && pnpm install       # OpenClaw plugin
+cd vercel-ai-sdk && pnpm install  # Vercel AI provider
+cd openclaw && pnpm install       # OpenClaw plugin
 ```
 
 ## Build, Lint, and Test Commands
@@ -163,10 +162,10 @@ pnpm run dev                       # tsx src/index.ts (development)
 - **Test:** vitest (not jest)
 - **Framework:** Commander + Chalk + ora + cli-table3
 
-### Vercel AI SDK Provider (`integrations/vercel-ai-sdk/`)
+### Vercel AI SDK Provider (`vercel-ai-sdk/`)
 
 ```bash
-cd integrations/vercel-ai-sdk
+cd vercel-ai-sdk
 pnpm install
 pnpm run build                     # tsup
 pnpm run lint                      # eslint
@@ -181,10 +180,10 @@ pnpm run test:node                 # vitest (node runtime)
 - **Lint:** ESLint + Prettier
 - **Test:** jest + vitest (edge/node configs)
 
-### OpenClaw Plugin (`integrations/openclaw/`)
+### OpenClaw Plugin (`openclaw/`)
 
 ```bash
-cd integrations/openclaw
+cd openclaw
 pnpm install
 pnpm run build                     # tsup
 pnpm run test                      # vitest run
@@ -246,19 +245,18 @@ make docs                          # or: cd docs && mintlify dev
 - **API spec:** `docs/openapi.json`
 - **Structure:** `api-reference/`, `open-source/`, `platform/`, `integrations/`, `cookbooks/`, `core-concepts/`
 
-### Evaluation / Benchmarking
-
-Benchmarking lives in the external [`mem0ai/memory-benchmarks`](https://github.com/mem0ai/memory-benchmarks) repo (LOCOMO + LongMemEval + BEAM). The in-repo `evaluation/` path is a **git submodule** pinned to that repo's `main` — populate it with `git submodule update --init evaluation` (or clone mem0 with `--recurse-submodules`), or clone the benchmarks repo standalone:
+### Evaluation (`evaluation/`)
 
 ```bash
-git clone https://github.com/mem0ai/memory-benchmarks.git
-cd memory-benchmarks
-pip install -r requirements.txt
-
-# Run a benchmark (Mem0 Cloud; use docker compose for OSS)
-python -m benchmarks.locomo.run --project-name my-test --backend cloud --mem0-api-key $MEM0_API_KEY
-python -m benchmarks.longmemeval.run --project-name my-test --backend cloud --mem0-api-key $MEM0_API_KEY --all-questions
-python -m benchmarks.beam.run --project-name my-test --backend cloud --mem0-api-key $MEM0_API_KEY --chat-sizes 100K --conversations 0-9
+cd evaluation
+make run-mem0-add                  # Run mem0 add experiments
+make run-mem0-search               # Run mem0 search experiments
+make run-mem0-plus-add             # With graph memory
+make run-mem0-plus-search          # With graph memory
+make run-rag                       # RAG baseline
+make run-full-context              # Full context baseline
+make run-langmem                   # LangMem comparison
+make run-openai                    # OpenAI comparison
 ```
 
 ## Core APIs
@@ -344,8 +342,8 @@ python -m benchmarks.beam.run --project-name my-test --backend cloud --mem0-api-
 |---------|--------|-----------|---------------|
 | `mem0-ts/` | — | Prettier | jest |
 | `cli/node/` | Biome | Biome | vitest |
-| `integrations/vercel-ai-sdk/` | ESLint | Prettier | jest + vitest |
-| `integrations/openclaw/` | — | — | vitest |
+| `vercel-ai-sdk/` | ESLint | Prettier | jest + vitest |
+| `openclaw/` | — | — | vitest |
 
 ### Type Checking
 
@@ -383,14 +381,14 @@ Model Context Protocol support in multiple places:
 
 - **Remote:** MCP server at `mcp.mem0.ai`
 - **Local:** MCP server in `openmemory/api/` (FastAPI-based)
-- **Plugin:** MCP tools in `integrations/mem0-plugin/` — 9 tools: `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`
+- **Plugin:** MCP tools in `mem0-plugin/` — 9 tools: `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`
 
 ### Plugin & Skills System
 
-- `integrations/mem0-plugin/` provides integrations for Claude Code, Cursor, and Codex via MCP server connections and lifecycle hooks for automatic memory capture.
+- `mem0-plugin/` provides integrations for Claude Code, Cursor, and Codex via MCP server connections and lifecycle hooks for automatic memory capture.
 - `skills/` contains structured skill definitions for AI agents, split into two categories:
   - **Reference skills** (always-on SDK knowledge): `mem0` (Python + TS SDKs, framework integrations), `mem0-cli` (terminal workflows), `mem0-vercel-ai-sdk` (Vercel AI provider).
-  - **Pipeline skills** (run on demand): `mem0-integrate` wires Mem0 into an existing repo via a TDD pipeline; `mem0-test-integration` verifies what the integrator produced on the same branch (the two are loosely coupled via `.mem0-integration/` artifacts); `mem0-oss-to-platform` migrates an existing project from Mem0 OSS to the hosted Platform SDK (plan, then execute on approval).
+  - **Pipeline skills** (run on demand): `mem0-integrate` wires Mem0 into an existing repo via a TDD pipeline; `mem0-test-integration` verifies what the integrator produced on the same branch. The two are loosely coupled via `.mem0-integration/` artifacts.
 
 ### Adding a New Provider
 
@@ -404,44 +402,23 @@ To add a new LLM, embedding, vector store, or reranker provider:
 6. Add any new dependencies to the appropriate optional group in `pyproject.toml` (never to core `dependencies`)
 7. Follow the exact pattern of existing providers in the same category — match method signatures, error handling, and config structure
 
-### Adding a New Integration
-
-Agent/editor integrations live under `integrations/`. Each is a self-contained directory (its own `package.json`/lockfile, build, and tests). To add one:
-
-1. Create `integrations/<name>/` and build the integration there.
-2. If it publishes to a registry, set `repository.directory: "integrations/<name>"` in its `package.json` so npm provenance links to the correct subdirectory.
-3. Add CI/CD under `.github/workflows/` (`<name>-checks.yml`, `<name>-cd.yml`). Use `integrations/<name>` in `paths:` triggers, `working-directory`, and `cache-dependency-path`. Register the release tag prefix in the `case` block in `release.yml` (keep the bare `v*` arm last). Keep workflow **filenames** stable — npm OIDC trusted publishing is pinned to repo + workflow filename.
-4. If it is a Claude Code / editor marketplace plugin, register its path in the five `marketplace.json` files (root + `.claude-plugin/`, `.cursor-plugin/`, `.codex-plugin/`, `.agents/plugins/`).
-5. Document it under `docs/integrations/` and add the page to `docs/docs.json` and `docs/llms.txt`.
-6. Add rows to the "Key Directories" table and the CI/CD tables in this file.
-
 ## CI/CD
 
 ### CI Workflows (automated testing)
 
-PR testing is orchestrated by a single entry point: **`ci-gate.yml` (CI Gate)** runs on every PR, detects which packages changed, and invokes only the relevant package workflows below as reusable workflows (`workflow_call`). Its final **`CI Gate`** job aggregates the results (skipped pipelines pass; failed or cancelled ones fail) and is the **only status check that needs to be required** in branch protection. Package workflows keep their own push-to-main and manual triggers; their `pull_request` triggers moved into the gate's path filters.
-
-| Workflow | File | Standalone Triggers | Tests |
-|----------|------|---------------------|-------|
-| CI Gate | `ci-gate.yml` | All PRs | Routes to and aggregates the workflows below |
-| Python SDK | `ci.yml` | Push to main | Ruff lint + pytest on Python 3.10, 3.11, 3.12 |
-| TypeScript SDK | `ts-sdk-ci.yml` | Push to main (on `mem0-ts/`) | Prettier + build + jest on Node 20, 22 |
-| Python CLI | `cli-python-ci.yml` | Push to main (on `cli/python/`), manual | Ruff lint + pytest + hatch build on Python 3.10, 3.11, 3.12 |
-| Node CLI | `cli-node-ci.yml` | Push to main (on `cli/node/`), manual | Biome lint + tsc + vitest + tsup build on Node 20, 22 |
-| OpenClaw | `openclaw-checks.yml` | Push to main (on `integrations/openclaw/`), manual | tsc + vitest (with Codecov) + tsup build on Node 20, 22 |
-| OpenCode Plugin | `opencode-plugin-checks.yml` | Push to main (on `integrations/mem0-plugin/.opencode-plugin/`), manual | Bun: tsc type-check + build + dist artifact check |
-| Pi Agent Plugin | `pi-agent-plugin-checks.yml` | Push to main (on `integrations/pi-agent-plugin/`), manual | tsc + vitest + tsup build (dist artifact check) on Node 20, 22 |
-| docs llms.txt | `docs-llms-txt-check.yml` | Manual | `docs/llms.txt` coverage check |
-
-When adding a new package CI workflow: give it `workflow_call` (plus `push`/`workflow_dispatch` as needed, but no `pull_request` trigger), then register it in `ci-gate.yml` — a path filter under the `changes` job, a call job, and an entry in the gate job's `needs` list.
+| Workflow | File | Triggers | Tests |
+|----------|------|----------|-------|
+| Python SDK | `ci.yml` | Push to main, PRs on `mem0/`, `tests/`, `pyproject.toml` | Ruff lint + pytest on Python 3.10, 3.11, 3.12 |
+| TypeScript SDK | `ts-sdk-ci.yml` | Push to main, PRs on `mem0-ts/` | Prettier + build + jest on Node 20, 22 |
+| Python CLI | `cli-python-ci.yml` | Push to `cli/python/`, PRs, manual | Ruff lint + pytest + hatch build on Python 3.10, 3.11, 3.12 |
+| Node CLI | `cli-node-ci.yml` | Push to `cli/node/`, PRs, manual | Biome lint + tsc + vitest + tsup build on Node 20, 22 |
+| OpenClaw | `openclaw-checks.yml` | Push to `openclaw/`, PRs, manual | tsc + vitest (with Codecov) + tsup build on Node 20, 22 |
+| OpenCode Plugin | `opencode-plugin-checks.yml` | Push to `mem0-plugin/.opencode-plugin/`, PRs, manual | Bun: tsc type-check + build + dist artifact check |
 
 ### CD Workflows (automated publishing)
 
-Publishing is routed through a single entry point: **`release.yml` (Release Router)** is the only workflow that listens to `release: published` events. It matches the release tag prefix and dispatches the corresponding package workflow via `workflow_dispatch`, so each release produces exactly one routed run (no skipped runs from the other pipelines).
-
 | Workflow | File | Tag Prefix | Target |
 |----------|------|------------|--------|
-| Release Router | `release.yml` | (all releases) | dispatches the matching workflow below |
 | Python SDK | `cd.yml` | `v*` | PyPI (`mem0ai`) |
 | TypeScript SDK | `ts-sdk-cd.yml` | `ts-v*` | npm (`mem0ai`) |
 | Python CLI | `cli-python-cd.yml` | `cli-v*` | PyPI (`mem0-cli`) |
@@ -449,13 +426,9 @@ Publishing is routed through a single entry point: **`release.yml` (Release Rout
 | Vercel AI SDK | `vercel-ai-cd.yml` | `vercel-ai-v*` | npm (`@mem0/vercel-ai-provider`) |
 | OpenClaw | `openclaw-cd.yml` | `openclaw-v*` | npm (`@mem0/openclaw-mem0`) |
 | OpenCode Plugin | `opencode-plugin-cd.yml` | `opencode-v*` | npm (`@mem0/opencode-plugin`) |
-| Pi Agent Plugin | `pi-agent-plugin-cd.yml` | `pi-agent-v*` | npm (`@mem0/pi-agent-plugin`) |
 
-- Package CD workflows are `workflow_dispatch`-only (inputs: `tag`, `prerelease`); they check out and build the given tag. Registry trusted-publisher settings stay pinned to each package's own workflow filename.
 - All publishing uses **OIDC trusted publishing** — no tokens or secrets required.
 - First publish of a new npm package must be done manually; OIDC works for subsequent versions.
-- To re-publish a release (e.g. after a registry settings fix), do **not** delete/recreate the GitHub release — manually dispatch the package workflow instead: `gh workflow run <package>-cd.yml --ref refs/tags/<tag> -f tag=<tag>`.
-- When adding a new package: add its CD workflow (`workflow_dispatch` with `tag`/`prerelease` inputs), then register its tag prefix in the `case` block in `release.yml`. Keep the bare `v*` arm last.
 
 ### Utility Workflows
 

CONTRIBUTING.md

@@ -1,157 +1,72 @@
-# Contributing to Mem0
+# Contributing to mem0
 
-First off, thank you for taking the time to contribute! 🎉 Mem0 is a
-community-driven project and we welcome contributions of all kinds — bug fixes,
-new features, documentation, examples, and integrations.
+Let us make contribution easy, collaborative and fun.
 
-Mem0 is a polyglot monorepo, and this guide covers contributing to both the
-**Python SDK** and the **TypeScript SDK** (and the rest of the repository).
+## Submit your Contribution through PR
 
-## Before You Start
+To make a contribution, follow these steps:
 
-### 1. Open an Issue First
+1. Fork and clone this repository
+2. Do the changes on your fork with dedicated feature branch `feature/f1`
+3. If you modified the code (new feature or bug-fix), please add tests for it
+4. Include proper documentation / docstring and examples to run the feature
+5. Ensure that all tests pass
+6. Submit a pull request
 
-**Always open an issue before opening a pull request.** This lets us discuss the
-change, avoid duplicate effort, and agree on the approach before you invest time
-in code.
+For more details about pull requests, please read [GitHub's guides](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request).
 
-- Search [existing issues](https://github.com/mem0ai/mem0/issues) first to see if
-  your bug or idea already exists.
-- If it doesn't, open a
-  [bug report](https://github.com/mem0ai/mem0/issues/new?template=bug_report.yml) or
-  [feature request](https://github.com/mem0ai/mem0/issues/new?template=feature_request.yml).
-- For anything beyond a trivial fix, wait for a maintainer to confirm the approach
-  before starting significant work.
 
-Every pull request must link to an issue using `Closes #<issue-number>`.
+### 📦 Development Environment
 
-### 2. Sign the Contributor License Agreement (CLA)
-
-**We cannot accept or merge any pull request until you have signed our Contributor
-License Agreement (CLA).**
-
-When you open your first PR, the CLA bot will automatically comment with a link to
-sign. Signing takes less than a minute and only needs to be done once. Pull
-requests from contributors who have not signed the CLA will be blocked from
-merging.
-
-## Repository Layout
-
-The two most common contribution targets are the SDKs:
-
-| Package               | Path       | Language     | Package manager |
-| --------------------- | ---------- | ------------ | --------------- |
-| Python SDK (`mem0ai`) | `mem0/`    | Python 3.9+  | `hatch`         |
-| TypeScript SDK (`mem0ai`) | `mem0-ts/` | TypeScript | `pnpm`        |
-
-Other packages include the CLIs (`cli/python/`, `cli/node/`), integrations
-(`integrations/`), the self-hosted `server/`, `openmemory/`, and the docs site
-(`docs/`). See [AGENTS.md](./AGENTS.md) for a full map of the repository.
-
-## Development Workflow
-
-1. **Fork** the repository and **clone** your fork.
-2. Create a **feature branch** from `main` (e.g. `feature/my-new-feature` or
-   `fix/issue-1234`).
-3. Make your changes — add **tests**, **documentation**, and **examples** as
-   appropriate.
-4. Run **linting and tests** for every package you touched (see below).
-5. Commit using [Conventional Commits](https://www.conventionalcommits.org/)
-   (e.g. `feat:`, `fix:`, `docs:`, `refactor:`, `test:`).
-6. Push and open a **pull request** against `main`, linking the issue with
-   `Closes #<number>` and filling out the
-   [PR template](./.github/PULL_REQUEST_TEMPLATE.md).
-
-### Contributing to the Python SDK (`mem0/`)
-
-We use [`hatch`](https://hatch.pypa.io/latest/install/) to manage environments.
-**Do not use `pip` or `conda` for dependency management.**
+We use `hatch` for managing development environments. To set up:
 
 ```bash
-# Activate a dev environment (3.9 / 3.10 / 3.11 / 3.12)
-hatch shell dev_py_3_11
+# Activate environment for specific Python version:
+hatch shell dev_py_3_9   # Python 3.9
+hatch shell dev_py_3_10  # Python 3.10  
+hatch shell dev_py_3_11  # Python 3.11
+hatch shell dev_py_3_12  # Python 3.12
 
-# Install pre-commit hooks (runs ruff + isort on commit)
-pre-commit install
-
-# Lint, format, and sort imports
-make lint
-make format
-make sort
-
-# Run the test suite (run `make install_all` first if deps are missing)
+# The environment will automatically install all dev dependencies
+# Run tests within the activated shell:
 make test
 ```
 
-- **Linter / formatter:** Ruff (line length **120**)
-- **Import sorting:** isort (`profile = "black"`)
-- **Tests:** pytest (in `tests/`)
+### 📌 Pre-commit
 
-See the full [Development guide](https://docs.mem0.ai/contributing/development) for
-environment details.
-
-### Contributing to the TypeScript SDK (`mem0-ts/`)
-
-We use [`pnpm`](https://pnpm.io/) (v10+) for all TypeScript packages. **Do not use
-`npm` or `yarn`.**
+To ensure our standards, make sure to install pre-commit before starting to contribute.
 
 ```bash
-cd mem0-ts
-pnpm install
-
-pnpm run build        # tsup (CJS + ESM)
-pnpm run test         # jest (all tests)
-pnpm run test:unit    # unit tests with coverage
+pre-commit install
 ```
 
-- **Build:** tsup
-- **Formatter:** Prettier
-- **Tests:** jest
-- Always run type checking after changes: `pnpm run typecheck` (or `tsc --noEmit`).
-- Use ES module `import` syntax — never `require()`.
+### 🧪 Testing
 
-## Good Contribution Practices
+We use `pytest` to test our code across multiple Python versions. You can run tests using:
 
-- **Keep PRs small and focused.** One logical change per PR is easier to review and
-  merge.
-- **Follow existing patterns.** Match the style, structure, and conventions of the
-  code around you. Don't introduce new frameworks or abstractions without
-  discussion.
-- **Write tests** that would fail without your change — regression tests for bugs,
-  coverage for new features.
-- **Update documentation** in `docs/` for any user-facing change. New `.mdx` pages
-  must be added to `docs/llms.txt` (run
-  `python scripts/check-llms-txt-coverage.py --write` to scaffold entries).
-- **Add examples** when introducing new user-facing behavior.
-- **Run linters and tests locally** before pushing — CI re-runs them on every PR
-  via the CI Gate.
-- **Never commit secrets** — no `.env` files, API keys, or credentials.
-- **Don't add core dependencies lightly.** New Python dependencies belong in an
-  optional group in `pyproject.toml`, not the core `dependencies` list.
-- **Be responsive** to review feedback and keep your branch up to date with `main`.
+```bash
+# Run tests with default Python version
+make test
 
-## Pull Request Checklist
+# Test specific Python versions:
+make test-py-3.9   # Python 3.9 environment
+make test-py-3.10  # Python 3.10 environment
+make test-py-3.11  # Python 3.11 environment
+make test-py-3.12  # Python 3.12 environment
 
-Before requesting review, make sure:
+# When using hatch shells, run tests with:
+make test  # After activating a shell with hatch shell test_XX
+```
 
-- [ ] An issue exists and is linked with `Closes #<number>`
-- [ ] You have signed the CLA
-- [ ] Your code follows the project's style guidelines (lint passes)
-- [ ] You performed a self-review of your changes
-- [ ] Tests are added/updated and pass locally
-- [ ] Documentation is updated if needed
+Make sure that all tests pass across all supported Python versions before submitting a pull request.
 
-## Reporting Security Issues
+We look forward to your pull requests and can't wait to see your contributions!
 
-**Do not report security vulnerabilities through public issues or pull requests.**
-Please follow our [Security Policy](./SECURITY.md) to report them privately.
+### 🚀 Releasing
 
-## Releasing
+All packages are published automatically via GitHub Actions when a GitHub Release is created with the correct tag prefix.
 
-All packages are published automatically via GitHub Actions when a GitHub Release
-is created with the correct tag prefix.
-
-### Tag Prefixes
+#### Tag Prefixes
 
 | Package | Registry | Tag Prefix | Example |
 |---------|----------|------------|---------|
@@ -162,17 +77,15 @@ is created with the correct tag prefix.
 | `@mem0/vercel-ai-provider` | npm | `vercel-ai-v*` | `vercel-ai-v2.0.6` |
 | `@mem0/openclaw-mem0` | npm | `openclaw-v*` | `openclaw-v1.0.1` |
 
-### How to Release
+#### How to Release
 
 1. Bump the version in `pyproject.toml` (Python) or `package.json` (Node)
 2. Create a [GitHub Release](https://github.com/mem0ai/mem0/releases/new) with the matching tag prefix
 3. The correct workflow will trigger automatically — verify in the [Actions tab](https://github.com/mem0ai/mem0/actions)
 
-### Publishing Details
+#### Publishing Details
 
 - **PyPI packages** use OIDC trusted publishing via `pypa/gh-action-pypi-publish`
 - **npm packages** use OIDC trusted publishing via npm CLI (>= 11.5.1) — no tokens or secrets required
 - All workflows require `permissions: id-token: write` for OIDC authentication
 - First publish of a new npm package must be done manually; OIDC works for subsequent versions
-
-We look forward to your pull requests and can't wait to see your contributions!

LLM.md

@@ -1026,8 +1026,7 @@ def get_user_preferences(user_id: str):
 ### AutoGen Integration
 
 ```python
-# Mem0Teachability lives in examples/notebooks/helper/ — see examples/notebooks/mem0-autogen.ipynb
-from helper.mem0_teachability import Mem0Teachability
+from cookbooks.helper.mem0_teachability import Mem0Teachability
 from mem0 import Memory
 
 # Add memory capability to AutoGen agents

README.md

@@ -186,10 +186,9 @@ npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
 ```bash
 npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
 npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
-npx skills add https://github.com/mem0ai/mem0 --skill mem0-oss-to-platform
 ```
 
-Use `/mem0-integrate` to wire Mem0 into an existing repo via a test-first pipeline, then `/mem0-test-integration` to verify. Use `/mem0-oss-to-platform` to migrate an existing project from Mem0 OSS to the hosted Platform SDK. See the [skills catalog](./skills/) or [Vibecoding with Mem0](https://docs.mem0.ai/vibecoding) for the full picture.
+Use `/mem0-integrate` to wire Mem0 into an existing repo via a test-first pipeline, then `/mem0-test-integration` to verify. See the [skills catalog](./skills/) or [Vibecoding with Mem0](https://docs.mem0.ai/vibecoding) for the full picture.
 
 ### Basic Usage
 

SECURITY.md

@@ -1,48 +0,0 @@
-# Security Policy
-
-We take the security of Mem0 and our community seriously. Thank you for helping
-keep Mem0 and its users safe by disclosing vulnerabilities responsibly.
-
-## Reporting a Vulnerability
-
-Please **do not** report security vulnerabilities through public GitHub issues,
-pull requests, or discussions.
-
-If you believe you have found a security vulnerability in Mem0, please report it
-privately through one of the following channels:
-
-1. **GitHub Private Vulnerability Reporting** — open a
-   [private security advisory](https://github.com/mem0ai/mem0/security/advisories/new)
-   directly on this repository.
-2. **Email** the maintainers at **support@mem0.ai** with the subject line:
-
-   `SECURITY: Mem0 vulnerability report`
-
-To help us triage and resolve the issue quickly, please include as much of the
-following as you can:
-
-- Affected component or package (e.g. Python SDK, TypeScript SDK, server, OpenMemory)
-- Affected version, tag, or commit
-- Clear, step-by-step reproduction instructions
-- The security impact and a proof of concept, if available
-- Any suggested fix or mitigation
-
-## Response Process
-
-- We will acknowledge receipt of your report within **72 hours**.
-- We will work with you privately to confirm the issue and assess its impact.
-- Once a fix or mitigation is ready, we will coordinate a disclosure timeline
-  with you and credit you for the discovery, unless you prefer to remain anonymous.
-
-## Public Disclosure
-
-Please avoid sharing technical details of the vulnerability publicly until the
-maintainers have reviewed the issue and a fix or mitigation has been released. We
-are committed to resolving valid reports promptly and keeping you informed
-throughout the process.
-
-## Supported Versions
-
-We release security fixes against the latest published version of each package.
-Whenever possible, please reproduce the issue on the most recent release before
-reporting.

cli/node/CHANGELOG.md

@@ -5,30 +5,6 @@ All notable changes to `@mem0/cli` are documented here.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [0.2.9] — 2026-06-19
-
-### Security
-
-- Telemetry no longer passes the Mem0 API key to its child process via
-  command-line arguments. The context is now sent over stdin, so the key is no
-  longer visible in the process list (`ps`, `/proc/<pid>/cmdline`, Activity
-  Monitor). Fixes #4862.
-
-## [0.2.8] — 2026-06-01
-
-### Security
-
-- Pinned transitive dependencies via pnpm overrides to remediate high-severity CVEs:
-  - `jws` → 4.0.1 (CVE-2025-65945)
-  - `langsmith` → ^0.6.0 (CVE-2026-45134)
-  - `tar-fs` → ^2.1.4 (CVE-2025-48387, CVE-2025-59343)
-  - `picomatch` → ^2.3.2 (CVE-2026-33671)
-  - `minimatch` → ^3.1.3 / ^5.1.8 / ^9.0.7 (CVE-2026-27903, CVE-2026-27904, CVE-2026-26996)
-  - `path-to-regexp` → ^8.4.0 (CVE-2026-4926)
-  - `rollup` → ^4.59.0 (CVE-2026-27606)
-  - `glob` → ^10.5.0 (CVE-2025-64756)
-  - `@modelcontextprotocol/sdk` → ^1.25.4 (CVE-2025-66414, CVE-2026-0621)
-
 ## [0.2.7] — 2026-05-20
 
 ### Added

cli/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/cli",
-  "version": "0.2.9",
+  "version": "0.2.7",
   "description": "The official CLI for mem0 — the memory layer for AI agents",
   "type": "module",
   "bin": {
@@ -40,19 +40,8 @@
     "typescript": "^5.4.0",
     "tsup": "^8.0.0",
     "tsx": "^4.7.0",
-    "vite": "^6.0.0",
-    "vitest": "^4.1.0",
+    "vitest": "^1.5.0",
     "@biomejs/biome": "^1.7.0",
     "@types/node": "^20.0.0"
-  },
-  "pnpm": {
-    "overrides": {
-      "jws@4.0.0": "4.0.1",
-      "langsmith@<0.6.0": "^0.6.0",
-      "tar-fs@>=2.0.0 <2.1.4": "^2.1.4",
-      "picomatch@<2.3.2": "^2.3.2",
-      "postcss@<8.5.10": ">=8.5.10",
-      "esbuild": ">=0.28.1"
-    }
   }
 }

cli/node/pnpm-workspace.yaml

@@ -1,14 +0,0 @@
-packages:
-  - '.'
-
-onlyBuiltDependencies:
-  - "@biomejs/biome"
-  - esbuild
-
-overrides:
-  jws@4.0.0: 4.0.1
-  langsmith@<0.6.0: ^0.6.0
-  tar-fs@>=2.0.0 <2.1.4: ^2.1.4
-  picomatch@<2.3.2: ^2.3.2
-  "postcss@<8.5.10": ">=8.5.10"
-  "esbuild": ">=0.28.1"

cli/node/src/telemetry.ts

@@ -145,11 +145,11 @@ export function captureEvent(
 			anonDistinctIdToAlias: anonIdToAlias,
 		};
 
-		const child = spawn(process.execPath, [SENDER_SCRIPT], {
-			detached: true,
-			stdio: ["pipe", "ignore", "ignore"],
-		});
-		child.stdin?.end(JSON.stringify(context));
+		const child = spawn(
+			process.execPath,
+			[SENDER_SCRIPT, JSON.stringify(context)],
+			{ detached: true, stdio: "ignore" },
+		);
 		child.unref();
 	} catch {
 		/* silently swallow */

cli/node/telemetry-sender.cjs

@@ -1,8 +1,7 @@
 /**
  * Standalone telemetry sender — runs as a detached child process.
  *
- * Usage: node telemetry-sender.cjs   (JSON context is read from stdin; a single
- * argv argument is still accepted as a legacy fallback)
+ * Usage: node telemetry-sender.cjs '<json context>'
  *
  * This script is spawned by telemetry.captureEvent() and runs independently
  * of the parent CLI process. It:
@@ -20,31 +19,6 @@
 const https = require("https");
 const fs = require("fs");
 
-function loadContext() {
-	return new Promise((resolve, reject) => {
-		if (process.argv[2]) {
-			try {
-				resolve(JSON.parse(process.argv[2]));
-			} catch (err) {
-				reject(err);
-			}
-			return;
-		}
-
-		let data = "";
-		process.stdin.setEncoding("utf8");
-		process.stdin.on("data", (chunk) => (data += chunk));
-		process.stdin.on("end", () => {
-			try {
-				resolve(JSON.parse(data));
-			} catch (err) {
-				reject(err);
-			}
-		});
-		process.stdin.on("error", reject);
-	});
-}
-
 function httpsRequest(url, method, headers, body) {
 	return new Promise((resolve, reject) => {
 		const u = new URL(url);
@@ -134,7 +108,7 @@ async function sendIdentifyEvent(ctx, payload, anonId) {
 }
 
 async function main() {
-	const ctx = await loadContext();
+	const ctx = JSON.parse(process.argv[2]);
 	const payload = ctx.payload;
 
 	if (ctx.needsEmail && ctx.mem0ApiKey) {

cli/node/tests/telemetry.test.ts

@@ -1,59 +0,0 @@
-import { beforeEach, describe, expect, it, vi } from "vitest";
-
-const mockLoadConfig = vi.fn();
-const mockSaveConfig = vi.fn();
-const mockSpawn = vi.fn();
-
-vi.mock("../src/config.js", () => ({
-  CONFIG_FILE: "/tmp/mem0-config.json",
-  loadConfig: mockLoadConfig,
-  saveConfig: mockSaveConfig,
-}));
-
-vi.mock("node:child_process", () => ({
-  spawn: mockSpawn,
-}));
-
-describe("captureEvent", () => {
-  beforeEach(() => {
-    vi.resetModules();
-    mockLoadConfig.mockReset();
-    mockSaveConfig.mockReset();
-    mockSpawn.mockReset();
-    delete process.env.MEM0_TELEMETRY;
-  });
-
-  it("pipes the telemetry context through stdin instead of argv", async () => {
-    mockLoadConfig.mockReturnValue({
-      platform: {
-        apiKey: "m0-node-secret",
-        baseUrl: "https://api.mem0.ai",
-        userEmail: "",
-      },
-      telemetry: {
-        anonymousId: "cli-anon-node",
-      },
-    });
-
-    const stdin = { end: vi.fn() };
-    const child = { stdin, unref: vi.fn() };
-    mockSpawn.mockReturnValue(child);
-
-    const { captureEvent } = await import("../src/telemetry.js");
-    captureEvent("node_test_event", { case: "stdin-secret" });
-
-    expect(mockSpawn).toHaveBeenCalledTimes(1);
-    const [execPath, args, options] = mockSpawn.mock.calls[0];
-    expect(execPath).toBe(process.execPath);
-    expect(args).toHaveLength(1);
-    expect(String(args[0])).toContain("telemetry-sender.cjs");
-    expect(JSON.stringify(args)).not.toContain("m0-node-secret");
-    expect(options).toMatchObject({ detached: true, stdio: ["pipe", "ignore", "ignore"] });
-
-    expect(stdin.end).toHaveBeenCalledTimes(1);
-    const payload = JSON.parse(stdin.end.mock.calls[0][0]);
-    expect(payload.mem0ApiKey).toBe("m0-node-secret");
-    expect(payload.payload.event).toBe("node_test_event");
-    expect(child.unref).toHaveBeenCalledTimes(1);
-  });
-});

cli/node/vitest.config.ts

@@ -8,10 +8,4 @@ export default defineConfig({
 	define: {
 		__CLI_VERSION__: JSON.stringify(pkg.version),
 	},
-	test: {
-		// Integration tests spawn the CLI via `npx tsx` (15s subprocess
-		// timeout); the first spawn in a file pays a cold-start cost that can
-		// exceed vitest's 5s default on CI runners.
-		testTimeout: 30_000,
-	},
 });

cli/python/CHANGELOG.md

@@ -5,19 +5,6 @@ All notable changes to `mem0-cli` (Python) are documented here.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [0.2.8] — 2026-06-19
-
-### Security
-
-- Telemetry no longer passes the Mem0 API key to its child process via
-  command-line arguments. The context is now sent over stdin, so the key is no
-  longer visible in the process list (`ps`, `/proc/<pid>/cmdline`, Activity
-  Monitor). Fixes #4862.
-
-### Fixed
-
-- `__version__` now matches the packaged version (was stale at 0.2.4).
-
 ## [0.2.7] — 2026-05-20
 
 ### Added

cli/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0-cli"
-version = "0.2.8"
+version = "0.2.7"
 description = "The official CLI for mem0 — the memory layer for AI agents"
 readme = "README.md"
 license = "Apache-2.0"

cli/python/src/mem0_cli/__init__.py

@@ -1,3 +1,3 @@
 """mem0 CLI — the command-line interface for the mem0 memory layer."""
 
-__version__ = "0.2.8"
+__version__ = "0.2.4"

cli/python/src/mem0_cli/telemetry.py

@@ -137,19 +137,12 @@ def capture_event(
             "anon_distinct_id_to_alias": anon_id_to_alias,
         }
 
-        child = subprocess.Popen(
-            [sys.executable, "-m", "mem0_cli.telemetry_sender"],
-            stdin=subprocess.PIPE,
+        subprocess.Popen(
+            [sys.executable, "-m", "mem0_cli.telemetry_sender", json.dumps(context)],
             stdout=subprocess.DEVNULL,
             stderr=subprocess.DEVNULL,
             start_new_session=True,
             close_fds=True,
-            text=True,
         )
-        if child.stdin:
-            with contextlib.suppress(Exception):
-                child.stdin.write(json.dumps(context))
-            with contextlib.suppress(Exception):
-                child.stdin.close()
     except Exception:
         pass

cli/python/src/mem0_cli/telemetry_sender.py

@@ -1,7 +1,6 @@
 """Standalone telemetry sender — runs as a detached subprocess.
 
-Usage: python -m mem0_cli.telemetry_sender   (JSON context is read from stdin;
-a single argv argument is still accepted as a legacy fallback)
+Usage: python -m mem0_cli.telemetry_sender '<json context>'
 
 This module is spawned by telemetry.capture_event() and runs independently
 of the parent CLI process. It:
@@ -21,18 +20,8 @@ import sys
 import urllib.request
 
 
-def _load_context() -> dict:
-    """Load telemetry context from stdin, falling back to argv for compatibility."""
-    raw = ""
-    if not sys.stdin.isatty():
-        raw = sys.stdin.read().strip()
-    if not raw and len(sys.argv) > 1:
-        raw = sys.argv[1]
-    return json.loads(raw)
-
-
 def main() -> None:
-    ctx = _load_context()
+    ctx = json.loads(sys.argv[1])
     payload = ctx["payload"]
 
     if ctx.get("needs_email") and ctx.get("mem0_api_key"):

cli/python/tests/test_agent_mode.py

@@ -32,13 +32,12 @@ def _run(args: list[str], home_dir: str | None = None) -> subprocess.CompletedPr
         if key.startswith("MEM0_"):
             del env[key]
     env.pop("FORCE_COLOR", None)
-    env["PYTHONIOENCODING"] = "utf-8"
     if home_dir:
         env["HOME"] = home_dir
     result = subprocess.run(
         [sys.executable, "-m", "mem0_cli", *args],
         capture_output=True,
-        encoding="utf-8",
+        text=True,
         env=env,
         timeout=15,
     )
@@ -100,13 +99,12 @@ class TestArgvPreprocessing:
         result = subprocess.run(
             [sys.executable, "-m", "mem0_cli", "init", "--agent"],
             capture_output=True,
-            encoding="utf-8",
+            text=True,
             env={
                 **{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
                 "HOME": clean_home,
                 "MEM0_BASE_URL": "http://127.0.0.1:1",  # blackhole
                 "FORCE_COLOR": "0",
-                "PYTHONIOENCODING": "utf-8",
             },
             timeout=15,
         )
@@ -135,13 +133,12 @@ class TestJsonEnvelopeParity:
         result = subprocess.run(
             [sys.executable, "-m", "mem0_cli", "init", "--agent", "--json"],
             capture_output=True,
-            encoding="utf-8",
+            text=True,
             env={
                 **{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
                 "HOME": clean_home,
                 "MEM0_BASE_URL": "http://127.0.0.1:1",
                 "FORCE_COLOR": "0",
-                "PYTHONIOENCODING": "utf-8",
             },
             timeout=15,
         )

cli/python/tests/test_cli_integration.py

@@ -49,7 +49,6 @@ def _run(
         if key.startswith("MEM0_"):
             del env[key]
     env.pop("FORCE_COLOR", None)
-    env["PYTHONIOENCODING"] = "utf-8"
     if home_dir:
         env["HOME"] = home_dir
     if env_override:
@@ -57,7 +56,7 @@ def _run(
     result = subprocess.run(
         [sys.executable, "-m", "mem0_cli", *args],
         capture_output=True,
-        encoding="utf-8",
+        text=True,
         env=env,
     )
     return subprocess.CompletedProcess(

cli/python/tests/test_commands.py

@@ -8,8 +8,8 @@ from io import StringIO
 from unittest.mock import patch
 
 import pytest
+from click.exceptions import Exit as ClickExit
 from rich.console import Console
-from typer import Exit as TyperExit
 
 from mem0_cli.commands.config_cmd import (
     cmd_config_get,
@@ -181,7 +181,7 @@ class TestAddCommand:
             patch("mem0_cli.commands.memory.console", console),
             patch("mem0_cli.commands.memory.err_console", err_console),
             patch("mem0_cli.commands.memory._stdin_is_piped", return_value=False),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_add(
                 mock_backend,
@@ -206,7 +206,7 @@ class TestAddCommand:
         with (
             patch("mem0_cli.commands.memory.console", console),
             patch("mem0_cli.commands.memory.err_console", err_console),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_add(
                 mock_backend,
@@ -764,7 +764,7 @@ class TestImportCommand:
         with (
             patch("mem0_cli.commands.utils.console", console),
             patch("mem0_cli.commands.utils.err_console", err_console),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_import(mock_backend, "/nonexistent/file.json", user_id=None, agent_id=None)
 
@@ -801,7 +801,7 @@ class TestEntitiesListCommand:
         with (
             patch("mem0_cli.commands.entities.console", console),
             patch("mem0_cli.commands.entities.err_console", err_console),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_entities_list(mock_backend, "invalid", output="table")
 
@@ -944,7 +944,7 @@ class TestEntitiesDeleteCommand:
         with (
             patch("mem0_cli.commands.entities.console", console),
             patch("mem0_cli.commands.entities.err_console", err_console),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_entities_delete(
                 mock_backend,
@@ -1308,7 +1308,7 @@ class TestAgentMode:
             patch("mem0_cli.commands.memory.console", console),
             patch("mem0_cli.commands.memory.err_console", err_console),
             patch("sys.stdout", captured_stdout),
-            pytest.raises((SystemExit, TyperExit)),
+            pytest.raises((SystemExit, ClickExit)),
         ):
             cmd_get(mock_backend, "bad-id", output="text")
 

cli/python/tests/test_config.py

@@ -67,8 +67,7 @@ class TestConfig:
         from mem0_cli.config import CONFIG_FILE
 
         mode = os.stat(CONFIG_FILE).st_mode & 0o777
-        if os.name != "nt":
-            assert mode == 0o600
+        assert mode == 0o600
 
     def test_defaults_save_and_load(self, isolate_config):
         config = Mem0Config()

cli/python/tests/test_telemetry.py

@@ -1,80 +0,0 @@
-"""Tests for telemetry subprocess secret handling."""
-
-from __future__ import annotations
-
-import io
-import json
-import subprocess
-import sys
-
-from mem0_cli.config import Mem0Config, save_config
-from mem0_cli.telemetry import capture_event
-from mem0_cli.telemetry_sender import _load_context
-
-
-class _CaptureStdin:
-    def __init__(self):
-        self.buffer = ""
-        self.closed = False
-
-    def write(self, value: str) -> None:
-        self.buffer += value
-
-    def close(self) -> None:
-        self.closed = True
-
-
-class _DummyProcess:
-    def __init__(self):
-        self.stdin = _CaptureStdin()
-
-
-def test_capture_event_writes_context_to_stdin_not_argv(isolate_config, monkeypatch):
-    config = Mem0Config()
-    config.platform.api_key = "m0-test-secret"
-    config.telemetry.anonymous_id = "cli-anon-test"
-    save_config(config)
-
-    captured: dict[str, object] = {}
-    proc = _DummyProcess()
-
-    def fake_popen(args, **kwargs):
-        captured["args"] = args
-        captured["kwargs"] = kwargs
-        return proc
-
-    monkeypatch.setattr("mem0_cli.telemetry.subprocess.Popen", fake_popen)
-
-    capture_event("unit_test_event", {"case": "stdin-secret"})
-
-    argv = captured["args"]
-    assert argv == [sys.executable, "-m", "mem0_cli.telemetry_sender"]
-    assert all("m0-test-secret" not in arg for arg in argv)
-
-    kwargs = captured["kwargs"]
-    assert kwargs["stdin"] == subprocess.PIPE
-    assert kwargs["text"] is True
-
-    ctx = json.loads(proc.stdin.buffer)
-    assert ctx["mem0_api_key"] == "m0-test-secret"
-    assert ctx["payload"]["event"] == "unit_test_event"
-
-    assert proc.stdin.closed
-
-
-def test_load_context_reads_from_stdin(monkeypatch):
-    monkeypatch.setattr("sys.argv", ["telemetry_sender"])
-    monkeypatch.setattr("sys.stdin", io.StringIO('{"payload": {"event": "stdin"}}'))
-
-    ctx = _load_context()
-
-    assert ctx["payload"]["event"] == "stdin"
-
-
-def test_load_context_falls_back_to_argv(monkeypatch):
-    monkeypatch.setattr("sys.argv", ["telemetry_sender", '{"payload": {"event": "argv"}}'])
-    monkeypatch.setattr("sys.stdin", io.StringIO(""))
-
-    ctx = _load_context()
-
-    assert ctx["payload"]["event"] == "argv"

cookbooks/mem0-autogen.ipynb

@@ -555,7 +555,7 @@
     "# - Enables creation of AI agents with long-term memory and learning abilities.\n",
     "# - Improves consistency and reduces repetition in user-agent interactions.\n",
     "\n",
-    "from helper.mem0_teachability import Mem0Teachability\n",
+    "from cookbooks.helper.mem0_teachability import Mem0Teachability\n",
     "\n",
     "teachability = Mem0Teachability(\n",
     "    verbosity=2,  # for visibility of what's happening\n",

docs/api-reference/memory/add-memories.mdx

@@ -50,7 +50,6 @@ Provide conversation messages for Mem0 to extract memories from. At least one en
 | `app_id` | string | No* | Associates the memory with an app. |
 | `metadata` | object | Optional | Custom key/value metadata (e.g., `{"topic": "preferences"}`). |
 | `infer` | boolean (default `true`) | Optional | Set to `false` to skip inference and store the provided text as-is. |
-| `expiration_date` | string | Optional | Date in `YYYY-MM-DD` format. The memory is visible through this date and hidden by default after it passes. |
 
 > \* At least one entity ID (`user_id`, `agent_id`, `app_id`, or `run_id`) is required.
 
@@ -84,11 +83,3 @@ The request is queued for background processing. The response contains an `event
 <Info>
 Poll the event status via `GET /v1/event/{event_id}/`. Status will be `SUCCEEDED` or `FAILED` once processing completes.
 </Info>
-
-<Info>
-Memories with `expiration_date` remain stored after they expire. Search and get-all hide them by default; pass `show_expired: true` to include them.
-</Info>
-
-<Info>
-Python uses `expiration_date`; TypeScript uses `expirationDate`.
-</Info>

docs/api-reference/memory/create-memory-export.mdx

@@ -4,4 +4,4 @@ description: "Submit an export job to create a structured memory export using a
 openapi: post /v1/exports/
 ---
 
-Submit a job to create a structured export of memories using a customizable Pydantic schema. This process may take some time to complete, especially if you're exporting a large number of memories. You can tailor the export by applying various filters (e.g., `user_id`, `agent_id`, `app_id`, or `run_id`) and by modifying the Pydantic schema to ensure the final data matches your exact needs.
+Submit a job to create a structured export of memories using a customizable Pydantic schema. This process may take some time to complete, especially if you're exporting a large number of memories. You can tailor the export by applying various filters (e.g., `user_id`, `agent_id`, `run_id`, or `session_id`) and by modifying the Pydantic schema to ensure the final data matches your exact needs.

docs/api-reference/memory/get-memories.mdx

@@ -6,10 +6,6 @@ openapi: post /v3/memories/
 
 List memories scoped by filters with paginated results. Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400.
 
-Expired memories are hidden by default. Pass `show_expired: true` to include memories whose `expiration_date` has passed.
-
-Python uses `show_expired`; TypeScript uses `showExpired`.
-
 The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
 
 - `in`: Matches any of the values specified
@@ -36,7 +32,6 @@ memories = client.get_all(
             }
         ]
     },
-    show_expired=False,
     page=1,
     page_size=50
 )
@@ -51,14 +46,12 @@ memories = client.get_all(
         {
             "id": "f4cbdb08-7062-4f3e-8eb2-9f5c80dfe64c",
             "memory": "Alex is planning a trip to San Francisco from July 1st to July 10th",
-            "expiration_date": null,
             "created_at": "2024-07-01T12:00:00Z",
             "updated_at": "2024-07-01T12:00:00Z"
         },
         {
             "id": "a2b8c3d4-5e6f-7g8h-9i0j-1k2l3m4n5o6p",
             "memory": "Alex prefers vegetarian restaurants",
-            "expiration_date": null,
             "created_at": "2024-07-05T15:30:00Z",
             "updated_at": "2024-07-05T15:30:00Z"
         }

docs/api-reference/memory/get-memory-export.mdx

@@ -4,4 +4,4 @@ description: "Retrieve the latest structured memory export after submitting an e
 openapi: post /v1/exports/get
 ---
 
-Retrieve the latest structured memory export after submitting an export job. You can filter the export by `user_id`, `agent_id`, `app_id`, `run_id`, `created_at`, or `updated_at` to get the most recent export matching your filters.
+Retrieve the latest structured memory export after submitting an export job. You can filter the export by `user_id`, `run_id`, `session_id`, or `app_id` to get the most recent export matching your filters.

docs/api-reference/memory/search-memories.mdx

@@ -8,10 +8,6 @@ Relevance-ranked hybrid search across stored memories. V3 uses multi-signal retr
 
 Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400. At least one entity ID is required.
 
-Expired memories are hidden by default. Pass `show_expired: true` to include memories whose `expiration_date` has passed.
-
-Python uses `show_expired`; TypeScript uses `showExpired`.
-
 The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
 - `in`: Matches any of the values specified
 - `gte`: Greater than or equal to
@@ -24,17 +20,16 @@ The `filters` object supports complex logical operations (AND, OR, NOT) and comp
 
 ### Search parameter defaults
 
-| Parameter | Default |
-| --- | --- |
-| `top_k` | `10` (range 1–1000) |
-| `threshold` | `0.1` (pass `0.0` to disable) |
-| `rerank` | `false` (pass `true` to enable) |
+| Parameter | V1/V2 | V3 |
+| --- | --- | --- |
+| `top_k` | Supported (default 10) | Supported (1-1000, default 10) |
+| `threshold` | No default | Default `0.1` (pass `0.0` to disable) |
+| `rerank` | Default `true` | Default `false` (pass `true` to enable) |
 
 <CodeGroup>
 ```python Platform API Example
 related_memories = client.search(
     query="What are Alice's hobbies?",
-    show_expired=False,
     filters={
         "OR": [
             {
@@ -59,7 +54,6 @@ related_memories = client.search(
         "category": "hobbies"
       },
       "score": 0.82,
-      "expiration_date": null,
       "created_at": "2024-07-26T10:29:36.630547-07:00",
       "updated_at": null,
       "categories": ["hobbies"]

docs/api-reference/memory/update-memory.mdx

@@ -1,14 +1,5 @@
 ---
 title: 'Update Memory'
-description: "Update the content, metadata, timestamp, or expiration date of a single memory by its unique ID using the PUT endpoint."
+description: "Update the content or metadata of a single memory by its unique ID using the PUT endpoint."
 openapi: put /v1/memories/{memory_id}/
----
-
-Use this endpoint to update mutable memory fields. To make a memory expire, set `expiration_date` to a `YYYY-MM-DD` date. To make it permanent again, send `expiration_date: null`.
-
-```python
-client.update("mem_123", expiration_date="2030-01-31")
-client.update("mem_123", expiration_date=None)
-```
-
-TypeScript uses `expirationDate`.
+---

docs/api-reference/organization/remove-org-member.mdx

@@ -1,5 +0,0 @@
----
-title: "Remove Organization Member"
-description: "Remove a member from an organization to revoke their access to its projects and resources."
-openapi: "delete /api/v1/orgs/organizations/{org_id}/members/"
----

docs/api-reference/organization/update-org-member.mdx

@@ -1,5 +0,0 @@
----
-title: "Update Organization Member"
-description: "Update an existing member's role within an organization to change their permissions and access level."
-openapi: "put /api/v1/orgs/organizations/{org_id}/members/"
----

docs/api-reference/organizations-projects.mdx

@@ -14,7 +14,7 @@ Organizations and projects are **optional** features. You can use Mem0 without t
 
 ## Key Capabilities
 
-- **Multi-org/project Support**: Organization and project are resolved automatically from your API key via `/v1/ping/` — no org or project params are accepted by `MemoryClient.__init__`. Use a project-specific API key to target a particular project.
+- **Multi-org/project Support**: Specify organization and project when initializing the Mem0 client to attribute API usage appropriately
 - **Member Management**: Control access to data through organization and project membership
 - **Access Control**: Only members can access memories and data within their organization/project scope
 - **Team Isolation**: Maintain data separation between different teams and projects for secure collaboration
@@ -79,7 +79,7 @@ new_project = client.project.create(
 
 ### Update Project Settings
 
-Modify project configuration including custom instructions, categories, language preferences, retrieval criteria, and memory decay:
+Modify project configuration including custom instructions, categories, and language preferences:
 
 ```python
 # Update project with custom categories
@@ -98,17 +98,6 @@ client.project.update(
 # Use the input language for memory storage and retrieval
 client.project.update(multilingual=True)
 
-# Set retrieval criteria to control which memories are surfaced in search
-client.project.update(
-    retrieval_criteria=[
-        {"name": "relevance", "description": "How directly relevant this memory is to the current topic or user query", "weight": 3},
-        {"name": "access_frequency", "description": "How often this memory has been accessed or surfaced recently", "weight": 1}
-    ]
-)
-
-# Enable Memory Decay (boosts recently-accessed memories at search time)
-client.project.update(decay=True)
-
 # Update multiple settings at once
 client.project.update(
     custom_instructions="...",
@@ -120,34 +109,6 @@ client.project.update(
 )
 ```
 
-#### Set Retrieval Criteria
-
-`retrieval_criteria` is a per-project list of dictionaries (`List[Dict]`) that shapes how memories are ranked and filtered during search. Each dictionary has three fields: `name` (identifier), `description` (interpreted by the LLM to score each memory), and `weight` (relative influence on the final score). Use this to focus retrieval on intent-aligned or signal-specific memories:
-
-```python
-client.project.update(
-    retrieval_criteria=[
-        {
-            "name": "joy",
-            "description": "Measure the intensity of positive emotions such as happiness, excitement, or amusement expressed in the memory. A higher score reflects greater joy.",
-            "weight": 3
-        },
-        {
-            "name": "curiosity",
-            "description": "Assess the extent to which the memory reflects inquisitiveness or interest in exploring new information. A higher score reflects stronger curiosity.",
-            "weight": 2
-        },
-        {
-            "name": "access_frequency",
-            "description": "How often this memory has been accessed or surfaced recently.",
-            "weight": 1
-        }
-    ]
-)
-```
-
-Pass an empty list to clear all criteria and restore default retrieval behaviour.
-
 #### Toggle Memory Decay
 
 `decay` is a per-project boolean that turns on [Memory Decay](/platform/features/memory-decay) — a search-time ranking bias that reinforces recently-accessed memories and gently dampens stale ones. The flag is `false` by default; set it via the same project-update endpoint:

docs/api-reference/project/remove-project-member.mdx

@@ -1,5 +0,0 @@
----
-title: "Remove Project Member"
-description: "Remove a member from a project to revoke their access to its memories, configuration, and resources."
-openapi: "delete /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/"
----

docs/api-reference/project/update-project-member.mdx

@@ -1,5 +0,0 @@
----
-title: "Update Project Member"
-description: "Update an existing member's role within a project to change their permissions and access level."
-openapi: "put /api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/"
----

docs/api-reference/project/update-project.mdx

@@ -1,5 +0,0 @@
----
-title: "Update Project"
-description: "Update a project's settings, including name, custom instructions, and other configuration options."
-openapi: "patch /api/v1/orgs/organizations/{org_id}/projects/{project_id}/"
----

docs/changelog/highlights.mdx

@@ -46,9 +46,9 @@ Ground-up rewrite of the memory pipeline with 20+ point benchmark improvements:
 - **~3-4x fewer tokens** — Under 7K tokens per retrieval vs 25K+ for full-context approaches
 - **ADD-only extraction** — Memories accumulate; nothing is overwritten or deleted
 - **Hybrid retrieval** — Semantic + BM25 keyword + entity boost, scored in parallel
-- **Graph memory (built-in)**: entities extracted, embedded, and linked across memories, with no external graph store required
+- **Entity linking** — Entities extracted, embedded, and linked across memories
 
-Breaking changes: external graph stores removed from OSS (replaced by built-in graph memory), `search()` defaults changed, deprecated params removed. See [migration guide](/migration/oss-v2-to-v3).
+Breaking changes: Graph memory removed from OSS, `search()` defaults changed, deprecated params removed. See [migration guide](/migration/oss-v2-to-v3).
 
 </Update>
 
@@ -113,7 +113,7 @@ Launched a unified Mem0 plugin across three major AI development environments
 
 Major expansion of the provider ecosystem:
 
-- **Apache AGE** — New graph store support, bringing the total to 4 graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE). **Note:** All external graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE) were subsequently removed in v2.0.0 (2026-04-14). Graph memory is now built-in entity linking with no external graph store required; see the [v2.0.0 entry above](#mem0-sdk-v2-0-0-v3-0-0).
+- **Apache AGE** — New graph store support, bringing the total to 4 graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE)
 - **Turbopuffer** — New vector database provider for Python SDK
 - **MiniMax** — New LLM provider with dedicated AWS Bedrock support
 - **pgvector for Node.js** — PostgreSQL vector support added to the TypeScript OSS SDK

docs/changelog/openclaw.mdx

@@ -4,39 +4,6 @@ description: "Release notes for the OpenClaw plugin and agent harness."
 mode: "wide"
 ---
 
-<Update label="2026-06-12" description="v1.0.13">
-
-**Fixes:**
-- **Custom categories payload:** `customCategories` (a `Record<string, string>` map) is now converted via the new `customCategoryMapToList()` helper into the `Array<Record<string, string>>` shape the Mem0 SDK expects on `add` calls — previously the raw object was passed as `custom_categories` and silently ignored ([#5345](https://github.com/mem0ai/mem0/pull/5345))
-- **Skip runtime setup during metadata registration:** `register()` now detects `registrationMode === "cli-metadata"`, registers only the CLI commands, and returns early — avoiding backend initialization, service/tool registration, and hook installation during OpenClaw's metadata-only registration pass ([#5383](https://github.com/mem0ai/mem0/pull/5383))
-
-**Security:**
-- Bumped `mem0ai` from `3.0.3` to `3.0.7` (latest Node SDK) — includes the transitive axios CVE remediation shipped in `3.0.6` ([#5460](https://github.com/mem0ai/mem0/pull/5460))
-- Added pnpm override `uuid@<11.1.1` → `>=11.1.1` to resolve an open MEDIUM Dependabot alert ([#5489](https://github.com/mem0ai/mem0/pull/5489))
-
-**Improvements:**
-- **Repo consolidation:** Plugin moved from repo-root `openclaw/` to `integrations/openclaw/`; `package.json` `repository.directory` updated to match so npm provenance links to the correct subdirectory ([#5491](https://github.com/mem0ai/mem0/pull/5491))
-
-**Tests:**
-- Added `customCategoryMapToList` unit tests and a `PlatformProvider` test asserting `custom_categories` is passed to the Mem0 SDK as a list ([#5345](https://github.com/mem0ai/mem0/pull/5345))
-- Added a regression test asserting `cli-metadata` registration registers only CLI commands and triggers no runtime side effects ([#5383](https://github.com/mem0ai/mem0/pull/5383))
-
-</Update>
-
-<Update label="2026-06-02" description="v1.0.12">
-
-**Docs:**
-- **Agent Mode onboarding:** README now documents an autonomous setup path for AI agents — `mem0 init --agent --json` mints an evaluation Mem0 API key with no email, OTP, or browser and exports it as `MEM0_API_KEY` for `openclaw mem0 init`; a human owner can later run `mem0 init --email <email>` to claim ownership without disrupting the agent ([#5123](https://github.com/mem0ai/mem0/pull/5123))
-
-**Security:**
-- Added pnpm overrides to remediate advisories in transitive dependencies: `langsmith@<0.6.0` → `^0.6.0`, `picomatch@<2.3.2` → `^2.3.2`, `vite` → `^8.0.5`, and `@qdrant/js-client-rest` → `^1.18.0` ([#5294](https://github.com/mem0ai/mem0/pull/5294))
-
-**Dependencies:**
-- Bumped `mem0ai` from `3.0.2` to `3.0.3` ([#5212](https://github.com/mem0ai/mem0/pull/5212))
-- Bumped dev dependencies `@vitest/coverage-v8` and `vitest` from `^4.0.18` to `^4.1.7`; added `vite@^8.0.5` and `@qdrant/js-client-rest@^1.18.0` ([#5294](https://github.com/mem0ai/mem0/pull/5294))
-
-</Update>
-
 <Update label="2026-04-29" description="v1.0.11">
 
 **New Features:**

docs/changelog/platform.mdx

@@ -25,7 +25,7 @@ mode: "wide"
 <Update label="2026-04-16" description="">
 
 **Improvements:**
-- **UI:** Removed the legacy external-graph-store visualization tab, page, and its references from dashboard, sidebar, project settings, playground, and billing
+- **UI:** Removed Graph Memory tab, page, and all references from dashboard, sidebar, project settings, playground, and billing
 
 </Update>
 

docs/changelog/sdk.mdx

@@ -7,151 +7,6 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">
 
-<Update label="2026-06-27" description="v2.0.10">
-
-**New Features:**
-- **Client:** Expose `expiration_date` on `MemoryClient.update()` and `AsyncMemoryClient.update()` — callers can now set or clear a memory's expiration date; `None` is preserved and forwarded to the API ([#5874](https://github.com/mem0ai/mem0/pull/5874))
-
-**Bug Fixes:**
-- **Memory (OSS):** Apply `remove_code_blocks()` to the LangChain path in async `_create_procedural_memory` so code fences are stripped consistently ([#5711](https://github.com/mem0ai/mem0/pull/5711))
-- **Rerankers:** Score HuggingFace cross-encoder results with per-document sigmoid instead of set-relative min-max, preventing a single low-score document from collapsing all relevance scores to zero ([#5715](https://github.com/mem0ai/mem0/pull/5715))
-- **Core:** Validate and trim entity IDs (`user_id`, `agent_id`, `run_id`) in `delete_all()` for both sync and async `Memory` ([#5735](https://github.com/mem0ai/mem0/pull/5735))
-- **Vector Stores:** Use `.get()` for `hash` and `created_at` in the Redis `insert()` and `update()` paths so entity payloads that omit those fields no longer raise `KeyError` ([#5709](https://github.com/mem0ai/mem0/pull/5709))
-- **Memory:** Fix scale-threshold notices not firing for Redis and search-engine backends by resolving `col_info()` signature differences and adding `num_docs` to the count-extraction lookup ([#5687](https://github.com/mem0ai/mem0/pull/5687))
-- **Vector Stores:** Escape special characters in Valkey FT.SEARCH tag filter values to prevent wildcard and operator injection through tenant-isolation filters ([#5750](https://github.com/mem0ai/mem0/pull/5750))
-
-</Update>
-
-<Update label="2026-06-24" description="v2.0.9">
-
-**Bug Fixes:**
-- **Memory (OSS):** Improve entity extraction precision by avoiding sentence-start common noun noise, preserving useful topic phrases, and exact-deduplicating entity links before semantic matching ([#5829](https://github.com/mem0ai/mem0/pull/5829))
-
-</Update>
-
-<Update label="2026-06-24" description="v2.0.8">
-
-**New Features:**
-- **Embeddings:** Add native `embed_batch` to five embedders — LM Studio, Together, HuggingFace, Vertex AI, and Google GenAI — for batched embedding requests ([#5609](https://github.com/mem0ai/mem0/pull/5609))
-
-**Bug Fixes:**
-- **Core:** Guard against malformed `image_url` entries in `parse_vision_messages` to prevent crashes ([#5631](https://github.com/mem0ai/mem0/pull/5631))
-- **Core:** Return `attributed_to` from `get()`, `get_all()`, and `search()` ([#5629](https://github.com/mem0ai/mem0/pull/5629))
-- **Core:** Fix `reset()` only dropping the history table and leaving stale messages behind ([#5541](https://github.com/mem0ai/mem0/pull/5541))
-- **Core:** Guard against an entity `embed_batch` count mismatch in the v3 add pipeline ([#5604](https://github.com/mem0ai/mem0/pull/5604))
-- **Core:** Fix an async `delete_all` race condition that corrupted the entity store's `linked_memory_ids` ([#5553](https://github.com/mem0ai/mem0/pull/5553))
-- **LLMs:** Skip the JSON `response_format` for Groq compound models that reject it ([#5513](https://github.com/mem0ai/mem0/pull/5513))
-- **LLMs:** Preserve reasoning fields during base-to-provider config conversion ([#5638](https://github.com/mem0ai/mem0/pull/5638))
-- **LLMs:** Pass the configured `anthropic_base_url` to the Anthropic client ([#5626](https://github.com/mem0ai/mem0/pull/5626))
-- **LLMs:** Stop the Azure provider from mutating and corrupting caller messages during content rewrite ([#5731](https://github.com/mem0ai/mem0/pull/5731))
-- **LLMs & Embeddings:** Repair HTTP proxy support for `httpx>=0.28` and preserve `proxies` in `LlmFactory` ([#5447](https://github.com/mem0ai/mem0/pull/5447))
-- **Embeddings:** Forward `embedding_dims` to Titan V2 in the AWS Bedrock embedder ([#5671](https://github.com/mem0ai/mem0/pull/5671))
-- **Rerankers:** Log reranking failures instead of swallowing them silently ([#5717](https://github.com/mem0ai/mem0/pull/5717))
-- **Rerankers:** Clamp out-of-range LLM scores instead of mis-parsing them ([#5635](https://github.com/mem0ai/mem0/pull/5635))
-- **Rerankers:** Export all five rerankers from the package root ([#5636](https://github.com/mem0ai/mem0/pull/5636))
-- **Vector Stores:** Point the FastEmbed-missing warning at `mem0ai[extras]` ([#5622](https://github.com/mem0ai/mem0/pull/5622))
-- **Vector Stores:** Preserve empty Azure AI Search update values ([#5524](https://github.com/mem0ai/mem0/pull/5524))
-- **Vector Stores:** Add an `auto_refresh` option for OpenSearch Serverless compatibility ([#3893](https://github.com/mem0ai/mem0/pull/3893))
-- **Vector Stores:** Wrap a scalar `vector_id` in a list for Chroma `delete()` ([#5703](https://github.com/mem0ai/mem0/pull/5703))
-- **Vector Stores:** Wrap Chroma `update()` ids, embeddings, and metadatas in lists ([#5757](https://github.com/mem0ai/mem0/pull/5757))
-- **Vector Stores:** Wrap a scalar `vector_id` in a list for Milvus `delete()` ([#5704](https://github.com/mem0ai/mem0/pull/5704))
-- **Vector Stores:** Map all comparison operators in the Pinecone `_create_filter()` ([#5707](https://github.com/mem0ai/mem0/pull/5707))
-- **Vector Stores:** Return `None` instead of `{}` from Chroma `_generate_where_clause` for empty filters ([#5713](https://github.com/mem0ai/mem0/pull/5713))
-- **Vector Stores:** Return `[[]]` from the OpenSearch `list()` error path to honor the `list()` contract ([#5727](https://github.com/mem0ai/mem0/pull/5727))
-- **Vector Stores:** Return `[[]]` from the Pinecone `list()` error path instead of a dict ([#5706](https://github.com/mem0ai/mem0/pull/5706))
-- **Vector Stores:** Return `[[]]` for an uninitialized FAISS index to honor the `list()` contract ([#5725](https://github.com/mem0ai/mem0/pull/5725))
-- **Vector Stores:** Wrap the MongoDB `list()` return in an outer list to match the interface contract ([#5729](https://github.com/mem0ai/mem0/pull/5729))
-- **Vector Stores:** Deep-copy Redis `DEFAULT_FIELDS` so instances keep distinct dims ([#5633](https://github.com/mem0ai/mem0/pull/5633))
-- **Vector Stores:** Pass the required `vectors` arg in Vertex AI `list()` and similarity search ([#5627](https://github.com/mem0ai/mem0/pull/5627))
-- **Vector Stores:** Return `None` from Redis `get()` for missing IDs ([#5625](https://github.com/mem0ai/mem0/pull/5625))
-- **Vector Stores:** Drop a stray `print` in Weaviate `list_cols` ([#5637](https://github.com/mem0ai/mem0/pull/5637))
-- **Graph:** Keep distinct entities that share a substring prefix ([#5630](https://github.com/mem0ai/mem0/pull/5630))
-- **Client:** Check the HTTP status before parsing the ping response in `_validate_api_key` ([#5639](https://github.com/mem0ai/mem0/pull/5639))
-- **Server:** Fetch filtered dashboard memories beyond the default page ([#5753](https://github.com/mem0ai/mem0/pull/5753))
-- **Server:** Return 404/400 instead of 502 for not-found and invalid input ([#5634](https://github.com/mem0ai/mem0/pull/5634))
-- **Server:** Return 404 instead of 500 for a malformed API key id on revoke ([#5640](https://github.com/mem0ai/mem0/pull/5640))
-- **Server:** Use `127.0.0.1` in the dashboard healthcheck to avoid IPv6 localhost resolution ([#5612](https://github.com/mem0ai/mem0/pull/5612))
-
-**Improvements:**
-- **Vector Stores:** Batch BM25 sparse encoding in Qdrant insert ([#5592](https://github.com/mem0ai/mem0/pull/5592))
-
-**Security:**
-- **Vector Stores:** Sanitize Milvus and Baidu filter values to prevent expression injection ([#5746](https://github.com/mem0ai/mem0/pull/5746))
-- **Vector Stores:** Reject dict filter values in MongoDB to prevent NoSQL operator injection ([#5748](https://github.com/mem0ai/mem0/pull/5748))
-
-</Update>
-
-<Update label="2026-06-17" description="v2.0.7">
-
-**New Features:**
-- **LLMs:** Add Gemini via Vertex AI as LLM provider ([#4030](https://github.com/mem0ai/mem0/pull/4030))
-- **Embeddings:** Add native `embed_batch` to `OllamaEmbedding` for batched embedding requests ([#5415](https://github.com/mem0ai/mem0/pull/5415))
-
-**Bug Fixes:**
-- **Core:** Fix `api_error_handler` silently dropping return values from async methods ([#5540](https://github.com/mem0ai/mem0/pull/5540))
-- **Core:** Fix `AsyncMemory.reset()` not resetting the entity store ([#5535](https://github.com/mem0ai/mem0/pull/5535))
-- **Core:** Fix `async delete_all` aborting on first error, leaving partial deletion ([#5529](https://github.com/mem0ai/mem0/pull/5529))
-- **Core:** Skip messages without a `content` key in message parsers to prevent `KeyError` crashes ([#5575](https://github.com/mem0ai/mem0/pull/5575))
-- **Core:** Preserve custom metadata fields during memory update ([#5480](https://github.com/mem0ai/mem0/pull/5480))
-- **LLMs:** Fix Anthropic `tool_choice` format and tool response parsing ([#5537](https://github.com/mem0ai/mem0/pull/5537))
-- **LLMs:** Fix Ollama `json` format mutating the caller's messages list in-place ([#5539](https://github.com/mem0ai/mem0/pull/5539))
-- **LLMs:** Omit `None` config values from Gemini `GenerateContentConfig` to prevent validation errors ([#5528](https://github.com/mem0ai/mem0/pull/5528))
-- **LLMs:** Honor reasoning-model params in `AzureOpenAIStructuredLLM` ([#5548](https://github.com/mem0ai/mem0/pull/5548))
-- **LLMs:** Honor reasoning-model params in `OpenAIStructuredLLM` ([#5458](https://github.com/mem0ai/mem0/pull/5458))
-- **LLMs:** Send `max_completion_tokens` for the GPT-5 family across all providers ([#5547](https://github.com/mem0ai/mem0/pull/5547))
-- **LLMs:** Accept and forward `**kwargs` in Together, LangChain, and Sarvam providers ([#5556](https://github.com/mem0ai/mem0/pull/5556))
-- **LLMs:** Fix Bedrock AI21 response parse default using `dict` literal instead of `set` ([#5527](https://github.com/mem0ai/mem0/pull/5527))
-- **LLMs:** Fix LiteLLM function-calling check blocking all calls on non-tool models ([#5536](https://github.com/mem0ai/mem0/pull/5536))
-- **LLMs:** Fix HuggingFace provider using `self.config` instead of raw `config` parameter ([#5538](https://github.com/mem0ai/mem0/pull/5538))
-- **Embeddings:** Honor `aws_session_token` in AWS Bedrock embeddings ([#5566](https://github.com/mem0ai/mem0/pull/5566))
-- **Rerankers:** Respect `config.top_k` in Cohere and ZeroEntropy fallback paths ([#5560](https://github.com/mem0ai/mem0/pull/5560))
-- **Vector Stores:** Fix FAISS filtered search dropping over-fetched candidates before filtering ([#5453](https://github.com/mem0ai/mem0/pull/5453))
-- **Vector Stores:** Fix Weaviate `reset()` crashing with missing `vector_size` argument ([#5531](https://github.com/mem0ai/mem0/pull/5531))
-- **Vector Stores:** Pass embedding dims in Weaviate `reset()` to avoid re-init crash ([#5570](https://github.com/mem0ai/mem0/pull/5570))
-- **Vector Stores:** Fix MongoDB `reset()` passing wrong argument to `create_col()` ([#5532](https://github.com/mem0ai/mem0/pull/5532))
-- **Vector Stores:** Fix Pinecone hybrid search crashing when `filters` is `None` ([#5533](https://github.com/mem0ai/mem0/pull/5533))
-- **Vector Stores:** Fix Redis crashing on empty or `None` filters in `search()` and `list()` ([#5446](https://github.com/mem0ai/mem0/pull/5446))
-- **Vector Stores:** Return `None` from `get()` for missing IDs in Milvus, Weaviate, and Supabase ([#5562](https://github.com/mem0ai/mem0/pull/5562))
-- **Vector Stores:** Return `None` from ChromaDB `get()` for missing IDs ([#5561](https://github.com/mem0ai/mem0/pull/5561))
-
-</Update>
-
-<Update label="2026-06-13" description="v2.0.6">
-
-**New Features:**
-- **Memory:** Add a contextual OSS-to-Platform notices system that surfaces occasional, situation-aware messages (first run, scale/performance thresholds, slow queries, and when temporal/decay features are relevant) pointing to the corresponding Mem0 Platform capabilities; disable via `MEM0_TELEMETRY=false` ([#5494](https://github.com/mem0ai/mem0/pull/5494))
-
-**Bug Fixes:**
-- **Memory:** Prevent a crash in `parse_vision_messages` when vision support is disabled ([#5487](https://github.com/mem0ai/mem0/pull/5487))
-- **Vector Stores:** Expose the `https` option on the Qdrant vector store configuration so TLS endpoints can be targeted explicitly ([#5380](https://github.com/mem0ai/mem0/pull/5380))
-- **Vector Stores:** Use valid S3 Vectors entity index names, fixing index operations that failed on invalid names ([#5416](https://github.com/mem0ai/mem0/pull/5416))
-- **Vector Stores:** Fix `search()` crashing with a `TypeError` in the LangChain vector store when a result score is `None` ([#5072](https://github.com/mem0ai/mem0/pull/5072))
-- **Vector Stores:** Use `is not None` instead of a truthiness check for vector/payload in the PGVector `update()` path, so valid empty/zero values are no longer skipped ([#5488](https://github.com/mem0ai/mem0/pull/5488))
-- **Vector Stores:** Index the Valkey `memory` field as `TEXT` rather than `TAG` so full-text search behaves correctly ([#5443](https://github.com/mem0ai/mem0/pull/5443))
-- **Vector Stores:** Implement `$not` filter support in the ChromaDB vector store ([#5485](https://github.com/mem0ai/mem0/pull/5485))
-
-</Update>
-
-<Update label="2026-06-10" description="v2.0.5">
-
-**New Features:**
-- **Memory:** Warn at init time when hybrid/BM25 search silently degrades to semantic-only because the configured vector store does not implement `keyword_search`. Affected stores: Chroma, FAISS, Cassandra, LangChain, Neptune Analytics, S3 Vectors, Supabase, TurboPuffer, Valkey ([#5444](https://github.com/mem0ai/mem0/pull/5444))
-- **Memory:** Add opt-in `explain=True` parameter to `Memory.search()` and `AsyncMemory.search()`. When enabled, each result includes a `score_details` dict with `semantic_score`, `bm25_score`, `entity_boost`, `raw_score`, `max_possible_score`, `final_score`, and `threshold` so callers can understand and tune retrieval ranking ([#5102](https://github.com/mem0ai/mem0/pull/5102))
-
-**Bug Fixes:**
-- **Vector Stores:** Normalize similarity scores to `[0, 1]` (higher = better) consistently across all backends. 11 adapters previously returned raw distance metrics (lower = better) — FAISS, Chroma, Milvus, Redis, Cassandra, PGVector, S3 Vectors, Supabase, Valkey, Azure MySQL, and Vertex AI Vector Search — causing incorrect ranking in multi-store setups ([#5391](https://github.com/mem0ai/mem0/pull/5391))
-- **Memory:** Parallelize entity boost searches in `Memory.search()` and `AsyncMemory.search()`. Previously up to 8 entities were embedded and queried sequentially (16 serial round-trips with remote embedders); all entity lookups now run concurrently, eliminating multi-second latency on entity-rich queries ([#5377](https://github.com/mem0ai/mem0/pull/5377))
-- **Memory:** Reject empty or whitespace-only queries in `Memory.search()`, `AsyncMemory.search()`, `MemoryClient.search()`, and `AsyncMemoryClient.search()` before any embedding or API call is made. Also strips leading/trailing whitespace from valid queries ([#5258](https://github.com/mem0ai/mem0/pull/5258))
-- **LLMs:** Add `is_reasoning_model: Optional[bool]` override to `BaseLlmConfig` (surfaced on `OpenAILlmConfig` and `AzureOpenAILlmConfig`). Fixes silent zero-extraction when using Azure deployments with versioned `gpt-5.x` names that the automatic name-based heuristic cannot recognize ([#5327](https://github.com/mem0ai/mem0/pull/5327))
-- **LLMs:** Fix xAI LLM provider: add `XAIConfig` with `xai_base_url`, forward `tools`/`tool_choice` in `generate_response()`, and parse `tool_calls` in the response. Previously the provider raised `AttributeError` at init and silently dropped tool results ([#5190](https://github.com/mem0ai/mem0/pull/5190))
-- **Vector Stores:** Fix PGVector `ConnectionPool` hang in Docker Compose environments where the app container starts before Postgres is DNS-resolvable — switched to `open=False` to avoid blocking constructor or silent zombie pool ([#5155](https://github.com/mem0ai/mem0/pull/5155))
-- **Vector Stores:** Fix PGVector `sslmode` handling for PostgreSQL URIs — the `sslmode` query parameter is now correctly extracted and forwarded when building the async connection pool ([#5308](https://github.com/mem0ai/mem0/pull/5308))
-- **Vector Stores:** Fix S3 Vectors `list()` not applying metadata filters — filtering is now done client-side after fetching, with pagination preserved and `top_k` applied after filtering to prevent pre-truncation of matching rows ([#5018](https://github.com/mem0ai/mem0/pull/5018))
-- **Vector Stores:** Fix Upstash Vector `search()` routing all queries to the default namespace — `namespace` is now passed as a top-level keyword argument to `query_many()` instead of inside the per-query dict where it was silently ignored ([#5202](https://github.com/mem0ai/mem0/pull/5202))
-- **Core:** Replace mutable default arguments with `None` sentinels in embedder configs and the proxy module, preventing cross-request state contamination ([#5302](https://github.com/mem0ai/mem0/pull/5302))
-
-</Update>
-
 <Update label="2026-05-27" description="v2.0.4">
 
 **New Features:**
@@ -223,8 +78,8 @@ mode: "wide"
 - **`messages` in `Memory.add()` rejects invalid types:** Passing `None` or non-`(str | dict | list)` values raises `Mem0ValidationError` (`error_code="VALIDATION_003"`) ([#4843](https://github.com/mem0ai/mem0/pull/4843))
 - **`qdrant-client>=1.12.0` required** — Upgrade from `>=1.9.1` ([#4805](https://github.com/mem0ai/mem0/pull/4805))
 - **`org_id` and `project_id` removed** — Removed from `MemoryClient` constructor and all method signatures ([#4740](https://github.com/mem0ai/mem0/pull/4740))
-- **External Graph Store Removed (OSS):** `mem0/memory/graph_memory.py`, `memgraph_memory.py`, `kuzu_memory.py`, `apache_age_memory.py`, and `mem0/graphs/` (Neo4j / Memgraph / Kuzu / Apache AGE / Neptune drivers) deleted, about 4,000 lines. The external graph store integration is no longer part of the OSS SDK; graph drivers (neo4j, memgraph, kuzu, etc.) can be uninstalled. Graph memory now runs natively as built-in entity linking. Remove `enable_graph` and `graph_store` from your config ([#4805](https://github.com/mem0ai/mem0/pull/4805))
-- **`enable_graph` removed from Client SDK:** Graph memory now runs automatically and no longer needs a flag. Remove `enable_graph` from `MemoryClient.add()` / `search()` / `get_all()` / `update_project()` calls ([#4776](https://github.com/mem0ai/mem0/pull/4776))
+- **Graph Memory Removed (OSS):** `mem0/memory/graph_memory.py`, `memgraph_memory.py`, `kuzu_memory.py`, `apache_age_memory.py`, and `mem0/graphs/` (Neo4j / Memgraph / Kuzu / Apache AGE / Neptune drivers) deleted — ~4,000 lines. Graph memory is no longer supported in the OSS SDK; graph drivers (neo4j, memgraph, kuzu, etc.) can be uninstalled. Use the Platform API for graph features. Remove `enable_graph` and `graph_store` from your config ([#4805](https://github.com/mem0ai/mem0/pull/4805))
+- **`enable_graph` removed from Client SDK** — Graph memory is now a project-level setting on the Platform. Remove `enable_graph` from `MemoryClient.add()` / `search()` / `get_all()` / `update_project()` calls ([#4776](https://github.com/mem0ai/mem0/pull/4776))
 - **`custom_fact_extraction_prompt` renamed to `custom_instructions`** — Update config and memory module references ([#4740](https://github.com/mem0ai/mem0/pull/4740))
 - **Typed option classes** — Added Pydantic v2 typed classes: `AddMemoryOptions`, `SearchMemoryOptions`, `GetAllMemoryOptions`, `DeleteAllMemoryOptions`, `UpdateMemoryOptions`, `ProjectUpdateOptions` ([#4740](https://github.com/mem0ai/mem0/pull/4740))
 
@@ -244,7 +99,7 @@ mode: "wide"
 **Improvements:**
 - **Telemetry:** Sample OSS hot-path events at 10% via PostHog `before_send` hook to reduce event volume ([#4771](https://github.com/mem0ai/mem0/pull/4771))
 
-See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) and [Platform migration guide](https://docs.mem0.ai/migration/platform-v2-to-v3) for upgrade instructions.
+See the [OSS v1 to v2 migration guide](https://docs.mem0.ai/migration/oss-v1-to-v2) and [Platform migration guide](https://docs.mem0.ai/migration/platform-v2-to-v3) for upgrade instructions.
 
 </Update>
 
@@ -1084,92 +939,6 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
 </Tab>
 
 <Tab title="TypeScript">
-
-<Update label="2026-06-27" description="v3.0.12">
-
-**New Features:**
-- **Client:** Add `expirationDate` to `AddMemoryOptions`, `update()`, and the `Memory` interface; add `showExpired` to `SearchMemoryOptions` and `GetAllMemoryOptions` ([#5874](https://github.com/mem0ai/mem0/pull/5874))
-- **LLMs:** Add `MiniMaxLLM` provider backed by the OpenAI-compatible MiniMax API (`api.minimax.io/v1`, default model `MiniMax-M2.7`) ([#5858](https://github.com/mem0ai/mem0/pull/5858))
-- **LLMs:** Add `LiteLLM` provider for routing requests through a local or hosted LiteLLM proxy ([#5830](https://github.com/mem0ai/mem0/pull/5830))
-- **Vector Stores:** Add `connectionString` and `ssl` options to the PGVector config, allowing connection via URI instead of individual host/user/password/port fields ([#5789](https://github.com/mem0ai/mem0/pull/5789))
-
-**Bug Fixes:**
-- **Memory (OSS):** Validate and trim entity IDs (`userId`, `agentId`, `runId`) in `deleteAll()` via `validateAndTrimEntityId` ([#5735](https://github.com/mem0ai/mem0/pull/5735))
-- **Vector Stores:** Use nullish coalescing for `hash` and timestamps in the Redis `insert()` and `update()` paths so entity payloads that omit those fields no longer crash ([#5860](https://github.com/mem0ai/mem0/pull/5860))
-
-**Security:**
-- **Dependencies:** Bump `undici` to `>=6.27.0` via pnpm override to remediate CVE-2026-12151 ([#5861](https://github.com/mem0ai/mem0/pull/5861))
-
-</Update>
-
-<Update label="2026-06-24" description="v3.0.11">
-
-**Bug Fixes:**
-- **Memory (OSS):** Align entity extraction with Python by reducing generic entity noise, preserving useful topic phrases, and exact-deduplicating entity links before semantic matching ([#5829](https://github.com/mem0ai/mem0/pull/5829))
-
-</Update>
-
-<Update label="2026-06-24" description="v3.0.10">
-
-**Bug Fixes:**
-- **Memory (OSS):** Guard against malformed `image_url` entries in `parseVisionMessages` to prevent crashes ([#5631](https://github.com/mem0ai/mem0/pull/5631))
-- **Memory (OSS):** Return `attributedTo` from `get()`, `search()`, and `getAll()` ([#5675](https://github.com/mem0ai/mem0/pull/5675))
-- **Memory (OSS):** Preserve message roles in the extraction input so assistant facts aren't attributed to the user ([#5643](https://github.com/mem0ai/mem0/pull/5643))
-- **Memory (OSS):** Reject empty or blank messages in `Memory.add()` to prevent hallucinated memories ([#5545](https://github.com/mem0ai/mem0/pull/5545))
-- **Memory (OSS):** Check `message.role` instead of `content` when detecting system messages ([#3921](https://github.com/mem0ai/mem0/pull/3921))
-- **LLMs:** Honor the configured `baseURL` in `AnthropicLLM` ([#5740](https://github.com/mem0ai/mem0/pull/5740))
-- **Client:** Preserve `customCategories` names through key conversion ([#5741](https://github.com/mem0ai/mem0/pull/5741))
-- **Client:** Prevent hallucinated memories on an empty messages payload ([#5613](https://github.com/mem0ai/mem0/pull/5613))
-- **Client:** Preserve user metadata keys across the case-conversion round-trip ([#5515](https://github.com/mem0ai/mem0/pull/5515))
-
-**Security:**
-- **Dependencies:** Upgrade `form-data` to `>=4.0.6` across pnpm workspaces to remediate CVE-2026-12143 ([#5618](https://github.com/mem0ai/mem0/pull/5618))
-
-</Update>
-
-<Update label="2026-06-17" description="v3.0.9">
-
-**Bug Fixes:**
-- **LLMs:** Fix Anthropic `tool_choice` format — was incorrectly sent as a bare string `"auto"` (rejected by the API); now correctly sent as `{ type: "auto" }`. Also fixes tool response parsing: `tool_use` blocks are now parsed into `toolCalls` objects instead of throwing. Updated default model to `claude-sonnet-4-6` and default `max_tokens` to `2000` to match the Python provider. Added `temperature`, `topP`, and `maxTokens` to `LLMConfig` so Anthropic params can be configured ([#5537](https://github.com/mem0ai/mem0/pull/5537))
-- **Memory (OSS):** Preserve custom metadata fields during `update()` — fields such as `category`, `priority`, and other user-defined keys were previously dropped on update; the existing payload is now spread before applying the new data ([#5480](https://github.com/mem0ai/mem0/pull/5480))
-- **Client:** Preserve user-defined schema keys in `createMemoryExport` ([#5594](https://github.com/mem0ai/mem0/pull/5594))
-
-**Security:**
-- **Dependencies:** Bump `esbuild` to `>=0.28.1` across all npm packages via pnpm overrides to remediate upstream vulnerability ([#5563](https://github.com/mem0ai/mem0/pull/5563))
-
-</Update>
-
-<Update label="2026-06-13" description="v3.0.8">
-
-**New Features:**
-- **Memory:** Add a contextual OSS-to-Platform notices system that surfaces occasional, situation-aware messages (first run, scale/performance thresholds, slow queries, and when temporal/decay features are relevant) pointing to the corresponding Mem0 Platform capabilities; disable via `MEM0_TELEMETRY=false` ([#5494](https://github.com/mem0ai/mem0/pull/5494))
-
-**Security:**
-- **Dependencies:** Upgrade `@langchain/community` to `^1.1.18` to remediate CVE-2026-27795 and CVE-2026-26019 ([#5510](https://github.com/mem0ai/mem0/pull/5510))
-- **Dependencies:** Resolve all open MEDIUM Dependabot alerts via pnpm overrides ([#5489](https://github.com/mem0ai/mem0/pull/5489))
-
-</Update>
-
-<Update label="2026-06-10" description="v3.0.7">
-
-**New Features:**
-- **Embeddings:** Add `LMStudioEmbedding` provider for local embeddings via the LM Studio server ([#5377](https://github.com/mem0ai/mem0/pull/5377))
-- **Memory:** Add opt-in `explain: true` option to `Memory.search()`. When enabled, each result includes a `scoreBreakdown` object with `semantic`, `keyword`, `entityBoost`, and `temporalBoost` fields so callers can inspect and tune retrieval ranking ([#5102](https://github.com/mem0ai/mem0/pull/5102))
-
-**Bug Fixes:**
-- **Memory:** Parallelize entity boost searches in `Memory.search()`. All entity embed + store lookups now run concurrently instead of sequentially, eliminating multi-second latency on entity-rich queries with remote embedding providers ([#5377](https://github.com/mem0ai/mem0/pull/5377))
-- **Vector Stores:** Normalize similarity scores to `[0, 1]` (higher = better) — fixed score inversion in the Redis vector store adapter ([#5391](https://github.com/mem0ai/mem0/pull/5391))
-- **Embeddings:** Request `encoding_format: "float"` from the OpenAI embedder in both `embed()` and `embedBatch()`. Fixes incorrect vector dimensions when using OpenAI-compatible proxies that default to base64 encoding ([#5170](https://github.com/mem0ai/mem0/pull/5170))
-
-</Update>
-
-<Update label="2026-06-01" description="v3.0.6">
-
-**Security:**
-- **Dependencies:** Bumped `axios` to `^1.16.0` to remediate high-severity prototype-pollution CVEs (credential theft, MITM, DoS). Pinned transitive dependencies via pnpm overrides: `jws` → 4.0.1 (CVE-2025-65945), `langsmith` → ^0.6.0 (CVE-2026-45134), `tar-fs` → ^2.1.4 (CVE-2025-48387, CVE-2025-59343), `picomatch` → ^2.3.2 (CVE-2026-33671), `minimatch` → ^3.1.3 / ^5.1.8 / ^9.0.7 (CVE-2026-27903, CVE-2026-27904, CVE-2026-26996), `path-to-regexp` → ^8.4.0 (CVE-2026-4926), `rollup` → ^4.59.0 (CVE-2026-27606), `glob` → ^10.5.0 (CVE-2025-64756), `@modelcontextprotocol/sdk` → ^1.25.4 (CVE-2025-66414, CVE-2026-0621)
-
-</Update>
-
 <Update label="2026-05-27" description="v3.0.5">
 
 **New Features:**
@@ -1229,7 +998,7 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
 - **Default model:** `gpt-5-mini` is now the default in `OpenAI`, `OpenAIStructured`, and `Azure` LLM providers ([#4829](https://github.com/mem0ai/mem0/pull/4829))
 
 **Breaking Changes:**
-- **External Graph Store Removed (OSS):** `graph_memory.ts` (675 lines), `graphs/tools.ts` (267 lines), `graphs/utils.ts` (116 lines), `graphs/configs.ts` (30 lines) deleted. The external graph store integration is no longer part of the OSS SDK; graph memory now runs natively as built-in entity linking ([#4805](https://github.com/mem0ai/mem0/pull/4805))
+- **Graph Memory Removed (OSS):** `graph_memory.ts` (675 lines), `graphs/tools.ts` (267 lines), `graphs/utils.ts` (116 lines), `graphs/configs.ts` (30 lines) deleted. Graph memory is no longer supported in the OSS SDK — use Platform API for graph features ([#4805](https://github.com/mem0ai/mem0/pull/4805))
 - **camelCase Parameters (Client SDK):** All user-facing parameters converted from snake_case to camelCase. Mapping is transparent at API boundary via `camelToSnakeKeys()` / `snakeToCamelKeys()` ([#4776](https://github.com/mem0ai/mem0/pull/4776))
   ```typescript
   // Before
@@ -1583,13 +1352,6 @@ See the [TypeScript SDK migration guide](https://docs.mem0.ai/migration/ts-v2-to
 
 <Tab title="CLI">
 
-<Update label="2026-06-01" description="Node v0.2.8">
-
-**Security:**
-- **Dependencies:** Pinned transitive dependencies via pnpm overrides to remediate high-severity CVEs: `jws` → 4.0.1 (CVE-2025-65945), `langsmith` → ^0.6.0 (CVE-2026-45134), `tar-fs` → ^2.1.4 (CVE-2025-48387, CVE-2025-59343), `picomatch` → ^2.3.2 (CVE-2026-33671), `minimatch` → ^3.1.3 / ^5.1.8 / ^9.0.7 (CVE-2026-27903, CVE-2026-27904, CVE-2026-26996), `path-to-regexp` → ^8.4.0 (CVE-2026-4926), `rollup` → ^4.59.0 (CVE-2026-27606), `glob` → ^10.5.0 (CVE-2025-64756), `@modelcontextprotocol/sdk` → ^1.25.4 (CVE-2025-66414, CVE-2026-0621)
-
-</Update>
-
 <Update label="2026-05-16" description="Python v0.2.6 / Node v0.2.6">
 
 **Bug Fixes:**
@@ -1706,43 +1468,6 @@ A full-featured command-line interface for Mem0, available in both Python and No
 
 <Tab title="Plugins">
 
-<Update label="2026-06-01" description="openclaw-mem0 v1.0.12">
-
-**Security:**
-- **Dependencies:** Pinned transitive dependencies via pnpm overrides to remediate high-severity CVEs: `protobufjs` → ^7.5.5, `vite` → ^8.0.5, `langsmith` → ^0.6.0 (CVE-2026-45134), `picomatch` → ^2.3.2 (CVE-2026-33671), `@qdrant/js-client-rest` → ^1.18.0
-
-</Update>
-
-<Update label="2026-06-10" description="Vercel AI SDK v3.0.0">
-
-**Major Release** — Migrated to Vercel AI SDK v6 (`LanguageModelV3` / `ProviderV3`) and Mem0 v3 API.
-
-**Breaking Changes:**
-- **AI SDK v6:** Upgraded from AI SDK v5 (`LanguageModelV2`) to v6 (`LanguageModelV3`). Users must upgrade `ai` to `^6.0.199` and all `@ai-sdk/*` provider packages to `^3.x` ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Mem0 v3 API:** Memory endpoints migrated from `/v1/memories/` and `/v2/memories/search/` to `/v3/memories/add/` and `/v3/memories/search/`. Entity IDs (`user_id`, `agent_id`, `run_id`) now go inside the `filters` object for search requests ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Graph memory removed:** All `enable_graph`, graph prompts, and relation-extraction code removed. Graph memory is now a project-level setting on the Platform ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Deprecated params removed:** `org_id`, `project_id`, `org_name`, `project_name`, `output_format`, `filter_memories`, `async_mode`, `enable_graph`, `version`, `api_version` removed from `Mem0ConfigSettings` ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-
-**New Features:**
-- **V3 provider contract:** `specificationVersion: 'v3'`, `supportedUrls` property, V3 content array in `doGenerate`, V3 stream lifecycle events in `doStream` ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Mem0 source in responses:** Memories are attached as a `source` in `generateText`/`streamText` responses with `providerMetadata.mem0.memories` for programmatic access ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-
-**Bug Fixes:**
-- **Async memory storage:** `addMemories` is now properly `await`ed — memories no longer silently fail to store ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Prompt mutation:** Prompt array is now cloned before injecting memory context, preventing side effects on the caller's array ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Null guard on content:** `doGenerate` guards against null `content` from upstream providers ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Stream response:** `doStream` now returns the full `LanguageModelV3StreamResult` object preserving all V3 fields ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-- **Response normalization:** `getMemories` and `retrieveMemories` now handle both array and `{results: [...]}` envelope responses from the v3 API ([#4741](https://github.com/mem0ai/mem0/pull/4741))
-
-</Update>
-
-<Update label="2026-06-01" description="Vercel AI SDK v2.0.6">
-
-**Security:**
-- **Dependencies:** Pinned transitive dependencies via pnpm overrides to remediate high-severity CVEs: `glob` → ^10.5.0 (CVE-2025-64756), `minimatch` → ^3.1.3 / ^5.1.8 / ^9.0.7 (CVE-2026-27903, CVE-2026-27904, CVE-2026-26996), `picomatch` → ^2.3.2 (CVE-2026-33671), `rollup` → ^4.59.0 (CVE-2026-27606)
-
-</Update>
-
 <Update label="2026-04-02" description="mem0-plugin v1.0.0">
 
 **Mem0 Plugin for Claude Code, Cursor, and Codex**

docs/components/embedders/models/aws_bedrock.mdx

@@ -59,9 +59,5 @@ Here are the parameters available for configuring AWS Bedrock embedder:
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the embedding model to use | `amazon.titan-embed-text-v1` |
-| `aws_region` | AWS region for the Bedrock client | `us-west-2` |
-| `aws_access_key_id` | AWS access key ID for authentication | `None` |
-| `aws_secret_access_key` | AWS secret access key for authentication | `None` |
-| `aws_session_token` | AWS session token for temporary credentials | `None` |
 </Tab>
 </Tabs>

docs/components/embedders/models/fastembed.mdx

@@ -1,50 +0,0 @@
----
-title: "FastEmbed"
-description: "Configure FastEmbed as an embedding provider in Mem0 to generate embeddings locally using ONNX-based models without a GPU."
----
-
-You can use FastEmbed to run embedding models locally in Mem0. FastEmbed is an ONNX-based embedding library that runs efficiently on CPU without requiring a GPU or an external API key.
-
-### Installation
-
-```bash
-pip install fastembed
-```
-
-### Usage
-
-<CodeGroup>
-```python Python
-import os
-from mem0 import Memory
-
-os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM
-
-config = {
-    "embedder": {
-        "provider": "fastembed",
-        "config": {
-            "model": "thenlper/gte-large"
-        }
-    }
-}
-
-m = Memory.from_config(config)
-messages = [
-    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
-    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
-    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
-]
-m.add(messages, user_id="john")
-```
-</CodeGroup>
-
-### Config
-
-Here are the parameters available for configuring FastEmbed embedder:
-
-| Parameter | Description | Default Value |
-| --- | --- | --- |
-| `model` | The name of the FastEmbed model to use | `thenlper/gte-large` |
-| `embedding_dims` | Dimensions of the embedding model (auto-derived from the model if not set) | `None` |

docs/components/embedders/models/google_AI.mdx

@@ -67,15 +67,14 @@ Here are the parameters available for configuring Gemini embedder:
 | Parameter        | Description                          | Default Value           |
 | ---------------- | ------------------------------------ | ----------------------- |
 | `model`          | The name of the embedding model to use| `models/gemini-embedding-001` |
-| `embedding_dims` | Dimensions of the embedding model     | `768`                   |
+| `embedding_dims` | Dimensions of the embedding model     | `1536`                  |
 | `api_key`        | The Google API key                   | `None`                  |
-| `output_dimensionality` | Output dimensionality for the embedding model (Gemini-specific; used when `embedding_dims` is not set) | `None` |
 </Tab>
 <Tab title="TypeScript">
 | Parameter         | Description                                   | Default Value              |
 | ----------------- | --------------------------------------------- | -------------------------- |
 | `model`           | The name of the embedding model to use        | `gemini-embedding-001`     |
-| `embeddingDims`   | Dimensions of the embedding model. When not set, uses the model's native output dimensionality (3072 for `gemini-embedding-001`; MRL truncation to 768, 1536, or 3072 is supported) | `None`                     |
+| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
 | `apiKey`          | Google API key                                | `None`                     |
 </Tab>
 </Tabs>

docs/components/embedders/models/lmstudio.mdx

@@ -16,7 +16,7 @@ config = {
     "embedder": {
         "provider": "lmstudio",
         "config": {
-            "model": "nomic-ai/nomic-embed-text-v1.5-GGUF"
+            "model": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"
         }
     }
 }
@@ -37,6 +37,6 @@ Here are the parameters available for configuring LM Studio embedder:
 
 | Parameter | Description | Default Value |
 | --- | --- | --- |
-| `model` | The name of the LM Studio model to use | `nomic-ai/nomic-embed-text-v1.5-GGUF` |
+| `model` | The name of the LM Studio model to use | `nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf` |
 | `embedding_dims` | Dimensions of the embedding model | `1536` |
 | `lmstudio_base_url` | Base URL for LM Studio connection | `http://localhost:1234/v1` |

docs/components/embedders/overview.mdx

@@ -10,7 +10,7 @@ Mem0 offers support for various embedding models, allowing users to choose the o
 See the list of supported embedders below.
 
 <Note>
-  All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **Google AI**, **Langchain**, **LM Studio**, and **Ollama**.
+  The following embedders are supported in the Python implementation. The TypeScript implementation currently only supports OpenAI.
 </Note>
 
 <CardGroup cols={4}>
@@ -24,7 +24,6 @@ See the list of supported embedders below.
   <Card title="LM Studio" href="/components/embedders/models/lmstudio"></Card>
   <Card title="Langchain" href="/components/embedders/models/langchain"></Card>
   <Card title="AWS Bedrock" href="/components/embedders/models/aws_bedrock"></Card>
-  <Card title="FastEmbed" href="/components/embedders/models/fastembed"></Card>
 </CardGroup>
 
 ## Usage

docs/components/llms/config.mdx

@@ -98,7 +98,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `max_tokens`         | Tokens to generate                            | All               |
     | `top_p`              | Probability threshold for nucleus sampling    | All               |
     | `top_k`              | Number of highest probability tokens to keep  | All               |
-    | `http_client_proxies`| Allow proxy server settings                   | All               |
+    | `http_client_proxies`| Allow proxy server settings                   | AzureOpenAI       |
     | `models`             | List of models                                | Openrouter        |
     | `route`              | Routing strategy                              | Openrouter        |
     | `openrouter_base_url`| Base URL for Openrouter API                   | Openrouter        |
@@ -110,7 +110,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `deepseek_base_url`  | Base URL for DeepSeek API                     | DeepSeek          |
     | `xai_base_url`       | Base URL for XAI API                          | XAI               |
     | `sarvam_base_url`    | Base URL for Sarvam API                       | Sarvam            |
-    | `reasoning_effort`   | Reasoning level (low, medium, high)           | All               |
+    | `reasoning_effort`   | Reasoning level (low, medium, high)           | Sarvam            |
     | `frequency_penalty`  | Penalize frequent tokens (-2.0 to 2.0)        | Sarvam            |
     | `presence_penalty`   | Penalize existing tokens (-2.0 to 2.0)        | Sarvam            |
     | `seed`               | Seed for deterministic sampling               | Sarvam            |

docs/components/llms/models/anthropic.mdx

@@ -20,7 +20,7 @@ config = {
     "llm": {
         "provider": "anthropic",
         "config": {
-            "model": "claude-sonnet-4-6",
+            "model": "claude-sonnet-4-20250514",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -45,7 +45,7 @@ const config = {
     provider: 'anthropic',
     config: {
       apiKey: process.env.ANTHROPIC_API_KEY || '',
-      model: 'claude-sonnet-4-6',
+      model: 'claude-sonnet-4-20250514',
       temperature: 0.1,
       maxTokens: 2000,
     },

docs/components/llms/models/aws_bedrock.mdx

@@ -6,7 +6,7 @@ description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authenti
 ### Setup
 - Before using the AWS Bedrock LLM, make sure you have the appropriate model access from [Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess).
 - You will also need to authenticate the `boto3` client by using a method in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials)
-- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY_ID`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
+- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
 
 ### Usage
 

docs/components/llms/models/deepseek.mdx

@@ -7,8 +7,7 @@ To use DeepSeek LLM models, you have to set the `DEEPSEEK_API_KEY` environment v
 
 ## Usage
 
-<CodeGroup>
-```python Python
+```python
 import os
 from mem0 import Memory
 
@@ -37,32 +36,6 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
-```typescript TypeScript
-import { Memory } from 'mem0ai/oss';
-
-const config = {
-  llm: {
-    provider: 'deepseek',
-    config: {
-      apiKey: process.env.DEEPSEEK_API_KEY || '',
-      model: 'deepseek-chat',
-      temperature: 0.2,
-      maxTokens: 2000,
-      top_p: 1.0,
-    },
-  },
-};
-const memory = new Memory(config);
-const messages = [
-    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
-    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
-    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
-];
-await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
-``` 
-</CodeGroup>
-
 You can also configure the API base URL in the config:
 
 ```python

docs/components/llms/models/groq.mdx

@@ -21,7 +21,7 @@ config = {
     "llm": {
         "provider": "groq",
         "config": {
-            "model": "llama-3.3-70b-versatile",
+            "model": "mixtral-8x7b-32768",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -46,7 +46,7 @@ const config = {
     provider: 'groq',
     config: {
       apiKey: process.env.GROQ_API_KEY || '',
-      model: 'llama3-70b-8192',
+      model: 'mixtral-8x7b-32768',
       temperature: 0.1,
       maxTokens: 1000,
     },

docs/components/llms/models/litellm.mdx

@@ -4,12 +4,9 @@ description: "Use LiteLLM as an LLM provider in Mem0 to access over 100 language
 ---
 [Litellm](https://litellm.vercel.app/docs/) is compatible with over 100 large language models (LLMs), all using a standardized input/output format. You can explore the [available models](https://litellm.vercel.app/docs/providers) to use with Litellm. Ensure you set the `API_KEY` for the model you choose to use.
 
-In the TypeScript SDK, run LiteLLM as a [proxy server](https://docs.litellm.ai/docs/simple_proxy) (an OpenAI-compatible endpoint) and point Mem0 at it via `LITELLM_API_BASE` (defaults to `http://localhost:4000`).
-
 ## Usage
 
-<CodeGroup>
-```python Python
+```python
 import os
 from mem0 import Memory
 
@@ -36,33 +33,6 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
-```typescript TypeScript
-import { Memory } from 'mem0ai/oss';
-
-// Point Mem0 at your LiteLLM proxy. apiKey defaults to "sk-anything"
-// (the proxy handles real auth); baseURL defaults to http://localhost:4000.
-const config = {
-  llm: {
-    provider: 'litellm',
-    config: {
-      apiKey: process.env.LITELLM_API_KEY || 'sk-anything',
-      baseURL: process.env.LITELLM_API_BASE || 'http://localhost:4000',
-      model: 'gpt-5-mini',
-    },
-  },
-};
-
-const memory = new Memory(config);
-const messages = [
-    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
-    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
-    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
-];
-await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
-```
-</CodeGroup>
-
 ## Config
 
 All available parameters for the `litellm` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/minimax.mdx

@@ -7,8 +7,7 @@ To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment var
 
 ## Usage
 
-<CodeGroup>
-```python Python
+```python
 import os
 from mem0 import Memory
 
@@ -37,37 +36,9 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
-```typescript TypeScript
-import { Memory } from 'mem0ai/oss';
-
-const config = {
-  llm: {
-    provider: 'minimax',
-    config: {
-      apiKey: process.env.MINIMAX_API_KEY || '',
-      model: 'MiniMax-M2.7',
-      temperature: 0.2,
-      maxTokens: 2000,
-      topP: 1.0,
-    },
-  },
-};
-const memory = new Memory(config);
-const messages = [
-  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
-  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
-  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
-  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
-];
-await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
-```
-
-</CodeGroup>
-
 You can also configure the API base URL in the config:
 
-<CodeGroup>
-```python Python
+```python
 config = {
     "llm": {
         "provider": "minimax",
@@ -80,20 +51,6 @@ config = {
 }
 ```
 
-```typescript TypeScript
-const config = {
-  llm: {
-    provider: 'minimax',
-    config: {
-      model: 'MiniMax-M2.7',
-      baseURL: 'https://your-custom-endpoint.com',
-      apiKey: 'your-api-key', // alternatively to using the environment variable
-    },
-  },
-};
-```
-</CodeGroup>
-
 ## Config
 
 All available parameters for the `minimax` config are present in [Master List of All Params in Config](../config).

docs/components/llms/models/xAI.mdx

@@ -20,7 +20,7 @@ config = {
     "llm": {
         "provider": "xai",
         "config": {
-            "model": "grok-4.3",
+            "model": "grok-3-beta",
             "temperature": 0.1,
             "max_tokens": 2000,
         }

docs/components/llms/overview.mdx

@@ -16,7 +16,7 @@ For a comprehensive list of available parameters for llm configuration, please r
 See the list of supported LLMs below.
 
 <Note>
-  All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, **Groq**, **Azure OpenAI**, **DeepSeek**, **Google AI**, **Langchain**, **LM Studio**, **Mistral AI**, and **Ollama**.
+  All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, and **Groq**.
 </Note>
 
 <CardGroup cols={4}>

docs/components/rerankers/models/llm.mdx

@@ -0,0 +1,226 @@
+---
+title: LLM as Reranker
+description: "Use any LLM as a flexible reranker in Mem0 with custom prompts and domain-specific scoring logic."
+---
+
+<Warning>
+**This page has been superseded.** Please see [LLM Reranker](/components/rerankers/models/llm_reranker) for the complete and up-to-date documentation on using LLMs for reranking.
+</Warning>
+
+LLM-based reranker provides maximum flexibility by using any Large Language Model to score document relevance. This approach allows for custom prompts and domain-specific scoring logic.
+
+## Supported LLM Providers
+
+Any LLM provider supported by Mem0 can be used for reranking:
+
+- **OpenAI**: GPT-4, GPT-3.5-turbo, etc.
+- **Anthropic**: Claude models
+- **Together**: Open-source models
+- **Groq**: Fast inference
+- **Ollama**: Local models
+- And more...
+
+## Configuration
+
+```python Python
+from mem0 import Memory
+
+config = {
+    "vector_store": {
+        "provider": "chroma",
+        "config": {
+            "collection_name": "my_memories",
+            "path": "./chroma_db"
+        }
+    },
+    "llm": {
+        "provider": "openai",
+        "config": {
+            "model": "gpt-4o-mini"
+        }
+    },
+    "reranker": {
+        "provider": "llm",
+        "config": {
+            "model": "gpt-4o-mini",
+            "provider": "openai",
+            "api_key": "your-openai-api-key",  # or set OPENAI_API_KEY
+            "top_k": 5,
+            "temperature": 0.0
+        }
+    }
+}
+
+memory = Memory.from_config(config)
+```
+
+## Custom Scoring Prompt
+
+You can provide a custom prompt for relevance scoring:
+
+```python Python
+custom_prompt = """You are a relevance scoring assistant. Rate how well this document answers the query.
+
+Query: "{query}"
+Document: "{document}"
+
+Score from 0.0 to 1.0 where:
+- 1.0: Perfect match, directly answers the query
+- 0.8-0.9: Highly relevant, good match  
+- 0.6-0.7: Moderately relevant, partial match
+- 0.4-0.5: Slightly relevant, limited useful information
+- 0.0-0.3: Not relevant or no useful information
+
+Provide only a single numerical score between 0.0 and 1.0."""
+
+config["reranker"]["config"]["scoring_prompt"] = custom_prompt
+```
+
+## Usage Example
+
+```python Python
+import os
+from mem0 import Memory
+
+# Set API key
+os.environ["OPENAI_API_KEY"] = "your-api-key"
+
+# Initialize memory with LLM reranker
+config = {
+    "vector_store": {"provider": "chroma"},
+    "llm": {"provider": "openai", "config": {"model": "gpt-4o-mini"}},
+    "reranker": {
+        "provider": "llm",
+        "config": {
+            "model": "gpt-4o-mini",
+            "provider": "openai",
+            "temperature": 0.0
+        }
+    }
+}
+
+memory = Memory.from_config(config)
+
+# Add memories
+messages = [
+    {"role": "user", "content": "I'm learning Python programming"},
+    {"role": "user", "content": "I find object-oriented programming challenging"}, 
+    {"role": "user", "content": "I love hiking in national parks"}
+]
+
+memory.add(messages, user_id="david")
+
+# Search with LLM reranking
+results = memory.search("What programming topics is the user studying?", filters={"user_id": "david"})
+
+for result in results['results']:
+    print(f"Memory: {result['memory']}")
+    print(f"Vector Score: {result['score']:.3f}")
+    print(f"Rerank Score: {result['rerank_score']:.3f}")
+    print()
+```
+
+```text Output
+Memory: I'm learning Python programming
+Vector Score: 0.856
+Rerank Score: 0.920
+
+Memory: I find object-oriented programming challenging
+Vector Score: 0.782
+Rerank Score: 0.850
+```
+
+## Domain-Specific Scoring
+
+Create specialized scoring for your domain:
+
+```python Python
+medical_prompt = """You are a medical relevance expert. Score how relevant this medical record is to the clinical query.
+
+Clinical Query: "{query}"
+Medical Record: "{document}"
+
+Consider:
+- Clinical relevance and accuracy
+- Patient safety implications
+- Diagnostic value
+- Treatment relevance
+
+Score from 0.0 to 1.0. Provide only the numerical score."""
+
+config = {
+    "reranker": {
+        "provider": "llm",
+        "config": {
+            "model": "gpt-4o-mini",
+            "provider": "openai",
+            "scoring_prompt": medical_prompt,
+            "temperature": 0.0
+        }
+    }
+}
+```
+
+## Multiple LLM Providers
+
+Use different LLM providers for reranking:
+
+```python Python
+# Using Anthropic Claude
+anthropic_config = {
+    "reranker": {
+        "provider": "llm",
+        "config": {
+            "model": "claude-3-haiku-20240307",
+            "provider": "anthropic",
+            "temperature": 0.0
+        }
+    }
+}
+
+# Using local Ollama model
+ollama_config = {
+    "reranker": {
+        "provider": "llm",
+        "config": {
+            "model": "llama2:7b",
+            "provider": "ollama",
+            "temperature": 0.0
+        }
+    }
+}
+```
+
+## Configuration Parameters
+
+| Parameter | Description | Type | Default |
+|-----------|-------------|------|---------|
+| `model` | LLM model to use for scoring | `str` | `"gpt-4o-mini"` |
+| `provider` | LLM provider name | `str` | `"openai"` |
+| `api_key` | API key for the LLM provider | `str` | `None` |
+| `top_k` | Maximum documents to return | `int` | `None` |
+| `temperature` | Temperature for LLM generation | `float` | `0.0` |
+| `max_tokens` | Maximum tokens for LLM response | `int` | `100` |
+| `scoring_prompt` | Custom prompt template | `str` | Default prompt |
+
+## Advantages
+
+- **Maximum Flexibility**: Custom prompts for any use case
+- **Domain Expertise**: Leverage LLM knowledge for specialized domains
+- **Interpretability**: Understand scoring through prompt engineering
+- **Multi-criteria**: Score based on multiple relevance factors
+
+## Considerations
+
+- **Latency**: Higher latency than specialized rerankers
+- **Cost**: LLM API costs per reranking operation
+- **Consistency**: May have slight variations in scoring
+- **Prompt Engineering**: Requires careful prompt design
+
+## Best Practices
+
+1. **Temperature**: Use 0.0 for consistent scoring
+2. **Prompt Design**: Be specific about scoring criteria
+3. **Token Efficiency**: Keep prompts concise to reduce costs
+4. **Caching**: Cache results for repeated queries when possible
+5. **Fallback**: Handle API errors gracefully

docs/components/vectordbs/dbs/baidu.mdx

@@ -46,7 +46,7 @@ Here are the parameters available for configuring Baidu VectorDB:
 | `account` | Baidu VectorDB account name | `root` |
 | `api_key` | API key for accessing Baidu VectorDB | Required |
 | `database_name` | Name of the database | `mem0` |
-| `table_name` | Name of the table | `mem0` |
+| `table_name` | Name of the table | `mem0_table` |
 | `embedding_model_dims` | Dimensions of the embedding model | `1536` |
 | `metric_type` | Distance metric for similarity search | `L2` |
 

docs/components/vectordbs/dbs/elasticsearch.mdx

@@ -56,8 +56,6 @@ Here are the parameters available for configuring Elasticsearch:
 | `api_key`              | API key for authentication                         | `None`        |
 | `user`                 | Username for basic authentication                  | `None`        |
 | `password`             | Password for basic authentication                  | `None`        |
-| `use_ssl`              | Whether to use SSL for the connection              | `True`        |
-| `ca_certs`             | Path to CA bundle for SSL certificate verification | `None`        |
 | `verify_certs`         | Whether to verify SSL certificates                 | `True`        |
 | `auto_create_index`    | Whether to automatically create the index          | `True`        |
 | `custom_search_query`  | Function returning a custom search query           | `None`        |

docs/components/vectordbs/dbs/faiss.mdx

@@ -55,7 +55,6 @@ Here are the parameters available for configuring FAISS:
 | `path` | Path to store FAISS index and metadata | `/tmp/faiss/<collection_name>` |
 | `distance_strategy` | Distance metric strategy to use (options: 'euclidean', 'inner_product', 'cosine') | `euclidean` |
 | `normalize_L2` | Whether to normalize L2 vectors (only applicable for euclidean distance) | `False` |
-| `embedding_model_dims` | Dimensions of the embedding model | `1536` |
 
 ### Performance Considerations
 

docs/components/vectordbs/dbs/langchain.mdx

@@ -47,12 +47,12 @@ m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
 ```typescript TypeScript
-import { Memory } from "mem0ai/oss";
+import { Memory } from "mem0ai";
 import { OpenAIEmbeddings } from "@langchain/openai";
-import { MemoryVectorStore } from "langchain/vectorstores/memory";
+import { MemoryVectorStore as LangchainMemoryStore } from "langchain/vectorstores/memory";
 
 const embeddings = new OpenAIEmbeddings();
-const vectorStore = new MemoryVectorStore(embeddings);
+const vectorStore = new LangchainVectorStore(embeddings);
 
 const config = {
     "vector_store": {

docs/components/vectordbs/dbs/mongodb.mdx

@@ -42,8 +42,8 @@ Here are the parameters available for configuring MongoDB:
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | db_name | Name of the MongoDB database | `"mem0_db"` |
-| collection_name | Name of the MongoDB collection | `"mem0"` |
+| collection_name | Name of the MongoDB collection | `"mem0_collection"` |
 | embedding_model_dims | Dimensions of the embedding vectors | `1536` |
-| mongo_uri | The MongoDB URI connection string | `mongodb://localhost:27017` |
+| mongo_uri | The MongoDB URI connection string | `mongodb://username:password@localhost:27017` |
 
-> **Note**: If `mongo_uri` is not provided, it will default to `mongodb://localhost:27017`.
+> **Note**: If `mongo_uri` is not provided, it will default to `mongodb://username:password@localhost:27017`.

docs/components/vectordbs/dbs/neon.mdx

@@ -1,153 +0,0 @@
----
-title: "Neon"
-description: "Use Neon as a vector store in Mem0, powered by PostgreSQL and pgvector."
----
-
-Use [Neon](https://neon.com/) as a vector store in Mem0, powered by PostgreSQL and the
-[pgvector extension](https://neon.com/docs/extensions/pgvector).
-
-Neon is a serverless Postgres platform. Since Mem0 supports Postgres through the
-`pgvector` provider, Neon can be used with a standard Postgres connection string.
-
-## Usage
-
-<CodeGroup>
-```python Python
-import os
-
-from dotenv import load_dotenv
-from mem0 import Memory
-
-load_dotenv()
-
-config = {
-    "vector_store": {
-        "provider": "pgvector",
-        "config": {
-            "connection_string": os.environ["DATABASE_URL"],
-            "collection_name": "memories",
-            "embedding_model_dims": 1536,
-            "hnsw": True,
-        },
-    },
-}
-
-m = Memory.from_config(config)
-messages = [
-    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
-    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
-    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
-    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."},
-]
-m.add(messages, user_id="alice", metadata={"category": "movies"})
-
-results = m.search(
-    "What movies should I recommend?",
-    filters={"user_id": "alice"},
-)
-
-print(results)
-```
-
-```typescript TypeScript
-import "dotenv/config";
-import { Memory } from "mem0ai/oss";
-
-const m = new Memory({
-  vectorStore: {
-    provider: "pgvector",
-    config: {
-      connectionString: process.env.DATABASE_URL!,
-      ssl: {
-        rejectUnauthorized: false,
-      },
-      collectionName: "memories",
-      dimension: 1536,
-      embeddingModelDims: 1536,
-      hnsw: true,
-    },
-  },
-});
-
-const messages = [
-  { role: "user" as const, content: "I'm planning to watch a movie tonight. Any recommendations?" },
-  { role: "assistant" as const, content: "How about thriller movies? They can be quite engaging." },
-  { role: "user" as const, content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
-  { role: "assistant" as const, content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
-];
-
-await m.add(messages, {
-  userId: "alice",
-  metadata: { category: "movies" },
-});
-
-const results = await m.search("What movies should I recommend?", {
-  filters: { user_id: "alice" },
-});
-
-console.log(results);
-```
-
-</CodeGroup>
-
-## SQL Migration
-
-You don't need to run any SQL migrations. Mem0 creates the collection table when it initializes the `pgvector` store.
-
-## Environment
-
-```env
-OPENAI_API_KEY=sk-xx...
-DATABASE_URL=postgresql://user:password@ep-example.us-east-2.aws.neon.tech/neondb?sslmode=require
-```
-
-## Config
-
-<Tabs>
-<Tab title="Python">
-| Parameter | Description | Default Value |
-| --- | --- | --- |
-| `connection_string` | Neon Postgres connection string. | Required |
-| `collection_name` | Name for the vector collection. | `mem0` |
-| `embedding_model_dims` | Embedding model dimensions. | `1536` |
-| `hnsw` | Enables HNSW indexing. | `False` |
-| `sslmode` | PostgreSQL SSL mode. Use `require` for Neon. | Driver default |
-</Tab>
-<Tab title="TypeScript">
-Use the Neon `DATABASE_URL` directly with `connectionString`. Set `ssl` if your runtime needs an explicit TLS config object.
-
-| Parameter            | Description                                    | Default        |
-| -------------------- | ---------------------------------------------- | -------------- |
-| `connectionString`   | Neon Postgres connection string.               | Required       |
-| `ssl`                | Optional TLS settings passed directly to `pg`. | Driver default |
-| `collectionName`     | Name for the vector collection.                | `memories`     |
-| `dimension`          | Vector dimension for Mem0 config.              | Auto-detected  |
-| `embeddingModelDims` | Embedding model dimensions for table creation. | Required       |
-| `hnsw`               | Enables HNSW indexing.                         | `false`        |
-
-**TLS note:** `ssl: true` is sufficient for most Neon connections since Neon uses valid certificates. Use `ssl: { rejectUnauthorized: false }` only when connecting through Neon's connection pooler on certain edge runtimes (e.g. Cloudflare Workers) that require it, or when your environment does not trust the Neon CA chain.
-
-</Tab>
-</Tabs>
-
-### Indexing
-
-The `pgvector` provider can create an HNSW index for faster vector search.
-
-- Set `hnsw` to `true` to enable a Hierarchical Navigable Small World index.
-- Leave `hnsw` as `false` if you want to create or manage indexes yourself.
-
-### Similarity Search
-
-The `pgvector` provider uses cosine similarity for vector search. Make sure your
-embedding dimensions match the configured `embedding_model_dims` value.
-
-### Best Practices
-
-1. **Index Selection**:
-   - Use `hnsw` for faster search performance when memory usage is not a constraint
-   - Manage indexes manually if you need a different pgvector index strategy
-
-2. **Connection String**:
-   - Always use environment variables or even better, a secret manager for sensitive information in the connection string
-   - Format: `postgresql://user:password@host:port/database`

docs/components/vectordbs/dbs/neptune_analytics.mdx

@@ -10,7 +10,7 @@ description: "Use AWS Neptune Analytics as a vector store in Mem0, combining gra
 ## Installation
 
 ```bash
-pip install mem0ai[vector-stores]
+pip install mem0ai[vector_stores]
 ```
 
 ## Usage

docs/components/vectordbs/dbs/opensearch.mdx

@@ -56,30 +56,6 @@ config = {
 }
 ```
 
-### Configuration Options
-
-| Parameter | Type | Default | Description |
-|-----------|------|---------|-------------|
-| `collection_name` | string | required | Name of the OpenSearch index |
-| `host` | string | required | OpenSearch endpoint URL |
-| `port` | int | 9200 | Port number |
-| `http_auth` | object | None | Authentication credentials (e.g., AWSV4SignerAuth) |
-| `embedding_model_dims` | int | 1536 | Dimension of embedding vectors |
-| `use_ssl` | bool | False | Enable SSL/TLS connection |
-| `verify_certs` | bool | False | Verify SSL certificates |
-| `auto_refresh` | bool | False | Automatically refresh index after insert. OpenSearch refreshes every ~1 second by default, so this is rarely needed. |
-
-<Note>
-  The defaults above match a local OpenSearch instance. The AWS OpenSearch Serverless
-  example earlier on this page intentionally overrides them with `port=443`, `use_ssl=True`,
-  and `verify_certs=True`, which are required when connecting to a Serverless collection.
-</Note>
-
-<Note>
-  For **AWS OpenSearch Serverless**, keep `auto_refresh=False` (the default).
-  The `indices.refresh()` API is not supported on Serverless collections.
-</Note>
-
 ### Add Memories
 
 ```python

docs/components/vectordbs/dbs/pgvector.mdx

@@ -2,7 +2,6 @@
 title: "pgvector"
 description: "Use pgvector as a vector store in Mem0 for PostgreSQL-based vector similarity search with open-source simplicity."
 ---
-
 [pgvector](https://github.com/pgvector/pgvector) is an open-source vector similarity search extension for Postgres. After connecting to Postgres, run `CREATE EXTENSION IF NOT EXISTS vector;` to create the vector extension.
 
 ### Usage
@@ -22,7 +21,7 @@ config = {
             "password": "123",
             "host": "127.0.0.1",
             "port": "5432",
-        },
+        }
     }
 }
 
@@ -31,22 +30,25 @@ messages = [
     {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
     {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
     {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
-    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="alice", metadata={"category": "movies"})
-
 ```
 
 ```typescript TypeScript
-import { Memory } from "mem0ai/oss";
+import { Memory } from 'mem0ai/oss';
 
 const config = {
   vectorStore: {
-    provider: "pgvector",
+    provider: 'pgvector',
     config: {
-      collectionName: "memories",
+      collectionName: 'memories',
       embeddingModelDims: 1536,
-      connectionString: "postgresql://test:123@localhost:5432/vector_store",
+      user: 'test',
+      password: '123',
+      host: '127.0.0.1',
+      port: 5432,
+      dbname: 'vector_store', // Optional; TypeScript OSS defaults to `vector_store` when omitted
       diskann: false, // Optional, requires pgvectorscale extension
       hnsw: false, // Optional, for HNSW indexing
     },
@@ -55,44 +57,37 @@ const config = {
 
 const memory = new Memory(config);
 const messages = [
-  { role: "user", content: "I'm planning to watch a movie tonight. Any recommendations?" },
-  { role: "assistant", content: "How about thriller movies? They can be quite engaging." },
-  { role: "user", content: "I'm not a big fan of thriller movies but I love sci-fi movies." },
-  { role: "assistant", content: "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future." },
-];
-
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+]
 await memory.add(messages, { userId: "alice", metadata: { category: "movies" } });
 ```
-
 </CodeGroup>
 
 ### Config
 
 Here are the parameters available for configuring pgvector:
 
-| Parameter            | SDK                     | Description                                                                                                                                                    | Default Value                           |
-| -------------------- | ----------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
-| `connectionString`   | TypeScript OSS          | PostgreSQL connection string for direct connections. When set, Mem0 connects to the target database directly and skips the bootstrap `postgres` database flow. | `None`                                  |
-| `ssl`                | TypeScript OSS          | SSL option passed directly to `pg`, either `true` or an SSL config object, for both `connectionString` and split-field connections.                            | `None`                                  |
-| `dbname`             | TypeScript OSS          | Split-field database name. This is only used when `connectionString` is absent.                                                                                | `vector_store`                          |
-| `collectionName`     | TypeScript OSS          | Collection name.                                                                                                                                               | `memories`                              |
-| `embeddingModelDims` | TypeScript OSS          | Dimensions of the embedding model.                                                                                                                             | Required                                |
-| `user`               | TypeScript OSS + Python | Database user for split-field connections.                                                                                                                     | `None`                                  |
-| `password`           | TypeScript OSS + Python | Database password for split-field connections.                                                                                                                 | `None`                                  |
-| `host`               | TypeScript OSS + Python | Database host for split-field connections.                                                                                                                     | `None`                                  |
-| `port`               | TypeScript OSS + Python | Database port for split-field connections.                                                                                                                     | `None`                                  |
-| `diskann`            | TypeScript OSS + Python | Whether to use DiskANN for vector similarity search, requires pgvectorscale.                                                                                   | `False`                                 |
-| `hnsw`               | TypeScript OSS + Python | Whether to use HNSW for vector similarity search.                                                                                                              | TypeScript OSS: `False`, Python: `True` |
-| `connection_string`  | Python only             | PostgreSQL connection string, overrides individual connection parameters.                                                                                      | `None`                                  |
-| `sslmode`            | Python only             | SSL mode for PostgreSQL connections, such as `require`, `prefer`, or `disable`.                                                                                | `None`                                  |
-| `connection_pool`    | Python only             | psycopg connection pool object, overrides connection string and individual connection parameters.                                                              | `None`                                  |
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `dbname` | The name of the database | `postgres` |
+| `collection_name` | The name of the collection | `mem0` |
+| `embedding_model_dims` | Dimensions of the embedding model | `1536` |
+| `user` | User name to connect to the database | `None` |
+| `password` | Password to connect to the database | `None` |
+| `host` | The host where the Postgres server is running | `None` |
+| `port` | The port where the Postgres server is running | `None` |
+| `diskann` | Whether to use diskann for vector similarity search (requires pgvectorscale) | `True` |
+| `hnsw` | Whether to use hnsw for vector similarity search | `False` |
+| `sslmode` | SSL mode for PostgreSQL connection (e.g., 'require', 'prefer', 'disable') | `None` |
+| `connection_string` | PostgreSQL connection string (overrides individual connection parameters) | `None` |
+| `connection_pool` | psycopg2 connection pool object (overrides connection string and individual parameters) | `None` |
 
-**TypeScript OSS:** Use `connectionString` plus optional `ssl` for managed Postgres setups. If you omit `connectionString`, Mem0 falls back to split fields and uses `dbname`, `user`, `password`, `host`, `port`, and optional `ssl`.
-
-**Python:** The Python SDK uses snake_case keys such as `connection_string`, `sslmode`, `collection_name`, and `embedding_model_dims`.
-
-**Python connection priority**:
+**Note (TypeScript OSS):** If you omit `dbname`, the TypeScript client uses the database name `vector_store`. Python defaults to `postgres` for `dbname`, as in the table above.
 
+**Note**: The connection parameters have the following priority:
 1. `connection_pool` (highest priority)
 2. `connection_string`
-3. Individual connection parameters (`user`, `password`, `host`, `port`, `sslmode`)
+3. Individual connection parameters (`user`, `password`, `host`, `port`, `sslmode`)

docs/components/vectordbs/dbs/qdrant.mdx

@@ -76,7 +76,6 @@ Let's see the available parameters for the `qdrant` config:
 | `path` | Path for the qdrant database | `/tmp/qdrant` |
 | `url` | Full URL for the qdrant server | `None` |
 | `api_key` | API key for the qdrant server | `None` |
-| `https` | Whether to force HTTPS on or off. `None` lets the client decide; set `False` for plain HTTP Qdrant with API key authentication. | `None` |
 | `on_disk` | For enabling persistent storage | `False` |
 </Tab>
 <Tab title="TypeScript">
@@ -91,4 +90,4 @@ Let's see the available parameters for the `qdrant` config:
 | `apiKey` | API key for the Qdrant server | `None` |
 | `onDisk` | For enabling persistent storage | `False` |
 </Tab>
-</Tabs>
+</Tabs>

docs/components/vectordbs/dbs/upstash-vector.mdx

@@ -18,9 +18,7 @@ os.environ["UPSTASH_VECTOR_REST_TOKEN"] = "..."
 config = {
     "vector_store": {
         "provider": "upstash_vector",
-        "config": {
-            "enable_embeddings": True,
-        }
+        "enable_embeddings": True,
     }
 }
 

docs/components/vectordbs/dbs/valkey.mdx

@@ -9,7 +9,7 @@ description: "Use Valkey as an open-source vector store in Mem0 for high-perform
 ## Installation
 
 ```bash
-pip install mem0ai[vector-stores]
+pip install mem0ai[vector_stores]
 ```
 
 ## Usage
@@ -51,7 +51,7 @@ Here are the parameters available for configuring Valkey:
 | `hnsw_ef_construction` | Size of dynamic candidate list for HNSW | `200` |
 | `hnsw_ef_runtime` | Size of dynamic candidate list for search | `10` |
 | `cluster_mode` | Enable cluster mode for Valkey cluster (CME) deployments | `false` |
-| `timezone` | Timezone for timestamp handling | `UTC` |
+| `distance_metric` | Distance metric for vector similarity | `cosine` |
 
 ## Cluster Mode
 

docs/components/vectordbs/dbs/vertex_ai.mdx

@@ -24,7 +24,7 @@ config = {
             "deployment_index_id": "YOUR_DEPLOYMENT_INDEX_ID",  # Required: Deployment-specific ID
             "project_id": "YOUR_PROJECT_ID",              # Required: Google Cloud project ID
             "project_number": "YOUR_PROJECT_NUMBER",      # Required: Google Cloud project number
-            "region": "YOUR_REGION",                      # Required: Google Cloud region
+            "region": "YOUR_REGION",                      # Optional: Defaults to GOOGLE_CLOUD_REGION
             "credentials_path": "path/to/credentials.json", # Optional: Defaults to GOOGLE_APPLICATION_CREDENTIALS
             "vector_search_api_endpoint": "YOUR_API_ENDPOINT" # Required for get operations
         }
@@ -45,6 +45,5 @@ m.add("Your text here", user_id="user", metadata={"category": "example"})
 | `project_id` | Google Cloud project ID | Yes |
 | `project_number` | Google Cloud project number | Yes |
 | `vector_search_api_endpoint` | Vector search API endpoint | Yes (for get operations) |
-| `region` | Google Cloud region | Yes |
+| `region` | Google Cloud region | No (defaults to GOOGLE_CLOUD_REGION) |
 | `credentials_path` | Path to service account credentials | No (defaults to GOOGLE_APPLICATION_CREDENTIALS) |
-| `service_account_json` | Service account credentials as a dictionary (alternative to `credentials_path`) | `None` |

docs/components/vectordbs/dbs/weaviate.mdx

@@ -7,7 +7,7 @@ description: "Use Weaviate as an open-source vector search engine in Mem0 for st
 
 ### Installation
 ```bash
-pip install weaviate-client
+pip install weaviate weaviate-client
 ```
 
 ### Usage
@@ -48,5 +48,4 @@ Here are the parameters available for configuring Weaviate:
 | `collection_name` | The name of the collection to store the vectors | `mem0` |
 | `embedding_model_dims` | Dimensions of the embedding model | `1536` |
 | `cluster_url` | URL for the Weaviate server | `None` |
-| `auth_client_secret` | API key for Weaviate authentication | `None` |
-| `additional_headers` | Additional headers to include in requests (`Dict[str, str]`) | `None` |
+| `auth_client_secret` | API key for Weaviate authentication | `None` |

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, and an in-memory store.
+  The following vector databases are supported in the Python implementation. The TypeScript implementation currently only supports Qdrant, Redis, Valkey, Vectorize and in-memory vector database.
 </Note>
 
 <CardGroup cols={3}>

docs/contributing/development.mdx

@@ -1,65 +1,32 @@
 ---
 title: Development
-description: "Guide to contributing code to Mem0, covering the issue-first workflow, the CLA, environment setup for the Python and TypeScript SDKs, and code quality checks."
+description: "Guide to contributing code to Mem0, covering the fork and clone workflow, PR submission, and code quality checks."
 icon: "code"
 ---
 
 # Development Contributions
 
-We strive to make contributions **easy, collaborative, and enjoyable**. Mem0 is a
-polyglot monorepo containing the **Python SDK** (`mem0/`), the **TypeScript SDK**
-(`mem0-ts/`), CLIs, integrations, the self-hosted server, and the docs site.
-Follow the steps below for a smooth contribution process.
+We strive to make contributions **easy, collaborative, and enjoyable**. Follow the steps below to ensure a smooth contribution process.
 
-<Note>
-  For the complete contributor checklist, see
-  [CONTRIBUTING.md](https://github.com/mem0ai/mem0/blob/main/CONTRIBUTING.md) in
-  the repository root.
-</Note>
+## Submitting Your Contribution through PR
 
-## Before You Start
-
-### 1. Open an Issue First
-
-**Always open an issue before opening a pull request.** This lets us discuss the
-change, avoid duplicate work, and agree on the approach before you write code.
-
-- Search [existing issues](https://github.com/mem0ai/mem0/issues) first.
-- If none match, open a
-  [bug report](https://github.com/mem0ai/mem0/issues/new?template=bug_report.yml)
-  or [feature request](https://github.com/mem0ai/mem0/issues/new?template=feature_request.yml).
-- For anything beyond a trivial fix, wait for a maintainer to confirm the approach.
-
-Every pull request must link to an issue using `Closes #<issue-number>`.
-
-### 2. Sign the Contributor License Agreement (CLA)
-
-**We cannot merge any pull request until you have signed our Contributor License
-Agreement (CLA).** When you open your first PR, the CLA bot will comment with a
-link to sign — it takes less than a minute and only needs to be done once.
-
-## Submitting Your Contribution through a PR
+To contribute, follow these steps:
 
 1. **Fork & Clone** the repository: [Mem0 on GitHub](https://github.com/mem0ai/mem0)
-2. **Create a Feature Branch**: Use a dedicated branch, e.g., `feature/my-new-feature`
-3. **Implement Changes**: If adding a feature or fixing a bug, be sure to:
+2. **Create a Feature Branch**: Use a dedicated branch for your changes, e.g., `feature/my-new-feature`
+3. **Implement Changes**: If adding a feature or fixing a bug, ensure to:
    - Write necessary **tests**
    - Add **documentation, docstrings, and runnable examples**
 4. **Code Quality Checks**:
    - Run **linting** to catch style issues
    - Ensure **all tests pass**
-5. **Commit** using [Conventional Commits](https://www.conventionalcommits.org/)
-   (`feat:`, `fix:`, `docs:`, `refactor:`, `test:`)
-6. **Submit a Pull Request** against `main`, linking the issue and filling out the
-   PR template.
+5. **Submit a Pull Request**
 
 For detailed guidance on pull requests, refer to [GitHub's documentation](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request).
 
 ---
 
-## Python SDK (`mem0/`)
-
-### Dependency Management
+## Dependency Management
 
 We use `hatch` as our package manager. Install it by following the [official instructions](https://hatch.pypa.io/latest/install/).
 
@@ -77,9 +44,13 @@ hatch -e dev_py_3_11 shell  # For dev_py_3_11 (differences are mentioned in pypr
 make install_all
 ```
 
+---
+
+## Development Standards
+
 ### Pre-commit Hooks
 
-Ensure `pre-commit` is installed before contributing (hooks run ruff + isort):
+Ensure `pre-commit` is installed before contributing:
 
 ```bash
 pre-commit install
@@ -87,7 +58,7 @@ pre-commit install
 
 ### Linting with `ruff`
 
-Run the linter and fix any reported issues before submitting your PR (line length **120**):
+Run the linter and fix any reported issues before submitting your PR:
 
 ```bash
 make lint
@@ -95,11 +66,10 @@ make lint
 
 ### Code Formatting
 
-To maintain a consistent code style, format your code and sort imports (isort, `profile = "black"`):
+To maintain a consistent code style, format your code:
 
 ```bash
 make format
-make sort
 ```
 
 ### Testing with `pytest`
@@ -114,46 +84,10 @@ make test
 
 ---
 
-## TypeScript SDK (`mem0-ts/`)
-
-We use [`pnpm`](https://pnpm.io/) (v10+) for all TypeScript packages. **Do NOT use
-`npm` or `yarn`.**
-
-```bash
-cd mem0-ts
-pnpm install
-
-pnpm run build        # tsup (CJS + ESM)
-pnpm run test         # jest (all tests)
-pnpm run test:unit    # unit tests with coverage
-```
-
-### Standards
-
-- **Build:** tsup
-- **Formatter:** Prettier
-- **Tests:** jest
-- Always run type checking after changes: `pnpm run typecheck` (or `tsc --noEmit`)
-- Use ES module `import` syntax — never `require()`
-
----
-
-## Reporting Security Issues
-
-**Do not report security vulnerabilities through public issues or pull requests.**
-Please follow our [Security Policy](https://github.com/mem0ai/mem0/blob/main/SECURITY.md)
-to report them privately.
-
----
-
 ## Release Process
 
-Packages are published automatically via GitHub Actions when a GitHub Release is
-created with the correct tag prefix (e.g. `v*` for the Python SDK, `ts-v*` for the
-TypeScript SDK). See
-[CONTRIBUTING.md](https://github.com/mem0ai/mem0/blob/main/CONTRIBUTING.md#releasing)
-for the full tag-prefix table and publishing details.
+Currently, releases are handled manually. We aim for frequent releases, typically when new features or bug fixes are introduced.
 
 ---
 
-Thank you for contributing to Mem0!
+Thank you for contributing to Mem0!

docs/cookbooks/companions/nodejs-companion.mdx

@@ -31,7 +31,7 @@ const openaiClient = new OpenAI();
 const memory = new Memory();
 
 async function chatWithMemories(message, userId = "default_user") {
-  const relevantMemories = await memory.search(message, { filters: { user_id: userId } });
+  const relevantMemories = await memory.search(message, { userId: userId });
   
   const memoriesStr = relevantMemories.results
     .map(entry => `- ${entry.memory}`)

docs/cookbooks/essentials/building-ai-companion.mdx

@@ -289,7 +289,8 @@ print([m["memory"] for m in constraints["results"]])
 ```python
 constraints = memory.search(
     query="injury concerns",
-    filters={"user_id": "max", "memory_bucket": {"in": ["constraints"]}},
+    user_id="max",
+    filters={"memory_bucket": {"in": ["constraints"]}},
     threshold=0.0  # optional: widen recall for short phrases
 )
 print([m["memory"] for m in constraints["results"]])
@@ -735,7 +736,8 @@ mem0_client.add(messages, user_id="max", run_id="nyc-2025")
 # Retrieve only Boston memories
 boston_memories = mem0_client.search(
     "training plan",
-    filters={"user_id": "max", "run_id": "boston-2025"}
+    user_id="max",
+    run_id="boston-2025"
 )
 ```
   </Tab>
@@ -747,7 +749,8 @@ memory.add(messages, user_id="max", run_id="nyc-2025")
 # Retrieve only Boston memories
 boston_memories = memory.search(
     "training plan",
-    filters={"user_id": "max", "run_id": "boston-2025"},
+    user_id="max",
+    run_id="boston-2025",
 )
 ```
   </Tab>
@@ -843,7 +846,8 @@ Prioritize recent training over old data:
 ```python
 recent = mem0_client.search(
     "training progress",
-    filters={"user_id": "max", "created_at": {"gte": "2025-10-01"}}
+    user_id="max",
+    filters={"created_at": {"gte": "2025-10-01"}}
 )
 ```
   </Tab>
@@ -862,7 +866,8 @@ memory.add(
 cutoff = int(datetime(2025, 10, 1).timestamp())
 recent = memory.search(
     "training progress",
-    filters={"user_id": "max", "logged_epoch": {"gte": cutoff}},
+    user_id="max",
+    filters={"logged_epoch": {"gte": cutoff}},
 )
 ```
   </Tab>
@@ -884,7 +889,8 @@ mem0_client.add(
 # Later, find all speed workouts
 speed_sessions = mem0_client.search(
     "speed work",
-    filters={"user_id": "max", "metadata": {"workout_type": "speed"}}
+    user_id="max",
+    filters={"metadata": {"workout_type": "speed"}}
 )
 ```
   </Tab>
@@ -899,7 +905,8 @@ memory.add(
 # Later, find all speed workouts
 speed_sessions = memory.search(
     "speed work",
-    filters={"user_id": "max", "workout_type": "speed"},
+    user_id="max",
+    filters={"workout_type": "speed"},
 )
 ```
   </Tab>