fix(oss): v3 entity cleanup, filter fixes, and QA hardening (TS + Python)

Bugs found and fixed during end-to-end QA testing of the v3 OSS pipeline
across both the TypeScript and Python SDKs. All changes are OSS-side
only; platform client untouched.

## TypeScript fixes (mem0-ts/)

### 1. Entity extractor trailing punctuation (utils/entity_extraction.ts)
End-of-sentence proper nouns retained their trailing period ("Paris."
vs "Paris"), causing cross-batch entity dedup to fail silently —
embeddings of "Paris." and "Paris" don't hit the 0.95 similarity
threshold. Fix: strip trailing sentence punctuation (. , ; ! ?) in
the existing cleanup pass.

### 2. Undefined filter values leak into vector stores (memory/index.ts)
PR #4843's validateAndTrimEntityId refactor spread agent_id: undefined
and run_id: undefined into every getAll/search filter dict. Qdrant
rejected the malformed match (400), pgvector bound NULL (0 rows),
Redis emitted literal "undefined" in TAG filters. Fix: strip
undefined values via Object.fromEntries filter at both call sites.

### 3. Redis TAG filter values unescaped (vector_stores/redis.ts)
Every UUID contains hyphens, which RediSearch interprets as minus
operators. @user_id:{legacy-abc} parses as "legacy AND NOT abc" —
zero matches. Fix: escapeRedisTagValue helper backslash-escapes all
RediSearch TAG special characters.

### 4. Entity cleanup on delete/update/deleteAll (memory/index.ts)
delete(), update(), and deleteAll() never touched the _entities
collection — linkedMemoryIds accumulated stale ids on every mutation.
Search entity-boost then surfaced deleted or rewritten memories. Fix:
new _removeMemoryFromEntityStore and _linkEntitiesForMemory helpers,
wired into deleteMemory and updateMemory. deleteAll gets coverage for
free (loops deleteMemory).

### 5. textLemmatized missing on infer:false path (memory/index.ts)
createMemory() (used by infer:false) set data and hash but never
called lemmatizeForBm25(). Memories added with infer:false had
degraded BM25 — keyword search fell back to raw data. Fix: one-line
addition of textLemmatized to createMemory payload.

## Python fix (mem0/)

### 6. Entity cleanup on delete/update/deleteAll (memory/main.py)
Same bug as TS #4 — _delete_memory and _update_memory never touched
the entity store. Fix: _remove_memory_from_entity_store and
_link_entities_for_memory helpers (sync + async), wired into both
Memory and AsyncMemory. delete_all covered transitively.

## Verification

All changes verified via scratch QA probes against live vector stores:

TS probes (in-memory SQLite, Qdrant, pgvector, Redis):
- Entity cross-batch dedup: Paris entity merges linkedMemoryIds
- Entity boost at search: +67% score delta with vs without entities
- Delete cleanup: stale id removed, ghost entities deleted
- Update cleanup: old entity unlinked, new entity created
- deleteAll: entity store fully cleared
- Legacy data compat: all 4 stores pass (seed v1 record, v3 read/write)
- BM25 contributes real signal on in-memory store
- infer:false: 0 LLM calls, textLemmatized populated, entities skipped
- No-graph: clean separation, legacy config silently ignored

Python probes (Qdrant server):
- Delete/update/deleteAll entity cleanup: all 3 scenarios pass

TS build: clean (552 unit tests pass)
Python tests: 25 + 35 + 173 pass (2 pre-existing failures unrelated)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

AGENTS.md

@@ -0,0 +1,580 @@
+# AGENTS.md
+
+This file provides context for AI coding assistants (Claude Code, Cursor, GitHub Copilot, Codex, etc.) working with the Mem0 repository.
+
+## Project Overview
+
+**Mem0** ("mem-zero") is an intelligent memory layer for AI agents and assistants. It provides persistent, personalized memory via both a hosted platform API and self-hosted open-source SDKs.
+
+- **Repository**: https://github.com/mem0ai/mem0
+- **Documentation**: https://docs.mem0.ai
+- **License**: Apache-2.0
+
+## Repository Structure
+
+This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs, servers, plugins, documentation, and evaluation tooling.
+
+### Key Directories
+
+| Directory | Description |
+|-----------|-------------|
+| `mem0/` | Core Python SDK (`mem0ai` on PyPI) — memory, LLMs, embeddings, vector stores, graphs, rerankers |
+| `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` |
+| `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) |
+| `mem0-plugin/` | AI editor plugins (Claude Code, Cursor, Codex) — MCP server connection, lifecycle hooks, skills |
+| `skills/` | Claude Code skill definitions — `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/` |
+| `docs/` | Documentation site (Mintlify) |
+| `tests/` | Python SDK tests (pytest) |
+| `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 |
+| `embedchain/` | Legacy Embedchain RAG framework (maintained separately, Poetry-based) |
+| `pr-reviews/` | Pull request review materials |
+
+### Core Package Dependencies
+
+```
+mem0 (Python SDK)          mem0-ts (TypeScript SDK)
+├── mem0/memory/           ├── src/client/        (MemoryClient — hosted)
+├── mem0/llms/             └── src/oss/           (Memory — self-hosted)
+├── mem0/embeddings/           ├── src/llms/
+├── mem0/vector_stores/        ├── src/embeddings/
+├── mem0/graphs/               ├── src/vector_stores/
+└── mem0/reranker/             └── src/graphs/
+
+cli/python/ ──▶ mem0ai (optional, for OSS mode)
+cli/node/   ──▶ mem0ai (npm, for API calls)
+vercel-ai-sdk/ ──▶ ai, @ai-sdk/* providers
+openclaw/   ──▶ mem0ai (npm)
+```
+
+## Development Setup
+
+### Requirements
+
+- **Python**: 3.9+ (3.10+ for CLI)
+- **Node.js**: v18+ (v20 or v22 recommended)
+- **pnpm**: v10+ (`npm install -g pnpm@10`) — used for all TypeScript packages
+- **Hatch**: Python build/environment tool (`pip install hatch`)
+- **Docker**: Required for `server/` and `openmemory/` development
+
+### Initial Setup
+
+```bash
+# Python SDK
+hatch shell dev_py_3_11           # creates environment with all deps
+pre-commit install                # install git hooks
+
+# TypeScript packages
+cd mem0-ts && pnpm install        # TS SDK
+cd cli/node && pnpm install       # Node CLI
+cd vercel-ai-sdk && pnpm install  # Vercel AI provider
+cd openclaw && pnpm install       # OpenClaw plugin
+```
+
+## Build, Lint, and Test Commands
+
+### Python SDK (`mem0/`)
+
+```bash
+# Environment setup (uses Hatch)
+hatch shell dev_py_3_11           # or dev_py_3_9, dev_py_3_10, dev_py_3_12
+
+# Linting and formatting
+make lint                          # ruff check
+make format                        # ruff format
+make sort                          # isort mem0/
+
+# Tests
+make test                          # pytest tests/
+make test-py-3.9                   # test specific Python version (3.9–3.12)
+
+# Build and publish
+make build                         # hatch build
+make publish                       # hatch publish
+```
+
+- **Python:** 3.9, 3.10, 3.11, 3.12
+- **Linter/formatter:** Ruff (line length **120**)
+- **Import sorting:** isort (`profile = "black"`)
+- **Test framework:** pytest (with pytest-mock, pytest-asyncio)
+- **Pre-commit hooks:** ruff + isort — run `pre-commit install` before committing
+
+### TypeScript SDK (`mem0-ts/`)
+
+```bash
+cd mem0-ts
+pnpm install
+pnpm run build                     # tsup
+pnpm run test                      # jest (all tests)
+pnpm run test:unit                 # jest --coverage (unit tests only)
+pnpm run test:integration          # jest (integration tests, needs MEM0_API_KEY)
+pnpm run test:ci                   # jest --coverage --ci (CI mode)
+pnpm run test:watch                # jest watch mode
+```
+
+- **Node:** 20, 22 (CI-tested)
+- **Build:** tsup (CJS + ESM)
+- **Test:** jest
+- **Formatter:** prettier
+
+### Python CLI (`cli/python/`)
+
+```bash
+cd cli/python
+pip install -e ".[dev]"            # dev install with ruff + pytest
+ruff check .                       # lint
+ruff format .                      # format
+pytest                             # test
+hatch build                        # build
+```
+
+- **Python:** 3.10+ (not 3.9)
+- **Linter/formatter:** Ruff (line length **100** — different from root SDK)
+- **Ruff rules:** E, F, I, W, UP, B, SIM, RUF (ignores E501, B008 for Typer patterns, SIM108)
+- **Framework:** Typer + Rich + httpx
+- **Entry point:** `mem0 = "mem0_cli.app:main"`
+- **Source layout:** `src/mem0_cli/`
+- **Optional dependency:** `mem0ai` (for OSS mode, via `[oss]` extra)
+
+### Node CLI (`cli/node/`)
+
+```bash
+cd cli/node
+pnpm install
+pnpm run build                     # tsup
+pnpm run lint                      # biome check src/
+pnpm run lint:fix                  # biome check --write src/
+pnpm run typecheck                 # tsc --noEmit
+pnpm run test                      # vitest run
+pnpm run test:watch                # vitest (watch mode)
+pnpm run dev                       # tsx src/index.ts (development)
+```
+
+- **Node:** 18+ required
+- **Build:** tsup (ESM)
+- **Linter:** Biome (not ESLint, not Ruff)
+- **Test:** vitest (not jest)
+- **Framework:** Commander + Chalk + ora + cli-table3
+
+### Vercel AI SDK Provider (`vercel-ai-sdk/`)
+
+```bash
+cd vercel-ai-sdk
+pnpm install
+pnpm run build                     # tsup
+pnpm run lint                      # eslint
+pnpm run type-check                # tsc --noEmit
+pnpm run prettier-check            # prettier --check
+pnpm run test                      # jest
+pnpm run test:edge                 # vitest (edge runtime)
+pnpm run test:node                 # vitest (node runtime)
+```
+
+- **Build:** tsup (CJS + ESM)
+- **Lint:** ESLint + Prettier
+- **Test:** jest + vitest (edge/node configs)
+
+### OpenClaw Plugin (`openclaw/`)
+
+```bash
+cd openclaw
+pnpm install
+pnpm run build                     # tsup
+pnpm run test                      # vitest run
+```
+
+- **Build:** tsup (ESM)
+- **Test:** vitest (with Codecov in CI)
+- **Plugin manifest:** `openclaw.plugin.json`
+
+### Server (`server/`)
+
+```bash
+# Docker production build
+cd server
+make build                         # docker build -t mem0-api-server .
+make run_local                     # docker run -p 8000:8000 with .env
+
+# Docker Compose development (FastAPI + PostgreSQL/pgvector + Neo4j)
+cd server
+docker-compose up                  # starts all 3 services
+# mem0 API: localhost:8888
+# PostgreSQL: localhost:8432
+# Neo4j HTTP: localhost:8474, Bolt: localhost:8687
+```
+
+- **Framework:** FastAPI with uvicorn (auto-reload in dev)
+- **Services:** PostgreSQL with pgvector, Neo4j 5.x with APOC plugin
+- **Hot reload:** Dev Dockerfile mounts `server/` and `mem0/` for live changes
+
+### OpenMemory (`openmemory/`)
+
+```bash
+# Full stack via Docker Compose
+cd openmemory
+docker-compose up
+# Qdrant: localhost:6333
+# API (MCP): localhost:8765
+# UI: localhost:3000
+
+# Individual development
+cd openmemory/api && uvicorn main:app --reload       # FastAPI backend
+cd openmemory/ui && npm run dev                       # Next.js frontend
+
+# Tests
+cd openmemory/api && pytest tests/                   # API tests (e.g., test_mcp_server.py)
+```
+
+- **API:** FastAPI + Alembic (DB migrations) + MCP server (Model Context Protocol)
+- **UI:** Next.js 15, React 19, Radix UI, Redux Toolkit, TailwindCSS, Recharts
+- **Vector store:** Qdrant
+
+### Documentation (`docs/`)
+
+```bash
+make docs                          # or: cd docs && mintlify dev
+```
+
+- **Framework:** Mintlify
+- **API spec:** `docs/openapi.json`
+- **Structure:** `api-reference/`, `open-source/`, `platform/`, `integrations/`, `cookbooks/`, `core-concepts/`
+
+### Evaluation (`evaluation/`)
+
+```bash
+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
+
+### Python
+
+| Function / Class | Purpose | Import |
+|-----------------|---------|--------|
+| `Memory` | Self-hosted memory (sync) | `from mem0 import Memory` |
+| `AsyncMemory` | Self-hosted memory (async) | `from mem0 import AsyncMemory` |
+| `MemoryClient` | Hosted platform client (sync) | `from mem0 import MemoryClient` |
+| `AsyncMemoryClient` | Hosted platform client (async) | `from mem0 import AsyncMemoryClient` |
+
+**Key `Memory` / `MemoryClient` methods:**
+
+| Method | Purpose |
+|--------|---------|
+| `add(messages, *, user_id, agent_id, run_id, metadata)` | Store a new memory |
+| `search(query, *, user_id, agent_id, run_id, limit, filters)` | Search memories |
+| `get(memory_id)` | Retrieve a single memory by ID |
+| `get_all(*, user_id, agent_id, run_id, limit)` | List all memories |
+| `update(memory_id, data)` | Update a memory |
+| `delete(memory_id)` | Delete a memory |
+| `delete_all(*, user_id, agent_id, run_id)` | Delete all memories |
+| `history(memory_id)` | Get change history for a memory |
+
+### TypeScript
+
+| Export | Purpose | Import |
+|--------|---------|--------|
+| `MemoryClient` | Hosted platform client | `import { MemoryClient } from 'mem0ai'` |
+| `Memory` | Self-hosted OSS memory | `import { Memory } from 'mem0ai/oss'` |
+
+## Import Patterns
+
+### Python
+
+| What | Import |
+|------|--------|
+| Core memory classes | `from mem0 import Memory, AsyncMemory` |
+| Platform client | `from mem0 import MemoryClient, AsyncMemoryClient` |
+| Configuration | `from mem0.configs.base import MemoryConfig` |
+| LLM providers | `from mem0.llms.<provider> import <ProviderLLM>` |
+| Embedding providers | `from mem0.embeddings.<provider> import <ProviderEmbedding>` |
+| Vector store providers | `from mem0.vector_stores.<provider> import <ProviderVectorStore>` |
+
+### TypeScript
+
+| What | Import |
+|------|--------|
+| Hosted client | `import { MemoryClient } from 'mem0ai'` |
+| OSS memory | `import { Memory } from 'mem0ai/oss'` |
+| Specific providers (OSS) | `import { OpenAIEmbedding } from 'mem0ai/oss'` |
+
+## Coding Standards
+
+### File Naming Conventions
+
+- **Python source files:** `snake_case.py` (e.g., `azure_openai.py`, `cohere_reranker.py`)
+- **Python test files:** `test_<module>.py` (e.g., `test_memory.py`, `test_main.py`)
+- **TypeScript source files:** `snake_case.ts` (e.g., `azure_ai_search.ts`)
+- **TypeScript test files:** `<module>.test.ts` (e.g., `memory.test.ts`)
+- **Config/manifest files:** `kebab-case` (e.g., `openclaw.plugin.json`, `jest.config.js`)
+
+### Python Conventions
+
+- **Provider pattern:** All providers (LLMs, embeddings, vector stores, graphs, rerankers) inherit from a `base.py` abstract class in their directory. Config classes live in `configs.py`.
+- **Pydantic v2** for all data models and configuration.
+- **Ruff** is the single linting and formatting tool — no black, no flake8.
+  - Root SDK: line length **120**
+  - Python CLI: line length **100** with extended rule set (UP, B, SIM, RUF)
+- **isort** with `profile = "black"` for import sorting.
+- Ruff excludes `embedchain/` and `openmemory/` from root config.
+
+### TypeScript Conventions
+
+- **Build:** tsup across all packages.
+- **Package manager:** pnpm everywhere (no npm, no yarn).
+- **TypeScript strict mode** across all packages.
+- **Linting varies by package:**
+
+| Package | Linter | Formatter | Test Framework |
+|---------|--------|-----------|---------------|
+| `mem0-ts/` | — | Prettier | jest |
+| `cli/node/` | Biome | Biome | vitest |
+| `vercel-ai-sdk/` | ESLint | Prettier | jest + vitest |
+| `openclaw/` | — | — | vitest |
+
+### Type Checking
+
+Always run type checking after modifying TypeScript code:
+
+```bash
+cd <package> && pnpm run typecheck    # or: tsc --noEmit
+```
+
+## Architecture
+
+### Provider Pattern
+
+The SDK uses a consistent plugin architecture across 5 categories. Each category has a `base.py` abstract class and concrete provider implementations:
+
+| Category | Count | Examples |
+|----------|-------|---------|
+| **LLMs** | 24 | OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Gemini, Groq, Ollama, Together, DeepSeek, vLLM, LiteLLM, LM Studio, xAI |
+| **Vector Stores** | 30 | Qdrant, Pinecone, Chroma, Weaviate, Milvus, MongoDB, Redis, Elasticsearch, pgvector, Supabase, Faiss, S3 Vectors |
+| **Embeddings** | 15 | OpenAI, Azure OpenAI, Gemini, HuggingFace, FastEmbed, Together, AWS Bedrock, Ollama, Vertex AI |
+| **Graph Stores** | 4 | Neo4j, Memgraph, Kuzu, Apache AGE |
+| **Rerankers** | 5 | Cohere, HuggingFace, LLM-based, Sentence Transformer, Zero Entropy |
+
+### Two Usage Modes
+
+Self-hosted `Memory` / `AsyncMemory` classes and hosted-platform `MemoryClient` — both in Python and TypeScript.
+
+### Graph Memory
+
+Optional layer on top of vector memory for relationship-aware retrieval. Configured via the `graph` section of `MemoryConfig`.
+
+### MCP Integration
+
+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 `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
+
+- `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, covering SDK usage, CLI workflows, and Vercel AI SDK patterns.
+
+### Adding a New Provider
+
+To add a new LLM, embedding, vector store, or reranker provider:
+
+1. Create `mem0/<category>/<provider_name>.py`
+2. Inherit from the abstract base class in `mem0/<category>/base.py`
+3. Add configuration to `mem0/<category>/configs.py` (if the category uses one)
+4. Register the provider in `mem0/<category>/__init__.py`
+5. Add tests in `tests/<category>/<provider_name>/`
+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
+
+## CI/CD
+
+### CI Workflows (automated testing)
+
+| 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 |
+| Embedchain | `ci.yml` (shared) | PRs on `embedchain/` | Ruff + pytest + coverage on Python 3.9–3.12 |
+
+### CD Workflows (automated publishing)
+
+| Workflow | File | Tag Prefix | Target |
+|----------|------|------------|--------|
+| 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`) |
+| Node CLI | `cli-node-cd.yml` | `cli-node-v*` | npm (`@mem0/cli`) |
+| 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`) |
+
+- 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.
+
+### Utility Workflows
+
+| Workflow | File | Purpose |
+|----------|------|---------|
+| Issue Labeler | `issue-labeler.yml` | Automatic issue labeling |
+| Stale Bot | `stale.yml` | Marks stale issues and PRs |
+
+## Task Completion Guidelines
+
+These guidelines outline typical artifacts for different task types. Use judgment to adapt based on scope and context.
+
+### Bug Fixes
+
+1. **Unit tests**: Add tests that would fail without the fix (regression tests)
+2. **Implementation**: Fix the bug
+3. **Manual verification**: Run the relevant test suite to confirm the fix
+4. **Lint**: Run the appropriate linter for the package you modified
+
+### New Features
+
+1. **Implementation**: Build the feature following existing patterns
+2. **Unit tests**: Comprehensive test coverage for new functionality
+3. **Documentation**: Update relevant docs in `docs/` for public APIs
+4. **Examples**: Add usage examples if the feature introduces new user-facing behavior
+
+### New Provider (LLM / Embedding / Vector Store / Reranker)
+
+1. **Implementation**: Follow the "Adding a New Provider" steps above
+2. **Tests**: Add unit tests matching the pattern of existing providers
+3. **Configuration**: Add to the appropriate `configs.py` and `__init__.py`
+4. **Dependencies**: Add to the correct optional group in `pyproject.toml`
+5. **Documentation**: Add an integration guide in `docs/integrations/`
+
+### Refactoring / Internal Changes
+
+- Unit tests for any changed behavior
+- No documentation needed for internal-only changes
+- Ensure all existing tests still pass
+
+### When to Deviate
+
+These are guidelines, not rigid rules. Adjust based on:
+
+- **Scope**: Trivial fixes (typos, comments) may not need tests
+- **Visibility**: Internal changes may not need documentation
+- **Context**: Some changes span multiple categories — use judgment
+
+When uncertain about expected artifacts, ask for clarification.
+
+## Contributing Guidelines
+
+### Workflow
+
+1. Fork and clone the repository.
+2. Create a feature branch from `main` (e.g., `feature/my-new-feature`).
+3. Make your changes — add tests, docs, and examples as appropriate.
+4. Run linting and tests for every package you modified (see commands above).
+5. Run `pre-commit install` on first setup — hooks run ruff + isort automatically.
+6. Commit with a clear message following [Conventional Commits](https://www.conventionalcommits.org/) (e.g., `feat:`, `fix:`, `docs:`, `refactor:`).
+7. Push and open a Pull Request against `main`.
+
+### Pull Request Requirements
+
+Every PR must follow the repo's PR template (`.github/PULL_REQUEST_TEMPLATE.md`):
+
+1. **Linked Issue** — Reference the issue with `Closes #<number>`. If no issue exists, create one first or explain why in the description.
+2. **Description** — Explain what the PR does and why it's needed.
+3. **Type of Change** — Check the appropriate box:
+   - Bug fix / New feature / Breaking change / Refactor / Documentation update
+4. **Breaking Changes** — If applicable, describe what breaks and the migration path.
+5. **Test Coverage** — Check what applies:
+   - Added/updated unit tests
+   - Added/updated integration tests
+   - Tested manually (describe how)
+   - No tests needed (explain why)
+6. **Checklist** — All must be checked before merge:
+   - [ ] Code follows the project's style guidelines
+   - [ ] Self-review performed
+   - [ ] Tests added that prove the fix/feature works
+   - [ ] New and existing tests pass locally
+   - [ ] Documentation updated if needed
+
+### PR Description Template
+
+```markdown
+## Linked Issue
+
+Closes #<!-- issue number -->
+
+## Description
+
+<!-- What does this PR do? Why is it needed? -->
+
+## Type of Change
+
+- [ ] Bug fix (non-breaking change that fixes an issue)
+- [ ] New feature (non-breaking change that adds functionality)
+- [ ] Breaking change (fix or feature that would cause existing functionality to change)
+- [ ] Refactor (no functional changes)
+- [ ] Documentation update
+
+## Breaking Changes
+
+N/A
+
+## Test Coverage
+
+- [ ] I added/updated unit tests
+- [ ] I added/updated integration tests
+- [ ] I tested manually (describe below)
+- [ ] No tests needed (explain why)
+
+## Checklist
+
+- [ ] My code follows the project's style guidelines
+- [ ] I have performed a self-review of my code
+- [ ] I have added tests that prove my fix/feature works
+- [ ] New and existing tests pass locally
+- [ ] I have updated documentation if needed
+```
+
+### General Rules
+
+- Follow existing code patterns — don't introduce new frameworks or abstractions without discussion.
+- Version bumps go in `pyproject.toml` (Python) or `package.json` (TypeScript).
+- For `server/` and `openmemory/` work, use Docker Compose for local development.
+- Do NOT use `pip` or `conda` for dependency management — use `hatch` (see `docs/contributing/development.mdx`).
+
+### Contributing Guides
+
+| Task | Guide |
+|------|-------|
+| Code contributions | `docs/contributing/development.mdx` |
+| Documentation contributions | `docs/contributing/documentation.mdx` |
+| PR template | `.github/PULL_REQUEST_TEMPLATE.md` |
+| Bug reports | `.github/ISSUE_TEMPLATE/bug_report.yml` |
+| Feature requests | `.github/ISSUE_TEMPLATE/feature_request.yml` |
+| Documentation issues | `.github/ISSUE_TEMPLATE/documentation_issue.yml` |
+
+## Do NOT
+
+- Modify CI/CD workflows without explicit approval.
+- Add new Python dependencies to the core `dependencies` list in `pyproject.toml` without discussion — use optional dependency groups instead.
+- Commit `.env` files, API keys, or credentials.
+- Modify `embedchain/` unless specifically working on that package — it has its own build system (Poetry).
+- Skip pre-commit hooks.
+- Use npm or yarn in TypeScript packages — this repo uses pnpm exclusively.
+- Use `require()` for imports in TypeScript — use ES module `import` syntax.
+- Mix up linter configs: root Python SDK uses line-length 120, Python CLI uses 100, Node CLI uses Biome (not ESLint/Ruff).
+- Modify `openmemory/` database migrations without understanding the Alembic migration chain.
+- Change public APIs without updating documentation in `docs/`.

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

LLM.md

@@ -266,7 +266,7 @@ config = MemoryConfig(
     graph_store=GraphStoreConfig(provider="neo4j", config={...}),  # optional
     history_db_path="~/.mem0/history.db",
     version="v1.1",
-    custom_fact_extraction_prompt="Custom prompt...",
+    custom_instructions="Custom prompt...",
     custom_update_memory_prompt="Custom prompt..."
 )
 ```
@@ -684,7 +684,7 @@ Conversation: {messages}
 """
 
 config = MemoryConfig(
-    custom_fact_extraction_prompt=custom_extraction_prompt
+    custom_instructions=custom_extraction_prompt
 )
 memory = Memory(config)
 ```

README.md

@@ -88,6 +88,13 @@ Install the sdk via pip:
 pip install mem0ai
 ```
 
+For enhanced hybrid search with BM25 keyword matching and entity extraction, install with NLP support:
+
+```bash
+pip install mem0ai[nlp]
+python -m spacy download en_core_web_sm
+```
+
 Install sdk via npm:
 ```bash
 npm install mem0ai
@@ -109,7 +116,9 @@ See the [CLI documentation](https://docs.mem0.ai/platform/cli) for the full comm
 
 ### Basic Usage
 
-Mem0 requires an LLM to function, with `gpt-4.1-nano-2025-04-14 from OpenAI as the default. However, it supports a variety of LLMs; for details, refer to our [Supported LLMs documentation](https://docs.mem0.ai/components/llms/overview).
+Mem0 requires an LLM to function, with `gpt-4.1-nano-2025-04-14` from OpenAI as the default. However, it supports a variety of LLMs; for details, refer to our [Supported LLMs documentation](https://docs.mem0.ai/components/llms/overview).
+
+Mem0 uses `text-embedding-3-small` from OpenAI as the default embedding model. For best results with hybrid search (semantic + keyword + entity boosting), we recommend using at least [Qwen 600M](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) or a comparable embedding model. See [Supported Embeddings](https://docs.mem0.ai/components/embedders/overview) for configuration details.
 
 First step is to instantiate the memory:
 

cli/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/cli",
-  "version": "0.2.2",
+  "version": "0.2.3",
   "description": "The official CLI for mem0 — the memory layer for AI agents",
   "type": "module",
   "bin": {

cli/node/src/backend/platform.ts

@@ -116,6 +116,7 @@ export class PlatformBackend implements Backend {
 		if (opts.expires) payload.expiration_date = opts.expires;
 		if (opts.categories) payload.categories = opts.categories;
 		if (opts.enableGraph) payload.enable_graph = true;
+		payload.source = "CLI";
 
 		return (await this._request("POST", "/v1/memories/", {
 			json: payload,
@@ -176,6 +177,7 @@ export class PlatformBackend implements Backend {
 		if (opts.keyword) payload.keyword_search = true;
 		if (opts.fields) payload.fields = opts.fields;
 		if (opts.enableGraph) payload.enable_graph = true;
+		payload.source = "CLI";
 
 		const result = (await this._request("POST", "/v2/memories/search/", {
 			json: payload,
@@ -186,10 +188,9 @@ export class PlatformBackend implements Backend {
 	}
 
 	async get(memoryId: string): Promise<Record<string, unknown>> {
-		return (await this._request("GET", `/v1/memories/${memoryId}/`)) as Record<
-			string,
-			unknown
-		>;
+		return (await this._request("GET", `/v1/memories/${memoryId}/`, {
+			params: { source: "CLI" },
+		})) as Record<string, unknown>;
 	}
 
 	async listMemories(
@@ -227,6 +228,7 @@ export class PlatformBackend implements Backend {
 		});
 		if (apiFilters) payload.filters = apiFilters;
 		if (opts.enableGraph) payload.enable_graph = true;
+		payload.source = "CLI";
 
 		const result = (await this._request("POST", "/v2/memories/", {
 			json: payload,
@@ -245,6 +247,7 @@ export class PlatformBackend implements Backend {
 		const payload: Record<string, unknown> = {};
 		if (content) payload.text = content;
 		if (metadata) payload.metadata = metadata;
+		payload.source = "CLI";
 		return (await this._request("PUT", `/v1/memories/${memoryId}/`, {
 			json: payload,
 		})) as Record<string, unknown>;
@@ -255,7 +258,7 @@ export class PlatformBackend implements Backend {
 		opts: DeleteOptions = {},
 	): Promise<Record<string, unknown>> {
 		if (opts.all) {
-			const params: Record<string, string> = {};
+			const params: Record<string, string> = { source: "CLI" };
 			if (opts.userId) params.user_id = opts.userId;
 			if (opts.agentId) params.agent_id = opts.agentId;
 			if (opts.appId) params.app_id = opts.appId;
@@ -265,10 +268,9 @@ export class PlatformBackend implements Backend {
 			})) as Record<string, unknown>;
 		}
 		if (memoryId) {
-			return (await this._request(
-				"DELETE",
-				`/v1/memories/${memoryId}/`,
-			)) as Record<string, unknown>;
+			return (await this._request("DELETE", `/v1/memories/${memoryId}/`, {
+				params: { source: "CLI" },
+			})) as Record<string, unknown>;
 		}
 		throw new Error("Either memoryId or --all is required");
 	}
@@ -291,6 +293,7 @@ export class PlatformBackend implements Backend {
 			result = (await this._request(
 				"DELETE",
 				`/v2/entities/${entityType}/${entityId}/`,
+				{ params: { source: "CLI" } },
 			)) as Record<string, unknown>;
 		}
 		return result;

cli/node/src/config.ts

@@ -31,10 +31,15 @@ export interface DefaultsConfig {
 	enableGraph: boolean;
 }
 
+export interface TelemetryConfig {
+	anonymousId: string;
+}
+
 export interface Mem0Config {
 	version: number;
 	defaults: DefaultsConfig;
 	platform: PlatformConfig;
+	telemetry: TelemetryConfig;
 }
 
 export function createDefaultConfig(): Mem0Config {
@@ -52,6 +57,9 @@ export function createDefaultConfig(): Mem0Config {
 			baseUrl: DEFAULT_BASE_URL,
 			userEmail: "",
 		},
+		telemetry: {
+			anonymousId: "",
+		},
 	};
 }
 
@@ -80,6 +88,9 @@ export function loadConfig(): Mem0Config {
 		config.defaults.appId = defaults.app_id ?? "";
 		config.defaults.runId = defaults.run_id ?? "";
 		config.defaults.enableGraph = defaults.enable_graph ?? false;
+
+		const telemetry = data.telemetry ?? {};
+		config.telemetry.anonymousId = telemetry.anonymous_id ?? "";
 	}
 
 	// Environment variable overrides
@@ -119,6 +130,9 @@ export function saveConfig(config: Mem0Config): void {
 			base_url: config.platform.baseUrl,
 			user_email: config.platform.userEmail,
 		},
+		telemetry: {
+			anonymous_id: config.telemetry.anonymousId,
+		},
 	};
 
 	fs.writeFileSync(CONFIG_FILE, JSON.stringify(data, null, 2));

cli/node/src/telemetry.ts

@@ -9,10 +9,10 @@
  */
 
 import { spawn } from "node:child_process";
-import { createHash } from "node:crypto";
+import { createHash, randomUUID } from "node:crypto";
 import path from "node:path";
 import { fileURLToPath } from "node:url";
-import { CONFIG_FILE, loadConfig } from "./config.js";
+import { CONFIG_FILE, loadConfig, saveConfig } from "./config.js";
 import { CLI_VERSION } from "./version.js";
 
 const POSTHOG_API_KEY = "phc_hgJkUVJFYtmaJqrvf6CYN67TIQ8yhXAkWzUn9AMU4yX";
@@ -29,11 +29,34 @@ function isTelemetryEnabled(): boolean {
 	}
 }
 
+/**
+ * Return a persistent per-machine anonymous ID, generating one if needed.
+ *
+ * Stored in ~/.mem0/config.json under `telemetry.anonymous_id` so that
+ * repeat runs on the same machine share one PostHog identity instead of
+ * collapsing into a single shared fallback string.
+ */
+function getOrCreateAnonymousId(): string {
+	const config = loadConfig();
+	if (config.telemetry.anonymousId) {
+		return config.telemetry.anonymousId;
+	}
+
+	const newId = `cli-anon-${randomUUID().replace(/-/g, "")}`;
+	config.telemetry.anonymousId = newId;
+	try {
+		saveConfig(config);
+	} catch {
+		/* ignore persistence failure — still return the generated ID */
+	}
+	return newId;
+}
+
 /**
  * Return a stable anonymous identifier for the current user.
  *
- * Priority: cached user_email (from /v1/ping/) > MD5(api_key) > fallback.
- * Matches the SDK pattern in mem0-ts/src/client/mem0.ts.
+ * Priority: cached user_email (from /v1/ping/) > MD5(api_key) >
+ * persistent per-machine anonymous ID.
  */
 function getDistinctId(): string {
 	try {
@@ -47,7 +70,11 @@ function getDistinctId(): string {
 	} catch {
 		/* ignore */
 	}
-	return "anonymous-cli";
+	try {
+		return getOrCreateAnonymousId();
+	} catch {
+		return `cli-anon-${randomUUID().replace(/-/g, "")}`;
+	}
 }
 
 /**
@@ -69,6 +96,25 @@ export function captureEvent(
 		const config = loadConfig();
 		const distinctId = preResolvedEmail || getDistinctId();
 
+		// Detect anonymous → identified transition. If a stored anonymous_id
+		// exists and we just resolved to a real identity, fire a one-shot
+		// $identify event so PostHog stitches the pre-signup history onto
+		// the authenticated profile. Clear the stored id so we don't re-alias.
+		let anonIdToAlias: string | null = null;
+		if (
+			distinctId &&
+			!distinctId.startsWith("cli-anon-") &&
+			config.telemetry.anonymousId
+		) {
+			anonIdToAlias = config.telemetry.anonymousId;
+			config.telemetry.anonymousId = "";
+			try {
+				saveConfig(config);
+			} catch {
+				/* ignore — alias may double-fire next run, harmless */
+			}
+		}
+
 		const payload = {
 			api_key: POSTHOG_API_KEY,
 			distinct_id: distinctId,
@@ -92,6 +138,7 @@ export function captureEvent(
 			mem0ApiKey: config.platform.apiKey || "",
 			mem0BaseUrl: config.platform.baseUrl || "https://api.mem0.ai",
 			configPath: CONFIG_FILE,
+			anonDistinctIdToAlias: anonIdToAlias,
 		};
 
 		const child = spawn(

cli/node/telemetry-sender.cjs

@@ -94,6 +94,19 @@ async function sendPosthogEvent(posthogHost, payload) {
 	}
 }
 
+async function sendIdentifyEvent(ctx, payload, anonId) {
+	const identifyPayload = {
+		api_key: payload.api_key,
+		event: "$identify",
+		distinct_id: payload.distinct_id,
+		properties: {
+			$anon_distinct_id: anonId,
+			$lib: (payload.properties && payload.properties.$lib) || "posthog-node",
+		},
+	};
+	await sendPosthogEvent(ctx.posthogHost, identifyPayload);
+}
+
 async function main() {
 	const ctx = JSON.parse(process.argv[2]);
 	const payload = ctx.payload;
@@ -102,6 +115,14 @@ async function main() {
 		await resolveAndCacheEmail(ctx, payload);
 	}
 
+	// Fire $identify *after* email resolution so PostHog links the stored
+	// anonymous id directly to the final identity (email, not the api-key
+	// hash). The regular event is sent next so it lands under the merged
+	// profile.
+	if (ctx.anonDistinctIdToAlias) {
+		await sendIdentifyEvent(ctx, payload, ctx.anonDistinctIdToAlias);
+	}
+
 	await sendPosthogEvent(ctx.posthogHost, payload);
 }
 

cli/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0-cli"
-version = "0.2.2"
+version = "0.2.3"
 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__ = "0.2.2"
+__version__ = "0.2.3"

cli/python/src/mem0_cli/backend/platform.py

@@ -93,6 +93,7 @@ class PlatformBackend(Backend):
             payload["categories"] = categories
         if enable_graph:
             payload["enable_graph"] = True
+        payload["source"] = "CLI"
 
         return self._request("POST", "/v1/memories/", json=payload)
 
@@ -172,6 +173,7 @@ class PlatformBackend(Backend):
             payload["fields"] = fields
         if enable_graph:
             payload["enable_graph"] = True
+        payload["source"] = "CLI"
 
         result = self._request("POST", "/v2/memories/search/", json=payload)
         return (
@@ -181,7 +183,7 @@ class PlatformBackend(Backend):
         )
 
     def get(self, memory_id: str) -> dict:
-        return self._request("GET", f"/v1/memories/{memory_id}/")
+        return self._request("GET", f"/v1/memories/{memory_id}/", params={"source": "CLI"})
 
     def list_memories(
         self,
@@ -220,6 +222,7 @@ class PlatformBackend(Backend):
             payload["filters"] = api_filters
         if enable_graph:
             payload["enable_graph"] = True
+        payload["source"] = "CLI"
 
         result = self._request("POST", "/v2/memories/", json=payload, params=params)
         return (
@@ -236,6 +239,7 @@ class PlatformBackend(Backend):
             payload["text"] = content
         if metadata:
             payload["metadata"] = metadata
+        payload["source"] = "CLI"
         return self._request("PUT", f"/v1/memories/{memory_id}/", json=payload)
 
     def delete(
@@ -249,7 +253,7 @@ class PlatformBackend(Backend):
         run_id: str | None = None,
     ) -> dict:
         if all:
-            params: dict[str, str] = {}
+            params: dict[str, str] = {"source": "CLI"}
             if user_id:
                 params["user_id"] = user_id
             if agent_id:
@@ -260,7 +264,7 @@ class PlatformBackend(Backend):
                 params["run_id"] = run_id
             return self._request("DELETE", "/v1/memories/", params=params)
         elif memory_id:
-            return self._request("DELETE", f"/v1/memories/{memory_id}/")
+            return self._request("DELETE", f"/v1/memories/{memory_id}/", params={"source": "CLI"})
         else:
             raise ValueError("Either memory_id or --all is required")
 
@@ -285,7 +289,9 @@ class PlatformBackend(Backend):
         # Delete each provided entity via the v2 path-based endpoint
         result: dict = {}
         for entity_type, entity_id in entities.items():
-            result = self._request("DELETE", f"/v2/entities/{entity_type}/{entity_id}/")
+            result = self._request(
+                "DELETE", f"/v2/entities/{entity_type}/{entity_id}/", params={"source": "CLI"}
+            )
         return result
 
     def ping(self, timeout: float | None = None) -> dict:

cli/python/src/mem0_cli/config.py

@@ -39,11 +39,17 @@ class DefaultsConfig:
     enable_graph: bool = False
 
 
+@dataclass
+class TelemetryConfig:
+    anonymous_id: str = ""
+
+
 @dataclass
 class Mem0Config:
     version: int = CONFIG_VERSION
     defaults: DefaultsConfig = field(default_factory=DefaultsConfig)
     platform: PlatformConfig = field(default_factory=PlatformConfig)
+    telemetry: TelemetryConfig = field(default_factory=TelemetryConfig)
 
 
 SHORT_KEY_ALIASES: dict[str, str] = {
@@ -87,6 +93,9 @@ def load_config() -> Mem0Config:
         config.defaults.run_id = defaults.get("run_id", "")
         config.defaults.enable_graph = defaults.get("enable_graph", False)
 
+        telemetry = data.get("telemetry", {})
+        config.telemetry.anonymous_id = telemetry.get("anonymous_id", "")
+
     # Environment variable overrides
     env_key = os.environ.get("MEM0_API_KEY")
     if env_key:
@@ -137,6 +146,9 @@ def save_config(config: Mem0Config) -> None:
             "base_url": config.platform.base_url,
             "user_email": config.platform.user_email,
         },
+        "telemetry": {
+            "anonymous_id": config.telemetry.anonymous_id,
+        },
     }
 
     with open(CONFIG_FILE, "w") as f:

cli/python/src/mem0_cli/telemetry.py

@@ -9,12 +9,14 @@ Disable with: MEM0_TELEMETRY=false
 
 from __future__ import annotations
 
+import contextlib
 import hashlib
 import json
 import os
 import platform
 import subprocess
 import sys
+import uuid
 from typing import Any
 
 POSTHOG_API_KEY = "phc_hgJkUVJFYtmaJqrvf6CYN67TIQ8yhXAkWzUn9AMU4yX"
@@ -26,11 +28,31 @@ def _is_telemetry_enabled() -> bool:
     return val not in ("false", "0", "no")
 
 
+def _get_or_create_anonymous_id() -> str:
+    """Return a persistent per-machine anonymous ID, generating one if needed.
+
+    Stored in ~/.mem0/config.json under `telemetry.anonymous_id` so that
+    repeat runs on the same machine share one PostHog identity instead of
+    collapsing into a single shared fallback string.
+    """
+    from mem0_cli.config import load_config, save_config
+
+    config = load_config()
+    if config.telemetry.anonymous_id:
+        return config.telemetry.anonymous_id
+
+    new_id = f"cli-anon-{uuid.uuid4().hex}"
+    config.telemetry.anonymous_id = new_id
+    with contextlib.suppress(Exception):
+        save_config(config)
+    return new_id
+
+
 def _get_distinct_id() -> str:
     """Return a stable anonymous identifier for the current user.
 
-    Priority: cached user_email (from /v1/ping/) > MD5(api_key) > fallback.
-    Matches the SDK pattern in mem0/client/main.py.
+    Priority: cached user_email (from /v1/ping/) > MD5(api_key) >
+    persistent per-machine anonymous ID.
     """
     try:
         from mem0_cli.config import load_config
@@ -42,7 +64,10 @@ def _get_distinct_id() -> str:
             return hashlib.md5(config.platform.api_key.encode()).hexdigest()
     except Exception:
         pass
-    return "anonymous-cli"
+    try:
+        return _get_or_create_anonymous_id()
+    except Exception:
+        return f"cli-anon-{uuid.uuid4().hex}"
 
 
 def capture_event(
@@ -61,12 +86,27 @@ def capture_event(
 
     try:
         from mem0_cli import __version__
-        from mem0_cli.config import CONFIG_FILE, load_config
+        from mem0_cli.config import CONFIG_FILE, load_config, save_config
         from mem0_cli.state import is_agent_mode
 
         config = load_config()
         distinct_id = pre_resolved_email or _get_distinct_id()
 
+        # Detect anonymous → identified transition. If a stored anonymous_id
+        # exists and we just resolved to a real identity, fire a one-shot
+        # $identify event so PostHog stitches the pre-signup history onto
+        # the authenticated profile. Clear the stored id so we don't re-alias.
+        anon_id_to_alias: str | None = None
+        if (
+            distinct_id
+            and not distinct_id.startswith("cli-anon-")
+            and config.telemetry.anonymous_id
+        ):
+            anon_id_to_alias = config.telemetry.anonymous_id
+            config.telemetry.anonymous_id = ""
+            with contextlib.suppress(Exception):
+                save_config(config)
+
         payload = {
             "api_key": POSTHOG_API_KEY,
             "distinct_id": distinct_id,
@@ -92,6 +132,7 @@ def capture_event(
             "mem0_api_key": config.platform.api_key or "",
             "mem0_base_url": config.platform.base_url or "https://api.mem0.ai",
             "config_path": str(CONFIG_FILE),
+            "anon_distinct_id_to_alias": anon_id_to_alias,
         }
 
         subprocess.Popen(

cli/python/src/mem0_cli/telemetry_sender.py

@@ -27,9 +27,31 @@ def main() -> None:
     if ctx.get("needs_email") and ctx.get("mem0_api_key"):
         _resolve_and_cache_email(ctx, payload)
 
+    # Fire $identify *after* email resolution so PostHog links the stored
+    # anonymous id directly to the final identity (email, not the api-key
+    # hash). The regular event is sent next so it lands under the merged
+    # profile.
+    anon_id = ctx.get("anon_distinct_id_to_alias")
+    if anon_id:
+        _send_identify_event(ctx, payload, anon_id)
+
     _send_posthog_event(ctx["posthog_host"], payload)
 
 
+def _send_identify_event(ctx: dict, payload: dict, anon_id: str) -> None:
+    """Send a PostHog $identify event aliasing anon_id → payload['distinct_id']."""
+    identify_payload = {
+        "api_key": payload["api_key"],
+        "event": "$identify",
+        "distinct_id": payload["distinct_id"],
+        "properties": {
+            "$anon_distinct_id": anon_id,
+            "$lib": payload.get("properties", {}).get("$lib", "posthog-python"),
+        },
+    }
+    _send_posthog_event(ctx["posthog_host"], identify_payload)
+
+
 def _resolve_and_cache_email(ctx: dict, payload: dict) -> None:
     """Call /v1/ping/ to get the user's email, update the payload, and cache it."""
     try:

docs/api-reference.mdx

@@ -10,7 +10,7 @@ description: "REST APIs for memory management, search, and entity operations"
 Mem0 provides a comprehensive REST API for integrating advanced memory capabilities into your applications. Create, search, update, and manage memories across users, agents, and custom entities with simple HTTP requests.
 
 <Info>
-**Quick start:** Get your API key from the [Mem0 Dashboard](https://app.mem0.ai/dashboard/api-keys) and make your first memory operation in minutes.
+**Quick start:** Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a> and make your first memory operation in minutes.
 </Info>
 
 ---
@@ -87,7 +87,7 @@ All API requests require authentication using Token-based authentication. Includ
 Authorization: Token <your-api-key>
 ```
 
-Get your API key from the [Mem0 Dashboard](https://app.mem0.ai/dashboard/api-keys).
+Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
 
 <Warning>
 **Keep your API key secure.** Never expose it in client-side code or public repositories. Use environment variables and server-side requests only.

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

@@ -47,8 +47,6 @@ Provide at least one message or direct memory string. Most callers supply `messa
 | `messages` | array | No* | Conversation turns for Mem0 to infer memories from. Each object should include `role` and `content`. |
 | `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. |
-| `async_mode` | boolean (default `true`) | Optional | Controls asynchronous processing. Most clients leave this enabled. |
-| `output_format` | string (default `v1.1`) | Optional | Response format. `v1.1` wraps results in a `results` array. |
 
 > \* Provide at least one `messages` entry to describe what you are storing. For scoped memories, include `user_id`. You can also attach `agent_id`, `app_id`, `run_id`, `project_id`, or `org_id` to refine ownership.
 
@@ -83,20 +81,3 @@ Successful requests return an array of events queued for processing. Each event
 ```
 </CodeGroup>
 
-## Graph relationships
-
-Add Memories can enrich the knowledge graph on write. Set `enable_graph: true` to create entity nodes and relationships for the stored memory. Use this when you want downstream `get_all` or search calls to traverse connected entities.
-
-<CodeGroup>
-```json Graph-aware request
-{
-  "user_id": "alice",
-  "messages": [
-    { "role": "user", "content": "I met with Dr. Lee at General Hospital." }
-  ],
-  "enable_graph": true
-}
-```
-</CodeGroup>
-
-The response follows the same format, and related entities become available in [Graph Memory](/platform/features/graph-memory) queries.

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

@@ -62,8 +62,7 @@ To retrieve graph memory relationships between entities, pass `output_format="v1
 memories = client.get_all(
     filters={
         "user_id": "alex"
-    },
-    output_format="v1.1"
+    }
 )
 ```
 

docs/api-reference/organizations-projects.mdx

@@ -32,7 +32,7 @@ Example with the mem0 Python package:
 
 ```python
 from mem0 import MemoryClient
-client = MemoryClient(org_id='YOUR_ORG_ID', project_id='YOUR_PROJECT_ID')
+client = MemoryClient(api_key="your-api-key")
 ```
 
   </Tab>
@@ -41,10 +41,7 @@ client = MemoryClient(org_id='YOUR_ORG_ID', project_id='YOUR_PROJECT_ID')
 
 ```javascript
 import { MemoryClient } from "mem0ai";
-const client = new MemoryClient({
-  organizationId: "YOUR_ORG_ID",
-  projectId: "YOUR_PROJECT_ID"
-});
+const client = new MemoryClient({ apiKey: "your-api-key" });
 ```
 
   </Tab>
@@ -98,9 +95,6 @@ client.project.update(
     custom_instructions="..."
 )
 
-# Enable graph memory for the project
-client.project.update(enable_graph=True)
-
 # Use the input language for memory storage and retrieval
 client.project.update(multilingual=True)
 
@@ -111,7 +105,6 @@ client.project.update(
         {"personal_info": "User personal information and preferences"},
         {"work_context": "Professional context and work-related information"}
     ],
-    enable_graph=True,
     multilingual=True
 )
 ```
@@ -172,11 +165,11 @@ All project methods are available in async mode:
 from mem0 import AsyncMemoryClient
 
 async def manage_project():
-    client = AsyncMemoryClient(org_id='YOUR_ORG_ID', project_id='YOUR_PROJECT_ID')
+    client = AsyncMemoryClient(api_key="your-api-key")
 
     # All methods support async/await
     project_info = await client.project.get()
-    await client.project.update(enable_graph=True)
+    await client.project.update(multilingual=True)
     members = await client.project.get_members()
 
 # To call the async function properly

docs/changelog/highlights.mdx

@@ -0,0 +1,82 @@
+---
+title: "Highlights"
+description: "Major product launches, headline features, and milestones for Mem0."
+mode: "wide"
+---
+
+<Update label="2026-04-06" description="Mem0 Skill Graph">
+
+**Mem0 Skill Graph — In-Context Documentation for AI Agents**
+
+AI coding agents in Claude Code, Cursor, and Codex can now access Mem0 knowledge directly in their workflow — no doc searching required. Three interconnected skills launched:
+
+- **mem0 Core Skill** — Complete Python and TypeScript SDK reference, REST API patterns, and integration guides for LangChain, CrewAI, Autogen, and more
+- **mem0-cli Skill** — Terminal command reference, configuration walkthroughs, and CI/CD recipes
+- **mem0-vercel-ai-sdk Skill** — Vercel AI SDK provider API, memory-augmented generation patterns, and multi-provider setup
+
+</Update>
+
+<Update label="2026-04-06" description="Mem0 CLI v0.2.2">
+
+**Official Mem0 CLI — Now on PyPI and npm**
+
+A full-featured command-line interface for Mem0, available in both Python and Node.js:
+
+- **Install:** `pip install mem0-cli` or `npm install -g @mem0/cli`
+- **Full command suite** — `add`, `search`, `list`, `get`, `update`, `delete`, `import`, `config`, `init`, `status`, `entity`, `event`
+- **Interactive setup** — `mem0 init` with email verification or direct API key entry
+- **Works everywhere** — Platform (Mem0 Cloud) and self-hosted OSS modes
+- **Scriptable** — `--json` flag for CI/CD pipelines and automation
+- **Dual SDK** — Same commands, same experience across Python and Node.js
+
+</Update>
+
+<Update label="2026-04-04" description="OpenClaw v1.0.4">
+
+**OpenClaw Plugin — Production-Ready**
+
+The OpenClaw Mem0 plugin went from initial release to production-ready in one week (v1.0.0 → v1.0.4):
+
+- **Skills-based memory architecture** — New extraction pipeline with skill-loader, batched extraction, and domain-aware memory triage
+- **Dream gate** — Automatic memory consolidation during idle periods for higher-quality long-term recall
+- **Interactive CLI** — `openclaw mem0 init`, `status`, `config`, `import`, and `event` commands
+- **Unified tool naming** — `memory_add` and `memory_delete` replace 4 legacy tools, matching the platform API
+- **Security hardened** — Path traversal protection, pinned dependencies, 329 tests across 10 files
+
+</Update>
+
+<Update label="2026-04-02" description="Mem0 Plugin for AI Editors">
+
+**Mem0 Plugin for Claude Code, Cursor, and Codex**
+
+Launched a unified Mem0 plugin across three major AI development environments — Claude Code and Cursor first (March 25), then Codex (April 2):
+
+- **9 MCP memory tools** — add, search, get, update, delete, bulk delete, entity management via `mcp.mem0.ai`
+- **Lifecycle hooks** — Automatic memory capture at session start, context compaction, task completion, and session end
+- **Cloud MCP server** — Managed endpoint replaces local MCP and Smithery setup
+- **Streamable HTTP transport** — New MCP transport protocol for real-time streaming
+- **Codex-specific skill** — Dedicated skill in `mem0-plugin/skills/mem0-codex` for Codex workflows
+
+</Update>
+
+<Update label="2026-03-21" description="New Providers">
+
+**Apache AGE, Turbopuffer, MiniMax, and pgvector for Node.js**
+
+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)
+- **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
+- **Reasoning models** — `reasoning_effort` parameter for OpenAI o1/o3-style models
+
+</Update>
+
+<Update label="2026-03-14" description="Mem0 Platform Skill">
+
+**Mem0 Platform Skill on skills.sh**
+
+First skill launch — a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.
+
+</Update>

docs/changelog/openclaw.mdx

@@ -0,0 +1,199 @@
+---
+title: "OpenClaw"
+description: "Release notes for the OpenClaw plugin and agent harness."
+mode: "wide"
+---
+
+<Update label="2026-04-11" description="v1.0.6">
+
+**Bug Fixes:**
+- **Telemetry:** Replaced shared `"anonymous-openclaw"` fallback with a persistent per-machine random hash (`openclaw-anon-<uuid>`), so anonymous plugin users are counted individually in PostHog ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+- **Telemetry:** Added PostHog `$identify` event on first authenticated run to stitch anonymous history onto the authenticated profile ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+- **Telemetry:** Fixed event loss on short-lived CLI invocations — added `beforeExit` handler to flush queued events before the process exits ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+- **Telemetry:** Added lazy `/v1/ping/` email resolution so users who configure API key outside `mem0 init` show as their email in PostHog, not an md5 hash ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+- **Telemetry:** Unified CLI event prefix from `openclaw.<cmd>` to `openclaw.cli.<cmd>` on the needsSetup branch to match the authenticated branch ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+
+**Improvements:**
+- **API:** Added `source: "OPENCLAW"` to all provider calls (`add`, `search`, `getAll`) across tools, CLI commands, recall, and the OSS backend adapter ([#4790](https://github.com/mem0ai/mem0/pull/4790))
+
+</Update>
+
+<Update label="2026-04-07" description="v1.0.5">
+
+**Bug Fixes:**
+- **Init interactive choice bug**: Fixed number selection in `openclaw mem0 init` — entering 1/2/3 now correctly selects the corresponding option (was broken by readline prefill concatenating with user input)
+- **OSS pgvector crash** ([#4727](https://github.com/mem0ai/mem0/issues/4727)): Fixed "Client has already been connected" cascade when using pgvector in OSS mode. The warmup call swallowed errors leaving a half-initialized pg client; concurrent recall/capture then all hit `client.connect()` on the same client. Fix: let warmup errors propagate (so `initPromise` resets and retries with a fresh Memory + fresh pg client) and build fresh config objects per attempt instead of mutating shared state.
+
+**Removed:**
+- **`orgId` / `projectId` config parameters**: Removed from config schema, CLI (`config show/get/set`), init display, and providers. The API key is project-scoped, so separate org/project IDs are unnecessary and could cause access errors if mismatched.
+- **`enableGraph` config parameter**: Removed from all config surfaces, providers, backend, and tools. Graph memory is being deprecated — removing the flag avoids unnecessary exposure.
+
+</Update>
+
+<Update label="2026-04-04" description="v1.0.4">
+
+**New Features:**
+- **Interactive init flow**: `openclaw mem0 init` with interactive menu (email verification or direct API key). Non-interactive modes: `--api-key`, `--email`, `--email --code`
+- **`memory_add` tool**: Replaces `memory_store` — name now matches `mem0` CLI and platform API
+- **`memory_delete` tool**: Unified delete — single ID, search-then-delete, bulk, entity cascade. Replaces `memory_forget` and `memory_delete_all`
+- **CLI subcommands**: `openclaw mem0 init`, `openclaw mem0 status`, `openclaw mem0 config show`, `openclaw mem0 config set`
+- **`import` CLI command**: Bulk-import memories from a JSON file with `--user-id` and `--agent-id` overrides
+- **`event list` / `event status` CLI commands**: Monitor background processing events
+- **`fs-safe.ts` module**: Isolated filesystem wrappers in a separate entry point
+- **`backend/` module**: `PlatformBackend` with direct HTTP API access for CLI commands
+- **Plugin manifest**: Added `contracts.tools`, `configSchema`, and `uiHints` to `openclaw.plugin.json`
+- **Test suite**: 329 tests across 10 test files
+
+**Changes:**
+- **Modular architecture**: Extracted tools into `tools/` directory (6 files) and CLI into `cli/commands.ts`
+- **Code splitting**: tsup builds with `splitting: true` and two entry points
+- **Skills updated**: All SKILL.md files reference new tool names (`memory_add`, `memory_delete`)
+- **Auto-recall timeout**: Recall wrapped in 8-second `Promise.race`
+- **Auto-capture fire-and-forget**: `provider.add()` runs in background via `.then()/.catch()`
+- **Auto-capture minimum content gate**: Skips extraction when total user content is fewer than 50 chars
+
+**Removed:**
+- `memory_store` tool — replaced by `memory_add`
+- `memory_forget` tool — replaced by `memory_delete`
+- `memory_delete_all` tool — merged into `memory_delete`
+- `memory_history` tool and `history` CLI command — deprecated
+
+</Update>
+
+<Update label="2026-04-03" description="v1.0.3">
+
+**Bug Fixes:**
+- **Security**: Added `safePath()` containment helper to `readSkillFile` and `readDomainOverlay` in `skill-loader.ts` — prevents directory traversal
+- **Noise filter**: Reverted incorrect `After-Compaction` regex rename back to `Post-Compaction`
+
+**Changes:**
+- **Supply-chain hardening**: Pinned `mem0ai` dependency to exact `2.3.0` (was `^2.3.0`)
+
+**Tests:**
+- 12 new tests covering `safePath`, `readSkillFile`, `readDomainOverlay`, and `loadSkill` with traversal inputs
+
+</Update>
+
+<Update label="2026-04-02" description="v1.0.2">
+
+**Bug Fixes:**
+- **Security**: Removed `resolveEnvVars()` and `resolveEnvVarsDeep()` from `config.ts` — plugin-side env resolution was redundant and triggered static analysis warnings ([#4676](https://github.com/mem0ai/mem0/pull/4676))
+
+</Update>
+
+<Update label="2026-04-02" description="v1.0.1">
+
+**New Features:**
+- **CD workflow**: Added continuous deployment workflow with OIDC trusted publishing ([#4672](https://github.com/mem0ai/mem0/pull/4672))
+- **Plugin configuration manifest**: Added `compat` and `build` metadata to `package.json` ([#4667](https://github.com/mem0ai/mem0/pull/4667))
+- **LICENSE**: Added Apache-2.0 license file ([#4667](https://github.com/mem0ai/mem0/pull/4667))
+
+**Bug Fixes:**
+- **Dream gate**: Fixed cheap-first ordering, session isolation, and verified completion ([#4666](https://github.com/mem0ai/mem0/pull/4666))
+- **Graceful startup**: Plugin now starts gracefully when no API key is configured ([#4669](https://github.com/mem0ai/mem0/pull/4669))
+
+</Update>
+
+<Update label="2026-04-01" description="v1.0.0">
+
+**New Features:**
+- **Skills-based memory architecture**: New skill-loader and skill-based extraction pipeline with batched extraction ([#4624](https://github.com/mem0ai/mem0/pull/4624))
+- **Dream gate**: Memory consolidation and dream-cycle processing during idle periods
+- **Enhanced recall**: New `recall.ts` module with improved recall logic and skill-aware retrieval
+- **Memory triage skill**: Domain-aware memory triage with companion domain support and recall protocol
+- **Memory dream skill**: Skill for memory consolidation during idle periods
+- **Plugin configuration**: Added `openclaw.plugin.json` manifest and `scripts/configure.py` setup helper
+
+**Changes:**
+- Extraction pipeline refactored to use skills-based architecture for more contextual and higher quality memory capture
+
+</Update>
+
+<Update label="2026-03-26" description="v0.4.1">
+
+**New Features:**
+- **Improved extraction quality**: Enhanced noise filtering, deduplication, and better extraction instructions
+
+**Bug Fixes:**
+- **Credential detection**: Improved detection of credentials, API keys, and secrets in extraction instructions (#4552)
+- **Standalone timestamps**: Prevented extraction of standalone timestamps as memories (#4550)
+
+</Update>
+
+<Update label="2026-03-16" description="v0.4.0">
+
+**New Features:**
+- **Non-interactive trigger filtering**: Skips recall and capture for `cron`, `heartbeat`, `automation`, and `schedule` triggers
+- **Subagent hallucination prevention**: Detects ephemeral subagent sessions and routes recall to parent namespace
+- **Dynamic recall thresholding**: Memories scoring less than 50% of top result are dropped
+- **SQLite resilience**: Init error recovery with automatic retry for OSS mode
+- **`disableHistory` config option**: New `oss.disableHistory` flag
+- 78 unit tests covering filtering, isolation, trigger filtering, subagent detection, and SQLite resilience
+
+**Changes:**
+- Auto-recall threshold raised from 0.5 to 0.6 for stricter precision
+- Recall candidate pool increased to `topK * 2` for better filtering headroom
+- Relaxed extraction instructions: related facts kept together to preserve context
+
+**Bug Fixes:**
+- **Concurrent session race condition**: Lifecycle hooks now use `ctx.sessionKey` directly instead of a shared mutable variable
+
+</Update>
+
+<Update label="2026-03-12" description="v0.3.1">
+
+**New Features:**
+- **Message filtering pipeline**: Multi-stage noise removal before extraction
+- **Broad recall for new sessions**: Short or new-session prompts trigger secondary broad search
+- **Client-side threshold filtering**: Safety net that drops low-relevance results
+- **Temporal anchoring**: Extraction instructions now include current date
+- 55 unit tests covering filtering and isolation helpers
+
+**Changes:**
+- Extraction window expanded from last 10 to last 20 messages
+- Rewritten custom extraction instructions for conciseness and deduplication
+- Refactored monolithic `index.ts` (1772 lines) into 6 focused modules
+
+</Update>
+
+<Update label="2026-03-10" description="v0.3.0">
+
+**Bug Fixes:**
+- Updated `mem0ai` dependency with sqlite3 to better-sqlite3 migration (#4270)
+
+</Update>
+
+<Update label="2026-03-09" description="v0.2.0">
+
+**New Features:**
+- Per-agent memory isolation for multi-agent setups via `agentId`
+- "Understanding userId" section in docs
+
+**Changes:**
+- Updated config examples to use concrete `userId` values instead of placeholders
+
+**Bug Fixes:**
+- Migrated platform search to Mem0 v2 API
+
+</Update>
+
+<Update label="2026-02-19" description="v0.1.2">
+
+**New Features:**
+- Source field for openclaw memory entries
+
+**Bug Fixes:**
+- Auto-recall injection and auto-capture message drop
+
+</Update>
+
+<Update label="2026-02-02" description="v0.1.0">
+
+**New Features:**
+- Initial release of the OpenClaw Mem0 plugin
+- Platform mode (Mem0 Cloud) and open-source mode support
+- Auto-recall: inject relevant memories before each turn
+- Auto-capture: store facts after each turn
+- Configurable `topK`, `threshold`, and `apiVersion` options
+
+</Update>

docs/changelog/platform.mdx

@@ -0,0 +1,290 @@
+---
+title: "Platform"
+description: "Release notes for the Mem0 hosted platform — backend, dashboard, billing, and infrastructure changes."
+mode: "wide"
+---
+
+<Update label="2025-07-23" description="">
+
+**Bug Fixes:**
+- **Memory:** Fixed ADD functionality
+
+</Update>
+
+<Update label="2025-07-19" description="">
+
+**New Features:**
+- **UI:** Added Settings UI and latency display
+- **Performance:** Neo4j query optimization
+
+**Bug Fixes:**
+- **OpenMemory:** Fixed OMM raising unnecessary exceptions
+
+</Update>
+
+<Update label="2025-07-18" description="">
+
+**Improvements:**
+- **UI:** Updated Event UI
+- **Performance:** Fixed N+1 query issue in semantic_search_v2 by optimizing MemorySerializer field selection
+
+**Bug Fixes:**
+- **Memory:** Fixed duplicate memory index sentry error
+
+</Update>
+
+<Update label="2025-07-17" description="">
+
+**New Features:**
+- **UI:** New Settings Page
+- **Memory:** Duplicate memories entities support
+
+**Improvements:**
+- **Performance:** Optimized semantic search and get_all APIs by eliminating N+1 queries
+
+</Update>
+
+<Update label="2025-07-16" description="">
+
+**New Features:**
+- **Database:** Implemented read replica routing with enhanced logging and app-specific DB routing
+
+**Improvements:**
+- **Performance:** Improved query performance in search v2 and get all v2 endpoints
+
+**Bug Fixes:**
+- **API:** Fixed pagination for get all API
+
+</Update>
+
+<Update label="2025-07-12" description="">
+
+**Bug Fixes:**
+- **Graph:** Fixed social graph bugs and connection issues
+
+</Update>
+
+<Update label="2025-07-11" description="">
+
+**Improvements:**
+- **Rate Limiting:** New rate limit for V2 Search
+
+**Bug Fixes:**
+- **Slack:** Fixed Slack rate limit error with backend improvements
+
+</Update>
+
+<Update label="2025-07-10" description="">
+
+**Improvements:**
+- **Performance:** 
+  - Changed connection pooling time to 5 minutes
+  - Separated graph lambdas for better performance
+
+</Update>
+
+<Update label="2025-07-09" description="">
+
+**Improvements:**
+- **Graph:** Graph Optimizations V2 and memory improvements
+
+</Update>
+
+<Update label="2025-07-08" description="">
+
+**New Features:**
+- **Database:** Added read replica support for improved database performance
+- **UI:** Implemented UI changes for Users Page
+- **Feedback:** Enabled feedback functionality
+
+**Bug Fixes:**
+- **Serializer:** Fixed GET ALL Serializer
+
+</Update>
+
+<Update label="2025-07-05" description="">
+
+**New Features:**
+- **UI:** User Page Revamp and New Users Page
+
+</Update>
+
+<Update label="2025-07-04" description="">
+
+**New Features:**
+- **Users:** New Users Page implementation
+- **Tools:** Added script to backfill memory categories
+
+**Bug Fixes:**
+- **Filters:** Fixed Filters Get All functionality
+
+</Update>
+
+<Update label="2025-07-03" description="">
+
+**Improvements:**
+- **Graph:** Graph Memory optimization
+- **Memory:** Fixed exact memories and semantically similar memories retrieval
+
+</Update>
+
+<Update label="2025-07-02" description="">
+
+**Improvements:**
+- **Categorization:** Refactored categorization logic to utilize Gemini 2.5 Flash and improve message handling
+
+</Update>
+
+<Update label="2025-07-01" description="">
+
+**Bug Fixes:**
+- **Memory:** Fixed old_memory issue in Async memory addition lambda
+- **Events:** Fixed missing events
+
+</Update>
+
+<Update label="2025-06-30" description="">
+
+**Improvements:**
+- **Graph:** Improvements to graph memory and added user to LTM-STM
+
+</Update>
+
+<Update label="2025-06-28" description="">
+
+**New Features:**
+- **Graph:** Added support for SQS in graph memory addition
+- **Testing:** Added Locust load testing script and Grafana Dashboard
+
+</Update>
+
+<Update label="2025-06-27" description="">
+
+**Improvements:**
+- **Rate Limiting:** Updated rate limiting for ADD API to 1000/min
+- **Performance:** Improved Neo4j performance
+
+</Update>
+
+<Update label="2025-06-26" description="">
+
+**New Features:**
+- **Memory:** Edit Memory From Drawer functionality
+- **API:** Added Topic Suggestions API Endpoint
+
+</Update>
+
+<Update label="2025-06-25" description="">
+
+**New Features:**
+- **Group Chat:** Group-Chat v2 with Actor-Aware Memories
+- **Memory:** Editable Metadata in Memories
+- **UI:** Memory Actions Badges
+
+</Update>
+
+<Update label="2025-06-19" description="">
+
+**New Features:**
+- **Rate Limiting:** Implemented comprehensive rate limiting system
+
+**Improvements:**
+- **Performance:** Added performance indexes for memory stats query
+
+**Bug Fixes:**
+- **Search:** Fixed search events not respecting top-k parameter
+
+</Update>
+
+<Update label="2025-06-18" description="">
+
+**New Features:**
+- **Memory Management:** Implemented OpenAI Batch API for Memory Cleaning with fallback
+- **Playground:** Added Claude 4 support on Playground
+
+**Improvements:**
+- **Memory:** Added ability to update memory metadata
+
+</Update>
+
+<Update label="2025-06-17" description="">
+
+**New Features:**
+- **UI:** New Memories Page UI design
+
+</Update>
+
+<Update label="2025-06-16" description="">
+
+**Improvements:**
+- **Infrastructure:** Migrated to Application Load Balancer (ALB)
+
+</Update>
+
+<Update label="2025-06-13" description="">
+
+**Improvements:**
+- **Memory Management:** Enhanced Memory Management with Cosine Similarity Fallback
+
+</Update>
+
+<Update label="2025-06-11" description="">
+
+**New Features:**
+- **OMM:** Added OMM Script and UI functionality
+
+**Improvements:**
+- **API:** Added filters validation to semantic_search_v2 endpoint
+
+</Update>
+
+<Update label="2025-06-09" description="">
+
+**New Features:**
+- **Intercom:** Set Intercom events for ADD and SEARCH operations
+- **OpenMemory:** Added Posthog integration and feedback functionality
+- **MCP:** New JavaScript MCP Server with feedback support
+
+**Improvements:**
+- **Structured Data:** Enhanced structured data handling in memory management
+
+</Update>
+
+<Update label="2025-06-06" description="">
+
+**New Features:**
+- **OAuth:** Added Mem0 OAuth integration
+- **OMM:** Added OMM-Mem0 sync for deleted memories
+
+</Update>
+
+<Update label="2025-06-05" description="">
+
+**New Features:**
+- **Filters:** Implemented Wildcard Filters and refactored filter logic in V2 Views
+
+</Update>
+
+<Update label="2025-06-02" description="">
+
+**New Features:**
+- **OpenMemory Cloud:** Added OpenMemory Cloud support
+- **Structured Data:** Added 'structured_attributes' field to Memory model
+
+</Update>
+
+<Update label="2025-05-30" description="">
+
+**New Features:**
+- **Projects:** Added version and enable_graph to project views
+- **OpenMemory:** Added Postgres support for OpenMemory
+
+</Update>
+
+<Update label="2025-05-19" description="">
+
+**Bug Fixes:**
+- **Core:** Fixed unicode error in user_id, agent_id, run_id and app_id
+
+</Update>
+

docs/changelog/sdk.mdx

@@ -1,10 +1,9 @@
 ---
-title: "Product Updates"
-description: "Latest releases, bug fixes, and improvements for the Mem0 Python and TypeScript SDKs."
+title: "SDK & Tools"
+description: "Release notes for the Mem0 Python SDK, TypeScript SDK, Vercel AI SDK, CLI, and editor plugins."
 mode: "wide"
 ---
 
- 
 <Tabs>
 <Tab title="Python">
 
@@ -844,7 +843,6 @@ mode: "wide"
 </Tab>
 
 <Tab title="TypeScript">
-
 <Update label="2026-04-04" description="v2.4.6">
 
 **New Features & Updates:**
@@ -1160,352 +1158,152 @@ mode: "wide"
 
 </Tab>
 
-<Tab title="Platform">
+<Tab title="CLI">
 
-<Update label="2025-07-23" description="">
+<Update label="2026-04-11" description="Python v0.2.3 / Node v0.2.3">
 
 **Bug Fixes:**
-- **Memory:** Fixed ADD functionality
+- **Telemetry:** Replaced shared `"anonymous-cli"` fallback with a persistent per-machine random hash (`cli-anon-<uuid>`), so anonymous CLI users are counted individually in PostHog instead of collapsing into one identity ([#4789](https://github.com/mem0ai/mem0/pull/4789))
+- **Telemetry:** Added PostHog `$identify` event on first authenticated run to stitch pre-signup anonymous history onto the authenticated user profile ([#4789](https://github.com/mem0ai/mem0/pull/4789))
+
+**Improvements:**
+- **API:** All API calls now include `source=CLI` in request bodies (POST/PUT) and query params (GET/DELETE) for server-side attribution ([#4789](https://github.com/mem0ai/mem0/pull/4789))
 
 </Update>
 
-<Update label="2025-07-19" description="">
+<Update label="2026-04-06" description="Python v0.2.2 / Node v0.2.2">
 
 **New Features:**
-- **UI:** Added Settings UI and latency display
-- **Performance:** Neo4j query optimization
+- **Telemetry:** Added PostHog telemetry and source tracking to both Python and Node CLIs ([#4699](https://github.com/mem0ai/mem0/pull/4699))
+- **Validation:** API key validated upfront via `/v1/ping/` on startup — fail-fast with a helpful error instead of cryptic 401s ([#4701](https://github.com/mem0ai/mem0/pull/4701))
 
 **Bug Fixes:**
-- **OpenMemory:** Fixed OMM raising unnecessary exceptions
+- **CD:** Fixed OIDC trusted publishing with `npx npm@latest` ([#4724](https://github.com/mem0ai/mem0/pull/4724))
+- **CD:** Removed npm self-upgrade from CD workflows ([#4723](https://github.com/mem0ai/mem0/pull/4723))
 
 </Update>
 
-<Update label="2025-07-18" description="">
+<Update label="2026-04-03" description="Python v0.2.1 / Node v0.2.1">
 
-**Improvements:**
-- **UI:** Updated Event UI
-- **Performance:** Fixed N+1 query issue in semantic_search_v2 by optimizing MemorySerializer field selection
+**New Features:**
+- **Docs:** Comprehensive README with installation, usage examples, and purple branding ([#4680](https://github.com/mem0ai/mem0/pull/4680))
 
 **Bug Fixes:**
-- **Memory:** Fixed duplicate memory index sentry error
+- **npm:** Added `repository` field to Node packages for npm provenance ([#4671](https://github.com/mem0ai/mem0/pull/4671))
+- **CD:** Added CD workflows for Node SDK packages with OIDC trusted publishing ([#4670](https://github.com/mem0ai/mem0/pull/4670))
 
 </Update>
 
-<Update label="2025-07-17" description="">
+<Update label="2026-04-02" description="Python v0.2.0 / Node v0.1.1">
 
 **New Features:**
-- **UI:** New Settings Page
-- **Memory:** Duplicate memories entities support
-
-**Improvements:**
-- **Performance:** Optimized semantic search and get_all APIs by eliminating N+1 queries
-
-</Update>
-
-<Update label="2025-07-16" description="">
-
-**New Features:**
-- **Database:** Implemented read replica routing with enhanced logging and app-specific DB routing
-
-**Improvements:**
-- **Performance:** Improved query performance in search v2 and get all v2 endpoints
+- **`event` commands:** `mem0 event list` shows recent background processing events in a table; `mem0 event status <id>` shows full detail including nested memory results ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **`--json` / `--agent` flag:** Root-level flag switches all command output to a structured JSON envelope for programmatic/agent consumption. Envelope format: `{"status", "command", "duration_ms", "scope", "count", "data"}` ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **Agent output sanitization:** Raw API responses projected to only relevant fields per command (e.g., `add` → `{id, memory, event}`, `search` → `{id, memory, score, created_at, categories}`) ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **Email login:** Added email verification code login to `mem0 init` ([#4623](https://github.com/mem0ai/mem0/pull/4623))
+- **Brand update:** Updated color palette from purple to golden ([#4664](https://github.com/mem0ai/mem0/pull/4664))
+- **CI/CD:** Added CI pipelines and CD workflows for both CLIs ([#4640](https://github.com/mem0ai/mem0/pull/4640), [#4653](https://github.com/mem0ai/mem0/pull/4653))
 
 **Bug Fixes:**
-- **API:** Fixed pagination for get all API
-
-</Update>
-
-<Update label="2025-07-12" description="">
-
-**Bug Fixes:**
-- **Graph:** Fixed social graph bugs and connection issues
-
-</Update>
-
-<Update label="2025-07-11" description="">
+- **Node:** Fixed critical `MODULE_NOT_FOUND` crash on `status`, `import`, and all commands when installed globally — replaced runtime `createRequire` with build-time version injection ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- **Node:** API errors now show full response detail instead of bare "Bad Request" ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- **Python:** Fixed double error printing on all commands ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- **`status` command:** Replaced heavyweight `/v1/entities/` check with dedicated `GET /v1/ping/` endpoint ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **`add` command:** Deduplicated PENDING results from API; changed misleading count message ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **`init` command:** Partial flags now work in non-TTY; warns before overwriting existing config; added `--force` flag ([#4649](https://github.com/mem0ai/mem0/pull/4649))
+- **`delete` command:** Fixed entity delete via v2 API for all entity types ([#4649](https://github.com/mem0ai/mem0/pull/4649))
 
 **Improvements:**
-- **Rate Limiting:** New rate limit for V2 Search
-
-**Bug Fixes:**
-- **Slack:** Fixed Slack rate limit error with backend improvements
+- Tables now show full UUIDs (was truncated to 8 chars, making `mem0 get <id>` fail) ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- Search table includes Score column ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- `config get api_key` short-form aliases added ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- Client-side validation for `--expires`, `--page-size`, `--page`, `--top-k`, `--threshold`, and empty content ([#4636](https://github.com/mem0ai/mem0/pull/4636))
+- `printInfo` / `printScope` moved to stderr to avoid contaminating JSON piping ([#4636](https://github.com/mem0ai/mem0/pull/4636))
 
 </Update>
 
-<Update label="2025-07-10" description="">
+<Update label="2026-03-26" description="Python v0.1.0 / Node v0.1.0">
 
-**Improvements:**
-- **Performance:** 
-  - Changed connection pooling time to 5 minutes
-  - Separated graph lambdas for better performance
+**Initial Release — Official Mem0 CLI**
 
-</Update>
+A full-featured command-line interface for Mem0, available in both Python and Node.js:
 
-<Update label="2025-07-09" description="">
-
-**Improvements:**
-- **Graph:** Graph Optimizations V2 and memory improvements
-
-</Update>
-
-<Update label="2025-07-08" description="">
-
-**New Features:**
-- **Database:** Added read replica support for improved database performance
-- **UI:** Implemented UI changes for Users Page
-- **Feedback:** Enabled feedback functionality
-
-**Bug Fixes:**
-- **Serializer:** Fixed GET ALL Serializer
-
-</Update>
-
-<Update label="2025-07-05" description="">
-
-**New Features:**
-- **UI:** User Page Revamp and New Users Page
-
-</Update>
-
-<Update label="2025-07-04" description="">
-
-**New Features:**
-- **Users:** New Users Page implementation
-- **Tools:** Added script to backfill memory categories
-
-**Bug Fixes:**
-- **Filters:** Fixed Filters Get All functionality
-
-</Update>
-
-<Update label="2025-07-03" description="">
-
-**Improvements:**
-- **Graph:** Graph Memory optimization
-- **Memory:** Fixed exact memories and semantically similar memories retrieval
-
-</Update>
-
-<Update label="2025-07-02" description="">
-
-**Improvements:**
-- **Categorization:** Refactored categorization logic to utilize Gemini 2.5 Flash and improve message handling
-
-</Update>
-
-<Update label="2025-07-01" description="">
-
-**Bug Fixes:**
-- **Memory:** Fixed old_memory issue in Async memory addition lambda
-- **Events:** Fixed missing events
-
-</Update>
-
-<Update label="2025-06-30" description="">
-
-**Improvements:**
-- **Graph:** Improvements to graph memory and added user to LTM-STM
-
-</Update>
-
-<Update label="2025-06-28" description="">
-
-**New Features:**
-- **Graph:** Added support for SQS in graph memory addition
-- **Testing:** Added Locust load testing script and Grafana Dashboard
-
-</Update>
-
-<Update label="2025-06-27" description="">
-
-**Improvements:**
-- **Rate Limiting:** Updated rate limiting for ADD API to 1000/min
-- **Performance:** Improved Neo4j performance
-
-</Update>
-
-<Update label="2025-06-26" description="">
-
-**New Features:**
-- **Memory:** Edit Memory From Drawer functionality
-- **API:** Added Topic Suggestions API Endpoint
-
-</Update>
-
-<Update label="2025-06-25" description="">
-
-**New Features:**
-- **Group Chat:** Group-Chat v2 with Actor-Aware Memories
-- **Memory:** Editable Metadata in Memories
-- **UI:** Memory Actions Badges
-
-</Update>
-
-<Update label="2025-06-19" description="">
-
-**New Features:**
-- **Rate Limiting:** Implemented comprehensive rate limiting system
-
-**Improvements:**
-- **Performance:** Added performance indexes for memory stats query
-
-**Bug Fixes:**
-- **Search:** Fixed search events not respecting top-k parameter
-
-</Update>
-
-<Update label="2025-06-18" description="">
-
-**New Features:**
-- **Memory Management:** Implemented OpenAI Batch API for Memory Cleaning with fallback
-- **Playground:** Added Claude 4 support on Playground
-
-**Improvements:**
-- **Memory:** Added ability to update memory metadata
-
-</Update>
-
-<Update label="2025-06-17" description="">
-
-**New Features:**
-- **UI:** New Memories Page UI design
-
-</Update>
-
-<Update label="2025-06-16" description="">
-
-**Improvements:**
-- **Infrastructure:** Migrated to Application Load Balancer (ALB)
-
-</Update>
-
-<Update label="2025-06-13" description="">
-
-**Improvements:**
-- **Memory Management:** Enhanced Memory Management with Cosine Similarity Fallback
-
-</Update>
-
-<Update label="2025-06-11" description="">
-
-**New Features:**
-- **OMM:** Added OMM Script and UI functionality
-
-**Improvements:**
-- **API:** Added filters validation to semantic_search_v2 endpoint
-
-</Update>
-
-<Update label="2025-06-09" description="">
-
-**New Features:**
-- **Intercom:** Set Intercom events for ADD and SEARCH operations
-- **OpenMemory:** Added Posthog integration and feedback functionality
-- **MCP:** New JavaScript MCP Server with feedback support
-
-**Improvements:**
-- **Structured Data:** Enhanced structured data handling in memory management
-
-</Update>
-
-<Update label="2025-06-06" description="">
-
-**New Features:**
-- **OAuth:** Added Mem0 OAuth integration
-- **OMM:** Added OMM-Mem0 sync for deleted memories
-
-</Update>
-
-<Update label="2025-06-05" description="">
-
-**New Features:**
-- **Filters:** Implemented Wildcard Filters and refactored filter logic in V2 Views
-
-</Update>
-
-<Update label="2025-06-02" description="">
-
-**New Features:**
-- **OpenMemory Cloud:** Added OpenMemory Cloud support
-- **Structured Data:** Added 'structured_attributes' field to Memory model
-
-</Update>
-
-<Update label="2025-05-30" description="">
-
-**New Features:**
-- **Projects:** Added version and enable_graph to project views
-- **OpenMemory:** Added Postgres support for OpenMemory
-
-</Update>
-
-<Update label="2025-05-19" description="">
-
-**Bug Fixes:**
-- **Core:** Fixed unicode error in user_id, agent_id, run_id and app_id
+- **Install:** `pip install mem0-cli` (Python) or `npm install -g @mem0/cli` (Node.js)
+- **Full command suite:** `add`, `search`, `list`, `get`, `update`, `delete`, `import`, `config`, `init`, `status`, `entity`
+- **Interactive setup:** `mem0 init` with API key entry and user ID configuration
+- **Works everywhere:** Platform (Mem0 Cloud) and self-hosted OSS modes
+- **Scriptable:** `-o json` flag for CI/CD pipelines and automation
+- **Dual SDK:** Same commands, same experience across Python and Node.js
+- **Shared spec:** Both implementations driven by a single `cli-spec.json` ensuring identical behavior ([#4575](https://github.com/mem0ai/mem0/pull/4575))
 
 </Update>
 
 </Tab>
 
-<Tab title="Vercel AI SDK">
+<Tab title="Plugins">
 
-<Update label="2025-12-26" description="v2.0.5">
+<Update label="2026-04-02" description="mem0-plugin v1.0.0">
+
+**Mem0 Plugin for Claude Code, Cursor, and Codex**
+
+The unified Mem0 plugin for AI development environments:
+
+- **9 MCP memory tools:** `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities` — all via `mcp.mem0.ai`
+- **Lifecycle hooks:** Automatic memory capture at session start, context compaction, task completion, and session end
+- **Cloud MCP server:** Managed endpoint replaces local MCP and Smithery setup
+- **Streamable HTTP transport:** New MCP transport protocol for real-time streaming
+- **Codex-specific skill:** Dedicated skill in `mem0-plugin/skills/mem0-codex` for Codex workflows
+- **Supported editors:** Claude Code, Claude Cowork, Cursor, Codex
+
+</Update>
+
+<Update label="2025-12-26" description="Vercel AI SDK v2.0.5">
 **Bug Fix:**
-- **Vercel AI SDK:** Removed unnecessary dependencies to make the package lighter.
+- Removed unnecessary dependencies to make the package lighter.
 </Update>
 
-<Update label="2025-09-25" description="v2.0.4">
+<Update label="2025-09-25" description="Vercel AI SDK v2.0.3 – v2.0.4">
+**New Features:**
+- Added file support for multimodal capabilities with memory context (v2.0.3)
+
 **Bug Fix:**
-- **Vercel AI SDK:** Fixed version parameter in the AI SDK to use V2 for addition.
+- Fixed version parameter to use V2 for addition (v2.0.4)
 </Update>
 
-<Update label="2025-09-25" description="v2.0.3">
-**New Features:**
-- **Vercel AI SDK:** Added file support for multimodal capabilities with memory context
-</Update>
-
-<Update label="2025-09-03" description="v2.0.2">
+<Update label="2025-09-03" description="Vercel AI SDK v2.0.2">
 **Bug Fix:**
-- **Vercel AI SDK:** Fixed streaming response in the AI SDK.
+- Fixed streaming response in the AI SDK.
 </Update>
 
-<Update label="2025-08-05" description="v2.0.1">
+<Update label="2025-08-05" description="Vercel AI SDK v2.0.0 – v2.0.1">
 **New Features:**
-- **Vercel AI SDK:** Added a new param `host` to the config.
+- Migration to AI SDK V5 (v2.0.0)
+- Added `host` param to the config (v2.0.1)
 </Update>
 
-<Update label="2025-08-05" description="v2.0.0">
+<Update label="2025-06-15" description="Vercel AI SDK v1.0.6">
 **New Features:**
-- **Vercel AI SDK:** Migration to AI SDK V5.
+- Added `filter_memories` param.
 </Update>
 
-<Update label="2025-06-15" description="v1.0.6">
+<Update label="2025-05-23" description="Vercel AI SDK v1.0.5">
 **New Features:**
-- **Vercel AI SDK:** Added param `filter_memories`.
+- Added support for Google provider.
 </Update>
 
-<Update label="2025-05-23" description="v1.0.5">
+<Update label="2025-05-10" description="Vercel AI SDK v1.0.3 – v1.0.4">
 **New Features:**
-- **Vercel AI SDK:** Added support for Google provider.
-</Update>
+- Added support for `output_format` param (v1.0.4)
 
-<Update label="2025-05-10" description="v1.0.4">
-**New Features:**
-- **Vercel AI SDK:** Added support for new param `output_format`.
-</Update>
-
-<Update label="2025-05-08" description="v1.0.3">
 **Improvements:**
-- **Vercel AI SDK:** Added support for graceful failure in cases services are down.
+- Added graceful failure handling when services are down (v1.0.3)
 </Update>
 
-<Update label="2025-05-01" description="v1.0.1">
+<Update label="2025-05-01" description="Vercel AI SDK v1.0.1">
 **New Features:**
-- **Vercel AI SDK:** Added support for graph memories
+- Added support for graph memories.
 </Update>
 
 </Tab>
 
 </Tabs>
-

docs/components/vectordbs/dbs/langchain.mdx

@@ -15,7 +15,7 @@ Mem0 supports LangChain as a provider for vector store integration. LangChain pr
 ```python Python
 import os
 from mem0 import Memory
-from langchain_community.vectorstores import Chroma
+from langchain_chroma import Chroma
 from langchain_openai import OpenAIEmbeddings
 
 # Initialize a LangChain vector store

docs/components/vectordbs/dbs/valkey.mdx

@@ -50,4 +50,25 @@ Here are the parameters available for configuring Valkey:
 | `hnsw_m` | Number of bi-directional links for HNSW | `16` |
 | `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` |
 | `distance_metric` | Distance metric for vector similarity | `cosine` |
+
+## Cluster Mode
+
+To use Valkey with cluster mode enabled (CME), set `cluster_mode` to `true`:
+
+```python
+config = {
+    "vector_store": {
+        "provider": "valkey",
+        "config": {
+            "collection_name": "memories",
+            "valkey_url": "valkey://cluster-endpoint:6379",
+            "embedding_model_dims": 1536,
+            "cluster_mode": True
+        }
+    }
+}
+```
+
+When cluster mode is enabled, the connector uses `ValkeyCluster` instead of the standalone client, which handles `MOVED`/`ASK` redirections automatically. Search queries are coordinated across all shards by the valkey-search module's built-in coordinator. See the [valkey-search documentation](https://github.com/valkey-io/valkey-search) for details on cluster mode behavior.

docs/cookbooks/companions/quickstart-demo.mdx

@@ -45,7 +45,7 @@ Before you begin, follow these steps to set up the demo application:
    OPENAI_API_KEY=your_openai_api_key
    MEM0_API_KEY=your_mem0_api_key
    ```
-   You can obtain your `MEM0_API_KEY` by signing up at [Mem0 API Dashboard](https://app.mem0.ai/dashboard/api-keys).
+   You can obtain your `MEM0_API_KEY` by signing up at <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Dashboard</a>.
 
 5. Start the development server:
    ```bash

docs/cookbooks/companions/voice-companion-openai.mdx

@@ -129,13 +129,13 @@ async def search_memories(
         user_id=USER_ID,
         limit=5,
         threshold=0.7,  # Higher threshold for more relevant results
-        
+
     )
-    
+
     # Format and return the results
     if not results.get('results', []):
         return "I don't have any relevant memories about this topic."
-    
+
     memories = [f"• {result['memory']}" for result in results.get('results', [])]
     return "Here's what I remember that might be relevant:\n" + "\n".join(memories)
 ```
@@ -345,13 +345,13 @@ async def search_memories(
         user_id=USER_ID,
         limit=5,
         threshold=0.7,  # Higher threshold for more relevant results
-        
+
     )
-    
+
     # Format and return the results
     if not results.get('results', []):
         return "I don't have any relevant memories about this topic."
-    
+
     memories = [f"• {result['memory']}" for result in results.get('results', [])]
     return "Here's what I remember that might be relevant:\n" + "\n".join(memories)
 

docs/cookbooks/essentials/controlling-memory-ingestion.mdx

@@ -38,7 +38,7 @@ client = MemoryClient(api_key="your-api-key")
 ```
 
 <Note>
-Replace `your-api-key` with your actual Mem0 API key from the [dashboard](https://app.mem0.ai). Without proper API authentication, memory operations will fail.
+Replace `your-api-key` with your actual Mem0 API key from the <a href="https://app.mem0.ai" rel="nofollow">dashboard</a>. Without proper API authentication, memory operations will fail.
 </Note>
 
 ---

docs/cookbooks/essentials/entity-partitioning-playbook.mdx

@@ -17,7 +17,7 @@ from mem0 import MemoryClient
 client = MemoryClient(api_key="m0-...")
 ```
 
-Grab an API key from the <Link href="https://app.mem0.ai/">Mem0 dashboard</Link> to get started.
+Grab an API key from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a> to get started.
 
 ## Store and Retrieve Scoped Memories
 

docs/cookbooks/essentials/exporting-memories.mdx

@@ -20,7 +20,7 @@ client = MemoryClient(api_key="your-api-key")
 ```
 
 <Note>
-Your API key needs export permissions to download memory data. Check your project settings on the [dashboard](https://app.mem0.ai) if export operations fail with authentication errors.
+Your API key needs export permissions to download memory data. Check your project settings on the <a href="https://app.mem0.ai" rel="nofollow">dashboard</a> if export operations fail with authentication errors.
 </Note>
 
 Let's add some sample memories to work with:

docs/cookbooks/frameworks/chrome-extension.mdx

@@ -1,70 +0,0 @@
----
-title: Browser Extension Memory
-description: "Add Mem0's universal memory layer to Chrome chat surfaces."
----
-
-
-Enhance your AI interactions with Mem0, a Chrome extension that introduces a universal memory layer across platforms like ChatGPT, Claude, and Perplexity. Mem0 ensures seamless context sharing, making your AI experiences more personalized and efficient.
-
-<Note>
-  We now support Grok! The Mem0 Chrome Extension has been updated to work with Grok, bringing the same powerful memory capabilities to your Grok conversations.
-</Note>
-
-
-## Features
-
-- **Universal Memory Layer**: Share context seamlessly across ChatGPT, Claude, Perplexity, and Grok.
-- **Smart Context Detection**: Automatically captures relevant information from your conversations.
-- **Intelligent Memory Retrieval**: Surfaces pertinent memories at the right time.
-- **One-Click Sync**: Easily synchronize with existing ChatGPT memories.
-- **Memory Dashboard**: Manage all your memories in one centralized location.
-
-## Installation
-
-You can install the Mem0 Chrome Extension using one of the following methods:
-
-### Method 1: Chrome Web Store Installation
-
-1. **Download the Extension**: Open Google Chrome and navigate to the [Mem0 Chrome Extension page](https://chromewebstore.google.com/detail/mem0/onihkkbipkfeijkadecaafbgagkhglop?hl=en).
-2. **Add to Chrome**: Click on the "Add to Chrome" button.
-3. **Confirm Installation**: In the pop-up dialog, click "Add extension" to confirm. The Mem0 icon should now appear in your Chrome toolbar.
-
-### Method 2: Manual Installation
-
-1. **Download the Extension**: Clone or download the extension files from the [Mem0 Chrome Extension GitHub repository](https://github.com/mem0ai/mem0-chrome-extension).
-2. **Access Chrome Extensions**: Open Google Chrome and navigate to `chrome://extensions`.
-3. **Enable Developer Mode**: Toggle the "Developer mode" switch in the top right corner.
-4. **Load Unpacked Extension**: Click "Load unpacked" and select the directory containing the extension files.
-5. **Confirm Installation**: The Mem0 Chrome Extension should now appear in your Chrome toolbar.
-
-## Usage
-
-1. **Locate the Mem0 Icon**: After installation, find the Mem0 icon in your Chrome toolbar.
-2. **Sign In**: Click the icon and sign in with your Google account.
-3. **Interact with AI Assistants**:
-   - **ChatGPT and Perplexity**: Continue your conversations as usual; Mem0 operates seamlessly in the background.
-   - **Claude**: Click the Mem0 button or use the shortcut `Ctrl + M` to activate memory functions.
-
-## Configuration
-
-- **API Key**: Obtain your API key from the Mem0 Dashboard to connect the extension to the Mem0 API.
-- **User ID**: This is your unique identifier in the Mem0 system. If not provided, it defaults to `chrome-extension-user`.
-
-## Demo Video
-
-<iframe width="700" height="400" src="https://www.youtube.com/embed/dqenCMMlfwQ?si=zhGVrkq6IS_0Jwyj" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
-
-## Privacy and Data Security
-
-Your messages are sent to the Mem0 API for extracting and retrieving memories. Mem0 is committed to ensuring your data's privacy and security.
-
----
-
-<CardGroup cols={2}>
-  <Card title="Build a Mem0 Companion" icon="users" href="/cookbooks/essentials/building-ai-companion">
-    Learn the foundations of memory-powered assistants that work across platforms.
-  </Card>
-  <Card title="Multimodal Support" icon="image" href="/platform/features/multimodal-support">
-    Extend your browser interactions with vision and audio memory.
-  </Card>
-</CardGroup>

docs/cookbooks/frameworks/gemini-3-with-mem0-mcp.mdx

@@ -55,7 +55,7 @@ GEMINI_API_KEY=your-gemini-api-key-here
 ```
 
 <Note>
-Ensure you have your Mem0 API key from the [Mem0 Dashboard](https://app.mem0.ai) and your Gemini API key from the [Google AI Studio](https://ai.studio/app/api-keys).
+Ensure you have your Mem0 API key from the <a href="https://app.mem0.ai" rel="nofollow">Mem0 Dashboard</a> and your Gemini API key from the [Google AI Studio](https://ai.studio/app/api-keys).
 </Note>
 
 ## Gemini Memory Agent

docs/cookbooks/frameworks/llamaindex-multiagent.mdx

@@ -41,7 +41,7 @@ Set up your environment variables:
 - `MEM0_API_KEY`: Your Mem0 Platform API key
 - `OPENAI_API_KEY`: Your OpenAI API key
 
-You can obtain your Mem0 Platform API key from the [Mem0 Platform](https://app.mem0.ai).
+You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.
 
 ## Complete Implementation
 
@@ -357,7 +357,7 @@ Based on our previous session, I remember we covered Vision Language Models and
 ## Help & Resources
 
 - [LlamaIndex Agent Workflows](https://docs.llamaindex.ai/en/stable/use_cases/agents/)
-- [Mem0 Platform](https://app.mem0.ai/)
+- <a href="https://app.mem0.ai/" rel="nofollow">Mem0 Platform</a>
 
 ---
 

docs/cookbooks/frameworks/llamaindex-react.mdx

@@ -25,7 +25,7 @@ os.environ["OPENAI_API_KEY"] = "<your-openai-api-key>"
 llm = OpenAI(model="gpt-4.1-nano-2025-04-14")
 ```
 
-Initialize the Mem0 client. You can find your API key [here](https://app.mem0.ai/dashboard/api-keys). Read about Mem0 [Open Source](https://docs.mem0.ai/open-source/overview).
+Initialize the Mem0 client. You can find your API key <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">here</a>. Read about Mem0 [Open Source](https://docs.mem0.ai/open-source/overview).
 ```python
 os.environ["MEM0_API_KEY"] = "<your-mem0-api-key>"
 

docs/cookbooks/frameworks/mirofish-swarm-memory.mdx

@@ -754,7 +754,7 @@ Exact output varies as Mem0 automatically extracts and deduplicates entities. Th
 - [MiroFish GitHub](https://github.com/666ghj/MiroFish) — Source code and setup guide
 - [MiroFish Documentation](https://deepwiki.com/666ghj/MiroFish) — Full framework docs
 - [Mem0 Graph Memory](/open-source/features/graph-memory) — Graph Memory documentation
-- [Mem0 Documentation](https://docs.mem0.ai/) — Full API reference
+- [Mem0 Documentation](https://docs.mem0.ai/introduction) — Full API reference
 
 <CardGroup cols={2}>
   <Card title="Graph Memory" icon="network-wired" href="/open-source/features/graph-memory">

docs/cookbooks/integrations/agents-sdk-tool.mdx

@@ -222,8 +222,8 @@ context = Mem0Context(user_id="user123")
 
 ## Resources
 
-- [Mem0 Documentation](https://docs.mem0.ai)
-- [Mem0 Dashboard](https://app.mem0.ai/dashboard)
+- [Mem0 Documentation](https://docs.mem0.ai/introduction)
+- <a href="https://app.mem0.ai/dashboard" rel="nofollow">Mem0 Dashboard</a>
 - [API Reference](https://docs.mem0.ai/api-reference)
 
 ---

docs/cookbooks/integrations/aws-bedrock.mdx

@@ -137,7 +137,7 @@ With Mem0 and AWS services like Bedrock, OpenSearch, and Neptune Analytics, you
   <Card title="Neptune Analytics with Mem0" icon="database" href="/cookbooks/integrations/neptune-analytics">
     Explore graph-based memory storage with AWS Neptune Analytics.
   </Card>
-  <Card title="Graph Memory Features" icon="sitemap" href="/platform/features/graph-memory">
+  <Card title="Graph Memory Features" icon="sitemap" href="/open-source/features/graph-memory">
     Learn how to leverage knowledge graphs for entity relationships.
   </Card>
 </CardGroup>

docs/cookbooks/integrations/openai-tool-calls.mdx

@@ -23,7 +23,7 @@ MEM0_API_KEY=your_mem0_api_key
 OPENAI_API_KEY=your_openai_api_key
 ```
 
-Get your Mem0 API key from the [Mem0 Dashboard](https://app.mem0.ai/dashboard/api-keys).
+Get your Mem0 API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
 
 ### Configuration
 
@@ -308,8 +308,8 @@ run().catch(console.error);
 
 ## Resources
 
-- [Mem0 Documentation](https://docs.mem0.ai)
-- [Mem0 Dashboard](https://app.mem0.ai/dashboard)
+- [Mem0 Documentation](https://docs.mem0.ai/introduction)
+- <a href="https://app.mem0.ai/dashboard" rel="nofollow">Mem0 Dashboard</a>
 - [API Reference](https://docs.mem0.ai/api-reference)
 - [OpenAI Documentation](https://platform.openai.com/docs)
 

docs/cookbooks/overview.mdx

@@ -201,10 +201,7 @@ Here are some examples of how Mem0 can be integrated into various applications:
   >
     Persistent personality for Eliza agents.
   </Card>
-  <Card title="Browser Extension Memory" icon="globe" href="/cookbooks/frameworks/chrome-extension">
-    Universal memory layer for Chrome.
-  </Card>
-</CardGroup>
+  </CardGroup>
 
 ---
 

docs/core-concepts/memory-operations/add.mdx

@@ -21,7 +21,7 @@ Adding memory is how Mem0 captures useful details from a conversation so your ag
 - **Messages** – The ordered list of user/assistant turns you send to `add`.
 - **Infer** – Controls whether Mem0 extracts structured memories (`infer=True`, default) or stores raw messages.
 - **Metadata** – Optional filters (e.g., `{"category": "movie_recommendations"}`) that improve retrieval later.
-- **User / Session identifiers** – `user_id`, `session_id`, or `run_id` that scope the memory for future searches.
+- **User / Session identifiers** – `user_id`, `agent_id`, or `run_id` that scope the memory for future searches.
 
 ## How does it work?
 
@@ -85,7 +85,6 @@ const messages = [
 
 await client.add(messages, {
   user_id: "alice",
-  version: "v2",
 });
 ```
 </CodeGroup>
@@ -173,7 +172,6 @@ For full list of supported fields, required formats, and advanced options, see t
 | Capability | Mem0 Platform | Mem0 OSS |
 | --- | --- | --- |
 | Conflict resolution | Automatic with dashboard visibility | SDK handles merges locally; you control storage |
-| Graph writes | Toggle per request (`enable_graph=True`) | Requires configuring a graph provider |
 | Rate limits | Managed quotas per workspace | Limited by your hardware and provider APIs |
 | Dashboard visibility | Yes — inspect memories visually | Inspect via CLI, logs, or custom UI |
 

docs/core-concepts/memory-operations/delete.mdx

@@ -120,7 +120,7 @@ import MemoryClient from 'mem0ai';
 
 const client = new MemoryClient({ apiKey: "your-api-key" });
 
-client.deleteAll({ user_id: "alice" })
+client.deleteAll({ userId: "alice" })
   .then(result => console.log(result))
   .catch(error => console.error(error));
 ```
@@ -162,12 +162,12 @@ import MemoryClient from 'mem0ai';
 const client = new MemoryClient({ apiKey: "your-api-key" });
 
 // Delete all memories across every user in the project
-client.deleteAll({ user_id: "*" })
+client.deleteAll({ userId: "*" })
   .then(result => console.log(result))
   .catch(error => console.error(error));
 
 // Full project wipe — all four filters must be explicitly set to "*"
-client.deleteAll({ user_id: "*", agent_id: "*", app_id: "*", run_id: "*" })
+client.deleteAll({ userId: "*", agentId: "*", appId: "*", runId: "*" })
   .then(result => console.log(result))
   .catch(error => console.error(error));
 ```

docs/core-concepts/memory-types.mdx

@@ -52,7 +52,7 @@ Mem0 maps these classic categories onto its layered storage so you can decide wh
 Mem0 stores each layer separately and merges them when you query:
 
 1. **Capture** – Messages enter the conversation layer while the turn is active.
-2. **Promote** – Relevant details persist to session or user memory based on your `user_id`, `session_id`, and metadata.
+2. **Promote** – Relevant details persist to session or user memory based on your `user_id`, `run_id`, and metadata.
 3. **Retrieve** – The search pipeline pulls from all layers, ranking user memories first, then session notes, then raw history.
 
 ```python
@@ -66,19 +66,19 @@ memory = Memory(api_key=os.environ["MEM0_API_KEY"])
 memory.add(
     ["I'm Alex and I prefer boutique hotels."],
     user_id="alex",
-    session_id="trip-planning-2025",
+    run_id="trip-planning-2025",
 )
 
 # Later in the session, pull long-term + session context
 results = memory.search(
     "Any hotel preferences?",
     user_id="alex",
-    session_id="trip-planning-2025",
+    run_id="trip-planning-2025",
 )
 ```
 
 <Tip>
-  Use `session_id` when you want short-term context to expire automatically; rely on `user_id` for lasting personalization.
+  Use `run_id` when you want short-term context to expire automatically; rely on `user_id` for lasting personalization.
 </Tip>
 
 ## When should you use each layer?

docs/docs.json

@@ -12,7 +12,7 @@
   "logo": {
     "light": "/logo/light.svg",
     "dark": "/logo/dark.svg",
-    "href": "https://app.mem0.ai/"
+    "href": "https://mem0.ai"
   },
   "navigation": {
     "anchors": [
@@ -70,7 +70,6 @@
                           "platform/features/v2-memory-filters",
                           "platform/features/entity-scoped-memory",
                           "platform/features/async-client",
-                          "platform/features/async-mode-default-change",
                           "platform/features/multimodal-support",
                           "platform/features/custom-categories"
                         ]
@@ -79,7 +78,6 @@
                         "group": "Advanced Features",
                         "icon": "bolt",
                         "pages": [
-                          "platform/features/graph-memory",
                           "platform/features/graph-threshold",
                           "platform/features/advanced-retrieval",
                           "platform/advanced-memory-operations",
@@ -94,8 +92,7 @@
                         "pages": [
                           "platform/features/direct-import",
                           "platform/features/memory-export",
-                          "platform/features/timestamp",
-                          "platform/features/expiration-date"
+                          "platform/features/timestamp"
                         ]
                       },
                       {
@@ -122,8 +119,6 @@
                     "icon": "arrow-right",
                     "pages": [
                       "migration/oss-to-platform",
-                      "migration/v0-to-v1",
-                      "migration/breaking-changes",
                       "migration/api-changes"
                     ]
                   },
@@ -133,13 +128,6 @@
                     "pages": [
                       "platform/contribute"
                     ]
-                  },
-                  {
-                    "group": "Release Notes",
-                    "icon": "rocket",
-                    "pages": [
-                      "changelog"
-                    ]
                   }
                 ]
               },
@@ -179,7 +167,7 @@
                       "open-source/features/reranker-search",
                       "open-source/features/async-memory",
                       "open-source/features/multimodal-support",
-                      "open-source/features/custom-fact-extraction-prompt",
+                      "open-source/features/custom-instructions",
                       "open-source/features/custom-update-memory-prompt",
                       "open-source/features/rest-api",
                       "open-source/features/openai_compatibility"
@@ -385,7 +373,6 @@
                       "cookbooks/frameworks/llamaindex-multiagent",
                       "cookbooks/frameworks/multimodal-retrieval",
                       "cookbooks/frameworks/eliza-os-character",
-                      "cookbooks/frameworks/chrome-extension",
                       "cookbooks/frameworks/gemini-3-with-mem0-mcp",
                       "cookbooks/frameworks/mirofish-swarm-memory"
                     ]
@@ -416,7 +403,8 @@
                       "integrations/openai-agents-sdk",
                       "integrations/google-ai-adk",
                       "integrations/mastra",
-                      "integrations/vercel-ai-sdk"
+                      "integrations/vercel-ai-sdk",
+                      "integrations/chatdev"
                     ]
                   },
                   {
@@ -558,6 +546,21 @@
                     ]
                   }
                 ]
+              },
+              {
+                "tab": "Release Notes",
+                "groups": [
+                  {
+                    "group": "Release Notes",
+                    "icon": "rocket",
+                    "pages": [
+                      "changelog/highlights",
+                      "changelog/sdk",
+                      "changelog/platform",
+                      "changelog/openclaw"
+                    ]
+                  }
+                ]
               }
             ]
           }
@@ -608,6 +611,34 @@
     ]
   },
   "redirects": [
+    {
+      "source": "/migration/breaking-changes",
+      "destination": "/"
+    },
+    {
+      "source": "/migration/v0-to-v1",
+      "destination": "/"
+    },
+    {
+      "source": "/platform/features/expiration-date",
+      "destination": "/"
+    },
+    {
+      "source": "/platform/features/async-mode-default-change",
+      "destination": "/"
+    },
+    {
+      "source": "/open-source/features/custom-fact-extraction-prompt",
+      "destination": "/open-source/features/custom-instructions"
+    },
+    {
+      "source": "/platform/features/graph-memory",
+      "destination": "/open-source/features/graph-memory"
+    },
+    {
+      "source": "/changelog",
+      "destination": "/changelog/highlights"
+    },
     {
       "source": "/api-reference/memory/v2-search-memories",
       "destination": "/api-reference/memory/search-memories"
@@ -766,7 +797,11 @@
     },
     {
       "source": "/examples/chrome-extension",
-      "destination": "/cookbooks/frameworks/chrome-extension"
+      "destination": "/cookbooks/overview"
+    },
+    {
+      "source": "/cookbooks/frameworks/chrome-extension",
+      "destination": "/cookbooks/overview"
     },
     {
       "source": "/examples",
@@ -806,7 +841,7 @@
     },
     {
       "source": "/v0x/examples/chrome-extension",
-      "destination": "/cookbooks/frameworks/chrome-extension"
+      "destination": "/cookbooks/overview"
     },
     {
       "source": "/v0x/examples/youtube-assistant",
@@ -958,7 +993,7 @@
     },
     {
       "source": "/features/graph-memory",
-      "destination": "/platform/features/graph-memory"
+      "destination": "/open-source/features/graph-memory"
     },
     {
       "source": "/features/:slug",

docs/integrations.mdx

@@ -409,4 +409,11 @@ Here are the available integrations for Mem0:
   >
     Use Mem0 with AWS Bedrock and OpenSearch Service for cloud-native persistent semantic memory storage.
   </Card>
+  <Card
+    title="ChatDev"
+    icon="comments"
+    href="/integrations/chatdev"
+  >
+    Add persistent cloud-managed memory to ChatDev multi-agent workflows with zero-code YAML configuration.
+  </Card>
 </CardGroup>

docs/integrations/agentops.mdx

@@ -24,7 +24,7 @@ pip install mem0ai agentops python-dotenv
 2. Valid API keys:
    - [AgentOps API Key](https://app.agentops.ai/dashboard/api-keys)
    - OpenAI API Key (for LLM operations)
-   - [Mem0 API Key](https://app.mem0.ai/dashboard/api-keys) (optional, for cloud operations)
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a> (optional, for cloud operations)
 
 ## Basic Integration Example
 

docs/integrations/agno.mdx

@@ -23,7 +23,7 @@ pip install agno mem0ai python-dotenv
 ```
 
 2. Valid API keys:
-   - [Mem0 API Key](https://app.mem0.ai/dashboard/api-keys)
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
    - OpenAI API Key (for the agent model)
 
 ## Quick Integration (Using `Mem0Tools`)

docs/integrations/autogen.mdx

@@ -19,7 +19,7 @@ pip install autogen mem0ai openai python-dotenv
 
 First, we'll import the necessary libraries and set up our configurations.
 
-<Note>Remember to get the Mem0 API key from [Mem0 Platform](https://app.mem0.ai).</Note>
+<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
 
 ```python
 import os

docs/integrations/chatdev.mdx

@@ -0,0 +1,243 @@
+---
+title: ChatDev
+description: "Add persistent, cloud-managed memory to ChatDev multi-agent workflows with Mem0 — no code required, just YAML configuration."
+---
+
+Build multi-agent workflows in [ChatDev](https://github.com/OpenBMB/ChatDev) with persistent memory powered by Mem0. ChatDev is a zero-code multi-agent platform where agents, tools, and workflows are defined entirely in YAML. Mem0 integrates as a built-in memory store (`type: mem0`), giving your agents cloud-managed semantic search and cross-session persistence — all without writing any code.
+
+## Overview
+
+In this guide, you'll:
+1. Set up ChatDev with the Mem0 memory store
+2. Configure agents with persistent memory using YAML
+3. Enable automatic memory retrieval and storage across conversations
+4. Leverage cross-session persistence for personalized multi-agent interactions
+
+## Prerequisites
+
+- **Python 3.12+**
+- **[uv](https://docs.astral.sh/uv/)** — Python package manager
+- **Node.js 18+** and **npm** — only needed if using the web console
+- A **Mem0 API key** from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>
+- An **OpenAI API key** (or another LLM provider supported by ChatDev)
+
+## Setup and Configuration
+
+Install ChatDev and its dependencies (includes `mem0ai`):
+
+```bash
+git clone https://github.com/OpenBMB/ChatDev.git
+cd ChatDev
+uv sync
+```
+
+If you plan to use the web console, also install the frontend:
+
+```bash
+cd frontend && npm install && cd ..
+```
+
+Set up your environment variables in a `.env` file:
+
+<Note>Get your Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
+
+```bash
+MEM0_API_KEY=your-mem0-api-key
+API_KEY=your-openai-api-key
+BASE_URL=https://api.openai.com/v1
+```
+
+## Configure Mem0 Memory Store
+
+In your ChatDev workflow YAML, add a Mem0 memory store in the `memory` section:
+
+```yaml
+memory:
+  - name: mem0_store
+    type: mem0
+    config:
+      api_key: ${MEM0_API_KEY}
+      user_id: my-user-123       # optional: scope memories to a user
+      agent_id: my-agent         # optional: scope memories to an agent
+```
+
+Mem0 handles all storage, embeddings, and search server-side — no local vector databases or embedding models are needed.
+
+## Attach Memory to an Agent
+
+Reference the memory store in your agent node's `memories` list:
+
+```yaml
+nodes:
+  - id: writer
+    type: agent
+    config:
+      role: |
+        You are a knowledgeable writer. Use your memories to build
+        on past interactions.
+      memories:
+        - name: mem0_store
+          top_k: 5
+          similarity_threshold: 0.5   # minimum relevance score (0.0–1.0); set to -1.0 to disable
+          retrieve_stage:
+            - gen
+          read: true
+          write: true
+```
+
+- **`read: true`** — Agent retrieves relevant memories before generating a response
+- **`write: true`** — Agent stores new memories from user input after each interaction
+- **`top_k`** — Number of memories to retrieve per query
+- **`similarity_threshold`** — Minimum relevance score for retrieved memories. Set to `-1.0` to return all results regardless of score
+- **`retrieve_stage`** — When to retrieve memories. Options: `pre_gen_thinking` (before generation), `gen` (during generation), `post_gen_thinking` (after generation), `finished` (after completion)
+
+## Full Example Workflow
+
+Here's a complete workflow YAML that creates a memory-backed conversational agent:
+
+```yaml
+version: 0.4.0
+graph:
+  description: Memory-backed conversation using Mem0
+
+  nodes:
+    - id: writer
+      type: agent
+      config:
+        base_url: ${BASE_URL}
+        api_key: ${API_KEY}
+        provider: openai
+        name: gpt-5.4
+        role: |
+          You are a knowledgeable writer. Use your memories to build
+          on past interactions. If memory sections are provided
+          (wrapped by ===== Related Memories =====), incorporate
+          relevant context from those memories into your response.
+        params:
+          temperature: 0.7
+          max_tokens: 2000
+        memories:
+          - name: mem0_store
+            top_k: 5
+            retrieve_stage:
+              - gen
+            read: true
+            write: true
+
+  memory:
+    - name: mem0_store
+      type: mem0
+      config:
+        api_key: ${MEM0_API_KEY}
+        user_id: project-user-123
+        agent_id: writer-agent
+
+  start:
+    - writer
+  end: []
+```
+
+Run the workflow:
+
+```bash
+# Option 1: CLI (recommended for quick testing)
+uv run python run.py --path yaml_instance/demo_mem0_memory.yaml --name my_project
+
+# Option 2: Web console
+make dev
+# Backend starts at http://localhost:6400, frontend at http://localhost:5173
+```
+
+To use the web console, open `http://localhost:5173`, create a new workflow, and paste your YAML configuration into the editor. The web console provides a visual chat interface for interacting with your memory-backed agents.
+
+## How It Works
+
+When an agent with Mem0 memory receives input, the following cycle runs automatically:
+
+**1. Retrieve** — Before generating a response, ChatDev queries Mem0 with the user's input using semantic search. Relevant memories are injected into the agent's context in this format:
+
+```
+===== Related Memories =====
+--- mem0_store ---
+1. User's favorite language is Rust
+2. User lives in San Francisco
+===== End of Memory =====
+```
+
+This is why the role prompt in the example references `===== Related Memories =====` — the agent needs to know how to use this injected context.
+
+**2. Generate** — The agent produces a response using the retrieved memories as additional context.
+
+**3. Store** — After generation, the user's input is sent to Mem0 via `client.add()`. Mem0's extraction model automatically identifies and stores facts, preferences, and key information. Only user input is stored — agent output is excluded to keep memories clean.
+
+Memories persist in Mem0's cloud across all sessions. The next time the same `user_id` or `agent_id` is used, previous memories are automatically retrieved.
+
+## Dual-Scope Memory (User + Agent)
+
+When both `user_id` and `agent_id` are configured, Mem0 uses an OR filter to search across both scopes in a single query:
+
+```yaml
+memory:
+  - name: shared_store
+    type: mem0
+    config:
+      api_key: ${MEM0_API_KEY}
+      user_id: alice              # stores user preferences ("Alice prefers dark mode")
+      agent_id: support-bot       # stores agent-learned context ("Resolved Alice's billing issue")
+```
+
+This means retrieval returns memories from **both** the user's scope and the agent's scope. Writes include both IDs, so each memory is accessible from either dimension. Use this when you want an agent to remember both what the user told it *and* what the agent learned across sessions.
+
+## Configuration Reference
+
+### Memory Store Config
+
+| Field | Required | Description |
+|-------|----------|-------------|
+| `api_key` | Yes | Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a> |
+| `user_id` | No | Scope memories to a specific user |
+| `agent_id` | No | Scope memories to a specific agent |
+
+### Memory Attachment Config
+
+| Field | Default | Description |
+|-------|---------|-------------|
+| `top_k` | `3` | Number of memories to retrieve |
+| `similarity_threshold` | `-1.0` (disabled) | Minimum relevance score. Set a value between `0.0` and `1.0` to filter low-relevance results. Default (`-1.0`) returns all matches without filtering |
+| `retrieve_stage` | `["gen"]` | When to retrieve: `pre_gen_thinking`, `gen`, `post_gen_thinking`, or `finished` |
+| `read` | `true` | Whether the agent retrieves memories |
+| `write` | `true` | Whether the agent stores new memories |
+
+## Tips and Common Pitfalls
+
+<Info>
+**Indexing delay** — Freshly stored memories may take a few seconds to become searchable. If a memory isn't retrieved immediately after being stored, wait a moment and try again.
+</Info>
+
+- **No memories returned on first run** — This is expected. Memories are stored *after* the agent responds, so the first interaction has no prior context. Memories appear starting from the second interaction onward.
+- **`mem0ai` not installed** — If you see `ImportError: mem0ai is required for Mem0Memory`, run `uv add mem0ai` or `pip install mem0ai` to add the dependency.
+- **Invalid API key** — A wrong or expired `MEM0_API_KEY` will log errors like `Mem0 search failed` or `Mem0 add failed` but won't crash the agent. Check your key at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>.
+- **Pipeline headers in memories** — ChatDev automatically strips internal pipeline headers (e.g., `=== INPUT FROM TASK (user) ===`) before sending text to Mem0, so your memories stay clean.
+- **Clearing test memories** — To delete memories created during testing, use the Mem0 dashboard at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a> or the Python SDK: `MemoryClient().delete_all(user_id="your-test-user")`.
+
+## Key Features
+
+1. **Zero-Code Integration** — Configure Mem0 entirely through YAML, no Python code required
+2. **Cloud-Managed Storage** — Mem0 handles embeddings, persistence, and search server-side
+3. **Semantic Search** — Retrieve contextually relevant memories, not just keyword matches
+4. **Cross-Session Persistence** — Memories survive across runs, sessions, and restarts
+5. **Multi-Agent Memory Sharing** — Multiple agents can share memories through common `user_id` or `agent_id` scopes
+6. **Intelligent Input Processing** — Only user input is stored; agent output is excluded to prevent noisy memories
+
+## Conclusion
+
+By adding Mem0 as a memory store in ChatDev, your multi-agent workflows gain persistent, intelligent memory with zero code changes. Agents automatically remember past interactions and use that context to provide personalized, coherent responses across sessions.
+
+<CardGroup cols={2}>
+  <Card title="CrewAI Integration" icon="users" href="/integrations/crewai">
+    Build multi-agent systems with CrewAI and Mem0
+  </Card>
+  <Card title="AutoGen Integration" icon="robot" href="/integrations/autogen">
+    Build conversational agents with AutoGen and Mem0
+  </Card>
+</CardGroup>

docs/integrations/claude-code.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**Claude Code**](https://docs.anthropic.com/en/docs/cl
 Before setting up Mem0 with Claude Code, ensure you have:
 
 1. A Mem0 Platform account and API key:
-   - [Sign up at app.mem0.ai](https://app.mem0.ai)
-   - [Get your API key](https://app.mem0.ai/dashboard/api-keys) (starts with `m0-`)
+   - <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
 
 2. Claude Code CLI or Claude Cowork desktop app installed
 

docs/integrations/codex.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**OpenAI Codex**](https://openai.com/index/codex/) wit
 Before setting up Mem0 with Codex, ensure you have:
 
 1. A Mem0 Platform account and API key:
-   - [Sign up at app.mem0.ai](https://app.mem0.ai)
-   - [Get your API key](https://app.mem0.ai/dashboard/api-keys) (starts with `m0-`)
+   - <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
 
 2. OpenAI Codex access
 

docs/integrations/crewai.mdx

@@ -22,7 +22,7 @@ pip install crewai crewai-tools mem0ai
 
 Import required modules and set up configurations:
 
-<Note>Remember to get your API keys from [Mem0 Platform](https://app.mem0.ai), [OpenAI](https://platform.openai.com) and [Serper Dev](https://serper.dev) for search capabilities.</Note>
+<Note>Remember to get your API keys from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>, [OpenAI](https://platform.openai.com) and [Serper Dev](https://serper.dev) for search capabilities.</Note>
 
 ```python
 import os

docs/integrations/cursor.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**Cursor**](https://cursor.com) with the Mem0 plugin.
 Before setting up Mem0 with Cursor, ensure you have:
 
 1. A Mem0 Platform account and API key:
-   - [Sign up at app.mem0.ai](https://app.mem0.ai)
-   - [Get your API key](https://app.mem0.ai/dashboard/api-keys) (starts with `m0-`)
+   - <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
 
 2. Cursor installed ([cursor.com](https://cursor.com))
 

docs/integrations/flowise.mdx

@@ -38,7 +38,7 @@ npx flowise start
 
 ### 2. Obtain Your Mem0 API Key
 
-1. Navigate to the [Mem0 API Key dashboard](https://app.mem0.ai/dashboard/api-keys).
+1. Navigate to the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key dashboard</a>.
 2. Generate or copy your existing Mem0 API Key.
 
 ![Mem0 API Key](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/api-key.png)
@@ -70,7 +70,7 @@ Test your memory configuration:
 
 1. Save your Flowise configuration
 2. Run a test chat and store some information
-3. Verify the stored memories in the [Mem0 Dashboard](https://app.mem0.ai/dashboard/requests)
+3. Verify the stored memories in the <a href="https://app.mem0.ai/dashboard/requests" rel="nofollow">Mem0 Dashboard</a>
 
 ![Flowise Test Chat](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/flowise-chat-1.png)
 
@@ -103,7 +103,7 @@ Available settings include:
 
 ### Platform Configuration
 
-Additional settings available in [Mem0 Project Settings](https://app.mem0.ai/dashboard/project-settings):
+Additional settings available in <a href="https://app.mem0.ai/dashboard/project-settings" rel="nofollow">Mem0 Project Settings</a>:
 
 1. **Custom Instructions**: Define memory extraction rules
 2. **Expiration Date**: Set automatic memory cleanup periods

docs/integrations/google-ai-adk.mdx

@@ -22,7 +22,7 @@ pip install google-adk mem0ai python-dotenv
 ```
 
 2. Valid API keys:
-   - [Mem0 API Key](https://app.mem0.ai/dashboard/api-keys)
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
    - Google AI Studio API Key
 
 ## Basic Integration Example
@@ -268,7 +268,7 @@ memories = mem0.search(
             {"categories": {"contains": "travel"}}
         ]
     },
-    limit=5
+    top_k=5
 )
 
 # Configure agent with custom model settings

docs/integrations/hermes.mdx

@@ -52,7 +52,7 @@ hermes memory setup
 
 Select **mem0** as the provider and enter your Mem0 API key when prompted. The wizard writes your config to `~/.hermes/mem0.json`.
 
-<Note>Get your API key from [app.mem0.ai](https://app.mem0.ai).</Note>
+<Note>Get your API key from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>.</Note>
 
 ### Option 2: Manual Configuration
 

docs/integrations/keywords.mdx

@@ -16,7 +16,7 @@ Combining Mem0 with Keywords AI allows you to:
 4. Optimize token usage and reduce costs
 
 <Note>
-You can get your Mem0 API key, user_id, and org_id from the [Mem0 dashboard](https://app.mem0.ai/). These are required for proper integration.
+You can get your Mem0 API key from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a>.
 </Note>
 
 ## Setup and Configuration
@@ -107,7 +107,6 @@ response = client.chat.completions.create(
     extra_body={
         "mem0_params": {
             "user_id": "test_user",
-            "org_id": "org_1",
             "api_key": os.environ.get("MEM0_API_KEY"),
             "add_memories": {
                 "messages": messages,

docs/integrations/langchain-tools.mdx

@@ -29,10 +29,7 @@ import os
 
 os.environ["MEM0_API_KEY"] = "your-api-key"
 
-client = MemoryClient(
-    org_id=your_org_id,
-    project_id=your_project_id
-)
+client = MemoryClient()
 ```
 
 ## Available Tools

docs/integrations/langchain.mdx

@@ -22,7 +22,7 @@ pip install langchain langchain_openai mem0ai python-dotenv
 
 Import required modules and set up configurations:
 
-<Note>Remember to get the Mem0 API key from [Mem0 Platform](https://app.mem0.ai).</Note>
+<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
 
 ```python
 import os

docs/integrations/langgraph.mdx

@@ -23,7 +23,7 @@ pip install langgraph langchain-openai mem0ai python-dotenv
 
 Import required modules and set up configurations:
 
-<Note>Remember to get the Mem0 API key from [Mem0 Platform](https://app.mem0.ai).</Note>
+<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
 
 ```python
 from typing import Annotated, TypedDict, List

docs/integrations/llama-index.mdx

@@ -22,7 +22,7 @@ pip install llama-index-core llama-index-memory-mem0 python-dotenv
 Set your Mem0 Platform API key as an environment variable. You can replace `<your-mem0-api-key>` with your actual API key:
 
 <Note type="info">
-  You can obtain your Mem0 Platform API key from the [Mem0 Platform](https://app.mem0.ai/login).
+  You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai/login" rel="nofollow">Mem0 Platform</a>.
 </Note>
 
 ```python

docs/integrations/mastra.mdx

@@ -23,7 +23,7 @@ npm install @mastra/core @mastra/mem0 @ai-sdk/openai zod
 
 Set up your environment variables:
 
-<Note>Remember to get the Mem0 API key from [Mem0 Platform](https://app.mem0.ai).</Note>
+<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
 
 ```bash
 MEM0_API_KEY=your-mem0-api-key

docs/integrations/openai-agents-sdk.mdx

@@ -22,7 +22,7 @@ pip install openai-agents mem0ai
 ```
 
 2. Valid API keys:
-   - [Mem0 API Key](https://app.mem0.ai/dashboard/api-keys)
+   - <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
    - [OpenAI API Key](https://platform.openai.com/api-keys)
 
 ## Basic Integration Example
@@ -45,7 +45,7 @@ mem0 = MemoryClient()
 @function_tool
 def search_memory(query: str, user_id: str) -> str:
     """Search through past conversations and memories"""
-    memories = mem0.search(query, user_id=user_id, limit=3)
+    memories = mem0.search(query, user_id=user_id, top_k=3)
     if memories and memories.get('results'):
         return "\n".join([f"- {mem['memory']}" for mem in memories['results']])
     return "No relevant memories found."
@@ -215,7 +215,7 @@ Customize memory behavior:
 memories = mem0.search(
     query="travel preferences",
     user_id="alex",
-    limit=5  # Number of memories to retrieve
+    top_k=5  # Number of memories to retrieve
 )
 
 # Add metadata to memories

docs/integrations/openclaw.mdx

@@ -42,7 +42,7 @@ All memories are scoped to this `userId` — different values create separate me
 
 ### Platform Mode (Mem0 Cloud)
 
-<Note>Get your API key from [app.mem0.ai](https://app.mem0.ai).</Note>
+<Note>Get your API key from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>.</Note>
 
 Add to your `openclaw.json`:
 
@@ -155,7 +155,7 @@ openclaw mem0 stats
 
 | Key | Type | Default | Description |
 |-----|------|---------|-------------|
-| `customPrompt` | `string` | *(built-in)* | Extraction prompt for memory processing |
+| `customInstructions` | `string` | *(built-in)* | Extraction prompt for memory processing |
 | `oss.embedder.provider` | `string` | `"openai"` | Embedding provider (`"openai"`, `"ollama"`, etc.) |
 | `oss.embedder.config` | `object` | — | Provider config: `apiKey`, `model`, `baseURL` |
 | `oss.vectorStore.provider` | `string` | `"memory"` | Vector store (`"memory"`, `"qdrant"`, `"chroma"`, etc.) |

docs/integrations/raycast.mdx

@@ -9,7 +9,7 @@ Mem0 is a self-improving memory layer for LLM applications, enabling personalize
 
 **Get your API Key**: You'll need a Mem0 API key to use this extension:
 
-a. Sign up at [app.mem0.ai](https://app.mem0.ai)
+a. Sign up at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>
 
 b. Navigate to your API Keys page
 

docs/integrations/vercel-ai-sdk.mdx

@@ -29,7 +29,7 @@ npm install @mem0/vercel-ai-provider
 
 ### Setting Up Mem0
 
-1. Get your **Mem0 API Key** from the [Mem0 Dashboard](https://app.mem0.ai/dashboard/api-keys).
+1. Get your **Mem0 API Key** from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
 
 2. Initialize the Mem0 Client in your application:
 
@@ -52,7 +52,7 @@ npm install @mem0/vercel-ai-provider
 
     > **Note**: The `openai` provider is set as default. Consider using `MEM0_API_KEY` and `OPENAI_API_KEY` as environment variables for security.
 
-    > **Note**: The `mem0Config` is optional. It is used to set the global config for the Mem0 Client (eg. `user_id`, `agent_id`, `app_id`, `run_id`, `org_id`, `project_id` etc).
+    > **Note**: The `mem0Config` is optional. It is used to set the global config for the Mem0 Client (eg. `user_id`, `agent_id`, `app_id`, `run_id` etc).
 
 3. Add Memories to Enhance Context:
 

docs/llms.txt

@@ -86,7 +86,7 @@ Key differentiators:
 - [Reranker Search](https://docs.mem0.ai/open-source/features/reranker-search): Enhanced search results with reranking models
 - [Async Memory](https://docs.mem0.ai/open-source/features/async-memory): Asynchronous memory operations for better performance
 - [Multimodal Support](https://docs.mem0.ai/open-source/features/multimodal-support): Handle text, images, and documents in self-hosted setup
-- [Custom Fact Extraction](https://docs.mem0.ai/open-source/features/custom-fact-extraction-prompt): Tailor information extraction for specific use cases
+- [Custom Instructions](https://docs.mem0.ai/open-source/features/custom-instructions): Tailor information extraction for specific use cases
 - [Custom Memory Update Prompt](https://docs.mem0.ai/open-source/features/custom-update-memory-prompt): Customize how memories are updated and merged
 - [REST API Server](https://docs.mem0.ai/open-source/features/rest-api): FastAPI-based server with core operations and OpenAPI documentation
 - [OpenAI Compatibility](https://docs.mem0.ai/open-source/features/openai_compatibility): Seamless integration with OpenAI-compatible APIs
@@ -245,7 +245,6 @@ Key differentiators:
 - [LlamaIndex Multiagent](https://docs.mem0.ai/cookbooks/frameworks/llamaindex-multiagent): Multi-agent systems with shared memory
 - [Multimodal Retrieval](https://docs.mem0.ai/cookbooks/frameworks/multimodal-retrieval): Memory systems handling text, images, and documents
 - [Eliza OS Character](https://docs.mem0.ai/cookbooks/frameworks/eliza-os-character): Character-based AI with persistent personality
-- [Chrome Extension](https://docs.mem0.ai/cookbooks/frameworks/chrome-extension): Browser extensions that remember user interactions
 - [Gemini with Mem0 MCP](https://docs.mem0.ai/cookbooks/frameworks/gemini-3-with-mem0-mcp): Google Gemini integration using MCP server
 - [Mirofish Swarm Memory](https://docs.mem0.ai/cookbooks/frameworks/mirofish-swarm-memory): Swarm-based multi-agent memory patterns
 

docs/migration/api-changes.mdx

@@ -319,7 +319,7 @@ config = {
     "graph_store": {...},
     "version": "v1.0",              # ❌ v1.0 no longer supported
     "history_db_path": "...",
-    "custom_fact_extraction_prompt": "..."
+    "custom_instructions": "..."
 }
 ```
 
@@ -336,7 +336,7 @@ config = {
     },
     "version": "v1.1",              # ✅ v1.1+ only
     "history_db_path": "...",
-    "custom_fact_extraction_prompt": "...",
+    "custom_instructions": "...",
     "custom_update_memory_prompt": "..."  # ✅ NEW: Custom update prompt
 }
 ```

docs/migration/breaking-changes.mdx

@@ -1,383 +0,0 @@
----
-title: Breaking Changes in v1.0.0 
-description: 'Complete list of breaking changes when upgrading from v0.x to v1.0.0 '
-icon: "triangle-exclamation"
-iconType: "solid"
----
-
-<Warning>
-**Important:** This page lists all breaking changes. Please review carefully before upgrading.
-</Warning>
-
-## API Version Changes
-
-### Removed v1.0 API Support
-
-**Breaking Change:** The v1.0 API format is completely removed and no longer supported.
-
-#### Before (v0.x)
-```python
-# This was supported in v0.x
-config = {
-    "version": "v1.0"  # ❌ No longer supported
-}
-
-result = m.add(
-    "memory content",
-    user_id="alice"
-)
-```
-
-#### After (v1.0.0 )
-```python
-# v1.1 is the minimum supported version
-config = {
-    "version": "v1.1"  # ✅ Required minimum
-}
-
-result = m.add(
-    "memory content",
-    user_id="alice"
-)
-```
-
-**Error Message:**
-```
-ValueError: The v1.0 API format is no longer supported in mem0ai 1.0.0+.
-Please use v1.1 format which returns a dict with 'results' key.
-```
-
-## Parameter Removals
-
-### 1. version Parameter in Method Calls
-
-**Breaking Change:** Version parameter removed from method calls.
-
-#### Before (v0.x)
-```python
-result = m.add("content", user_id="alice", version="v1.0")
-```
-
-#### After (v1.0.0 )
-```python
-result = m.add("content", user_id="alice")
-```
-
-### 2. async_mode Parameter (Platform Client)
-
-**Change:** For `MemoryClient` (Platform API), `async_mode` now defaults to `True` but can still be configured.
-
-#### Before (v0.x)
-```python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-key")
-result = client.add("content", user_id="alice", async_mode=True)
-result = client.add("content", user_id="alice", async_mode=False)
-```
-
-#### After (v1.0.0 )
-```python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-key")
-
-# async_mode now defaults to True, but you can still override it
-result = client.add("content", user_id="alice")  # Uses async_mode=True by default
-
-# You can still explicitly set it to False if needed
-result = client.add("content", user_id="alice", async_mode=False)
-```
-
-## Response Format Changes
-
-### Standardized Response Structure
-
-**Breaking Change:** All responses now return a standardized dictionary format.
-
-#### Before (v0.x)
-```python
-# Could return different formats based on version configuration
-result = m.add("content", user_id="alice")
-# With v1.0: Returns [{"id": "...", "memory": "...", "event": "ADD"}]
-# With v1.1: Returns {"results": [{"id": "...", "memory": "...", "event": "ADD"}]}
-```
-
-#### After (v1.0.0 )
-```python
-# Always returns standardized format
-result = m.add("content", user_id="alice")
-# Always returns: {"results": [{"id": "...", "memory": "...", "event": "ADD"}]}
-
-# Access results consistently
-for memory in result["results"]:
-    print(memory["memory"])
-```
-
-## Configuration Changes
-
-### Version Configuration
-
-**Breaking Change:** Default API version changed.
-
-#### Before (v0.x)
-```python
-# v1.0 was supported
-config = {
-    "version": "v1.0"  # ❌ No longer supported
-}
-```
-
-#### After (v1.0.0 )
-```python
-# v1.1 is minimum, v1.1 is default
-config = {
-    "version": "v1.1"  # ✅ Minimum supported
-}
-
-# Or omit for default
-config = {
-    # version defaults to v1.1
-}
-```
-
-### Memory Configuration
-
-**Breaking Change:** Some configuration options have changed defaults.
-
-#### Before (v0.x)
-```python
-from mem0 import Memory
-
-# Default configuration in v0.x
-m = Memory()  # Used default settings suitable for v0.x
-```
-
-#### After (v1.0.0 )
-```python
-from mem0 import Memory
-
-# Default configuration optimized for v1.0.0 
-m = Memory()  # Uses v1.1+ optimized defaults
-
-# Explicit configuration recommended
-config = {
-    "version": "v1.1",
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    }
-}
-m = Memory.from_config(config)
-```
-
-## Method Signature Changes
-
-### Search Method
-
-**Enhanced but backward compatible:**
-
-#### Before (v0.x)
-```python
-results = m.search(
-    "query",
-    user_id="alice",
-    filters={"key": "value"}  # Simple key-value only
-)
-```
-
-#### After (v1.0.0 )
-```python
-# Basic usage remains the same
-results = m.search("query", user_id="alice")
-
-# Enhanced filtering available (optional)
-results = m.search(
-    "query",
-    user_id="alice",
-    filters={
-        "AND": [
-            {"key": "value"},
-            {"score": {"gte": 0.8}}
-        ]
-    },
-    rerank=True  # New parameter
-)
-```
-
-## Error Handling Changes
-
-### New Error Types
-
-**Breaking Change:** More specific error types and messages.
-
-#### Before (v0.x)
-```python
-try:
-    result = m.add("content", user_id="alice", version="v1.0")
-except Exception as e:
-    print(f"Generic error: {e}")
-```
-
-#### After (v1.0.0 )
-```python
-try:
-    result = m.add("content", user_id="alice")
-except ValueError as e:
-    if "v1.0 API format is no longer supported" in str(e):
-        # Handle version error specifically
-        print("Please upgrade your code to use v1.1+ format")
-    else:
-        print(f"Value error: {e}")
-except Exception as e:
-    print(f"Unexpected error: {e}")
-```
-
-### Validation Changes
-
-**Breaking Change:** Stricter parameter validation.
-
-#### Before (v0.x)
-```python
-# Some invalid parameters might have been ignored
-result = m.add(
-    "content",
-    user_id="alice",
-    invalid_param="ignored"  # Might have been silently ignored
-)
-```
-
-#### After (v1.0.0 )
-```python
-# Strict validation - unknown parameters cause errors
-try:
-    result = m.add(
-        "content",
-        user_id="alice",
-        invalid_param="value"  # ❌ Will raise TypeError
-    )
-except TypeError as e:
-    print(f"Invalid parameter: {e}")
-```
-
-## Import Changes
-
-### No Breaking Changes in Imports
-
-**Good News:** Import statements remain the same.
-
-```python
-# These imports work in both v0.x and v1.0.0 
-from mem0 import Memory, AsyncMemory
-from mem0 import MemoryConfig
-```
-
-## Dependency Changes
-
-### Minimum Python Version
-
-**Potential Breaking Change:** Check Python version requirements.
-
-#### Before (v0.x)
-- Python 3.8+ supported
-
-#### After (v1.0.0 )
-- Python 3.9+ required (check current requirements)
-
-### Package Dependencies
-
-**Breaking Change:** Some dependencies updated with potential breaking changes.
-
-```bash
-# Check for conflicts after upgrade
-pip install --upgrade mem0ai
-pip check  # Verify no dependency conflicts
-```
-
-## Data Migration
-
-### Database Schema
-
-**Good News:** No database schema changes required.
-
-- Existing memories remain compatible
-- No data migration required
-- Vector store data unchanged
-
-### Memory Format
-
-**Good News:** Memory storage format unchanged.
-
-- Existing memories work with v1.0.0 
-- Search continues to work with old memories
-- No re-indexing required
-
-## Testing Changes
-
-### Test Updates Required
-
-**Breaking Change:** Update tests for new response format.
-
-#### Before (v0.x)
-```python
-def test_add_memory():
-    result = m.add("content", user_id="alice")
-    assert isinstance(result, list)  # ❌ No longer true
-    assert len(result) > 0
-```
-
-#### After (v1.0.0 )
-```python
-def test_add_memory():
-    result = m.add("content", user_id="alice")
-    assert isinstance(result, dict)  # ✅ Always dict
-    assert "results" in result       # ✅ Always has results key
-    assert len(result["results"]) > 0
-```
-
-## Rollback Considerations
-
-### Safe Rollback Process
-
-If you need to rollback:
-
-```bash
-# 1. Rollback package
-pip install mem0ai==0.1.20  # Last stable v0.x
-
-# 2. Revert code changes
-git checkout previous_commit
-
-# 3. Test functionality
-python test_mem0_functionality.py
-```
-
-### Data Safety
-
-- **Safe:** Memories stored in v0.x format work with v1.0.0 
-- **Safe:** Rollback doesn't lose data
-- **Safe:** Vector store data remains intact
-
-## Next Steps
-
-1. **Review all breaking changes** in your codebase
-2. **Update method calls** to remove deprecated parameters
-3. **Update response handling** to use standardized format
-4. **Test thoroughly** with your existing data
-5. **Update error handling** for new error types
-
-<CardGroup cols={2}>
-  <Card title="Migration Guide" icon="arrow-right" href="/migration/v0-to-v1">
-    Step-by-step migration instructions
-  </Card>
-  <Card title="API Changes" icon="code" href="/migration/api-changes">
-    Complete API reference changes
-  </Card>
-</CardGroup>
-
-<Warning>
-**Need Help?** If you encounter issues during migration, check our [GitHub Discussions](https://github.com/mem0ai/mem0/discussions) or community support channels.
-</Warning>

docs/migration/oss-to-platform.mdx

@@ -28,7 +28,7 @@ Move your Mem0 implementation to managed infrastructure with enterprise features
 
 ## Plan
 
-1. **Sign up**: Create an account on [Mem0 Platform](https://app.mem0.ai).
+1. **Sign up**: Create an account on <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.
 2. **Get API Key**: Navigate to **Settings > API Keys** and generate a new key.
 3. **Review Usage**: Identify where you instantiate `Memory` and where you call `search` or `get_all`.
 
@@ -81,6 +81,10 @@ client = MemoryClient(api_key="m0-...")
   **Critical Change**: Platform uses v2 endpoints that require filtering parameters to be nested inside a `filters` dictionary.
 </Warning>
 
+<Note>
+  The `limit` parameter has been removed in favor of `top_k` across all SDKs. Update any code using `limit=` to use `top_k=` instead.
+</Note>
+
 | Method | Open Source | Platform |
 | ------ | ----------- | -------- |
 | `search()` | `m.search(query, user_id="alex")` | `client.search(query, filters={"user_id": "alex"})` |
@@ -121,18 +125,18 @@ Note: `add()` and `delete()` methods remain unchanged. The `update()` method is
     <CodeGroup>
     ```python Open Source (Old)
     # Get all memories for a user
-    memories = m.get_all(user_id="alex", limit=10)
+    memories = m.get_all(user_id="alex", top_k=10)
 
     # Get memories with pagination
-    memories = m.get_all(user_id="alex", limit=5, offset=10)
+    memories = m.get_all(user_id="alex", top_k=5, offset=10)
     ```
 
     ```python Platform (New)
     # Get all memories for a user
-    memories = client.get_all(filters={"user_id": "alex"}, limit=10)
+    memories = client.get_all(filters={"user_id": "alex"}, top_k=10)
 
     # Get memories with pagination
-    memories = client.get_all(filters={"user_id": "alex"}, limit=5, offset=10)
+    memories = client.get_all(filters={"user_id": "alex"}, top_k=5, offset=10)
     ```
     </CodeGroup>
   </Accordion>
@@ -283,7 +287,7 @@ The Platform introduces powerful capabilities not available in OSS:
         "user preferences",
         filters={"user_id": "alex"},
         rerank=True,  # Platform exclusive
-        limit=5
+        top_k=5
     )
 
     # Search with keyword expansion
@@ -335,7 +339,7 @@ The Platform introduces powerful capabilities not available in OSS:
                 {"timestamp": {"gte": "2024-01-01"}}
             ]
         },
-        limit=100
+        top_k=100
     )
 
     # Monitor usage patterns
@@ -368,7 +372,7 @@ If you encounter issues, you can revert immediately by switching your import bac
 
 ## Next Steps
 
-- [Platform Dashboard](https://app.mem0.ai) - Monitor usage and manage settings.
+- <a href="https://app.mem0.ai" rel="nofollow">Platform Dashboard</a> - Monitor usage and manage settings.
 - [Webhooks Setup](/platform/features/webhooks) - Configure real-time event notifications.
 - [Organizations & Projects](/api-reference/organizations-projects) - Set up multi-tenancy for your team.
 

docs/migration/v0-to-v1.mdx

@@ -1,481 +0,0 @@
----
-title: Migrating from v0.x to v1.0.0 
-description: 'Complete guide to upgrade your Mem0 implementation to version 1.0.0 '
-icon: "arrow-right"
-iconType: "solid"
----
-
-<Warning>
-**Breaking Changes Ahead!** Mem0 1.0.0  introduces several breaking changes. Please read this guide carefully before upgrading.
-</Warning>
-
-## Overview
-
-Mem0 1.0.0  is a major release that modernizes the API, improves performance, and adds powerful new features. This guide will help you migrate your existing v0.x implementation to the new version.
-
-## Key Changes Summary
-
-| Feature | v0.x | v1.0.0  | Migration Required |
-|---------|------|-------------|-------------------|
-| API Version | v1.0 supported | v1.0 **removed**, v1.1+ only | ✅ Yes |
-| Async Mode (Platform Client) | Optional/manual | Defaults to `True`, configurable | ⚠️ Partial |
-| Metadata Filtering | Basic | Enhanced with operators | ⚠️ Optional |
-| Reranking | Not available | Full support | ⚠️ Optional |
-
-## Step-by-Step Migration
-
-### 1. Update Installation
-
-```bash
-# Update to the latest version
-pip install --upgrade mem0ai
-```
-
-### 2. Remove Deprecated Parameters
-
-#### Before (v0.x)
-```python
-from mem0 import Memory
-
-# These parameters are no longer supported
-m = Memory()
-result = m.add(
-    "I love pizza",
-    user_id="alice",
-    version="v1.0"         # ❌ REMOVED
-)
-```
-
-#### After (v1.0.0 )
-```python
-from mem0 import Memory
-
-# Clean, simplified API
-m = Memory()
-result = m.add(
-    "I love pizza",
-    user_id="alice"
-    # version parameter removed
-)
-```
-
-### 3. Update Configuration
-
-#### Before (v0.x)
-```python
-config = {
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    },
-    "version": "v1.0"  # ❌ No longer supported
-}
-
-m = Memory.from_config(config)
-```
-
-#### After (v1.0.0 )
-```python
-config = {
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    },
-    "version": "v1.1"  # ✅ v1.1 is the minimum supported version
-}
-
-m = Memory.from_config(config)
-```
-
-### 4. Handle Response Format Changes
-
-#### Before (v0.x)
-```python
-# Response could be a list or dict depending on version
-result = m.add("I love coffee", user_id="alice")
-
-if isinstance(result, list):
-    # Handle list format
-    for item in result:
-        print(item["memory"])
-else:
-    # Handle dict format
-    print(result["results"])
-```
-
-#### After (v1.0.0 )
-```python
-# Response is always a standardized dict with "results" key
-result = m.add("I love coffee", user_id="alice")
-
-# Always access via "results" key
-for item in result["results"]:
-    print(item["memory"])
-```
-
-### 5. Update Search Operations
-
-#### Before (v0.x)
-```python
-# Basic search
-results = m.search("What do I like?", user_id="alice")
-
-# With filters
-results = m.search(
-    "What do I like?",
-    user_id="alice",
-    filters={"category": "food"}
-)
-```
-
-#### After (v1.0.0 )
-```python
-# Same basic search API
-results = m.search("What do I like?", user_id="alice")
-
-# Enhanced filtering with operators (optional upgrade)
-results = m.search(
-    "What do I like?",
-    user_id="alice",
-    filters={
-        "AND": [
-            {"category": "food"},
-            {"rating": {"gte": 8}}
-        ]
-    }
-)
-
-# New: Reranking support (optional)
-results = m.search(
-    "What do I like?",
-    user_id="alice",
-    rerank=True  # Requires reranker configuration
-)
-```
-
-### 6. Platform Client async_mode Default Changed
-
-**Change:** For `MemoryClient`, the `async_mode` parameter now defaults to `True` for better performance.
-
-#### Before (v0.x)
-```python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-key")
-
-# Had to explicitly set async_mode
-result = client.add("I enjoy hiking", user_id="alice", async_mode=True)
-```
-
-#### After (v1.0.0 )
-```python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-key")
-
-# async_mode now defaults to True (best performance)
-result = client.add("I enjoy hiking", user_id="alice")
-
-# You can still override if needed for synchronous processing
-result = client.add("I enjoy hiking", user_id="alice", async_mode=False)
-```
-
-## Configuration Migration
-
-### Basic Configuration
-
-#### Before (v0.x)
-```python
-config = {
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    },
-    "llm": {
-        "provider": "openai",
-        "config": {
-            "model": "gpt-3.5-turbo",
-            "api_key": "your-key"
-        }
-    },
-    "version": "v1.0"
-}
-```
-
-#### After (v1.0.0 )
-```python
-config = {
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    },
-    "llm": {
-        "provider": "openai",
-        "config": {
-            "model": "gpt-3.5-turbo",
-            "api_key": "your-key"
-        }
-    },
-    "version": "v1.1",  # Minimum supported version
-
-    # New optional features
-    "reranker": {
-        "provider": "cohere",
-        "config": {
-            "model": "rerank-english-v3.0",
-            "api_key": "your-cohere-key"
-        }
-    }
-}
-```
-
-### Enhanced Features (Optional)
-
-```python
-# Take advantage of new features
-config = {
-    "vector_store": {
-        "provider": "qdrant",
-        "config": {
-            "host": "localhost",
-            "port": 6333
-        }
-    },
-    "llm": {
-        "provider": "openai",
-        "config": {
-            "model": "gpt-4",
-            "api_key": "your-key"
-        }
-    },
-    "embedder": {
-        "provider": "openai",
-        "config": {
-            "model": "text-embedding-3-small",
-            "api_key": "your-key"
-        }
-    },
-    "reranker": {
-        "provider": "sentence_transformer",
-        "config": {
-            "model": "cross-encoder/ms-marco-MiniLM-L-6-v2"
-        }
-    },
-    "version": "v1.1"
-}
-```
-
-## Error Handling Migration
-
-### Before (v0.x)
-```python
-try:
-    result = m.add("memory", user_id="alice", version="v1.0")
-except Exception as e:
-    print(f"Error: {e}")
-```
-
-### After (v1.0.0 )
-```python
-try:
-    result = m.add("memory", user_id="alice")
-except ValueError as e:
-    if "v1.0 API format is no longer supported" in str(e):
-        print("Please upgrade your code to use v1.1+ format")
-    else:
-        print(f"Error: {e}")
-except Exception as e:
-    print(f"Unexpected error: {e}")
-```
-
-## Testing Your Migration
-
-### 1. Basic Functionality Test
-
-```python
-def test_basic_functionality():
-    m = Memory()
-
-    # Test add
-    result = m.add("I love testing", user_id="test_user")
-    assert "results" in result
-    assert len(result["results"]) > 0
-
-    # Test search
-    search_results = m.search("testing", user_id="test_user")
-    assert "results" in search_results
-
-    # Test get_all
-    all_memories = m.get_all(user_id="test_user")
-    assert "results" in all_memories
-
-    print("✅ Basic functionality test passed")
-
-test_basic_functionality()
-```
-
-### 2. Enhanced Features Test
-
-```python
-def test_enhanced_features():
-    config = {
-        "reranker": {
-            "provider": "sentence_transformer",
-            "config": {
-                "model": "cross-encoder/ms-marco-MiniLM-L-6-v2"
-            }
-        }
-    }
-
-    m = Memory.from_config(config)
-
-    # Test reranking
-    m.add("I love advanced features", user_id="test_user")
-    results = m.search("features", user_id="test_user", rerank=True)
-    assert "results" in results
-
-    # Test enhanced filtering
-    results = m.search(
-        "features",
-        user_id="test_user",
-        filters={"user_id": {"eq": "test_user"}}
-    )
-    assert "results" in results
-
-    print("✅ Enhanced features test passed")
-
-test_enhanced_features()
-```
-
-## Common Migration Issues
-
-### Issue 1: Version Error
-
-**Error:**
-```
-ValueError: The v1.0 API format is no longer supported in mem0ai 1.0.0+
-```
-
-**Solution:**
-```python
-# Remove version parameters or set to v1.1+
-config = {
-    # ... other config
-    "version": "v1.1"  # or remove entirely for default
-}
-```
-
-### Issue 2: Response Format Error
-
-**Error:**
-```
-KeyError: 'results'
-```
-
-**Solution:**
-```python
-# Always access response via "results" key
-result = m.add("memory", user_id="alice")
-memories = result["results"]  # Not result directly
-```
-
-### Issue 3: Parameter Error
-
-**Error:**
-```
-TypeError: add() got an unexpected keyword argument 'output_format'
-```
-
-**Solution:**
-```python
-# Remove deprecated parameters
-result = m.add(
-    "memory",
-    user_id="alice"
-    # Remove: version
-)
-```
-
-## Rollback Plan
-
-If you encounter issues during migration:
-
-### 1. Immediate Rollback
-
-```bash
-# Downgrade to last v0.x version
-pip install mem0ai==0.1.20  # Replace with your last working version
-```
-
-### 2. Gradual Migration
-
-```python
-# Test both versions side by side
-import mem0_v0  # Your old version
-import mem0     # New version
-
-def compare_results(query, user_id):
-    old_results = mem0_v0.search(query, user_id=user_id)
-    new_results = mem0.search(query, user_id=user_id)
-
-    print("Old format:", old_results)
-    print("New format:", new_results["results"])
-```
-
-## Performance Improvements
-
-### Before (v0.x)
-```python
-# Sequential operations
-result1 = m.add("memory 1", user_id="alice")
-result2 = m.add("memory 2", user_id="alice")
-result3 = m.search("query", user_id="alice")
-```
-
-### After (v1.0.0 )
-```python
-# Better async performance
-async def batch_operations():
-    async_memory = AsyncMemory()
-
-    # Concurrent operations
-    results = await asyncio.gather(
-        async_memory.add("memory 1", user_id="alice"),
-        async_memory.add("memory 2", user_id="alice"),
-        async_memory.search("query", user_id="alice")
-    )
-    return results
-```
-
-## Next Steps
-
-1. **Complete the migration** using this guide
-2. **Test thoroughly** with your existing data
-3. **Explore new features** like enhanced filtering and reranking
-4. **Update your documentation** to reflect the new API
-5. **Monitor performance** and optimize as needed
-
-<CardGroup cols={2}>
-  <Card title="Breaking Changes" icon="triangle-exclamation" href="/migration/breaking-changes">
-    Detailed list of all breaking changes
-  </Card>
-  <Card title="API Changes" icon="code" href="/migration/api-changes">
-    Complete API reference changes
-  </Card>
-</CardGroup>
-
-<Info>
-Need help with migration? Check our [GitHub Discussions](https://github.com/mem0ai/mem0/discussions) or reach out to our community for support.
-</Info>

docs/open-source/features/async-memory.mdx

@@ -240,7 +240,7 @@ async_openai_client = AsyncOpenAI()
 async_memory = AsyncMemory()
 
 async def chat_with_memories(message: str, user_id: str = "default_user") -> str:
-    search_result = await async_memory.search(query=message, user_id=user_id, limit=3)
+    search_result = await async_memory.search(query=message, user_id=user_id, top_k=3)
     relevant_memories = search_result["results"]
     memories_str = "\n".join(f"- {entry['memory']}" for entry in relevant_memories)
 
@@ -326,7 +326,7 @@ async def add_memory(messages: list, user_id: str):
 @app.get("/memories/search")
 async def search_memories(query: str, user_id: str, limit: int = 10):
     try:
-        result = await memory.search(query=query, user_id=user_id, limit=limit)
+        result = await memory.search(query=query, user_id=user_id, top_k=limit)
         return {"status": "success", "data": result}
     except Exception as exc:
         raise HTTPException(status_code=500, detail=str(exc))

docs/open-source/features/custom-instructions.mdx

@@ -1,13 +1,13 @@
 ---
-title: Custom Fact Extraction Prompt
+title: Custom Instructions
 description: Tailor fact extraction so Mem0 stores only the details you care about.
 icon: "wand-magic-sparkles"
 ---
 
-Custom fact extraction prompts let you decide exactly which facts Mem0 records from a conversation. Define a focused prompt, give a few examples, and Mem0 will add only the memories that match your use case.
+Custom instructions let you decide exactly which facts Mem0 records from a conversation. Define a focused prompt, give a few examples, and Mem0 will add only the memories that match your use case.
 
 <Info>
-  **You’ll use this when…**
+  **You'll use this when...**
   - A project needs domain-specific facts (order numbers, customer info) without storing casual chatter.
   - You already have a clear schema for memories and want the LLM to follow it.
   - You must prevent irrelevant details from entering long-term storage.
@@ -17,6 +17,10 @@ Custom fact extraction prompts let you decide exactly which facts Mem0 records f
   Prompts that are too broad cause unrelated facts to slip through. Keep instructions tight and test them with real transcripts.
 </Warning>
 
+<Note>
+  The `custom_fact_extraction_prompt` parameter has been renamed to `custom_instructions`. If you are upgrading from an older version, update your configuration accordingly.
+</Note>
+
 ---
 
 ## Feature anatomy
@@ -24,13 +28,13 @@ Custom fact extraction prompts let you decide exactly which facts Mem0 records f
 - **Prompt instructions:** Describe which entities or phrases to keep. Specific guidance keeps the extractor focused.
 - **Few-shot examples:** Show positive and negative cases so the model copies the right format.
 - **Structured output:** Responses return JSON with a `facts` array that Mem0 converts into individual memories.
-- **LLM configuration:** `custom_fact_extraction_prompt` (Python) or `customPrompt` (TypeScript) lives alongside your model settings.
+- **LLM configuration:** `custom_instructions` (Python) or `customInstructions` (TypeScript) lives alongside your model settings.
 
 <AccordionGroup>
   <Accordion title="Prompt blueprint">
-    1. State the allowed fact types.  
-    2. Include short examples that mirror production messages.  
-    3. Show both empty (`[]`) and populated outputs.  
+    1. State the allowed fact types.
+    2. Include short examples that mirror production messages.
+    3. Show both empty (`[]`) and populated outputs.
     4. Remind the model to return JSON with a `facts` key only.
   </Accordion>
 </AccordionGroup>
@@ -43,8 +47,8 @@ Custom fact extraction prompts let you decide exactly which facts Mem0 records f
 
 <CodeGroup>
 ```python Python
-custom_fact_extraction_prompt = """
-Please only extract entities containing customer support information, order details, and user information. 
+custom_instructions = """
+Please only extract entities containing customer support information, order details, and user information.
 Here are some few shot examples:
 
 Input: Hi.
@@ -67,8 +71,8 @@ Return the facts and customer information in a json format as shown above.
 ```
 
 ```ts TypeScript
-const customPrompt = `
-Please only extract entities containing customer support information, order details, and user information. 
+const customInstructions = `
+Please only extract entities containing customer support information, order details, and user information.
 Here are some few shot examples:
 
 Input: Hi.
@@ -110,7 +114,7 @@ config = {
             "max_tokens": 2000,
         }
     },
-    "custom_fact_extraction_prompt": custom_fact_extraction_prompt,
+    "custom_instructions": custom_instructions,
     "version": "v1.1"
 }
 
@@ -131,7 +135,7 @@ const config = {
       maxTokens: 1500,
     },
   },
-  customPrompt: customPrompt,
+  customInstructions: customInstructions,
 };
 
 const memory = new Memory(config);

docs/open-source/features/custom-update-memory-prompt.mdx

@@ -263,7 +263,7 @@ Please note to return the IDs in the output from the input IDs only and do not g
 - Log each decision so product teams can review why a change happened.
 
 <Note>
-  The prompt works alongside `custom_fact_extraction_prompt`—fact extraction identifies candidate facts, and the update prompt decides how to merge them into long-term storage.
+  The prompt works alongside `custom_instructions`—fact extraction identifies candidate facts, and the update prompt decides how to merge them into long-term storage.
 </Note>
 
 ---
@@ -288,7 +288,7 @@ Please note to return the IDs in the output from the input IDs only and do not g
 
 ## Compare prompts
 
-| Feature | `custom_update_memory_prompt` | `custom_fact_extraction_prompt` |
+| Feature | `custom_update_memory_prompt` | `custom_instructions` |
 | --- | --- | --- |
 | Primary job | Decide memory actions (ADD/UPDATE/DELETE/NONE) | Pull facts from user and assistant messages |
 | Inputs | Retrieved facts + existing memory entries | Raw conversation turns |
@@ -297,7 +297,7 @@ Please note to return the IDs in the output from the input IDs only and do not g
 ---
 
 <CardGroup cols={2}>
-  <Card title="Design Fact Extraction" icon="sparkles" href="/open-source/features/custom-fact-extraction-prompt">
+  <Card title="Design Fact Extraction" icon="sparkles" href="/open-source/features/custom-instructions">
     Coordinate both prompts so fact extraction feeds clean inputs into the update flow.
   </Card>
   <Card title="Build Email Automations" icon="inbox" href="/cookbooks/operations/email-automation">

docs/open-source/features/graph-memory.mdx

@@ -94,7 +94,7 @@ memory.add(conversation, user_id="demo-user")
 results = memory.search(
     "Who did Alice meet at GraphConf?",
     user_id="demo-user",
-    limit=3,
+    top_k=3,
     rerank=True,
 )
 
@@ -123,7 +123,6 @@ export NEO4J_PASSWORD="your-password"
 import { Memory } from "mem0ai/oss";
 
 const config = {
-  enableGraph: true,
   graphStore: {
     provider: "neo4j",
     config: {
@@ -146,7 +145,7 @@ await memory.add(conversation, { userId: "demo-user" });
 
 const results = await memory.search(
   "Who did Alice meet at GraphConf?",
-  { userId: "demo-user", limit: 3, rerank: true }
+  { userId: "demo-user", topK: 3, rerank: true }
 );
 
 results.results.forEach((hit) => {
@@ -196,7 +195,6 @@ memory = Memory.from_config(config_dict=config)
 import { Memory } from "mem0ai/oss";
 
 const config = {
-  enableGraph: true,
   graphStore: {
     provider: "neo4j",
     config: {
@@ -204,7 +202,7 @@ const config = {
       username: process.env.NEO4J_USERNAME!,
       password: process.env.NEO4J_PASSWORD!,
     },
-    customPrompt: "Please only capture people, organisations, and project links.",
+    customInstructions: "Please only capture people, organisations, and project links.",
   }
 };
 
@@ -217,14 +215,6 @@ const memory = new Memory(config);
 
 ```python
 config["graph_store"]["config"]["threshold"] = 0.75
-```
-  </Accordion>
-  <Accordion title="Toggle graph writes per request">
-    Disable graph writes or reads when you only want vector behaviour.
-
-```python
-memory.add(messages, user_id="demo-user", enable_graph=False)
-results = memory.search("marketing partners", user_id="demo-user", enable_graph=False)
 ```
   </Accordion>
   <Accordion title="Organize multi-agent graphs">
@@ -257,15 +247,12 @@ Monitor graph growth, especially on free tiers, by periodically cleaning dormant
   <Accordion title="Neptune Analytics rejects requests">
     Ensure the graph identifier matches the vector dimension used by your embedder and that the IAM role allows `neptune-graph:*DataViaQuery` actions.
   </Accordion>
-  <Accordion title="Graph store outage fallback">
-    Catch the provider error and retry with `enable_graph=False` so vector-only search keeps serving responses while the graph backend recovers.
-  </Accordion>
 </AccordionGroup>
 
 ## Decision Points
 
 - Select the graph store that fits your deployment (managed Aura vs. self-hosted Neo4j vs. AWS Neptune vs. local Kuzu vs. Apache AGE on PostgreSQL).
-- Decide when to enable graph writes per request; routine conversations may stay vector-only to save latency.
+- Decide whether to include a graph store in your config; routine conversations may stay vector-only to save latency.
 - Set a policy for pruning stale relationships so your graph stays fast and affordable.
 
 ## Provider setup
@@ -280,7 +267,6 @@ Choose your backend and expand the matching panel for configuration details and
 import { Memory } from "mem0ai/oss";
 
 const config = {
-    enableGraph: true,
     graphStore: {
         provider: "neo4j",
         config: {

docs/open-source/features/multimodal-support.mdx

@@ -81,7 +81,7 @@ const messages = [
   }
 ];
 
-await client.add(messages, { user_id: "alice" });
+await client.add(messages, { userId: "alice" });
 ```
 </CodeGroup>
 
@@ -148,7 +148,7 @@ const messages = [
   }
 ];
 
-await client.add(messages, { user_id: "alice" });
+await client.add(messages, { userId: "alice" });
 ```
 </CodeGroup>
 
@@ -264,7 +264,7 @@ try {
     }
   }];
 
-  await client.add(messages, { user_id: "user123" });
+  await client.add(messages, { userId: "user123" });
   console.log("Image processed successfully");
 } catch (error: any) {
   if (error.type === "invalid_image") {

docs/open-source/features/openai_compatibility.mdx

@@ -131,7 +131,7 @@ print(response.choices[0].message.content)
 | `run_id` | `str` | Optional session/run identifier for short-lived flows. |
 | `metadata` | `dict` | Store extra fields alongside each memory entry. |
 | `filters` | `dict` | Restrict retrieval to specific memories while responding. |
-| `limit` | `int` | Cap how many memories Mem0 pulls into the context (default 10). |
+| `top_k` | `int` | Cap how many memories Mem0 pulls into the context (default 10). |
 
 Other request fields mirror OpenAI’s chat completion API.
 

docs/open-source/features/overview.mdx

@@ -30,7 +30,7 @@ Mem0 Open Source ships with capabilities that adapt memory behavior for producti
   <Card title="Multimodal Support" icon="image" href="/open-source/features/multimodal-support">
     Process images, audio, and video memories.
   </Card>
-  <Card title="Custom Fact Extraction" icon="wand-magic-sparkles" href="/open-source/features/custom-fact-extraction-prompt">
+  <Card title="Custom Instructions" icon="wand-magic-sparkles" href="/open-source/features/custom-instructions">
     Tailor how facts are extracted from text.
   </Card>
 </CardGroup>

docs/open-source/features/reranker-search.mdx

@@ -321,7 +321,7 @@ results = m.search(
         ]
     },
     rerank=True,
-    limit=20
+    top_k=20
 )
 ```
 
@@ -366,7 +366,7 @@ results = m.search(
     user_id="reader123",
     filters={"content_type": "book_recommendation"},
     rerank=True,
-    limit=10
+    top_k=10
 )
 
 for result in results["results"]:

docs/open-source/node-quickstart.mdx

@@ -209,14 +209,6 @@ Mem0 offers granular configuration across vector stores, LLMs, embedders, and hi
 | `topP` | Probability threshold | All |
 | `topK` | Token count to keep | All |
 | `openaiBaseUrl` | Base URL override | OpenAI |
-  </Accordion>
-  <Accordion title="Graph store">
-| Parameter | Description | Default |
-| --- | --- | --- |
-| `provider` | Graph store provider (e.g., `"neo4j"`) | `"neo4j"` |
-| `url` | Connection URL | `process.env.NEO4J_URL` |
-| `username` | Username | `process.env.NEO4J_USERNAME` |
-| `password` | Password | `process.env.NEO4J_PASSWORD` |
   </Accordion>
   <Accordion title="Embedder">
 | Parameter | Description | Default |
@@ -230,7 +222,7 @@ Mem0 offers granular configuration across vector stores, LLMs, embedders, and hi
 | --- | --- | --- |
 | `historyDbPath` | Path to history database | `"{mem0_dir}/history.db"` |
 | `version` | API version | `"v1.0"` |
-| `customPrompt` | Custom processing prompt | `undefined` |
+| `customInstructions` | Custom processing prompt | `undefined` |
   </Accordion>
   <Accordion title="History store">
 | Parameter | Description | Default |
@@ -273,7 +265,7 @@ const config = {
     }
   },
   disableHistory: false,
-  customPrompt: "I'm a virtual assistant. I'm here to help you with your queries."
+  customInstructions: "I'm a virtual assistant. I'm here to help you with your queries."
 };
 ```
   </Accordion>

docs/openapi.json

@@ -183,7 +183,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\nusers = client.users()\nprint(users)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\nusers = client.users()\nprint(users)"
 					},
 					{
 						"lang": "JavaScript",
@@ -717,7 +717,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\njson_schema = {pydantic_json_schema}\nfilters = {\n    \"AND\": [\n        {\"user_id\": \"alex\"}\n    ]\n}\n\nresponse = client.create_memory_export(\n    schema=json_schema,\n    filters=filters\n)\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\")\n\njson_schema = {pydantic_json_schema}\nfilters = {\n    \"AND\": [\n        {\"user_id\": \"alex\"}\n    ]\n}\n\nresponse = client.create_memory_export(\n    schema=json_schema,\n    filters=filters\n)\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -845,7 +845,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"project_id\")\n\nmemory_export_id = \"<memory_export_id>\"\n\nresponse = client.get_memory_export(memory_export_id=memory_export_id)\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\")\n\nmemory_export_id = \"<memory_export_id>\"\n\nresponse = client.get_memory_export(memory_export_id=memory_export_id)\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -1096,7 +1096,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Retrieve memories for a specific user\nuser_memories = client.get_all(user_id=\"<user_id>\")\n\nprint(user_memories)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Retrieve memories for a specific user\nuser_memories = client.get_all(user_id=\"<user_id>\")\n\nprint(user_memories)"
 					},
 					{
 						"lang": "JavaScript",
@@ -1203,11 +1203,11 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nmessages = [\n    {\"role\": \"user\", \"content\": \"<user-message>\"},\n    {\"role\": \"assistant\", \"content\": \"<assistant-response>\"}\n]\n\nclient.add(messages, user_id=\"<user-id>\", version=\"v2\")"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\")\n\nmessages = [\n    {\"role\": \"user\", \"content\": \"<user-message>\"},\n    {\"role\": \"assistant\", \"content\": \"<assistant-response>\"}\n]\n\nclient.add(messages, user_id=\"<user-id>\")"
 					},
 					{
 						"lang": "JavaScript",
-						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst messages = [\n  { role: \"user\", content: \"Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts.\" },\n  { role: \"assistant\", content: \"Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions.\" }\n];\n\nclient.add(messages, { user_id: \"<user_id>\", version: \"v2\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
+						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst messages = [\n  { role: \"user\", content: \"Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts.\" },\n  { role: \"assistant\", content: \"Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions.\" }\n];\n\nclient.add(messages, { user_id: \"<user_id>\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
 					},
 					{
 						"lang": "cURL",
@@ -1232,7 +1232,7 @@
 				"tags": [
 					"memories"
 				],
-				"description": "Delete memories by filter. At least one filter is required — previously omitting all filters silently deleted everything; now it returns a validation error.",
+				"description": "Delete memories by filter. At least one filter is required \u2014 previously omitting all filters silently deleted everything; now it returns a validation error.",
 				"operationId": "memories_delete",
 				"parameters": [
 					{
@@ -1315,15 +1315,15 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Delete all memories for a specific user\nclient.delete_all(user_id=\"<user_id>\")\n\n# Delete all memories for every user in the project (wildcard)\nclient.delete_all(user_id=\"*\")\n\n# Full project wipe — all four filters must be explicitly set to \"*\"\nclient.delete_all(user_id=\"*\", agent_id=\"*\", app_id=\"*\", run_id=\"*\")\n\n# NOTE: Calling delete_all() with no filters raises a validation error.\n# At least one filter is required to prevent accidental data loss."
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Delete all memories for a specific user\nclient.delete_all(user_id=\"<user_id>\")\n\n# Delete all memories for every user in the project (wildcard)\nclient.delete_all(user_id=\"*\")\n\n# Full project wipe \u2014 all four filters must be explicitly set to \"*\"\nclient.delete_all(user_id=\"*\", agent_id=\"*\", app_id=\"*\", run_id=\"*\")\n\n# NOTE: Calling delete_all() with no filters raises a validation error.\n# At least one filter is required to prevent accidental data loss."
 					},
 					{
 						"lang": "JavaScript",
-						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\n// Delete all memories for a specific user\nclient.deleteAll({ user_id: \"<user_id>\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));\n\n// Delete all memories for every user in the project (wildcard)\nclient.deleteAll({ user_id: \"*\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));\n\n// Full project wipe — all four filters must be explicitly set to \"*\"\nclient.deleteAll({ user_id: \"*\", agent_id: \"*\", app_id: \"*\", run_id: \"*\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
+						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\n// Delete all memories for a specific user\nclient.deleteAll({ user_id: \"<user_id>\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));\n\n// Delete all memories for every user in the project (wildcard)\nclient.deleteAll({ user_id: \"*\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));\n\n// Full project wipe \u2014 all four filters must be explicitly set to \"*\"\nclient.deleteAll({ user_id: \"*\", agent_id: \"*\", app_id: \"*\", run_id: \"*\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
 					},
 					{
 						"lang": "cURL",
-						"source": "# Delete memories for a specific user\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=<user_id>' \\\n  --header 'Authorization: Token <api-key>'\n\n# Delete memories for all users (wildcard)\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=*' \\\n  --header 'Authorization: Token <api-key>'\n\n# Full project wipe — all four filters must be set to *\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=*&agent_id=*&app_id=*&run_id=*' \\\n  --header 'Authorization: Token <api-key>'"
+						"source": "# Delete memories for a specific user\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=<user_id>' \\\n  --header 'Authorization: Token <api-key>'\n\n# Delete memories for all users (wildcard)\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=*' \\\n  --header 'Authorization: Token <api-key>'\n\n# Full project wipe \u2014 all four filters must be set to *\ncurl --request DELETE \\\n  --url 'https://api.mem0.ai/v1/memories/?user_id=*&agent_id=*&app_id=*&run_id=*' \\\n  --header 'Authorization: Token <api-key>'"
 					},
 					{
 						"lang": "Go",
@@ -1441,11 +1441,11 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Retrieve memories with filters\nmemories = client.get_all(\n    filters={\n        \"AND\": [\n            {\n                \"user_id\": \"alex\"\n            },\n            {\n                \"created_at\": {\n                    \"gte\": \"2024-07-01\",\n                    \"lte\": \"2024-07-31\"\n                }\n            }\n        ]\n    },\n    version=\"v2\"\n)\n\nprint(memories)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Retrieve memories with filters\nmemories = client.get_all(\n    filters={\n        \"AND\": [\n            {\n                \"user_id\": \"alex\"\n            },\n            {\n                \"created_at\": {\n                    \"gte\": \"2024-07-01\",\n                    \"lte\": \"2024-07-31\"\n                }\n            }\n        ]\n    }\n)\n\nprint(memories)"
 					},
 					{
 						"lang": "JavaScript",
-						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst filters = {\n  AND: [\n    { user_id: 'alex' },\n    { created_at: { gte: '2024-07-01', lte: '2024-07-31' } }\n  ]\n};\n\nclient.getAll({ filters, api_version: 'v2' })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
+						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst filters = {\n  AND: [\n    { user_id: 'alex' },\n    { created_at: { gte: '2024-07-01', lte: '2024-07-31' } }\n  ]\n};\n\nclient.getAll({ filters })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
 					},
 					{
 						"lang": "cURL",
@@ -1589,11 +1589,11 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nquery = \"Your search query here\"\n\nresults = client.search(query, user_id=\"<user_id>\", output_format=\"v1.1\")\nprint(results)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\nquery = \"Your search query here\"\n\nresults = client.search(query, user_id=\"<user_id>\")\nprint(results)"
 					},
 					{
 						"lang": "JavaScript",
-						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst query = \"Your search query here\";\n\nclient.search(query, { user_id: \"<user_id>\", output_format: \"v1.1\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
+						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst query = \"Your search query here\";\n\nclient.search(query, { user_id: \"<user_id>\" })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
 					},
 					{
 						"lang": "cURL",
@@ -1708,11 +1708,11 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nquery = \"What do you know about me?\"\nfilters = {\n   \"OR\":[\n      {\n         \"user_id\":\"alex\"\n      },\n      {\n         \"agent_id\":{\n            \"in\":[\n               \"travel-assistant\",\n               \"customer-support\"\n            ]\n         }\n      }\n   ]\n}\nclient.search(query, version=\"v2\", filters=filters)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\nquery = \"What do you know about me?\"\nfilters = {\n   \"OR\":[\n      {\n         \"user_id\":\"alex\"\n      },\n      {\n         \"agent_id\":{\n            \"in\":[\n               \"travel-assistant\",\n               \"customer-support\"\n            ]\n         }\n      }\n   ]\n}\nclient.search(query, filters=filters)"
 					},
 					{
 						"lang": "JavaScript",
-						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst query = \"What do you know about me?\";\nconst filters = {\n  OR: [\n    { user_id: \"alex\" },\n    { agent_id: { in: [\"travel-assistant\", \"customer-support\"] } }\n  ]\n};\n\nclient.search(query, { api_version: \"v2\", filters })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
+						"source": "// To use the JavaScript SDK, install the package:\n// npm i mem0ai\n\nimport MemoryClient from 'mem0ai';\nconst client = new MemoryClient({ apiKey: \"your-api-key\" });\n\nconst query = \"What do you know about me?\";\nconst filters = {\n  OR: [\n    { user_id: \"alex\" },\n    { agent_id: { in: [\"travel-assistant\", \"customer-support\"] } }\n  ]\n};\n\nclient.search(query, { filters })\n  .then(result => console.log(result))\n  .catch(error => console.error(error));"
 					},
 					{
 						"lang": "cURL",
@@ -1864,7 +1864,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nmemory = client.get(memory_id=\"<memory_id>\")"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\nmemory = client.get(memory_id=\"<memory_id>\")"
 					},
 					{
 						"lang": "JavaScript",
@@ -1989,7 +1989,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Update a memory\nmemory_id = \"<memory_id>\"\nclient.update(\n    memory_id=memory_id,\n    text=\"Your updated memory message here\",\n    metadata={\"category\": \"example\"}\n)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Update a memory\nmemory_id = \"<memory_id>\"\nclient.update(\n    memory_id=memory_id,\n    text=\"Your updated memory message here\",\n    metadata={\"category\": \"example\"}\n)"
 					},
 					{
 						"lang": "JavaScript",
@@ -2053,7 +2053,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nmemory_id = \"<memory_id>\"\nclient.delete(memory_id=memory_id)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\nmemory_id = \"<memory_id>\"\nclient.delete(memory_id=memory_id)"
 					},
 					{
 						"lang": "JavaScript",
@@ -2199,7 +2199,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Add some message to create history\nmessages = [{\"role\": \"user\", \"content\": \"<user-message>\"}]\nclient.add(messages, user_id=\"<user-id>\")\n\n# Add second message to update history\nmessages.append({\"role\": \"user\", \"content\": \"<user-message>\"})\nclient.add(messages, user_id=\"<user-id>\")\n\n# Get history of how memory changed over time\nmemory_id = \"<memory-id-here>\"\nhistory = client.history(memory_id)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Add some message to create history\nmessages = [{\"role\": \"user\", \"content\": \"<user-message>\"}]\nclient.add(messages, user_id=\"<user-id>\")\n\n# Add second message to update history\nmessages.append({\"role\": \"user\", \"content\": \"<user-message>\"})\nclient.add(messages, user_id=\"<user-id>\")\n\n# Get history of how memory changed over time\nmemory_id = \"<memory-id-here>\"\nhistory = client.history(memory_id)"
 					},
 					{
 						"lang": "JavaScript",
@@ -3608,7 +3608,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nresponse = client.get_project()\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\n\nclient = MemoryClient(api_key=\"your_api_key\")\n\nresponse = client.get_project()\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -4411,7 +4411,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\nupdate_memories = [\n    {\n        \"memory_id\": \"285ed74b-6e05-4043-b16b-3abd5b533496\",\n        \"text\": \"Watches football\"\n    },\n    {\n        \"memory_id\": \"2c9bd859-d1b7-4d33-a6b8-94e0147c4f07\",\n        \"text\": \"Likes to travel\"\n    }\n]\n\nresponse = client.batch_update(update_memories)\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\nupdate_memories = [\n    {\n        \"memory_id\": \"285ed74b-6e05-4043-b16b-3abd5b533496\",\n        \"text\": \"Watches football\"\n    },\n    {\n        \"memory_id\": \"2c9bd859-d1b7-4d33-a6b8-94e0147c4f07\",\n        \"text\": \"Likes to travel\"\n    }\n]\n\nresponse = client.batch_update(update_memories)\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -4490,7 +4490,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\ndelete_memories = [\n    {\"memory_id\": \"285ed74b-6e05-4043-b16b-3abd5b533496\"},\n    {\"memory_id\": \"2c9bd859-d1b7-4d33-a6b8-94e0147c4f07\"}\n]\n\nresponse = client.batch_delete(delete_memories)\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\ndelete_memories = [\n    {\"memory_id\": \"285ed74b-6e05-4043-b16b-3abd5b533496\"},\n    {\"memory_id\": \"2c9bd859-d1b7-4d33-a6b8-94e0147c4f07\"}\n]\n\nresponse = client.batch_delete(delete_memories)\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -4758,7 +4758,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Create a webhook\nwebhook = client.create_webhook(\n    url=\"https://your-webhook-url.com\",\n    name=\"My Webhook\",\n    project_id=\"your_project_id\",\n    event_types=[\"memory:add\", \"memory:categorize\"]\n)\nprint(webhook)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Create a webhook\nwebhook = client.create_webhook(\n    url=\"https://your-webhook-url.com\",\n    name=\"My Webhook\",\n    project_id=\"your_project_id\",\n    event_types=[\"memory:add\", \"memory:categorize\"]\n)\nprint(webhook)"
 					},
 					{
 						"lang": "JavaScript",
@@ -4998,7 +4998,7 @@
 				"x-code-samples": [
 					{
 						"lang": "Python",
-						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\", org_id=\"your_org_id\", project_id=\"your_project_id\")\n\n# Delete a webhook\nresponse = client.delete_webhook(webhook_id=\"your_webhook_id\")\nprint(response)"
+						"source": "# To use the Python SDK, install the package:\n# pip install mem0ai\n\nfrom mem0 import MemoryClient\nclient = MemoryClient(api_key=\"your_api_key\")\n\n# Delete a webhook\nresponse = client.delete_webhook(webhook_id=\"your_webhook_id\")\nprint(response)"
 					},
 					{
 						"lang": "JavaScript",
@@ -5742,4 +5742,4 @@
 		}
 	},
 	"x-original-swagger-version": "2.0"
-}
+}

docs/platform/advanced-memory-operations.mdx

@@ -81,7 +81,6 @@ result = await memory.add(
     conversation,
     user_id="traveler-42",
     metadata={"trip": "japan-2025", "preferences": ["boutique", "no-shellfish"]},
-    enable_graph=True,
     run_id="planning-call-1",
 )
 ```
@@ -101,7 +100,6 @@ const conversation = [
 const result = await memory.add(conversation, {
   userId: "traveler-42",
   metadata: { trip: "japan-2025", preferences: ["boutique", "no-shellfish"] },
-  enableGraph: true,
   runId: "planning-call-1",
 });
 ```
@@ -163,10 +161,6 @@ await memory.update(matches.results[0].id, {
   </Tab>
 </Tabs>
 
-<Tip>
-  Need to pause graph writes on a per-request basis? Pass `enableGraph: false` (TypeScript) or `enable_graph=False` (Python) when latency matters more than relationship building.
-</Tip>
-
 ## Clean up
 
 <Tabs>
@@ -192,8 +186,6 @@ await memory.deleteAll({ userId: "traveler-42", runId: "planning-call-1" });
 
 ## Quick recovery
 
-- `Missing required key enableGraph`: update the SDK to `mem0ai>=0.4.0`.
-- `Graph backend unavailable`: retry with `enableGraph=False` and inspect your graph provider status.
 - Empty results with filters: log `filters` values and confirm metadata keys match (case-sensitive).
 
 <Warning>

docs/platform/features/advanced-retrieval.mdx

@@ -1,6 +1,6 @@
 ---
 title: Advanced Retrieval
-description: "Advanced memory search with keyword expansion, intelligent reranking, and precision filtering"
+description: "Advanced memory search with intelligent reranking for precise results"
 ---
 
 ## What is Advanced Retrieval?
@@ -9,40 +9,6 @@ Advanced Retrieval gives you precise control over how memories are found and ran
 
 ## Search Enhancement Options
 
-### Keyword Search
-
-Expands results to include memories with specific terms, names, and technical keywords.
-
-<Tabs>
-  <Tab title="When to Use">
-- Searching for specific entities, names, or technical terms
-- Need comprehensive coverage of a topic  
-- Want broader recall even if some results are less relevant
-- Working with domain-specific terminology
-</Tab>
-<Tab title="How it Works">
-```python Python
-# Find memories containing specific food-related terms
-results = client.search(
-    query="What foods should I avoid?",
-    keyword_search=True,
-    user_id="user123"
-)
-
-# Results might include:
-# ✓ "Allergic to peanuts and shellfish"  
-# ✓ "Lactose intolerant - avoid dairy"
-# ✓ "Mentioned avoiding gluten last week"
-```
-  </Tab>
-  <Tab title="Performance">
-- **Latency**: ~10ms additional
-- **Recall**: Significantly increased
-- **Precision**: Slightly decreased
-- **Best for**: Entity search, comprehensive coverage
-</Tab>
-</Tabs>
-
 ### Reranking
 
 Reorders results using deep semantic understanding to put the most relevant memories first.
@@ -77,41 +43,6 @@ results = client.search(
 </Tab>
 </Tabs>
 
-### Memory Filtering
-
-Filters results to keep only the most precisely relevant memories.
-
-<Tabs>
-<Tab title="When to Use">
-- Need highly specific, focused results
-- Working with large datasets where noise is problematic  
-- Quality over quantity is essential
-- Building production or safety-critical applications
-</Tab>
-<Tab title="How it Works">
-```python Python
-# Get only the most relevant dietary restrictions
-results = client.search(
-    query="What are my dietary restrictions?",
-    filter_memories=True,
-    user_id="user123"
-)
-
-# Before filtering:           After filtering:
-# • "Allergic to nuts"    →   • "Allergic to nuts"
-# • "Likes Italian food"  →   • "Vegetarian diet"
-# • "Vegetarian diet"     →   
-# • "Eats dinner at 7pm"  →   
-```
-</Tab>
-<Tab title="Performance">
-- **Latency**: 200-300ms additional
-- **Precision**: Maximized
-- **Recall**: May be reduced
-- **Best for**: Focused queries, production systems
-</Tab>
-</Tabs>
-
 ## Real-World Use Cases
 
 <Tabs>
@@ -120,7 +51,6 @@ results = client.search(
 # Smart home assistant finding device preferences
 results = client.search(
     query="How do I like my bedroom temperature?",
-    keyword_search=True,    # Find specific temperature mentions
     rerank=True,           # Get most recent preferences first
     user_id="user123"
 )
@@ -133,8 +63,6 @@ results = client.search(
 # Find specific product issues with high precision
 results = client.search(
     query="Problems with premium subscription billing",
-    keyword_search=True,     # Find "premium", "billing", "subscription"
-    filter_memories=True,    # Only billing-related issues
     user_id="customer456"
 )
 
@@ -147,11 +75,10 @@ results = client.search(
 results = client.search(
     query="Patient allergies and contraindications",
     rerank=True,            # Most important info first
-    filter_memories=True,   # Only medical restrictions
     user_id="patient789"
 )
 
-# Ensures critical allergy info appears first and filters out non-medical data
+# Ensures critical allergy info appears first
 ```
 </Tab>
 <Tab title="Learning Platform">
@@ -159,7 +86,6 @@ results = client.search(
 # Find learning progress for specific topics
 results = client.search(
     query="Python programming progress and difficulties",
-    keyword_search=True,    # Find "Python", "programming", specific concepts
     rerank=True,           # Recent progress first
     user_id="student123"
 )
@@ -169,63 +95,57 @@ results = client.search(
 </Tab>
 </Tabs>
 
-## Choosing the Right Combination
+## Choosing the Right Configuration
 
 ### Recommended Configurations
 
 <CodeGroup>
 ```python Python
-# Fast and broad - good for exploration
+# Basic search - good for exploration
 def quick_search(query, user_id):
     return client.search(
         query=query,
-        keyword_search=True,
         user_id=user_id
     )
 
-# Balanced - good for most applications  
+# Reranked search - good for most applications
 def standard_search(query, user_id):
     return client.search(
         query=query,
-        keyword_search=True,
         rerank=True,
         user_id=user_id
     )
 
-# High precision - good for critical applications
+# Reranked search - good for critical applications
 def precise_search(query, user_id):
     return client.search(
         query=query,
         rerank=True,
-        filter_memories=True,
         user_id=user_id
     )
 ```
 
 ```javascript JavaScript
-// Fast and broad - good for exploration
+// Basic search - good for exploration
 function quickSearch(query, userId) {
     return client.search(query, {
-        user_id: userId,
-        keyword_search: true
+        user_id: userId
     });
 }
 
-// Balanced - good for most applications
+// Reranked search - good for most applications
 function standardSearch(query, userId) {
     return client.search(query, {
         user_id: userId,
-        keyword_search: true,
         rerank: true
     });
 }
 
-// High precision - good for critical applications
+// Reranked search - good for critical applications
 function preciseSearch(query, userId) {
     return client.search(query, {
         user_id: userId,
-        rerank: true,
-        filter_memories: true
+        rerank: true
     });
 }
 ```
@@ -235,19 +155,15 @@ function preciseSearch(query, userId) {
 
 ### Do
 
-- Start simple with just one enhancement and measure impact
-- Use keyword search for entity-heavy queries (names, places, technical terms)
+- Start simple with basic search and measure impact before enabling reranking
 - Use reranking when the top result quality matters most
-- Use filtering for production systems where precision is critical
-- Handle empty results gracefully when filtering is too aggressive
 - Monitor latency and adjust based on your application's needs
+- Handle empty results gracefully
 
 ### Don't
 
-- Enable all options by default without measuring necessity
-- Use filtering for broad exploratory queries
+- Enable reranking by default without measuring necessity
 - Ignore latency impact in real-time applications
-- Forget to handle cases where filtering returns no results
 - Use advanced retrieval for simple, fast lookup scenarios
 
 ## Performance Guidelines
@@ -261,20 +177,18 @@ import time
 start_time = time.time()
 results = client.search(
     query="user preferences",
-    keyword_search=True,  # +10ms
     rerank=True,         # +150ms
-    filter_memories=True, # +250ms
     user_id="user123"
 )
 latency = time.time() - start_time
-print(f"Search completed in {latency:.2f}s")  # ~0.41s expected
+print(f"Search completed in {latency:.2f}s")
 ```
 
 ### Optimization Tips
 
 1. **Cache frequent queries** to avoid repeated advanced processing
 2. **Use session-specific search** with `run_id` to reduce search space
-3. **Implement fallback logic** when filtering returns empty results
+3. **Implement fallback logic** when search returns empty results
 4. **Monitor and alert** on search latency patterns
 
 <Snippet file="get-help.mdx" />

docs/platform/features/async-client.mdx

@@ -50,7 +50,7 @@ const messages = [
     {"role": "user", "content": "Alice loves playing badminton"},
     {"role": "assistant", "content": "That's great! Alice is a fitness freak"},
 ];
-await client.add(messages, { user_id: "alice" });
+await client.add(messages, { userId: "alice" });
 ```
 
 </CodeGroup>
@@ -66,7 +66,7 @@ await client.search("What is Alice's favorite sport?", user_id="alice")
 ```
 
 ```javascript JavaScript
-await client.search("What is Alice's favorite sport?", { user_id: "alice" });
+await client.search("What is Alice's favorite sport?", { userId: "alice" });
 ```
 
 </CodeGroup>
@@ -118,7 +118,7 @@ await client.delete_all(user_id="alice")
 ```
 
 ```javascript JavaScript
-await client.deleteAll({ user_id: "alice" });
+await client.deleteAll({ userId: "alice" });
 ```
 
 </CodeGroup>

docs/platform/features/async-mode-default-change.mdx

@@ -1,197 +0,0 @@
----
-title: Async Mode Default Change
-description: "The async_mode parameter now defaults to true for all memory additions, changing from synchronous processing."
----
-
-<Note type="warning">
-  **Important Change**
-
-  The `async_mode` parameter defaults to `true` for all memory additions, changing the default API behavior to asynchronous processing.
-</Note>
-
-## Overview
-
-The Memory Addition API processes all memory additions asynchronously by default. This change improves performance and scalability by queuing memory operations in the background, allowing your application to continue without waiting for memory processing to complete.
-
-## What's Changing
-
-The parameter `async_mode` will default to `true` instead of `false`.
-
-This means memory additions will be **processed asynchronously** by default - queued for background execution instead of waiting for processing to complete.
-
-## Behavior Comparison
-
-### Old Default Behavior (async_mode = false)
-
-When `async_mode` was set to `false`, the API returned fully processed memory objects immediately:
-
-```json
-{
-  "results": [
-    {
-      "id": "de0ee948-af6a-436c-835c-efb6705207de",
-      "event": "ADD",
-      "memory": "User Order #1234 was for a 'Nova 2000'",
-      "structured_attributes": {
-        "day": 13,
-        "hour": 16,
-        "year": 2025,
-        "month": 10,
-        "minute": 59,
-        "quarter": 4,
-        "is_weekend": false,
-        "day_of_week": "monday",
-        "day_of_year": 286,
-        "week_of_year": 42
-      }
-    }
-  ]
-}
-```
-
-### New Default Behavior (async_mode = true)
-
-With `async_mode` defaulting to `true`, memory processing is queued in the background and the API returns immediately:
-
-```json
-{
-  "results": [
-    {
-      "message": "Memory processing has been queued for background execution",
-      "status": "PENDING",
-      "event_id": "d7b5282a-0031-4cc2-98ba-5a02d8531e17"
-    }
-  ]
-}
-```
-
-## Migration Guide
-
-### If You Need Synchronous Processing
-
-If your integration relies on receiving the processed memory object immediately, you can explicitly set `async_mode` to `false` in your requests:
-
-<CodeGroup>
-
-```python Python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-api-key")
-
-# Explicitly set async_mode=False to preserve synchronous behavior
-messages = [
-    {"role": "user", "content": "I ordered a Nova 2000"}
-]
-
-result = client.add(
-    messages,
-    user_id="user-123",
-    async_mode=False  # This ensures synchronous processing
-)
-```
-
-```javascript JavaScript
-const { MemoryClient } = require('mem0ai');
-
-const client = new MemoryClient({ apiKey: 'your-api-key' });
-
-// Explicitly set async_mode: false to preserve synchronous behavior
-const messages = [
-    { role: "user", content: "I ordered a Nova 2000" }
-];
-
-const result = await client.add(messages, {
-    user_id: "user-123",
-    async_mode: false  // This ensures synchronous processing
-});
-```
-
-```bash cURL
-curl -X POST https://api.mem0.ai/v1/memories/ \
-  -H "Authorization: Token your-api-key" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "messages": [
-      {"role": "user", "content": "I ordered a Nova 2000"}
-    ],
-    "user_id": "user-123",
-    "async_mode": false
-  }'
-```
-
-</CodeGroup>
-
-### If You Want to Adopt Asynchronous Processing
-
-If you want to benefit from the improved performance of asynchronous processing:
-
-1. **Remove** any explicit `async_mode=False` parameters from your code
-2. **Use webhooks** to receive notifications when memory processing completes
-
-<Note>
-Learn more about [Webhooks](/platform/features/webhooks) for real-time notifications about memory events.
-</Note>
-
-## Benefits of Asynchronous Processing
-
-Switching to asynchronous processing provides several advantages:
-
-- **Faster API Response Times**: Your application doesn't wait for memory processing
-- **Better Scalability**: Handle more memory additions concurrently
-- **Improved User Experience**: Reduced latency in your application
-- **Resource Efficiency**: Background processing optimizes server resources
-
-## Important Notes
-
-- The default behavior is now `async_mode=true` for asynchronous processing
-- Explicitly set `async_mode=false` if you need synchronous behavior
-- Use webhooks to receive notifications when memories are processed
-
-## Monitoring Memory Processing
-
-When using asynchronous mode, use webhooks to receive notifications about memory events:
-
-<Card title="Configure Webhooks" icon="webhook" href="/platform/features/webhooks">
-  Learn how to set up webhooks for memory processing events
-</Card>
-
-You can also retrieve all processed memories at any time:
-
-<CodeGroup>
-
-```python Python
-# Retrieve all memories for a user
-# Note: get_all now requires filters
-memories = client.get_all(filters={"AND": [{"user_id": "user-123"}]})
-```
-
-```javascript JavaScript
-// Retrieve all memories for a user
-// Note: getAll now requires filters
-const memories = await client.getAll({ filters: {"AND": [{"user_id": "user-123"}]} });
-```
-
-</CodeGroup>
-
-## Need Help?
-
-If you have questions about this change or need assistance updating your integration:
-
-<Snippet file="get-help.mdx" />
-
-## Related Documentation
-
-<CardGroup cols={2}>
-  <Card title="Async Client" icon="bolt" href="/platform/features/async-client">
-    Learn about the asynchronous client for Mem0
-  </Card>
-  <Card title="Add Memories API" icon="plus" href="/api-reference/memory/add-memories">
-    View the complete API reference for adding memories
-  </Card>
-  <Card title="Webhooks" icon="webhook" href="/platform/features/webhooks">
-    Configure webhooks for memory processing events
-  </Card>
-  <Card title="Memory Operations" icon="gear" href="/core-concepts/memory-operations/add">
-    Understand memory addition operations
-  </Card>
-</CardGroup>

docs/platform/features/contextual-add.mdx

@@ -25,7 +25,7 @@ const messages = [
     {"role": "assistant", "content": "Great! I'll remember your preference for Italian cuisine."}
 ];
 
-await client.add(messages, { user_id: "user123", version: "v2" });
+await client.add(messages, { userId: "user123", version: "v2" });
 ```
 </CodeGroup>
 
@@ -65,14 +65,14 @@ const messages1 = [
     {"role": "user", "content": "Hi, I'm Sarah from New York"},
     {"role": "assistant", "content": "Hello Sarah! Nice to meet you."}
 ];
-await client.add(messages1, { user_id: "sarah", version: "v2" });
+await client.add(messages1, { userId: "sarah", version: "v2" });
 
 // Later interaction - just send new messages
 const messages2 = [
     {"role": "user", "content": "I'm planning a trip to Italy next month"},
     {"role": "assistant", "content": "How exciting! Italy is beautiful this time of year."}
 ];
-await client.add(messages2, { user_id: "sarah", version: "v2" });
+await client.add(messages2, { userId: "sarah", version: "v2" });
 // Mem0 automatically knows Sarah is from New York and can use this context
 ```
 </CodeGroup>
@@ -104,7 +104,7 @@ const messages = [
     {"role": "assistant", "content": "I've noted your allergies for future reference."}
 ];
 
-await client.add(messages, { user_id: "user123", version: "v2" });
+await client.add(messages, { userId: "user123", version: "v2" });
 // This allergy info will be available in ALL future interactions
 ```
 </CodeGroup>
@@ -143,21 +143,21 @@ const messages1 = [
     {"role": "user", "content": "I want to plan a 5-day trip to Tokyo"},
     {"role": "assistant", "content": "Perfect! Let's plan your Tokyo adventure."}
 ];
-await client.add(messages1, { user_id: "user123", run_id: "tokyo-trip-2024", version: "v2" });
+await client.add(messages1, { userId: "user123", runId: "tokyo-trip-2024", version: "v2" });
 
 // Later in the same trip planning session
 const messages2 = [
     {"role": "user", "content": "I prefer staying near Shibuya"},
     {"role": "assistant", "content": "Great choice! Shibuya is very convenient."}
 ];
-await client.add(messages2, { user_id: "user123", run_id: "tokyo-trip-2024", version: "v2" });
+await client.add(messages2, { userId: "user123", runId: "tokyo-trip-2024", version: "v2" });
 
 // Different session for work project (separate context)
 const workMessages = [
     {"role": "user", "content": "Let's discuss the Q4 marketing strategy"},
     {"role": "assistant", "content": "Sure! What are your main goals for Q4?"}
 ];
-await client.add(workMessages, { user_id: "user123", run_id: "q4-marketing", version: "v2" });
+await client.add(workMessages, { userId: "user123", runId: "q4-marketing", version: "v2" });
 ```
 </CodeGroup>
 

docs/platform/features/criteria-retrieval.mdx

@@ -38,11 +38,7 @@ Before defining any criteria, make sure to initialize the `MemoryClient` with yo
 ```python
 from mem0 import MemoryClient
 
-client = MemoryClient(
-    api_key="your_mem0_api_key",
-    org_id="your_organization_id",
-    project_id="your_project_id"
-)
+client = MemoryClient(api_key="your_mem0_api_key")
 ```
 
 ### Define Your Criteria

docs/platform/features/custom-categories.mdx

@@ -98,7 +98,7 @@ messages = [
 ]
 
 # Add memories with project-level custom categories
-client.add(messages, user_id="alice", async_mode=False)
+client.add(messages, user_id="alice")
 ```
 </CodeGroup>
 
@@ -187,7 +187,7 @@ messages = [
 ]
 
 # Add memories with default categories
-client.add(messages, user_id='alice', async_mode=False)
+client.add(messages, user_id='alice')
 ```
 
 ```python Memories with categories

docs/platform/features/custom-instructions.mdx

@@ -33,7 +33,7 @@ Extract only health and wellness information:
 Exclude: Personal identifiers, financial data
 `;
 
-await client.project.update({ custom_instructions: prompt });
+await client.project.update({ customInstructions: prompt });
 ```
 </CodeGroup>
 
@@ -60,11 +60,11 @@ print(response["custom_instructions"])
 
 ```javascript JavaScript
 // Set instructions for your project
-await client.project.update({ custom_instructions: "Your guidelines here..." });
+await client.project.update({ customInstructions: "Your guidelines here..." });
 
 // Retrieve current instructions
-const response = await client.project.get({ fields: ["custom_instructions"] });
-console.log(response.custom_instructions);
+const response = await client.project.get({ fields: ["customInstructions"] });
+console.log(response.customInstructions);
 ```
 </CodeGroup>
 
@@ -145,7 +145,7 @@ Extract customer service information for better support:
 Exclude: Payment card numbers, passwords, personal identifiers.
 `;
 
-await client.project.update({ custom_instructions: instructions });
+await client.project.update({ customInstructions: instructions });
 ```
 </CodeGroup>
   </Tab>
@@ -198,7 +198,7 @@ Extract learning-related information for personalized education:
 Exclude: Specific grades, personal identifiers, financial information.
 `;
 
-await client.project.update({ custom_instructions: educationPrompt });
+await client.project.update({ customInstructions: educationPrompt });
 ```
 </CodeGroup>
   </Tab>
@@ -251,7 +251,7 @@ Extract financial planning information for advisory services:
 Exclude: Account numbers, SSNs, passwords, specific financial amounts.
 `;
 
-await client.project.update({ custom_instructions: financePrompt });
+await client.project.update({ customInstructions: financePrompt });
 ```
 </CodeGroup>
   </Tab>

docs/platform/features/expiration-date.mdx

@@ -1,109 +0,0 @@
----
-title: Expiration Date
-description: 'Set time-bound memories in Mem0 with automatic expiration dates to manage temporal information effectively.'
----
-
-## Benefits of Memory Expiration
-
-Setting expiration dates for memories offers several advantages:
-
-- **Time-Sensitive Information Management**: Handle information that is only relevant for a specific time period.
-- **Event-Based Memory**: Manage information related to upcoming events that becomes irrelevant after the event passes.
-
-These benefits enable more sophisticated memory management for applications where temporal context matters.
-
-## Setting Memory Expiration Date
-
-You can set an expiration date for memories, after which they will no longer be retrieved in searches. This is useful for creating temporary memories or memories that are relevant only for a specific time period.
-
-<CodeGroup>
-
-```python Python
-import datetime
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-api-key")
-
-messages = [
-    {
-        "role": "user", 
-        "content": "I'll be in San Francisco until the end of this month."
-    }
-]
-
-# Set an expiration date for this memory
-client.add(messages=messages, user_id="alex", expiration_date=str(datetime.datetime.now().date() + datetime.timedelta(days=30)))
-
-# You can also use an explicit date string
-client.add(messages=messages, user_id="alex", expiration_date="2023-08-31")
-```
-
-```javascript JavaScript
-import MemoryClient from 'mem0ai';
-const client = new MemoryClient({ apiKey: 'your-api-key' });
-
-const messages = [
-    {
-        "role": "user", 
-        "content": "I'll be in San Francisco until the end of this month."
-    }
-];
-
-// Set an expiration date 30 days from now
-const expirationDate = new Date();
-expirationDate.setDate(expirationDate.getDate() + 30);
-client.add(messages, { 
-    user_id: "alex", 
-    expiration_date: expirationDate.toISOString().split('T')[0] 
-})
-    .then(response => console.log(response))
-    .catch(error => console.error(error));
-
-// You can also use an explicit date string
-client.add(messages, { 
-    user_id: "alex", 
-    expiration_date: "2023-08-31" 
-})
-    .then(response => console.log(response))
-    .catch(error => console.error(error));
-```
-
-```bash cURL
-curl -X POST "https://api.mem0.ai/v1/memories/" \
-     -H "Authorization: Token your-api-key" \
-     -H "Content-Type: application/json" \
-     -d '{
-         "messages": [
-             {
-                "role": "user", 
-                "content": "I'll be in San Francisco until the end of this month."
-            }
-         ],
-         "user_id": "alex",
-         "expiration_date": "2023-08-31"
-     }'
-```
-
-```json Output
-{
-    "results": [
-        {
-            "id": "a1b2c3d4-e5f6-4g7h-8i9j-k0l1m2n3o4p5",
-            "data": {
-                "memory": "In San Francisco until the end of this month"
-            },
-            "event": "ADD"
-        }
-    ]
-}
-```
-
-</CodeGroup>
-
-<Note>
-Once a memory reaches its expiration date, it will not be included in search or get results, though the data remains stored in the system.
-</Note>
-
-If you have any questions, please feel free to reach out to us using one of the following methods:
-
-<Snippet file="get-help.mdx" />

docs/platform/features/graph-memory.mdx

@@ -1,349 +0,0 @@
----
-title: Graph Memory
-description: "Enable graph-based memory retrieval for more contextually relevant results"
----
-
-## Overview
-
-Graph Memory enhances the memory pipeline by creating relationships between entities in your data. It builds a network of interconnected information for more contextually relevant search results.
-
-This feature allows your AI applications to understand connections between entities, providing richer context for responses. It's ideal for applications needing relationship tracking and nuanced information retrieval across related memories.
-
-## How Graph Memory Works
-
-The Graph Memory feature analyzes how each entity connects and relates to each other. When enabled:
-
-1. Mem0 automatically builds a graph representation of entities
-2. Vector search returns the top semantic matches (with any reranker you configure)
-3. Graph relations are returned alongside those results to provide additional context—they do not reorder the vector hits
-
-## Using Graph Memory
-
-To use Graph Memory, you need to enable it in your API calls by setting the `enable_graph=True` parameter.
-
-### Adding Memories with Graph Memory
-
-When adding new memories, enable Graph Memory to automatically build relationships with existing memories:
-
-<CodeGroup>
-
-```python Python
-from mem0 import MemoryClient
-
-client = MemoryClient(
-    api_key="your-api-key",
-    org_id="your-org-id",
-    project_id="your-project-id"
-)
-
-messages = [
-    {"role": "user", "content": "My name is Joseph"},
-    {"role": "assistant", "content": "Hello Joseph, it's nice to meet you!"},
-    {"role": "user", "content": "I'm from Seattle and I work as a software engineer"}
-]
-
-# Enable graph memory when adding
-client.add(
-    messages,
-    user_id="joseph",
-    enable_graph=True
-)
-```
-
-```javascript JavaScript
-import { MemoryClient } from "mem0";
-
-const client = new MemoryClient({
-  apiKey: "your-api-key",
-  org_id: "your-org-id",
-  project_id: "your-project-id"
-});
-
-const messages = [
-  { role: "user", content: "My name is Joseph" },
-  { role: "assistant", content: "Hello Joseph, it's nice to meet you!" },
-  { role: "user", content: "I'm from Seattle and I work as a software engineer" }
-];
-
-// Enable graph memory when adding
-await client.add({
-  messages,
-  user_id: "joseph",
-  enable_graph: true
-});
-```
-
-```json Output
-{
-  "results": [
-    {
-      "memory": "Name is Joseph",
-      "event": "ADD",
-      "id": "4a5a417a-fa10-43b5-8c53-a77c45e80438"
-    },
-    {
-      "memory": "Is from Seattle",
-      "event": "ADD",
-      "id": "8d268d0f-5452-4714-b27d-ae46f676a49d"
-    },
-    {
-      "memory": "Is a software engineer",
-      "event": "ADD",
-      "id": "5f0a184e-ddea-4fe6-9b92-692d6a901df8"
-    }
-  ]
-}
-```
-</CodeGroup>
-
-The graph memory would look like this:
-
-<Frame>
-  <img src="/images/graph-platform.png" alt="Graph Memory Visualization showing relationships between entities" />
-</Frame>
-
-<Caption>Graph Memory creates a network of relationships between entities, enabling more contextual retrieval</Caption>
-
-
-<Note>
-Response for the graph memory's `add` operation will not be available directly in the response. As adding graph memories is an asynchronous operation due to heavy processing, you can use the `get_all()` endpoint to retrieve the memory with the graph metadata.
-</Note>
-
-
-### Searching with Graph Memory
-
-When searching memories, Graph Memory helps retrieve entities that are contextually important even if they're not direct semantic matches.
-
-<CodeGroup>
-
-```python Python
-# Search with graph memory enabled
-results = client.search(
-    "what is my name?",
-    user_id="joseph",
-    enable_graph=True
-)
-
-print(results)
-```
-
-```javascript JavaScript
-// Search with graph memory enabled
-const results = await client.search({
-  query: "what is my name?",
-  user_id: "joseph",
-  enable_graph: true
-});
-
-console.log(results);
-```
-
-```json Output
-{
-  "results": [
-    {
-      "id": "4a5a417a-fa10-43b5-8c53-a77c45e80438",
-      "memory": "Name is Joseph",
-      "user_id": "joseph",
-      "metadata": null,
-      "categories": ["personal_details"],
-      "immutable": false,
-      "created_at": "2025-03-19T09:09:00.146390-07:00",
-      "updated_at": "2025-03-19T09:09:00.146404-07:00",
-      "score": 0.3621795393335552
-    },
-    {
-      "id": "8d268d0f-5452-4714-b27d-ae46f676a49d",
-      "memory": "Is from Seattle",
-      "user_id": "joseph",
-      "metadata": null,
-      "categories": ["personal_details"],
-      "immutable": false,
-      "created_at": "2025-03-19T09:09:00.170680-07:00",
-      "updated_at": "2025-03-19T09:09:00.170692-07:00",
-      "score": 0.31212713194651254
-    }
-  ],
-  "relations": [
-    {
-      "source": "joseph",
-      "source_type": "person",
-      "relationship": "name",
-      "target": "joseph",
-      "target_type": "person",
-      "score": 0.39
-    }
-  ]
-}
-```
-
-</CodeGroup>
-
-<Note>
-`results` always reflects the vector search order (optionally reranked). Graph Memory augments that response by adding related entities in the `relations` array; it does not re-rank the vector results automatically.
-</Note>
-
-### Retrieving All Memories with Graph Memory
-
-When retrieving all memories, Graph Memory provides additional relationship context:
-
-<Callout type="warning" title="Filters Required">
-`get_all()` now requires filters to be specified.
-</Callout>
-
-<CodeGroup>
-
-```python Python
-# Get all memories with graph context
-memories = client.get_all(
-    filters={"AND": [{"user_id": "joseph"}]},
-    enable_graph=True
-)
-
-print(memories)
-```
-
-```javascript JavaScript
-// Get all memories with graph context
-const memories = await client.getAll({
-  filters: {"AND": [{"user_id": "joseph"}]},
-  enable_graph: true
-});
-
-console.log(memories);
-```
-
-```json Output
-{
-  "results": [
-    {
-      "id": "5f0a184e-ddea-4fe6-9b92-692d6a901df8",
-      "memory": "Is a software engineer",
-      "user_id": "joseph",
-      "metadata": null,
-      "categories": ["professional_details"],
-      "immutable": false,
-      "created_at": "2025-03-19T09:09:00.194116-07:00",
-      "updated_at": "2025-03-19T09:09:00.194128-07:00",
-    },
-    {
-      "id": "8d268d0f-5452-4714-b27d-ae46f676a49d",
-      "memory": "Is from Seattle",
-      "user_id": "joseph",
-      "metadata": null,
-      "categories": ["personal_details"],
-      "immutable": false,
-      "created_at": "2025-03-19T09:09:00.170680-07:00",
-      "updated_at": "2025-03-19T09:09:00.170692-07:00",
-    },
-    {
-      "id": "4a5a417a-fa10-43b5-8c53-a77c45e80438",
-      "memory": "Name is Joseph",
-      "user_id": "joseph",
-      "metadata": null,
-      "categories": ["personal_details"],
-      "immutable": false,
-      "created_at": "2025-03-19T09:09:00.146390-07:00",
-      "updated_at": "2025-03-19T09:09:00.146404-07:00",
-    }
-  ],
-  "relations": [
-    {
-      "source": "joseph",
-      "source_type": "person",
-      "relationship": "name",
-      "target": "joseph",
-      "target_type": "person"
-    },
-    {
-      "source": "joseph",
-      "source_type": "person",
-      "relationship": "city",
-      "target": "seattle",
-      "target_type": "city"
-    },
-    {
-      "source": "joseph",
-      "source_type": "person",
-      "relationship": "job",
-      "target": "software engineer",
-      "target_type": "job"
-    }
-  ]
-}
-```
-
-</CodeGroup>
-
-### Setting Graph Memory at Project Level
-
-Instead of passing `enable_graph=True` to every add call, you can enable it once at the project level:
-
-<CodeGroup>
-
-```python Python
-from mem0 import MemoryClient
-
-client = MemoryClient(
-    api_key="your-api-key",
-    org_id="your-org-id",
-    project_id="your-project-id"
-)
-
-# Enable graph memory for all operations in this project
-client.project.update(enable_graph=True)
-
-# Now all add operations will use graph memory by default
-messages = [
-    {"role": "user", "content": "My name is Joseph"},
-    {"role": "assistant", "content": "Hello Joseph, it's nice to meet you!"},
-    {"role": "user", "content": "I'm from Seattle and I work as a software engineer"}
-]
-
-client.add(
-    messages,
-    user_id="joseph"
-)
-```
-
-```javascript JavaScript
-import { MemoryClient } from "mem0";
-
-const client = new MemoryClient({
-  apiKey: "your-api-key",
-  org_id: "your-org-id",
-  project_id: "your-project-id"
-});
-
-// Enable graph memory for all operations in this project
-await client.project.update({ enable_graph: true });
-
-// Now all add operations will use graph memory by default
-const messages = [
-  { role: "user", content: "My name is Joseph" },
-  { role: "assistant", content: "Hello Joseph, it's nice to meet you!" },
-  { role: "user", content: "I'm from Seattle and I work as a software engineer" }
-];
-
-await client.add({
-  messages,
-  user_id: "joseph"
-});
-```
-
-</CodeGroup>
-
-
-## Best Practices
-
-- Enable Graph Memory for applications where understanding context and relationships between memories is important.
-- Graph Memory works best with a rich history of related conversations.
-- Consider Graph Memory for long-running assistants that need to track evolving information.
-
-## Performance Considerations
-
-Graph Memory requires additional processing and may increase response times slightly for very large memory stores. However, for most use cases, the improved retrieval quality outweighs the minimal performance impact.
-
-If you have any questions, please feel free to reach out to us using one of the following methods:
-
-<Snippet file="get-help.mdx" />

docs/platform/features/graph-threshold.mdx

@@ -206,5 +206,5 @@ config = {"graph_store": {"threshold": 0.7}}  # Valid: 0.0 ≤ x ≤ 1.0
 
 ## Related
 
-- [Graph Memory](/platform/features/graph-memory)
+- [Graph Memory](/open-source/features/graph-memory)
 - [Issue #3590](https://github.com/mem0ai/mem0/issues/3590)

docs/platform/features/group-chat.mdx

@@ -217,17 +217,16 @@ print(search_response)
 
 ## Async Mode Support
 
-Group chat also supports async processing for improved performance:
+Group chat supports async processing for improved performance. Memory additions are processed asynchronously by default.
 
 <CodeGroup>
 
 ```python Python
-# Group chat with async mode
+# Group chat — async processing is the default
 response = client.add(
     messages,
     run_id="groupchat_async",
     infer=True,
-    async_mode=True
 )
 print(response)
 ```
@@ -268,7 +267,7 @@ Each message in a group chat must include:
 
 4. **Memory Filtering**: Use filters to retrieve memories from specific participants or sessions when needed.
 
-5. **Async Processing**: Use `async_mode=True` for large group conversations to improve performance.
+5. **Async Processing**: Memory additions are processed asynchronously by default, which is ideal for large group conversations.
 
 6. **Search Context**: Leverage the search functionality to find specific information within group chat contexts.
 

docs/platform/features/memory-export.mdx

@@ -134,7 +134,7 @@ const filters = {
 const responseWithInstructions = await client.createMemoryExport({
     schema: json_schema,
     filters: filters,
-    export_instructions: export_instructions
+    exportInstructions: export_instructions
 });
 
 console.log(responseWithInstructions);
@@ -176,10 +176,10 @@ print(response)
 
 ```javascript JavaScript
 // Retrieve using export ID
-const memory_export_id = "550e8400-e29b-41d4-a716-446655440000";
+const memoryExportId = "550e8400-e29b-41d4-a716-446655440000";
 
 const response = await client.getMemoryExport({
-    memory_export_id: memory_export_id
+    memoryExportId: memoryExportId
 });
 
 console.log(response);

docs/platform/features/multimodal-support.mdx

@@ -67,7 +67,7 @@ const messages = [
     },
 ]
 
-await client.add(messages, { user_id: "alice" })
+await client.add(messages, { userId: "alice" })
 ```
 
 ```json Output
@@ -166,7 +166,7 @@ const imageMessage = {
     }
 };
 
-await client.add([imageMessage], { user_id: "alice" })
+await client.add([imageMessage], { userId: "alice" })
 ```
 </CodeGroup>
 

docs/platform/features/platform-overview.mdx

@@ -20,7 +20,7 @@ Mem0 Platform features help managed deployments scale from basic filtering to gr
   <Card title="Go Real-Time with Async" icon="bolt" href="/platform/features/async-client">
     Non-blocking add/search requests for agents.
   </Card>
-  <Card title="Unlock Graph Memory" icon="circle-nodes" href="/platform/features/graph-memory">
+  <Card title="Unlock Graph Memory" icon="circle-nodes" href="/open-source/features/graph-memory">
     Relationship-aware recall across entities.
   </Card>
   <Card

docs/platform/features/timestamp.mdx

@@ -76,7 +76,7 @@ const unixTimestamp = Math.floor(fiveDaysAgo.getTime() / 1000);
 const messages = [
     {"role": "user", "content": "I'm travelling to SF"}
 ]
-client.add(messages, { user_id: "user1", timestamp: unixTimestamp })
+client.add(messages, { userId: "user1", timestamp: unixTimestamp })
     .then(response => console.log(response))
     .catch(error => console.error(error));
 ```
@@ -131,7 +131,7 @@ const january2023Timestamp = 1672531200;  // Unix timestamp for 2023-01-01 00:00
 const messages = [
     {"role": "user", "content": "I'm travelling to SF"}
 ]
-client.add(messages, { user_id: "user1", timestamp: january2023Timestamp })
+client.add(messages, { userId: "user1", timestamp: january2023Timestamp })
     .then(response => console.log(response))
     .catch(error => console.error(error));
 ```

docs/platform/mem0-mcp.mdx

@@ -7,8 +7,8 @@ estimatedTime: "~2 minutes"
 
 <Info>
   **Prerequisites**
-  - Mem0 Platform account ([Sign up here](https://app.mem0.ai))
-  - API key ([Get one from dashboard](https://app.mem0.ai/settings/api-keys))
+  - Mem0 Platform account (<a href="https://app.mem0.ai" rel="nofollow">Sign up here</a>)
+  - API key (<a href="https://app.mem0.ai/settings/api-keys" rel="nofollow">Get one from dashboard</a>)
   - Node.js 14+ (for npx)
   - An MCP-compatible client (Claude, Claude Code, Cursor, Windsurf, VS Code, OpenCode)
 </Info>
@@ -163,7 +163,7 @@ Agent: Updated your project status successfully.
 ```
 
 <Info icon="check">
-  If you get "Connection failed", ensure you have a valid API key from [Mem0 Dashboard](https://app.mem0.ai/settings/api-keys).
+  If you get "Connection failed", ensure you have a valid API key from <a href="https://app.mem0.ai/settings/api-keys" rel="nofollow">Mem0 Dashboard</a>.
 </Info>
 
 ---
@@ -171,7 +171,7 @@ Agent: Updated your project status successfully.
 ## Quick Recovery
 
 - **"Connection refused"** → Check your internet connection and ensure the MCP client is correctly configured
-- **"Invalid API key"** → Get a new key from [Mem0 Dashboard](https://app.mem0.ai/settings/api-keys)
+- **"Invalid API key"** → Get a new key from <a href="https://app.mem0.ai/settings/api-keys" rel="nofollow">Mem0 Dashboard</a>
 - **"npx command not found"** → Install Node.js from [nodejs.org](https://nodejs.org)
 
 ---

docs/platform/overview.mdx

@@ -64,7 +64,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
   <Card title="Connect Integrations" icon="plug" href="/integrations">
     LangChain, CrewAI, Vercel AI SDK.
   </Card>
-  <Card title="Monitor in the Dashboard" icon="presentation" href="https://app.mem0.ai">
+  <Card title="Monitor in the Dashboard" icon="presentation" href="https://app.mem0.ai/login">
     Track activity and manage workspaces.
   </Card>
 </CardGroup>

docs/platform/platform-vs-oss.mdx

@@ -150,7 +150,7 @@ Mem0 offers two powerful ways to add memory to your AI applications. Choose base
   <Card
     title="Try Platform Free"
     icon="rocket"
-    href="https://app.mem0.ai"
+    href="https://app.mem0.ai/login"
   >
     Sign up and test the Platform with our free tier. No credit card required.
   </Card>

docs/platform/quickstart.mdx

@@ -9,8 +9,8 @@ Get started with Mem0 Platform's hosted API in under 5 minutes. This guide shows
 
 ## Prerequisites
 
-- Mem0 Platform account ([Sign up here](https://app.mem0.ai))
-- API key ([Get one from dashboard](https://app.mem0.ai/dashboard/settings?tab=api-keys&subtab=configuration))
+- Mem0 Platform account (<a href="https://app.mem0.ai" rel="nofollow">Sign up here</a>)
+- API key (<a href="https://app.mem0.ai/dashboard/settings?tab=api-keys&subtab=configuration" rel="nofollow">Get one from dashboard</a>)
 - Python 3.10+, Node.js 14+, or cURL
 
 ## Installation
@@ -68,7 +68,7 @@ const messages = [
     {"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
     {"role": "assistant", "content": "Got it! I'll remember your dietary preferences."}
 ];
-await client.add(messages, { user_id: "user123" });
+await client.add(messages, { userId: "user123" });
 ````
 
 ```bash cURL