Changelog

All notable changes to MemOS will be documented here
GitHub
v2.0.33

MemOS Cloud

Bug Fixes
Cloud Service:
  • Fixed the issue where the exception object in the request parameter validation information could not be serialized, causing the 422 validation error to be masked as a 500 service exception.
  • Fixed the issue where the skill URL returned empty for the memory list interface, resolving the problem with metadata.getKey() judgment and encrypting empty strings.

Open Source

Improvements
Preference Memory Extraction:
  • Improved the accuracy of preference memory extraction by excluding interference from Agent output, tool calls, and concatenated context, focusing solely on user expressions to identify preferences.
Bug Fixes
Open Source Project:
  • Fixed the issue where asynchronous tasks failed during add operations, preventing the cleanup of fast nodes.
v2.0.32

MemOS Cloud

New Features
Cloud service:
  • Added image and document content extraction, with support for custom prompts to adjust extraction rules.
v2.0.31

Open Source

Improvements
Open Source:
  • Added request headers for Qwen model calls to better handle sudden rate limiting
v2.0.30

MemOS Cloud

New Features
Cloud service:
  • Added an interface to support customizing the extraction prompt for each memory view through the custom_extract_prompt parameter.
Improvements
Cloud service:
  • Implemented independent asynchronous logging for each worker.

Open Source

Bug Fixes
Open Source:
  • Fixed vLLM streaming responses retaining only the final chunk, which caused truncated answers and errors on empty streams.
  • Fixed UniversalAPIEmbedder ignoring embedding_dims, enabling requested vector dimensions and automatic fallback for services that do not support the parameter.
  • Added enable_thinking control for OpenAI-compatible and Azure models to prevent reasoning content from corrupting structured outputs such as JSON.
v2.0.29

MemOS Cloud

Improvements
Cloud Playground:
  • Optimized the Dashboard memory-list deletion flow to improve locating and deleting target memories
v2.0.28

MemOS Cloud

Improvements
Cloud service:
  • Resolved low efficiency and high costs caused by missing routing information when deleting memories.

Open Source

Improvements
Open Source:
  • Improved MemOS documentation extraction, adjusted return mode and truncation character count.
v2.0.25

MemOS Cloud

Bug Fixes
Event Memory:
  • Fixed overlong model inputs caused by Event Memory content not being truncated

Open Source

Improvements
MMR optimization:
  • Optimized MMR by pruning candidates and reducing similarity-matrix computation latency
Bug Fixes
Feedback model parsing:
  • Fixed model parsing failures in feedback processing
Model configuration:
  • Unified and simplified model-related configuration options
Embedder logs:
  • Fixed embedder logging issues
SDK get_task_status:
  • Fixed SDK get_task_status() parsing for legacy task-status responses
v2.0.24

MemOS Cloud

New Features
Cloud service:
  • Property Tree
  • Event Memory
  • Multi-view
Property Tree:
  • Supports template management, instance binding, field editing, and instance deletion
Event Memory:
  • Supports event extraction, retrieval, display, update, and deletion
Event Memory extraction configuration:
  • Added Event Memory extraction configuration with prompt editing, AI optimization, restore defaults, and debug runs
Agent multi-view:
  • Added Agent multi-view support for independent memory generation, update, and recall by user and Agent
Improvements
Memory list:
  • Added Property Tree and Event Memory display
Cloud Playground:
  • Updated core memory APIs for multi-view and supports scoping generation and retrieval by memory view
  • Memory retrieval supports mixed multi-view results, unified reranking, and related_id range filtering
  • Supports multi-user and multi-Agent conversations
  • Optimized querying memory-change results for async tasks
Call logs:
  • Added user and Agent information, and adapted change records for Property Tree and Event Memory
Bug Fixes
Cloud Playground:
  • Fixed inaccurate related project IDs returned by knowledge-base details
  • Fixed messages imported through the OpenMem API being incorrectly written into local chat history
v2.0.23

MemOS Cloud

Improvements
Preference memory model invocation:
  • Made preference-memory model calls compatible with Qwen3 hybrid-thinking models and disabled thinking by default

Plugin

New Features
OpenClaw local plugin:
  • Added local memory data export
  • Added automatic recall Phase 1 retrieval parameter configuration
  • Added Chinese keyword tokenization configuration
  • Added a dedicated model configuration for L3 abstraction
Improvements
OpenClaw local plugin:
  • Optimized the plugin startup and registration flow
  • Routed embedding inputs by usage
  • Reduced unnecessary background evolution calls in lightweight memory mode
  • Added Chinese README and usage documentation
Bug Fixes
OpenClaw local plugin:
  • Fixed CPU spikes caused by vector scans in large-data scenarios
  • Fixed recovery when SQLite native binding versions mismatch
  • Fixed stability issues around Hermes provider links, OpenAI-compatible endpoint probing, FTS query escaping, and plugin entry publishing
v2.0.22

MemOS Cloud

New Features
Preference memory extraction:
  • Supports independent model configuration
Bug Fixes
Preference memory extraction:
  • Tightened the preference memory prompt to fix over-extraction issues
  • Improved preference memory post-processing
Chat API compatibility:
  • Added string input support for the Chat API content field

Plugin

Bug Fixes
OpenClaw local plugin:
  • Fixed stability, recall accuracy, bridge process leaks, configuration compatibility, and local memory write issues in the OpenClaw local plugin flow
  • Added preference memory and automatic recall capabilities
v2.0.21

MemOS Cloud

Improvements
search context_format update:
  • Renamed the heuristic_routing mode in context_format to mixed, with behavior unchanged
v2.0.20

MemOS Cloud

Improvements
search context_format support:
  • memory: returns the extracted memory text with a shorter context, and is used by default
  • sources: returns the original sources corresponding to the memory, better suited for questions that need original details, time, quantities, or order
  • heuristic_routing: automatically selects memory or sources based on the query, preserving the benefits of the original text where possible while keeping the context length under control
Scheduler optimization:
  • Adjusted scheduler concurrency limits to avoid CPU, thread, and PolarDB contention from background jobs
  • Adjusted queue polling intervals to reduce idle polling and CPU usage
  • Added log and queue switches to reduce log writes on high-frequency search APIs
v2.0.19

MemOS Cloud

New Features
MemOS Cloud CLI Enhancements:
  • Added MemOS Cloud knowledge base APIs with support for up to 12 Agents
Improvements
Dashboard Experience:
  • Improved quick start display logic
  • Added one-click integration prompts

Documentation

Improvements
Documentation:
  • Added a conversational guide for integrating MemOS Cloud into Agents

Plugin

Improvements
Local Plugin:
  • Optimized the local plugin algorithm for domain-aware task handling and prompt injection
v2.0.17

MemOS Cloud

New Features
Dream Core Release:
  • Dream context nodes after fine-mode add
  • Context binding and summarization in Dream phase
  • Search can recall context nodes with a toggle
  • Dream diary fixes and context content
  • Dream registered in plugins with pipeline fixes
Time-sensitive Memory:
  • Batched LLM write-back for time-related information to reduce LLM calls
Bug Fixes
Skill Generation:
  • Skills now require at least 5 rounds of tool-call history before generation
  • Fixed scheduler task loss and Redis serialization issues
v2.0.16

MemOS Cloud

Improvements
Keyword Search Token Selection:
  • Dynamically adjusts token count during keyword search
Search-side Memory Version:
  • Added search-side memory version switch
  • Removed low-impact sidecar recall that hurt search performance
PolarDB Storage Optimization:
  • Horizontally partitioned user memory data with dual-write and read-switchover migration for hundred-million scale performance
Bug Fixes
Memory Version Fixes:
  • Fixed duplicate version updates from a single add
  • Fixed unit test issues

Documentation

Improvements
Documentation Updates:
  • Added open-source docs under docs/ and examples/README.md
  • OpenClaw Plugin docs improvements
  • Added CONTRIBUTING.md with contributor guidelines

Open Source

Improvements
Test Scripts:
  • Added tests/mem_feedback and tests/reranker
v2.0.15

MemOS Cloud

New Features
Time-sensitive Memory Version:
  • Extracts timespec and memory_form on write; time-aware version selection and rerank on search
Skill Upload:
  • Users can upload skills via the add API and retrieve them via search
Improvements
Keyword Search:
  • jieba extract_tags for Chinese queries (max 12 tokens)
  • Tokenizer/regex tokenization for English (max 12)
  • Mandatory user_name validation to prevent cross-user scans

Open Source

New Features
Skill Upload Support:
  • Build skill memories from downloadable skill links with retrieval support
v2.0.14

MemOS Cloud

Bug Fixes
Memory Version:
  • Fixed memory version applying across chunks from the same source text

Open Source

New Features
Plugin Framework:
  • Introduced a lightweight plugin framework with @hookable hooks and entry_points discovery
Improvements
Scheduler Optimization:
  • Cache caps, lock splitting, refill race fixes, stream cleanup, and Redis calls moved outside locks
Bug Fixes
PolarDB & MemReader:
  • Fixed PolarDB metadata nesting bug
  • Fixed memreader chunking bug
LLM JSON Parsing:
  • Fixed LLM JSON output parsing issue (#1526)
v2.0.13

MemOS Cloud

Improvements
Service Optimization:
  • Scheduling log level tuning
  • Structured queue logs
  • Key-path observability for submit -> dequeue -> dispatch
v2.0.12

MemOS Cloud

Improvements
Service Optimization:
  • Configurable minimum thread pool size
  • LLM-based memory version routing with improved skip recall
v2.0.11

Open Source

New Features
LLM & Search:
  • MiniMax LLM (#1291)
  • Health check API (#1248)
  • delete_memory filters (#1104)
  • Tavily search (#1357)
  • Dockerfile & Helm chart (#1293)
Improvements
Scheduler & API:
  • Thread pool and PolarDB optimizations
  • Better API validation errors
  • Consolidated APIs into server_api (#1344)
Bug Fixes
Database & Memory:
  • Neo4j pre-filter fix (#1359)
  • Nested metadata write fix (#1178)
  • Feedback archival fix (#1243)
MCP & API:
  • MCP add_memory format fix (#1275)
  • get_further_suggestion string input fix (#1218)
v2.0.10

MemOS Cloud

Improvements
PolarDB & MemReader:
  • PolarDB multi-filter query optimization
  • MemReader updated to 0.6B model with lower latency
Memory Version Service:
  • Memory version pluginization
  • NLI high availability
  • MemReader routing for memory version plugin
Scheduler:
  • Scheduler improvements for better memory usage
v2.0.9

MemOS Cloud

Improvements
Memory Version:
  • Feedback-compatible memory version
  • Improved independent-fact recovery during conflict resolution
Bug Fixes
Memory Version & Feedback:
  • Parameter validation and timestamp fixes
  • Fixed empty sources during feedback
v2.0.8

MemOS Cloud

New Features
Memory Version:
  • Automatic conflict/duplicate detection, merge, and archive on add (enabled in this release)
Improvements
Preference Memory Migration:
  • Preference memories migrated to the graph database
Memory Version Async:
  • Memory version fully async without impacting addMessage latency
Memory Search:
  • Reduced redundant get_by_metadata calls during search
Bug Fixes
Add & Search Fixes:
  • Fast-mode embedding fix for MultiModalStruct
  • Image memory parsing fix
  • Concurrent add merge ordering fix

Open Source

Improvements
Performance:
  • Full-text warmup
  • Semaphore-based concurrency limiting
  • Database log trimming
v2.0.7

MemOS Cloud

New Features
Memory Version:
  • Automatic conflict/duplicate detection, merge, and archive on add
Improvements
Relativity Defaults:
  • Default relativity threshold set to 0.45 for search and chat
Logging:
  • Adjusted log levels and suppressed noisy errors
Bug Fixes
Preference Embedding:
  • Fixed preference embedding recomputation to only process missing entries
v2.0.6

MemOS Cloud

New Features
Keyword Search:
  • Added keyword recall path while keeping embedding-based relativity
Chat Relativity:
  • Chat API accepts relativity to control retrieval threshold
Bug Fixes
API & Model Fixes:
  • Preference threshold field fix
  • get_memory filter logic fix
  • LLM extra_body / enable_thinking compatibility

Open Source

New Features
Multi-perspective Memory:
  • Each agent memory cube can maintain its own subjective perspective
Multi-perspective Demo:
  • Ao Tai Line hiking mini-game demo
v2.0.5

MemOS Cloud

New Features
Search Relativity:
  • Added relativity field (0~1) to filter recalled memories by relevance score
Improvements
Skills:
  • Local skill document storage with URLs
  • Richer skill generation from user history

Playground

Bug Fixes
Playground:
  • Fixed known UX issues and improved environment stability

Plugin

New Features
MindDock Cloud Skills:
  • Skill page entry in plugin UI
  • Real-time Skill prompt injection across chatbots

MCP

New Features
MCP Memory Deletion:
  • Delete intent triggers both deleteMemory and addFeedback

Open Source

New Features
Knowledge Base Search:
  • Dual-track raw text + memory retrieval
  • Context neighbor recall for long documents
Improvements
Search Pipeline Refactor:
  • Search -> Enhance -> Rerank -> Filter pipeline
  • Modular schedulers with Redis Streams fixes
v2.0.4

MemOS Cloud

New Features
Skill Memory:
  • Extract skill memories from conversation history with downloadable skill files
chat/completions:
  • OpenAI-compatible chat/completions endpoint for no-code platforms
Bug Fixes
Cloud Stability:
  • Fixed occasional add-memory stalls
  • Improved graph database efficiency

Playground

Bug Fixes
Playground:
  • Fixed system-busy error in Playground chat

Open Source

New Features
Conflict / Duplicate Detection:
  • Related-memory recall and NLI-based conflict detection on add
Improvements
Search Deduplication:
  • Reduced duplicate fact and preference recalls
v2.0.3

MemOS Cloud

Improvements
Multimodal Memory:
  • Image parsing now uses conversational context for better memory extraction
Knowledge Base:
  • JSON / Markdown / XML file support
  • knowledgebase_ids: all for cross-project retrieval
Bug Fixes
search/memory:
  • Fixed failures when search input text is too long

Documentation

New Features
Open Source Docs:
  • Documentation fixes and tips
  • Server router startup examples
  • API docs published on Apifox
v2.0.2

MemOS Cloud

Improvements
Knowledge Base Recall:
  • Better fine-grained document detail recall
Tool Memory:
  • Procedural tool-call experience
  • Tool schema compression (>50% token reduction)
Fact Memory Merge:
  • Merge and archive mechanism to reduce duplicate writes/recalls
get/memory:
  • Tool memory in responses
  • Filter-based memory listing for debugging
Bug Fixes
get/memory:
  • Fixed error when include_preference=False

Documentation

New Features
Knowledge QA Assistant Guide:
  • Added best-practice tutorial for building a MemOS knowledge-base assistant
v2.0.1

MemOS Cloud

New Features
Get Memory API:
  • List all user memories with pagination
Chat on Cloud:
  • Chat API with memory-aware replies
Improvements
Delete Memory API:
  • Delete any memory type without specifying user
Preference Feedback:
  • Feedback API now updates preference memories

Playground

New Features
Memory Deletion:
  • Manual memory deletion in Playground memory management

Open Source

Improvements
Search Dedup:
  • Optional dedup parameter (no/sim) for semantic deduplication
Bug Fixes
Scheduler & KV Cache:
  • Local scheduler without Redis config fix
  • KV cache compatibility fix
v2.0.0

MemOS Cloud

New Features
Knowledge Base:
  • Multi-dimensional knowledge bases from documents or URLs
  • Share knowledge bases across projects
Feedback & Deletion:
  • add_feedback for natural-language memory edits
  • Cloud delete memory API by memory id
Multimodal & Tool Memory:
  • Image message memory
  • Tool call trajectory memory
  • Document and URL parsing via MemReader
Improvements
Database Upgrade:
  • Connection management and batch insert improvements
  • Custom tag/info filters on Search
Scheduler Upgrade:
  • Redis Streams multi-queue fair scheduling
  • Pending task auto-recovery

MCP

New Features
MCP Delete & Feedback:
  • MCP supports delete_memory and add_feedback

Open Source

New Features
Chat API:
  • Streaming and non-streaming Chat APIs
Improvements
Lightweight Deployment:
  • Fast and full deployment modes
Bug Fixes
Scheduler Tasks:
  • Legacy scheduler compatibility fix
  • Memory update task logging fix
v1.1.3
New Features
Memory Add & Search:
  • Added async mode (plaintext & preference)
  • Preference Memory now supported
  • Reranker strategy suite
  • BM25 for TreeTextMemory
Scheduler:
  • Modularized API scheduler
  • Redis ORM optimized for history sync & hybrid search
Data & Infra:
  • PolarDB graph backend connection pool/timeout & fixes
  • Unified graph factory (Neo4j/PolarDB/Nebula)
  • Milvus interface & item optimizations
  • Enhanced logging pipeline
  • Nacos-based dynamic configuration
Evaluation:
  • PrefEval field standardization
  • LoCoMo/LongMemEval/PrefEval/PersonaMem evaluation upgrades
Improvements
Plaintext Memory:
  • Standardized preference fields
Framework:
  • Updated API routes
  • More robust error handling & context tracing
Bug Fixes
Scheduler:
  • Fixed query scheduling edge case
  • Corrected message schema inconsistencies
Plaintext Memory:
  • Graph/DB：corrected PolarDB issues
Framework:
  • Fixed SQLite user listing bug
v1.1.1
New Features
Cloud Service 1.0 Beta Release:
  • 🛠️ Ready-to-Use：Deploy directly via cloud API without complex setup
  • 🔄 Cross-Session Memory：Automatically retrieve user profiles, preferences, and behaviors for continuous personalization
  • 📖 Developer-Friendly：Comprehensive documentation and example code support
  • 🎁 Free Quota：Every developer can receive basic quota to explore
Enterprise Group Q&A bot:
  • Supports Q&A based on cloud service knowledge base
v1.0.1
New Features
Group Q&A Bot:
  • Launched group Q&A bot based on MemOS Cube
KV-Cache Performance Optimization:
  • Updated comparative experimental data for KV-Cache on different GPU deployment schemes
  • Optimized test benchmarks and statistical methods
Plaintext Memory Enhancement:
  • Added Reranker sorting functionality for plaintext memory
Playground Updates:
  • Updated Playground version with all the above new features
Improvements
Plaintext Memory Optimization:
  • Optimized plaintext memory hallucination issues
v1.0.0
New Features
Playground:
  • Expanded Playground features and algorithm performance.
MemCube Construction:
  • Added a text game demo based on the MemCube novel.
Extended Evaluation Set:
  • Added LongMemEval evaluation results and scripts.
Improvements
Plaintext Memory:
  • Integrated internet search with Bocha.
  • Added support for Nebula database.
  • Added contextual understanding for the tree-structured plaintext memory search interface.
Bug Fixes
KV Cache Concatenation:
  • Fixed the concat_cache method.
Plaintext Memory:
  • Fixed Nebula search-related issues.
v0.2.2
New Features
Explicit Memory:
  • Implemented internet search integration with Nebula database support
  • Enhanced contextual understanding for memory extraction
  • Deployed internet search interface integrated with memreader for web message processing
KV Cache:
  • Conducted KV Cache evaluation including LMCache comprehensive research and performance testing
  • Completed stress testing for MemOS vllm (v0.2.1) in specific environments and models
  • Refined ttft test data for preloaded KV Cache on Qwen2.5-72B-Instruct model and updated report
  • Completed initial research and design for high-ROI inference service system using domestic hardware
Memory Operation Model:
  • Completed model training evaluation and release
  • Released 4b, 1.7b and 0.6b models supporting memory extraction and integration
Improvements
Documentation:
  • Added English version for first three chapters of Cookbook
Memory Scheduling:
  • Performed code refactoring and functionality improvements
  • Refactored functional modules including monitor, dispatcher and retriever
  • Enhanced network logging functionality
  • Improved scheduler robustness with new exception-catching decorators
  • Implemented locking for shared resources
Development Environment:
  • Updated Docker configuration
  • Updated dim environment configuration
API Enhancements:
  • Added playground context support
  • Enhanced product API functionality
  • Rewrote query module
  • Implemented chat history feature
Bug Fixes
Data Parsing:
  • Fixed date parsing error
  • Fixed memos_w_scheduler example code issues
  • Fixed fine-grained search bug in Nebula graph database
  • Fixed metadata filter retrieval logic
System Integration:
  • Aligned MOSProduct._build_system_prompt signature with MOSCore
Explicit Memory:
  • Fixed general text memory processing logic
  • Fixed memreader component issues
v0.2.1
New Features
MemCube Features:
  • Added plaintext memory + KV Cache functionality with reasoning and decoding performance report
  • Completed development of interactive cube feature with full workflow support and embedding model switching
MemOS System:
  • Released MemOS Neo lightweight version with simplified architecture and core API modules
  • Added MCP support research and preparation work, expanding MCP capabilities
  • Created embedded Agent flow Pipeline documentation with Coze framework integration
Deployment & Environment:
  • Added Docker deployment support
  • Enhanced API layer with multi-model support, compatible with OpenAI/Qwen/DeepSeek and other mainstream models
  • Improved embedding model support
  • Added neo4j Community Edition/Nebular database support
  • Implemented multi-tenant architecture support within single database
Evaluation & Testing:
  • Adapted and evaluated memos API interface format, updated evaluation code
Documentation & Examples:
  • Added new Cookbook content
  • Included Mud game example
v0.2.0
New Features
Website Usability Updates:
  • Added documentation search functionality
  • Implemented Chinese/English documentation switching
  • Enhanced footer navigation links and page editing features
Memory Operator Model:
  • Introduced MemReader-4B small model for memory extraction operations
  • Enabled fully local deployment for restricted network environments
  • Achieved lower cost and faster memory operations with performance exceeding GPT-4o-mini
  • Fine-tuned based on Qwen3-4b with human and model annotation data using supervised fine-tuning
Cross-Platform Framework Adaptation:
  • Added Windows platform deployment support
  • Added Mac platform deployment support
  • Completed adaptation for Linux, Windows, and macOS mainstream operating systems
  • Passed testing on Ubuntu 20.04+/CentOS, Windows 10+/11, macOS 14 Ventura+ platforms
  • Supports stable operation of core modules (memory lifecycle management, MIP protocol, memory cache scheduling)
Playground Progress:
  • Completed engineering, front-end, and algorithm end-to-end connection, and bug fixing and optimization in progress