Changelog

All notable changes to MemOS will be documented here
GitHubRelease Notes
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
  • { "Added major code categories": "schemas and utils" }
  • 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