memU
Memory for 24/7 proactive agents like openclaw (moltbot, clawdbot).
Compare SDK and HTTP client backends for LLM integration in memU. Understand which backend best suits your needs for OpenAI compatible APIs.
How Query Rewriting and Intent Prediction Work in LLM-Based Retrieval: A Deep Dive into memUDiscover how memU optimizes LLM retrieval with query rewriting and intent prediction. Learn how XML prompts enhance memory lookup accuracy and direct answers.
How to Integrate memU with LangGraph for Agent WorkflowsIntegrate memU with LangGraph for agent workflows. Use MemULangGraphTools to persist retrieve long-term memories via MemoryService, enhancing your agent's capabilities today.
How memU's Continuous Learning Pipeline Processes Inputs in Real-TimeDiscover how memU's continuous learning pipeline processes inputs in real-time using an asynchronous workflow. Learn how data is converted into memory items without interrupting applications.
What Memory Types Does memU Support? A Complete Guide to Profile, Knowledge, Skill, and MoreExplore memU's six supported memory types profile event knowledge behavior skill and tool. Learn how LLM prompts extract XML data for seamless storage and embedding.
How to Configure memU Memory Service for Multi-User Scenarios with user_id ScopingConfigure memU for multi-user isolation using user_id scoping. Learn how to pass custom UserConfig and scope operations with the where filter for secure multi-user memory management.
How the LazyLLM Client Backend Integration Works in memU: A Complete Technical GuideLearn how the LazyLLM client backend integration works in memU. Discover asynchronous chat, vision, embedding, and speech-to-text operations with our technical guide.
SQLite vs PostgreSQL Backends for memU Deployment: Architecture and Performance ComparisonCompare SQLite and PostgreSQL for memU deployment. Discover SQLite's ease for local use and PostgreSQL's power for scalable, high-performance vector search.
How to Use Custom Embedding Models with Different Backends in memUDynamically use custom embedding models with OpenAI Doubao and more via HTTPEmbeddingClient in memU. Effortlessly switch backends for your AI projects.
How memU Handles Cross-References Between Memory Items (Like Symlinks)Discover how memU manages cross-references between memory items using lightweight symlinks and short IDs for efficient data linking. Learn more about this innovative approach.
Understanding Blob Storage Configuration and Resource Mounting in memULearn how memU's blob storage configuration mounts local paths for external assets and how LocalFS handles resource mounting for consistent downstream processing. Discover efficient asset management for your AI projects.
How to Integrate memU with OpenRouter for Multi-Provider LLM AccessIntegrate memU with OpenRouter to access multiple LLM providers. Configure an OpenRouter profile in MemoryService for seamless chat and embedding operations via HTTPLLMClient and OpenRouterLLMBackend.
Have a question about this repo?
These articles cover the highlights, but your codebase questions are specific. Give your agent direct access to the source. Share this with your agent to get started:
curl -s "https://instagit.com/install.md" 
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