{"repo":"RichmondAlake/memorizz","free":true,"listed":false,"github":"https://github.com/RichmondAlake/memorizz","clone":"git clone https://github.com/RichmondAlake/memorizz.git","description":"MemoRizz: A Python library serving as a memory layer for AI applications. Leverages popular databases and storage solutions to optimize memory usage. Provides utility classes and methods for efficient data management.","language":"Python","stars":759,"topics":["artificial-intelligence","data-management","python","semantic-search","mongodb","ai","oracle","oracle-database"],"license":null,"category":"ai-agents","readme_excerpt":"Memorizz Experimental software Memorizz is an educational/experimental framework. APIs may change and the project has not undergone security hardening for production workloads. Memorizz is a Python framework for building memory-augmented AI agents. It provides: - multiple memory systems (episodic, semantic, procedural, short-term, shared) - pluggable storage providers (Oracle, MongoDB, filesystem) - agent builders and application modes ( assistant , workflow , deep research ) - scheduled automations (cron, interval, one-shot) with optional WhatsApp delivery - optional internet access, governed browser control, sandbox code execution, skills marketplace, and local web UI - first-class MCP connectivity over stdio, Streamable HTTP, and SSE, including OAuth, encrypted credentials, resources, prompts, and tool approval policy - an interactive, Claude-Code-style terminal CLI ( memorizz ) with persistent memory — see CLI Key Capabilities - Persistent memory across sessions and conversations - Semantic retrieval with embeddings + vector search - Knowledge base with file/folder ingestion ( .pdf , .md , .txt , .csv , .json , …) and configurable chunking ( fixed / sentence / paragraph / semantic / custom). Same extractor registry powers the SDK and the local UI's drag-and-drop uploader; see long term/semantic/README.md . - Entity memory tools for profile-style facts ( entity memory lookup / entity memory upsert ) - Tool calling with automatic function registration - Semantic cache to re","default_branch":null,"files":null,"tree":[],"storefront":"/r/RichmondAlake","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/RichmondAlake/memorizz/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}