Lemory: Local memory middleware for AI with knowledge graph

Lemory: Local AI Memory with Knowledge Graph Integration

Lemory is a middleware solution designed to enhance AI applications by providing robust local memory capabilities. It leverages your existing Obsidian vault, transforming it into a dynamic and searchable knowledge base for your AI agents. This approach ensures data privacy and control, allowing developers to build AI systems with a deep, personalized understanding without relying on external cloud services for core memory functions.

What Lemory Does

Lemory acts as an intermediary between your AI models and your personal knowledge base stored in Obsidian. It indexes your notes, documents, and any other content within your vault, making it accessible for AI agents to query and retrieve information. This process is facilitated by turning your unstructured data into a structured knowledge graph, enabling more sophisticated and context-aware memory retrieval.

Key Features

• Local Memory Storage: Utilizes your Obsidian vault for secure, private data storage.
• Knowledge Graph Generation: Automatically builds an interactive knowledge graph from your vault content.
• Keyless Search: Enables semantic and context-based search without requiring predefined keywords.
• AI Agent Integration: Designed to be integrated with AI agents and models for enhanced memory recall.
• Open Source: Available on GitHub, promoting transparency and community contribution.

Who Lemory is For

Lemory is an essential tool for AI developers and builders who prioritize data privacy and require sophisticated local memory management for their AI agents. It is particularly beneficial for those who already use Obsidian for personal knowledge management and wish to integrate this rich data source into their AI projects. Developers building applications such as personal AI assistants, research tools, or any system requiring deep contextual understanding will find Lemory invaluable.