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Empowers large language models to continuously learn, synthesize, and leverage knowledge through a lightweight, local-first knowledge management system.
소개
Provides a lightweight knowledge management service designed to enable Large Language Models (LLMs) to continuously learn, output, and utilize knowledge. This service helps individuals and small projects extract and integrate structured entities and their relationships from various unstructured texts, such as daily conversations and project notes, streamlining knowledge capture and organization. It facilitates building personalized knowledge assistants that can mimic your communication style and aid in tasks like project structuring and information processing. Inheriting concepts from Anthropic's memory-mcp, it focuses on transforming raw text into a personal knowledge graph of entities, relationships, and observations using LLM capabilities, ensuring flexible retrieval while maintaining data readability and local storage.
주요 기능
- Data Readability & Backup: Ensures raw data remains readable and provides simple backup functionalities.
- Flexible Retrieval: Supports searching by entity name, type, and observation keywords for efficient long-term memory access.
- Knowledge Fusion & Organization: Offers tools to rename entities and merge entity/relation types for refined knowledge management.
- Portable & Local-first: Operates on local files without requiring large online services, model, or service dependencies.
- Structured Knowledge Graph: Utilizes LLM capabilities to transform text into entities, relationships, and observations, building a personal knowledge graph.
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사용 사례
- Personalized Content Generation: Enables LLMs to understand personal thinking habits and networks for generating contextually relevant and style-consistent communications or documents.
- Personal Knowledge Extraction: Automatically extracts key knowledge points, people, and project information from documents or chat logs to build a customized knowledge base.
- Project Knowledge Base & Agent Optimization: Serves as a continuous knowledge repository for small teams and helps LLM Agents retain historical data to dynamically adjust processes and improve service quality.
