{"repo":"Technoculture/personal-graph","free":true,"listed":false,"github":"https://github.com/Technoculture/personal-graph","clone":"git clone https://github.com/Technoculture/personal-graph.git","description":"Simple Graph Memory for AI applications","language":"Jupyter Notebook","stars":105,"topics":["database","dspy","graph","sqlite3","vector-database"],"license":"MIT","category":"databases-storage","readme_excerpt":"Personal-Graph: Graph for building memory for AI applications Personal-Graph is a Python library for creating, managing, and querying knowledge graphs. It aims to help solve working and long-term memory challenges in AI systems, particularly Large Language Models (LLMs). Features - 🚀 Can Be Fast : Built on libsql, a high-performance SQLite engine in Rust - 👨 One DB per User : Integrate with Turso DB for private, user-specific knowledge graphs - 💬 Natural Language Interfaces : Natural language queries powered by Sqlite-vss and Instructor - 🤖 ML-Ready : Export data for machine learning libraries like Networkx and PyG - ✅ Supports local execution with Ollama LLMs and Embedding Models - ✅ Supports local db for both storing graph and embeddings WIP - Adding support for Columnar Database: DuckDB - Implementing Graph Neural Network Algorithms: TransE, TransE, Query2Box Installation Install Personal-Graph using pip: Usage Building a Working Memory for an AI In this example, we insert information about Alice and Bob into the knowledge graph. We then use the search method to retrieve relevant information based on the given queries. The retrieved information can be used as part of the AI's working memory to answer questions and provide context for further interactions. Building Long-Term Memory In this example, we store information about conversations with the user, including the date, topic, and a depth score. The depth score represents how meaningful the conversation was. When the","default_branch":null,"files":null,"tree":[],"storefront":"/r/Technoculture","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Technoculture/personal-graph/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."}