Persistent AI Memory FAQs

Question 1

Is Persistent AI Memory easy to install and configure?

Accepted Answer

Absolutely. It offers multiple straightforward installation methods, including one-command scripts for various operating systems (Linux/macOS, Windows), and works with sensible defaults right out-of-the-box, requiring zero initial configuration.

Question 2

Can I search my past AI conversations and memories?

Accepted Answer

Yes, it features advanced vector search capabilities using embeddings (e.g., via LM Studio) to perform semantic searches, allowing you to easily retrieve relevant information from your stored conversations and AI memories.

Question 3

What is Persistent AI Memory?

Accepted Answer

Persistent AI Memory is a comprehensive system that provides persistent, searchable local memory (SQLite-based) for AI assistants, LLMs, and GitHub Copilot, enhancing their long-term context and recall within development workflows.

Question 4

How does it store and organize AI memories?

Accepted Answer

It utilizes SQLite for durable storage across five specialized databases: Conversations (chat history), AI Memories (long-term data), Schedule (time-based events), VS Code Projects (context tracking), and MCP Tool Calls (interaction logs).

Question 5

Which AI platforms and models are compatible with Persistent AI Memory?

Accepted Answer

It offers multi-platform support for LM Studio, VS Code, Koboldcpp, and Ollama. Integration is facilitated through file monitoring, HTTP API, and the Model Context Protocol (MCP).

Persistent AI Memory

Persistent AI Memory

Características Principales

Casos de Uso

Características Principales

Casos de Uso