Persistent AI Memory provides the following core features:
- Persistent Storage: A SQLite database is used to keep records of AI's conversations, memories, and tool calls, ensuring that the data is available over time.
- semantic search: Semantic level searching of memories and conversations, not just keyword matching, is supported through LM Studio's embedding technology.
- real time monitoring: Utilize watchdog library to automatically monitor conversation file changes, e.g. capture ChatGPT exported conversation logs.
- Tool invocation log: Detailed documentation of the use of the Model Context Protocol (MCP) tool to support AI for self-reflection and analysis.
- Cross-platform supportCompatible with Windows, macOS and Linux systems, and adapted to a variety of development environments.
- VS Code Integration: Work seamlessly with Copilot in VS Code to improve development efficiency.
This answer comes from the articlePersistent AI Memory: Persistent Local Memory Storage for AI AssistantsThe
May not be reproduced without permission:AI productivity tools " What are the main features of Persistent AI Memory?
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