openscilab/memor
Reproducible Structured Memory for LLMs
This project helps developers manage and reproduce conversations with large language models (LLMs). It allows you to store detailed interaction histories, including prompts, responses, and technical metadata like token counts. The tool is for Python developers who are building or experimenting with LLM-powered applications and need to maintain context across different models or sessions.
Available on PyPI.
Use this if you are a developer working with LLMs and need a structured, reproducible way to log, review, and transfer conversation history between different models or sessions.
Not ideal if you are an end-user simply chatting with an LLM and do not need to programmatically manage conversation states or switch models.
Stars
57
Forks
4
Language
Python
License
MIT
Category
Last pushed
Jan 03, 2026
Commits (30d)
0
Dependencies
2
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