memor 0.4

Memor: A Python Library for Managing and Transferring Conversational Memory Across LLMs

Memor: A Python Library for Managing and Transferring Conversational Memory Across LLMs

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Overview

Memor is a library designed to help users manage the memory of their interactions with Large Language Models (LLMs). It enables users to seamlessly access and utilize the history of their conversations when prompting LLMs. That would create a more personalized and context-aware experience. Memor stands out by allowing users to transfer conversational history across different LLMs, eliminating cold starts where models don't have information about user and their preferences. Users can select specific parts of past interactions with one LLM and share them with another. By bridging the gap between isolated LLM instances, Memor revolutionizes the way users interact with AI by making transitions between models smoother.

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Installation

PyPI

• Check Python Packaging User Guide
• Run pip install memor==0.4

Source code

• Download Version 0.4 or Latest Source
• Run pip install .

Usage

Define your prompt and the response(s) to that; Memor will wrap it into a object with a templated representation. You can create a session by combining multiple prompts and responses, gradually building it up:

>>> from memor import Session, Prompt, Response, Role
>>> from memor import PresetPromptTemplate, RenderFormat
>>> response = Response(message="I am fine.", role=Role.ASSISTANT, temperature=0.9, score=0.9)
>>> prompt = Prompt(message="Hello, how are you?",
                    responses=[response],
                    role=Role.USER,
                    template=PresetPromptTemplate.INSTRUCTION1.PROMPT_RESPONSE_STANDARD)
>>> system_prompt = Prompt(message="You are a friendly and informative AI assistant designed to answer questions on a wide range of topics.",
                    role=Role.SYSTEM)
>>> session = Session(messages=[system_prompt, prompt])
>>> session.render(RenderFormat.OPENAI)

The rendered output will be a list of messages formatted for compatibility with the OpenAI API.

[{"content": "You are a friendly and informative AI assistant designed to answer questions on a wide range of topics.", "role": "system"},
 {"content": "I'm providing you with a history of a previous conversation. Please consider this context when responding to my new question.\n"
             "Prompt: Hello, how are you?\n"
             "Response: I am fine.",
  "role": "user"}]

Issues & bug reports

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• Please complete the issue template

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

Unreleased

0.4 - 2025-03-17

Added

• Session class __contains__ method
• Session class __getitem__ method
• Session class mask_message method
• Session class unmask_message method
• Session class masks attribute
• Response class __len__ method
• Prompt class __len__ method

Changed

• inference_time parameter added to Response class
• README.md updated
• Test system modified
• Python typing features added to all modules
• Prompt class default values updated
• Response class default values updated

0.3 - 2025-03-08

Added

• Session class __len__ method
• Session class __iter__ method
• Session class __add__ and __radd__ methods

Changed

• tokens parameter added to Prompt class
• tokens parameter added to Response class
• tokens parameter added to preset templates
• Prompt class modified
• Response class modified
• PromptTemplate class modified

0.2 - 2025-03-01

Added

• Session class

Changed

• Prompt class modified
• Response class modified
• PromptTemplate class modified
• README.md updated
• Test system modified

0.1 - 2025-02-12

Added

• Prompt class
• Response class
• PromptTemplate class
• PresetPromptTemplate class