momex 0.1.1

Memory system for AI agents with Structured RAG, built on TypeAgent

Fork Changes

I've been keeping an eye on this repo for a while. I'm also personally interested in personal assistant agents, and I've been trying to find best practices for memory. Structured RAG is a great design, but since this is an experimental project, the feature set isn't complete yet. So I forked the original repo and added more features, aiming to make it work for more general use cases and projects.

This fork adds Momex - a high-level API wrapper for TypeAgent's Structured RAG.

What's New

• Agent API - High-level chat interface with automatic memory management
• Short-term memory - Session-based conversation history with persistence
• Long-term memory - Structured RAG with entity/action/topic extraction
• Multi-tenant support with hierarchical collections (user:xiaoyuzhang)
• PostgreSQL backend with pgvector for production deployment

Installation

pip install momex

Quick Start

import asyncio
from momex import Agent, MomexConfig, LLMConfig

async def main():
    config = MomexConfig(
        llm=LLMConfig(
            provider="openai",
            model="gpt-4o",
            api_key="sk-xxx",
        ),
    )

    agent = Agent("user:xiaoyuzhang", config)

    r = await agent.chat("My name is Xiaoyu, I love Python")
    print(r.content)

    r = await agent.chat("What's my name?")
    print(r.content)  # "Your name is Xiaoyu"

asyncio.run(main())

Two API Levels

Level	API	Description
Level 1	Agent	Chat API with automatic memory (recommended)
Level 2	Memory	Manual control for custom agents

See docs/momex.md for full documentation.

---

Python package 'typeagent'

This is an experimental prototype

Working toward a shared understanding of the MVP for structured RAG.

This is sample code

This is an in-progress project aiming at a Pythonic translation of TypeAgent KnowPro and a few related packages from TypeScript to Python.

Warning

This library will send its input to an LLM hosted by a third party. Don't use it to index confidential information.

Documentation

• Found in the docs directory
• Quick install: pip install typeagent
• Download the PyBay '25 PowerPoint slides
• Download the PyBay '25 slides as PDF
• Watch the PyBay '25 video

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.