Memory for agentic AI. Inspired by the brain. Built for the future.
Project description
🧠 Mnemos
Memory for Agentic AI. Inspired by minds. Engineered for longevity.
Mnemos is a lightweight, extensible memory system for agentic AI.
It helps agents remember what matters — not just store data.
✨ What is Mnemos?
Mnemos is a memory-as-a-service toolkit that enables developers to add persistent, structured, and coherent memory to AI agents and LLM apps.
Think of it like a hippocampus for your agents:
- Clean API for memory storage and recall
- Optimized for simplicity and developer experience
- Designed for extensibility with pluggable storage backends
🧪 Example Usage
import mnemos
# Store a memory
mnemos.remember("The user prefers minimalist interfaces.", tags=["ui", "preference"])
# Recall related memories
results = mnemos.recall("user interface")
print(results[0].text) # "The user prefers minimalist interfaces."
🧱 Key Features
- 🧠 Simple, intuitive API with
remember()andrecall() - 🔍 Basic text and tag-based search
- 🧪 Fully typed with Python type hints
- 🧰 Extensible storage backends (in-memory included)
📦 Installation
Install with pip:
pip install mnemos
🧪 Running Tests
pytest tests/
🌱 Project Status
Mnemos is in early development. This initial version provides an in-memory implementation with a clean API. Future versions will add persistent storage and more advanced search capabilities.
Contributions, ideas, and feedback are welcome at github.com/iteebz/mnemos
📜 License
MIT
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