---
license: mit
tags:
- memory
- llm
- rag
- semantic-search
---

# 🧠 Mnemo v4.1 - SLM-Inspired Memory System

Memory augmentation library for LLMs based on the Semantic-Loop Memory architecture.

## Installation

```python
# Download mnemo.py from this repo
from mnemo import Mnemo

mnemo = Mnemo()
mnemo.add("User prefers Python for data analysis")
results = mnemo.search("programming language")
```

## Features

### Core
- **Three-Tier Memory**: Working (50 items) → Token Loops → Semantic (persistent)
- **Neural Links**: 8 link types with different creation thresholds and decay rates
- **Memory Utility Predictor**: Decides WHEN to inject memory (90% accuracy)
- **Self-Tuning**: Auto-adjusts thresholds based on feedback

### v4.1 New
- **Memory Decay**: Unused memories lose 1% quality per day
- **Auto-Pruning**: Removes stale memories (quality < 0.15, unused > 30 days)
- **Link Cleanup**: Orphaned links removed when memories are pruned

## Benchmark Results

| Test | Without Memory | With Mnemo | Improvement |
|------|----------------|------------|-------------|
| Novel retrieval | 5% | 85% | +80% |
| Code retrieval | 60% | 88% | +28% |
| ROS continuous learning | 25% | 75% | +50% |

## API

```python
mnemo = Mnemo()
mnemo.add(content, namespace="default")
results = mnemo.search(query, top_k=5)
context = mnemo.get_context(query, top_k=3)
should_inject = mnemo.should_inject(query)
mnemo.maintenance_cycle()
```

## Links

- [Demo](https://huggingface.co/spaces/AthelaPerk/mnemo)
- [MCP Server](https://huggingface.co/spaces/AthelaPerk/mnemo-mcp)