Voice
Moltbot Memory Local
By Privacy-first local memory plugin for Moltbot: SQLite + local embeddings, zero cloud calls
Install
npm install moltbot-memory-localConfiguration Example
{
"plugins": {
"slots": {
"memory": "moltbot-memory-local"
},
"entries": {
"moltbot-memory-local": {
"enabled": true,
"config": {
"dataDir": "~/.moltbot/memory",
"maxMemories": 10000,
"embeddingModel": "Xenova/all-MiniLM-L6-v2",
"enableEmbeddings": true
}
}
}
}
}README
# moltbot-memory-local
<p align="center">
<img src="https://raw.githubusercontent.com/48Nauts-Operator/moltbot-memory-local/main/assets/privacy-crab-small.png" alt="Privacy Crab" width="400">
</p>
> Privacy-first local memory plugin for Moltbot
**One plugin. Two search modes. Zero cloud calls.**
Combines SQLite (structured/temporal) + LanceDB (semantic/vector) into a single unified memory system. Everything runs locally on your machine.
## Why This Exists
Most AI memory plugins send your data to cloud APIs for embedding. Your "local" memory phones home before storing anything.
This plugin fixes that:
- **SQLite** for structured storage, timestamps, full-text search
- **LanceDB + local embeddings** for semantic similarity search
- **Smart routing** automatically picks the right backend
- **100% local** — no cloud calls, ever
## Installation
```bash
npm install moltbot-memory-local
```
## Configuration
```json
{
"plugins": {
"slots": {
"memory": "moltbot-memory-local"
},
"entries": {
"moltbot-memory-local": {
"enabled": true,
"config": {
"dataDir": "~/.moltbot/memory",
"maxMemories": 10000,
"embeddingModel": "Xenova/all-MiniLM-L6-v2",
"enableEmbeddings": true
}
}
}
}
}
```
### Options
| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `dataDir` | string | `~/.moltbot/memory` | Data directory |
| `maxMemories` | number | `10000` | Max before pruning |
| `embeddingModel` | string | `Xenova/all-MiniLM-L6-v2` | Local embedding model |
| `enableEmbeddings` | boolean | `true` | Enable semantic search |
| `defaultImportance` | number | `0.7` | Default memory importance |
## How It Works
### Automatic Query Routing
The plugin detects query type and routes automatically:
```
"What did you do Thursday at 14:04?" → SQLite (temporal)
"Find conversations about dark mode" → Vector search (semantic)
"What is my email address?" → SQLite (exact lookup)
"Similar ideas to X" → Vector search (semantic)
```
### Manual Mode Selection
Override automatic routing:
```typescript
// Force semantic search
await memory_recall({ query: "...", mode: "semantic" });
// Force structured search
await memory_recall({ query: "...", mode: "structured" });
// Let plugin decide (default)
await memory_recall({ query: "...", mode: "auto" });
```
## Usage
### Store
```typescript
await memory_store({
text: "User prefers dark mode in all applications",
category: "preference", // preference|fact|decision|entity|conversation|other
importance: 0.9 // 0-1, higher = kept longer
});
```
Memories are stored in both SQLite (full data) and LanceDB (vector for semantic search).
### Recall
```typescript
// Temporal query → routed to SQLite
const thursdayMemories = await memory_recall({
query: "what happened last Thursday",
limit: 5
});
// Semantic query → routed to vector search
const similarMemories = await memory_recall({
query: "display and theme preferences",
limit: 5
});
// With filters
const decisions = await memory_recall({
query: "project architecture",
category: "decision",
dateFrom: "2025-01-01"
});
```
### Forget (GDPR)
```typescript
// By ID
await memory_forget({ memoryId: "uuid-here" });
// By query (deletes from both SQLite and vectors)
await memory_forget({ query: "sensitive information" });
```
## Architecture
```
┌─────────────────────────────────────────────────────────────┐
│ moltbot-memory-local │
├─────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────────┐ ┌──────────────────┐ │
│ │ SQLite │ │ LanceDB │ │
│ │ ────────────── │ │ ────────────── │ │
│ │ Full text │ │ Vector store │ │
│ │ Timestamps │ │ Local embeddings│ │
│ │ Metadata │ │ Semantic search │ │
│ │ Categories │ │ │ │
│ └────────┬─────────┘ └────────┬─────────┘ │
│ │ │ │
│ └──────────┬──────────────┘ │
│ │ │
│ ┌────────▼────────┐ │
│ │ Query Router │ │
│ │ ────────────── │ │
│ │ "Thursday?" → │ → SQLite │
│ │ "Similar?" → │ → Vectors │
│ └─────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────┘
❌ No cloud ✅ 100% Local ✅ Your data
```
## Data Storage
```
~/.moltbot/memory/
├── memories.db # SQLite database (structured data)
└── vectors/ # LanceDB vector store (embeddings)
```
## Embedding Models
Default: `Xenova/all-MiniLM-L6-v2` (384 dimensions, ~23MB)
Alternatives:
- `Xenova/e5-small-v2` — Better quality, similar size
- `Xenova/all-MiniLM-L12-v2` — More accurate, larger
Models download automatically on first use.
## Fallback Behavior
- If LanceDB fails → falls back to SQLite-only search
- If embeddings disabled → SQLite full-text search only
- If embedding fails for a memory → stored in SQLite, skipped in vectors
## License
MIT © Andre Wolke
## Links
- [Documentation](https://gist.github.com/48Nauts-Operator/0c72802380ea03ec6b87c8ca8ff21b29)
- [Moltbot](https://github.com/moltbot/moltbot)
- [21nauts](https://21nauts.com)
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