Case
b93228ddc2
- Server recovery after 7-day outage - OpenClaw updated to 2026.2.6-3 - Fixed Proxmox noVNC (Wayland→X11, auto-login) - ChromaDB memory plugin live (LXC at 192.168.86.25) - Google Chrome installed, browser tool working - Built x-feed-scraper.sh for automated X feed capture - Sub-agent parallel analysis pipeline tested - Memory files updated
126 lines
3.7 KiB
Markdown
126 lines
3.7 KiB
Markdown
---
|
||
name: chromadb-memory
|
||
description: Long-term memory via ChromaDB with local Ollama embeddings. Auto-recall injects relevant context every turn. No cloud APIs required — fully self-hosted.
|
||
version: 1.0.0
|
||
author: matts
|
||
homepage: https://github.com/openclaw/openclaw
|
||
metadata:
|
||
openclaw:
|
||
emoji: "🧠"
|
||
requires:
|
||
bins: ["curl"]
|
||
category: "memory"
|
||
tags:
|
||
- memory
|
||
- chromadb
|
||
- ollama
|
||
- vector-search
|
||
- local
|
||
- self-hosted
|
||
- auto-recall
|
||
---
|
||
|
||
# ChromaDB Memory
|
||
|
||
Long-term semantic memory backed by ChromaDB and local Ollama embeddings. Zero cloud dependencies.
|
||
|
||
## What It Does
|
||
|
||
- **Auto-recall**: Before every agent turn, queries ChromaDB with the user's message and injects relevant context automatically
|
||
- **`chromadb_search` tool**: Manual semantic search over your ChromaDB collection
|
||
- **100% local**: Ollama (nomic-embed-text) for embeddings, ChromaDB for vector storage
|
||
|
||
## Prerequisites
|
||
|
||
1. **ChromaDB** running (Docker recommended):
|
||
```bash
|
||
docker run -d --name chromadb -p 8100:8000 chromadb/chroma:latest
|
||
```
|
||
|
||
2. **Ollama** with an embedding model:
|
||
```bash
|
||
ollama pull nomic-embed-text
|
||
```
|
||
|
||
3. **Indexed documents** in ChromaDB. Use any ChromaDB-compatible indexer to populate your collection.
|
||
|
||
## Install
|
||
|
||
```bash
|
||
# 1. Copy the plugin extension
|
||
mkdir -p ~/.openclaw/extensions/chromadb-memory
|
||
cp {baseDir}/scripts/index.ts ~/.openclaw/extensions/chromadb-memory/
|
||
cp {baseDir}/scripts/openclaw.plugin.json ~/.openclaw/extensions/chromadb-memory/
|
||
|
||
# 2. Get your collection ID
|
||
curl -s http://localhost:8100/api/v2/tenants/default_tenant/databases/default_database/collections | python3 -c "import json,sys; [print(f'{c[\"id\"]} {c[\"name\"]}') for c in json.load(sys.stdin)]"
|
||
|
||
# 3. Add to your OpenClaw config (~/.openclaw/openclaw.json):
|
||
```
|
||
|
||
```json
|
||
{
|
||
"plugins": {
|
||
"entries": {
|
||
"chromadb-memory": {
|
||
"enabled": true,
|
||
"config": {
|
||
"chromaUrl": "http://localhost:8100",
|
||
"collectionId": "YOUR_COLLECTION_ID",
|
||
"ollamaUrl": "http://localhost:11434",
|
||
"embeddingModel": "nomic-embed-text",
|
||
"autoRecall": true,
|
||
"autoRecallResults": 3,
|
||
"minScore": 0.5
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|
||
```
|
||
|
||
```bash
|
||
# 4. Restart the gateway
|
||
openclaw gateway restart
|
||
```
|
||
|
||
## Config Options
|
||
|
||
| Option | Default | Description |
|
||
|--------|---------|-------------|
|
||
| `chromaUrl` | `http://localhost:8100` | ChromaDB server URL |
|
||
| `collectionId` | *required* | ChromaDB collection UUID |
|
||
| `ollamaUrl` | `http://localhost:11434` | Ollama API URL |
|
||
| `embeddingModel` | `nomic-embed-text` | Ollama embedding model |
|
||
| `autoRecall` | `true` | Auto-inject relevant memories each turn |
|
||
| `autoRecallResults` | `3` | Max auto-recall results per turn |
|
||
| `minScore` | `0.5` | Minimum similarity score (0-1) |
|
||
|
||
## How It Works
|
||
|
||
1. You send a message
|
||
2. Plugin embeds your message via Ollama (nomic-embed-text, 768 dimensions)
|
||
3. Queries ChromaDB for nearest neighbors
|
||
4. Results above `minScore` are injected into the agent's context as `<chromadb-memories>`
|
||
5. Agent responds with relevant long-term context available
|
||
|
||
## Token Cost
|
||
|
||
Auto-recall adds ~275 tokens per turn worst case (3 results × ~300 chars + wrapper). Against a 200K+ context window, this is negligible.
|
||
|
||
## Tuning
|
||
|
||
- **Too noisy?** Raise `minScore` to 0.6 or 0.7
|
||
- **Missing context?** Lower `minScore` to 0.4, increase `autoRecallResults` to 5
|
||
- **Want manual only?** Set `autoRecall: false`, use `chromadb_search` tool
|
||
|
||
## Architecture
|
||
|
||
```
|
||
User Message → Ollama (embed) → ChromaDB (query) → Context Injection
|
||
↓
|
||
Agent Response
|
||
```
|
||
|
||
No OpenAI. No cloud. Your memories stay on your hardware.
|