Name: Chromadb Memory Pub
Availability: InStock
Author: msensintaffar

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

ChromaDB running (Docker recommended):

docker run -d --name chromadb -p 8100:8000 chromadb/chroma:latest

Ollama with an embedding model:

ollama pull nomic-embed-text

Indexed documents in ChromaDB. Use any ChromaDB-compatible indexer to populate your collection.

Install

# 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. Add to your OpenClaw config (~/.openclaw/openclaw.json):

{
  "plugins": {
    "entries": {
      "chromadb-memory": {
        "enabled": true,
        "config": {
          "chromaUrl": "http://localhost:8100",
          "collectionName": "longterm_memory",
          "ollamaUrl": "http://localhost:11434",
          "embeddingModel": "nomic-embed-text",
          "autoRecall": true,
          "autoRecallResults": 3,
          "minScore": 0.5
        }
      }
    }
  }
}

# 4. Restart the gateway
openclaw gateway restart

Config Options

Option	Default	Description
`chromaUrl`	`http://localhost:8100`	ChromaDB server URL
`collectionName`	`longterm_memory`	Collection name (auto-resolves UUID, survives reindexing)
`collectionId`	—	Collection UUID (optional fallback)
`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

You send a message
Plugin embeds your message via Ollama (nomic-embed-text, 768 dimensions)
Queries ChromaDB for nearest neighbors
Results above
```
minScore
```
are injected into the agent's context as
```
<chromadb-memories>
```
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.

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ChromaDB Memory

What It Does

Prerequisites

Install

2. Add to your OpenClaw config (~/.openclaw/openclaw.json):

Config Options

How It Works

Token Cost

Tuning

Architecture

Quick Start

Manual Installation

TEAR & SHARE

Tags

Multi-Agent Patterns

Memory Systems Design

Context Degradation Detection

Context Optimization

Tool Design for Agents

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