vidarbrekke

Ollama Memory Embeddings

AI Agentv1.0.4
By vidarbrekkeUpdated 2026-05-115 versions · latest released 2026-02-13ollama-memory-embeddings@clawhub_vidarbrekke/ollama-memory-embeddings
MemoryTool Use

According to AlphaMoat, as of 2026-09, Ollama Memory Embeddings has 3,025 downloads and 6 stars — ranked #3,712 of 5,078 AI skills overall, and #747 of 969 in AI Agent.

Installs
119
Downloads
3.0K
Stars
6
Overall Rank
#3,712
Top 74% overall · Top 78% in AI Agent
PlatformInstallsDownloadsStarsComments
ClawHub ↗903.0K5-
SkillHub ↗1193.0K6—

Platforms count differently and update at different times.

What this skill does

It can check whether Ollama is installed and reachable, let the user choose an embedding model, and optionally import an existing local embedding GGUF. It affects only memory-search embedding generation, not chat or completion routing.

Profile published 2026-10-29

What you can do with it

  • Configure Ollama as the embedding service for OpenClaw memory search
  • Choose an embedding model or import an existing local model file

When to use it

  • When you want OpenClaw memory search to use Ollama for embedding vectors

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Explain how to point OpenClaw memory search to Ollama embeddings and state which routing is unaffected; do not change configuration.

Monthly Trend

Downloads3.0K
1.6K2.3K3.1K2026-03 · Downloads 1.7K2026-05 · Downloads 2.2K2026-06 · Downloads 2.4K2026-07 · Downloads 2.7K2026-08 · Downloads 2.8K2026-09 · Downloads 3.0K26-0326-09
Stars6
5662026-03 · Stars 52026-05 · Stars 52026-06 · Stars 62026-07 · Stars 62026-08 · Stars 62026-09 · Stars 626-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

MonthDownloadsMoMStars
2026-093.0K—6
2026-082.8K+6.0%6
2026-072.7K+13.0%6
2026-062.4K+8.4%6
2026-052.2K—5
2026-031.7K—5

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

5.9 KB · ClawHub v1.0.4
---
slug: ollama-memory-embeddings
version: "1.0.4"
display_name: Ollama Memory Embeddings
displayName: Ollama Memory Embeddings
name: ollama-memory-embeddings
description: >
  Configure OpenClaw memory search to use Ollama as the embeddings server
  (OpenAI-compatible /v1/embeddings) instead of the built-in node-llama-cpp
  local GGUF loading. Includes interactive model selection and optional import
Show all (177 lines)
  of an existing local embedding GGUF into Ollama.
---

# Ollama Memory Embeddings

This skill configures OpenClaw memory search to use Ollama as the **embeddings
server** via its OpenAI-compatible `/v1/embeddings` endpoint.

> **Embeddings only.** This skill does not affect chat/completions routing —
> it only changes how memory-search embedding vectors are generated.

## What it does

- Installs this skill under `~/.openclaw/skills/ollama-memory-embeddings`
- Verifies Ollama is installed and reachable
- Lets the user choose an embedding model:
  - `embeddinggemma` (default — closest to OpenClaw built-in)
  - `nomic-embed-text` (strong quality, efficient)
  - `all-minilm` (smallest/fastest)
  - `mxbai-embed-large` (highest quality, larger)
- Optionally imports an existing local embedding GGUF into Ollama via
  `ollama create` (currently detects embeddinggemma, nomic-embed, all-minilm,
  and mxbai-embed GGUFs in known cache directories)
- Normalizes model names (handles `:latest` tag automatically)
- Updates `agents.defaults.memorySearch` in OpenClaw config (surgical — only
  touches keys this skill owns):
  - `provider = "openai"`
  - `model = <selected model>:latest`
  - `remote.baseUrl = "http://127.0.0.1:11434/v1/"`
  - `remote.apiKey = "ollama"` (required by client, ignored by Ollama)
- Performs a post-write config sanity check (reads back and validates JSON)
- Optionally restarts the OpenClaw gateway (with detection of available
  restart methods: `openclaw gateway restart`, systemd, launchd)
- Optional memory reindex during install (`openclaw memory index --force --verbose`)
- Runs a two-step verification:
  1. Checks model exists in `ollama list`
  2. Calls the embeddings endpoint and validates the response
- Adds an idempotent drift-enforcement command (`enforce.sh`)
- Adds optional config drift auto-healing watchdog (`watchdog.sh`)

## Install

```bash
bash ~/.openclaw/skills/ollama-memory-embeddings/install.sh
```

From this repository:

```bash
bash skills/ollama-memory-embeddings/install.sh
```

## Non-interactive usage

```bash
bash ~/.openclaw/skills/ollama-memory-embeddings/install.sh \
  --non-interactive \
  --model embeddinggemma \
  --reindex-memory auto
```

Bulletproof setup (install watchdog):

```bash
bash ~/.openclaw/skills/ollama-memory-embeddings/install.sh \
  --non-interactive \
  --model embeddinggemma \
  --reindex-memory auto \
  --install-watchdog \
  --watchdog-interval 60
```

> **Note:** In non-interactive mode, `--import-local-gguf auto` is treated as
> `no` (safe default). Use `--import-local-gguf yes` to explicitly opt in.

Options:

- `--model <id>`: one of `embeddinggemma`, `nomic-embed-text`, `all-minilm`, `mxbai-embed-large`
- `--import-local-gguf <auto|yes|no>`: default `no` (safer default; opt in with `yes`)
- `--import-model-name <name>`: default `embeddinggemma-local`
- `--restart-gateway <yes|no>`: default `no` (restart only when explicitly requested)
- `--skip-restart`: deprecated alias for `--restart-gateway no`
- `--openclaw-config <path>`: config file path override
- `--install-watchdog`: install launchd drift auto-heal watchdog (macOS)
- `--watchdog-interval <sec>`: watchdog interval (default 60)
- `--reindex-memory <auto|yes|no>`: memory rebuild mode (default `auto`)
- `--dry-run`: print planned changes and commands; make no modifications

## Verify

```bash
~/.openclaw/skills/ollama-memory-embeddings/verify.sh
```

Use `--verbose` to dump raw API response on failure:

```bash
~/.openclaw/skills/ollama-memory-embeddings/verify.sh --verbose
```

## Drift enforcement and auto-heal

Manually enforce desired state (safe to run repeatedly):

```bash
~/.openclaw/skills/ollama-memory-embeddings/enforce.sh \
  --model embeddinggemma \
  --openclaw-config ~/.openclaw/openclaw.json
```

Check for drift only:

```bash
~/.openclaw/skills/ollama-memory-embeddings/enforce.sh \
  --check-only \
  --model embeddinggemma
```

Run watchdog once (check + heal):

```bash
~/.openclaw/skills/ollama-memory-embeddings/watchdog.sh \
  --once \
  --model embeddinggemma
```

Install watchdog via launchd (macOS):

```bash
~/.openclaw/skills/ollama-memory-embeddings/watchdog.sh \
  --install-launchd \
  --model embeddinggemma \
  --interval-sec 60
```

## GGUF detection scope

The installer searches for embedding GGUFs matching these patterns in known
cache directories (`~/.node-llama-cpp/models`, `~/.cache/node-llama-cpp/models`,
`~/.cache/openclaw/models`):

- `*embeddinggemma*.gguf`
- `*nomic-embed*.gguf`
- `*all-minilm*.gguf`
- `*mxbai-embed*.gguf`

Other embedding GGUFs are not auto-detected. You can always import manually:

```bash
ollama create my-model -f /path/to/Modelfile
```

## Notes

- This does not modify OpenClaw package code. It only updates user config.
- A timestamped backup of config is written before changes.
- If no local GGUF exists, install proceeds by pulling the selected model from Ollama.
- Model names are normalized with `:latest` tag for consistent Ollama interaction.
- If embedding model changes, rebuild/re-embed existing memory vectors to avoid
  retrieval mismatch across incompatible vector spaces.
- With `--reindex-memory auto`, installer reindexes only when the effective
  embedding fingerprint changed (`provider`, `model`, `baseUrl`, `apiKey presence`).
- Drift checks require a non-empty apiKey but do not require a literal `"ollama"` value.
- Config backups are created only when a write is needed.
- Legacy schema fallback is supported: if `agents.defaults.memorySearch` is absent,
  the enforcer reads known legacy paths and mirrors writes to preserve compatibility.

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.