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ollama-memory-embeddingsOllama 记忆 embeddings

Agent Skill

用于搭建或维护带检索增强的 RAG 工作流,适合让 Agent 处理知识库问答、向量检索、来源引用和事实核查。它可以辅助整理数据接入、Embedding、向量库、召回参数和回答生成流程。使用时需要确认数据来源、更新频率、召回阈值和引用展示方式,避免把未命中的资料或过期内容包装成确定事实。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ollama-memory-embeddings(Ollama 记忆 embeddings)
来源仓库:https://github.com/vidarbrekke/ollama-memory-embeddings
安装命令:
openclaw skills install ollama-memory-embeddings
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ollama-memory-embeddings

简介

配置 OpenClaw 内存搜索以使用 Ollama 作为嵌入服务器(OpenAI 兼容的 /v1/embeddings),而不是内置的 node-llama-cpp 本地 GGUF 加载。包括交互式模型选择和可选地将现有本地嵌入 GGUF 导入 Ollama。

SKILL.md

slug
ollama-memory-embeddings
version
1.0.4
display_name
Ollama Memory Embeddings
displayName
Ollama Memory Embeddings
name
ollama-memory-embeddings
description
>

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

From this repository:

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

Non-interactive usage

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

Bulletproof setup (install watchdog):

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

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

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

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

Drift enforcement and auto-heal

Manually enforce desired state (safe to run repeatedly):

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

Check for drift only:

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

Run watchdog once (check + heal):

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

Install watchdog via launchd (macOS):

~/.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:

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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能力 5

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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按下载量换算13,297

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安装前确认

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来源信息

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