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Agent Skill · 研究检索

self-hosted-ai(自托管 AI)

self-hosted-ai 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

self-hosted-ai 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 25,079。

总安装 3,849周安装 162GitHub Stars 2下载 1,348核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.2

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:self-hosted-ai(自托管 AI)
来源仓库:https://github.com/twinsgeeks/self-hosted-ai
安装命令:
openclaw skills install self-hosted-ai
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 self-hosted-ai

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

运行自有LLM推理、图像生成与语音处理,无需云API与SaaS订阅。适用于数据不出内网、低延迟推理与高吞吐需求的场景。支持嵌入、TTS与视觉模型本地化运行。硬件选型需匹配模型规模,避免资源不足导致性能瓶颈。self-hosted-ai 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install self-hosted-ai;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

self-hosted-ai 怎么安装?

在终端执行 openclaw skills install self-hosted-ai。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

self-hosted-ai 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

self-hosted-ai 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

self-hosted-ai 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

self-hosted-ai 用的人多吗?

公开数据是累计安装 3,849 次,近一周安装 162 次,下载 1,348 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

self-hosted-ai 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
self-hosted-ai

自托管 AI · 本页

3,8492需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
self-hosted-ai
description
Self-hosted AI — run your own LLM inference, image generation, speech-to-text, and embeddings. No cloud APIs, no SaaS subscriptions, no data leaving your network. Self-hosted alternative to OpenAI, DALL-E, Whisper API, and cloud embedding services. Route across macOS, Linux, and Windows machines. 自托管AI本地推理平台。IA autoalojada sin dependencias en la nube.
version
1.0.2
homepage
https://github.com/geeks-accelerator/ollama-herd
metadata
{"openclaw":{"emoji":"server","requires":{"anyBins":["curl","wget"],"optionalBins":["python3","pip"]},"configPaths":["~/.fleet-manager/latency.db","~/.fleet-manager/logs/herd.jsonl"],"os":["darwin","linux","windows"]}}

Self-Hosted AI — Own Your Entire AI Stack

Stop paying per token. Stop sending data to cloud APIs. Run self-hosted LLMs, self-hosted image generation, self-hosted speech-to-text, and self-hosted embeddings on your own hardware. One self-hosted router makes all your devices act like one system.

What self-hosted AI replaces

Cloud serviceSelf-hosted replacementHow
OpenAI APISelf-hosted Llama 3.3, Qwen 3.5, DeepSeek-R1 via OllamaSame OpenAI SDK, swap the base URL
DALL-E / MidjourneySelf-hosted Stable Diffusion 3, Flux via mflux/DiffusionKitPOST /api/generate-image
Whisper APISelf-hosted Qwen3-ASR via MLXPOST /api/transcribe
OpenAI EmbeddingsSelf-hosted nomic-embed-text, mxbai-embed via OllamaPOST /api/embed

Same APIs. Same quality. Zero per-request costs. All data stays on your self-hosted machines.

Self-Hosted Setup

pip install ollama-herd    # Self-hosted AI router from PyPI
herd                       # start the self-hosted router
herd-node                  # run on each self-hosted machine — auto-discovers the router

No Docker. No Kubernetes. No config files. Self-hosted devices find each other automatically on your local network.

Self-Hosted LLM Inference

Drop-in self-hosted replacement for the OpenAI SDK:

from openai import OpenAI

# Self-hosted inference client — replaces OpenAI cloud
self_hosted_client = OpenAI(base_url="http://localhost:11435/v1", api_key="not-needed")

self_hosted_response = self_hosted_client.chat.completions.create(
    model="llama3.3:70b",  # self-hosted model, no cloud dependency
    messages=[{"role": "user", "content": "Analyze this contract for risks"}],
    stream=True,
)
for chunk in self_hosted_response:
    print(chunk.choices[0].delta.content or "", end="")

Self-hosted Ollama API

curl http://localhost:11435/api/chat -d '{
  "model": "deepseek-r1:70b",
  "messages": [{"role": "user", "content": "Explain self-hosted AI advantages over cloud APIs"}],
  "stream": false
}'

Self-Hosted Image Generation

Self-hosted replacement for DALL-E and Midjourney:

# Install self-hosted image backends on any node
uv tool install mflux           # Self-hosted Flux models (~7s)
uv tool install diffusionkit    # Self-hosted Stable Diffusion 3/3.5

# Generate on your self-hosted fleet
curl -o self_hosted_output.png http://localhost:11435/api/generate-image \
  -H "Content-Type: application/json" \
  -d '{"model": "z-image-turbo", "prompt": "self-hosted AI generating product mockup", "width": 1024, "height": 1024}'

Self-Hosted Speech-to-Text

Self-hosted replacement for Whisper API:

curl http://localhost:11435/api/transcribe \
  -F "file=@self_hosted_meeting.wav" \
  -F "model=qwen3-asr"

All self-hosted transcription stays on your network. No audio data sent to cloud services.

Self-Hosted Embeddings

Self-hosted replacement for OpenAI's embedding API:

curl http://localhost:11435/api/embed \
  -d '{"model": "nomic-embed-text", "input": "self-hosted document embedding for private RAG pipelines"}'

Self-Hosted Cost Comparison

ServiceCloud costSelf-hosted cost
GPT-4o (1M tokens/month)~$15-30/month$0 (self-hosted hardware you own)
DALL-E (1000 images/month)~$40/month$0 (self-hosted image gen)
Whisper API (10 hours audio/month)~$6/month$0 (self-hosted transcription)
OpenAI embeddings (1M tokens/month)~$0.10/month$0 (self-hosted embeddings)
Total~$60+/month$0/month self-hosted

After hardware investment, every self-hosted request is free forever. No rate limits, no usage caps, no surprise bills.

Self-Hosted Advantages

  • Self-hosted data sovereignty — prompts, images, audio, and documents never leave your network
  • Self-hosted throughput — your hardware, no rate limits
  • Self-hosted uptime — cloud API outages don't affect your self-hosted fleet
  • Self-hosted flexibility — switch models instantly, no vendor lock-in
  • Self-hosted compliance — HIPAA, GDPR, SOC2 — no third-party data processors
  • Self-hosted predictability — hardware depreciates, but never surprises you with a bill

Self-Hosted Fleet Routing

The self-hosted router scores each device on 7 signals and picks the best one for every request. Multiple self-hosted machines share the load automatically.

# Self-hosted fleet overview
curl -s http://localhost:11435/fleet/status | python3 -m json.tool

# Self-hosted health checks
curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool

# Self-hosted model recommendations for your hardware
curl -s http://localhost:11435/dashboard/api/recommendations | python3 -m json.tool

Self-hosted dashboard at http://localhost:11435/dashboard for visual monitoring of your entire self-hosted fleet.

Full self-hosted documentation

Contribute

Ollama Herd is open source (MIT). Self-hosted AI for everyone:

  • Star on GitHub — help others discover self-hosted AI
  • Open an issue — share your self-hosted setup
  • PRs welcome from humans and AI agents. CLAUDE.md gives full self-hosted context. 444 tests.

Self-Hosted Guardrails

  • No automatic downloads — all self-hosted model pulls require explicit user confirmation.
  • Self-hosted model deletion requires explicit user confirmation.
  • All self-hosted requests stay local — no data leaves your network. No telemetry, no analytics, no cloud callbacks.
  • Never delete or modify self-hosted files in ~/.fleet-manager/.
  • Your self-hosted fleet has zero cloud dependencies — works fully offline after initial model downloads.

平台分布

OpenClaw

88.68%
按下载量换算1,195

安全审计

VirusTotal

未展示

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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