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Private Ai
by
Twin Geeks
· GitHub ↗
· v1.0.2
· MIT-0
146
Downloads
0
Stars
2
Active Installs
3
Versions
Install in OpenClaw
/install private-ai
Description
Private AI — run LLMs, image generation, speech-to-text, and embeddings on your own hardware. Private AI keeps all data on your network. No cloud APIs, no te...
Usage Guidance
This skill is internally consistent with a private, on‑prem AI fleet, but an instruction file cannot prove the implementation. Before installing: (1) verify the pip package 'ollama-herd' source — inspect the project on GitHub or PyPI and pin to a specific release; (2) review the package code for any telemetry/callbacks if you require strict air‑gapped behavior; (3) run installs and model downloads in an isolated environment (VM/container) first; (4) confirm where models and logs are stored (~/.fleet-manager/) and ensure those paths are secured/encrypted if they will contain sensitive data; (5) control network exposure (bind to localhost or firewall port 11435) so the service is not unintentionally reachable from untrusted networks.
Capability Assessment
Purpose & Capability
Name/description (private, on‑prem inference, image gen, STT, embeddings) match the SKILL.md instructions which describe installing an on‑prem router ('herd', 'herd-node'), running a local HTTP API on port 11435, and downloading models. Declared binaries (curl/wget, optional python3/pip) are reasonable for these tasks and the declared configPaths (~/.fleet-manager/*) align with the stated local storage.
Instruction Scope
SKILL.md stays within the private‑AI scope: it instructs pip installing the package, running herd/herd-node, calling local endpoints (http://localhost:11435) and transferring models for air‑gapped setups. The doc repeatedly asserts 'no telemetry' and 'no cloud callbacks' but those claims are not verifiable from an instruction file alone — you'd need to inspect the package source before trusting this. Instructions do not ask for unrelated env vars or secret files.
Install Mechanism
There is no formal install spec in the registry (skill is instruction‑only), but SKILL.md tells users to 'pip install ollama-herd'. Installing via pip is a standard mechanism for Python packages; this is expected for this functionality. Because the registry did not provide an install artifact or pinned source, users should confirm the pip package's provenance and version (check PyPI/GitHub and pin versions) before running it.
Credentials
The skill does not request credentials or environment variables and only references local config paths under ~/.fleet-manager. That storage and the local HTTP endpoint are proportionate to running an on‑prem inference fleet. No unrelated secrets or system‑wide config paths are requested.
Persistence & Privilege
The skill is not set to always:true and is user‑invocable; it does not request elevated persistent platform privileges. It will run local services (herd) which listen on a port — that is expected for this functionality but you should control network exposure when deploying.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install private-ai - After installation, invoke the skill by name or use
/private-ai - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
Cross-platform support: macOS, Linux, and Windows. Updated OS metadata, descriptions, and hardware recommendations.
v1.0.1
- Updated branding and documentation to consistently use "Private AI" throughout for clarity and emphasis.
- Expanded description with multilingual and keyword-focused phrases (including Chinese and Spanish).
- Added and clarified compliance claims for HIPAA and GDPR, and organizational data control.
- Improved setup and usage instructions to reference "private AI" workflows and terminology.
- Enhanced examples and documentation to reinforce local, offline, and air-gapped operation.
v1.0.0
Private AI — First Release
- Introduces fully private, on-premise AI for LLMs, image generation, speech-to-text, and embeddings; no data ever leaves your hardware.
- No cloud APIs, telemetry, third-party access, or external network calls; compatible with air-gapped environments.
- Includes local fleet routing, model management, audit trails, and web dashboard accessible only on your local network.
- All state and logs stored locally; models require explicit download and run entirely offline once obtained.
- Designed for privacy, compliance, and data sovereignty (HIPAA-friendly, GDPR-ready).
Metadata
Frequently Asked Questions
What is Private Ai?
Private AI — run LLMs, image generation, speech-to-text, and embeddings on your own hardware. Private AI keeps all data on your network. No cloud APIs, no te... It is an AI Agent Skill for Claude Code / OpenClaw, with 146 downloads so far.
How do I install Private Ai?
Run "/install private-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Private Ai free?
Yes, Private Ai is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Private Ai support?
Private Ai is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, windows).
Who created Private Ai?
It is built and maintained by Twin Geeks (@twinsgeeks); the current version is v1.0.2.
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