hx-lightrag-advisor

Guides LightRAG deployment and validation on HX-11 within HX Eco-System architecture rules.

Updated Sep 9, 2026
One-click install
npx skills add https://github.com/HX-Infratstructure/HX-Eco-System --skill hx-lightrag-advisor-hx-infratstructure
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hx-lightrag-advisor
Source: https://github.com/HX-Infratstructure/HX-Eco-System/tree/main/skills/lightrag/hx-lightrag-advisor
Command: npx skills add https://github.com/HX-Infratstructure/HX-Eco-System --skill hx-lightrag-advisor-hx-infratstructure

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? LightRAG work inside the HX Eco-System risks drifting from owner-approved architecture when generic tutorials, Docker examples, or community MCP packages are applied blindly. This Skill reconciles current official HKUDS/LightRAG guidance with HX authority so HX-11 planning, installation, configuration, validation, and troubleshooting stay compliant. ## Core Features & Use Cases - Authority-ordered decision making: Applies a strict precedence chain from owner instruction down to general model knowledge, and classifies every recommendation as ACCEPT, ADAPT, REJECT_FOR_HX, or OWNER_DECISION_REQUIRED. - Native deployment guidance: Steers HX-11 toward the official lightrag-hku[api] package, lightrag-server entrypoint, and systemd service instead of containers or hand-written FastAPI servers. - Architecture preservation: Enforces BGE-M3 at 1024 dimensions, HX-10 Qdrant as the vector service, and smoke-test-based validation from HX-5 CentCom. - Use Case: When asked to configure LightRAG storage backends on HX-11, the Skill checks whether KV, graph, and document-status backends are owner-pinned, and stops with OWNER_DECISION_REQUIRED rather than guessing from an upstream tutorial. ## Quick Start Ask the advisor how to plan the HX-11 LightRAG base installation and which storage and embedding choices are already approved.

Frequently Asked Questions about hx-lightrag-advisor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy LightRAG on a bare-metal Linux server with systemd?▼

Install the lightrag-hku[api] package in an isolated Python environment (Python 3.10 or later) and run the official lightrag-server entrypoint under a systemd unit. Pin the verified stable version in your build record rather than floating to latest.

What storage backends does LightRAG require?▼

LightRAG uses four logical storage roles: KV, vector, graph, and document status. Upstream supports multiple implementations per role, but in HX each choice must be owner-approved; Qdrant via QdrantVectorDBStorage is the expected vector service on HX-10.

Can I use Docker or Kubernetes to run LightRAG in this environment?▼

No. The HX deployment boundary mandates native Ubuntu Linux with systemd and rejects Docker, Podman, and Kubernetes unless the owner explicitly changes the standard. Container-based upstream examples are classified REJECT_FOR_HX.

What embedding dimension does BGE-M3 use with LightRAG?▼

BGE-M3 uses 1024 dimensions, matching both current upstream guidance and HX authority. Never mix vectors from different embedding models in one Qdrant collection; a model change requires a new collection and re-embedding.

Are community LightRAG MCP servers safe to install directly?▼

No. Community LightRAG skills, hooks, and MCP servers are reference-only in HX and must pass source review, credential and network inspection, and skill/MCP governance validation before any operational use.

Why should LightRAG validation not rely on the /health endpoint alone?▼

A health check does not prove retrieval works. HX BASE validation requires known-answer ingestion, processed-state confirmation, retrieval, a RAG answer containing the known token, cleanup verification, MCP companion gating, and reboot persistence evidence.