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Neo4j LLM Graph Builder로 그래프 RAG 컨텍스트 구축

제한된 문서 집합을 Neo4j 지식 그래프로 변환하고, 추출된 노드와 관계를 검사하며, 그래프 기반 RAG에 활용합니다.

Neo4j LLM Graph Builder로 그래프 RAG 컨텍스트 구축란 무엇인가요?

이 스킬은 LLM Graph Builder를 사용하여 문서 집합에서 Neo4j 지식 그래프를 구축하고, 이를 그래프 기반 RAG(Retrieval-Augmented Generation)에 활용하는 방법을 제공합니다. 사용자는 문서에서 추출된 엔티티와 관계를 검사하고, 그래프 구조를 기반으로 한 검색 증강 생성 파이프라인을 구성할 수 있습니다. 이 스킬은 Neo4j 데이터베이스 5.23 이상과 APOC 라이브러리가 필요하며, Python 3.12 백엔드 환경에서 실행됩니다. Neo4j Aura(무료 티어 포함)를 지원하고, Docker를 통한 배포도 가능합니다. 설치 과정은 requirements.txt를 통해 Python 패키지를 설치하고, .env 파일을 통해 LLM 제공자 자격 증명을 구성하는 간단한 단계로 이루어져 있습니다. 이 도구는 특히 대규모 문서 컬렉션에서 지식 그래프를 생성하고, 질문 응답 시스템의 정확성을 높이는 데 유용합니다.

지원 대상~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/build-graph-rag-context-with-neo4j-llm-graph-builder

즐겨 사용하는 AI에게 물어보기

이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

미리보기

스킬 README에서

Python

문서

Neo4j LLM Graph Builder로 그래프 RAG 컨텍스트 구축은(는) 무엇을 하나요?

제한된 문서 집합을 Neo4j 지식 그래프로 변환하고, 추출된 노드와 관계를 검사하며, 그래프 기반 RAG에 활용합니다.

필수 조건

APOC가 설치된 Neo4j 데이터베이스 5.23 이상, Python 3.12 백엔드, 구성된 LLM 제공자 자격 증명, 업스트림 README의 선택적 프론트엔드 및 Docker 배포 경로.

설치

환경에 맞는 업스트림 설치 또는 설정 경로를 사용하십시오:

  • pip install -r requirements.txt -c constraints.txt

업스트림의 요구 사항 및 주의 사항:

  • Python
  • Python 3.12 이상 (로컬/분리형 백엔드 배포용)
  • Neo4j Desktop을 사용하는 경우 백엔드와 프론트엔드를 별도로 배포해야 합니다 (docker-compose는 지원되지 않음).

기본 사용법 또는 시작하기 참고 사항:

문서

출처

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.

ACF Custom Fields REST Exposer

Exposes Advanced Custom Fields data through the WordPress REST API using register_rest_field and acf_format_value. Handles repeater fields, flexible content layouts, and gallery fields with proper serialization.

ACF Extended for Advanced Custom Fields Workflows

An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.

ACF to Gutenberg Block Migrator

Converts Advanced Custom Fields field groups into native Gutenberg blocks using the ACF Block API v2 and @wordpress/scripts build pipeline. Maps ACF repeaters, groups, and flexible content to InnerBlocks and block attributes with server-side rendering via acf_register_block_type().

Activepieces Open Source Workflow Automation

Activepieces is an open-source, self-hostable workflow automation platform with 200+ integrations. It provides a visual builder for creating automated workflows and exposes all its connectors as MCP servers for AI agent use.

ActivityWatch Cross-Platform Automated Time Tracker and Producti

ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.

act Local GitHub Actions Runner

act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.

Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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