langchain-rag은(는) 무엇을 하나요?
검색 증강 생성(RAG) 시스템을 구축할 때 이 스킬을 호출하세요. 문서 로더, RecursiveCharacterTextSplitter, 임베딩(OpenAI), 벡터 스토어(Chroma, FAISS, Pinecone)를 다룹니다.
검색 증강 생성(RAG) 시스템을 구축할 때 사용하는 스킬입니다. 문서 로더, RecursiveCharacterTextSplitter, 임베딩(OpenAI), 벡터 스토어(Chroma, FAISS, Pinecone)를 다룹니다.
이 스킬은 LangChain을 기반으로 검색 증강 생성(RAG) 시스템을 구축하는 데 필요한 핵심 구성 요소를 제공합니다. 문서 로더를 통한 다양한 소스(로컬 파일, 웹 등)의 데이터 로딩, RecursiveCharacterTextSplitter를 사용한 효과적인 문서 분할, OpenAI 임베딩을 이용한 텍스트 임베딩 생성, 그리고 Chroma, FAISS, Pinecone과 같은 주요 벡터 스토어에 임베딩 저장 및 검색을 지원합니다. 개발자는 이 스킬을 호출하여 별도의 세부 구축 과정 없이도 RAG 파이프라인을 빠르게 프로토타이핑하고 구현할 수 있습니다. 주로 Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼에서 사용되며, SKILL.md에 정의된 지침에 따라 일관된 방식으로 RAG를 구현하도록 안내합니다.
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langchain-ragInstalled? Explore more 코딩 & 개발 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
검색 증강 생성(RAG) 시스템을 구축할 때 이 스킬을 호출하세요. 문서 로더, RecursiveCharacterTextSplitter, 임베딩(OpenAI), 벡터 스토어(Chroma, FAISS, Pinecone)를 다룹니다.
This repo contains 11 individual skills — each has its own dedicated page.
INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.
INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.
INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.
Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.
Send and manage iMessages via BlueBubbles, including attachments, tapbacks, edits, replies, and groups.
Control Eight Sleep pods (status, temperature, alarms, schedules).
BluOS CLI (blu) for discovery, playback, grouping, and volume.
Create, search, and manage Bear notes via grizzly CLI.
Capture frames or clips from RTSP/ONVIF cameras.
Search GIF providers with CLI/TUI, download results, and extract stills/sheets.