langchain-rag 是做什麼的？
建立任何檢索增強生成（RAG）系統時請使用此技能。涵蓋文檔載入器、遞迴字元文字分割器、嵌入（OpenAI）以及向量資料庫（Chroma、FAISS、Pinecone）。
建立任何檢索增強生成（RAG）系統時請使用此技能。涵蓋文檔載入器、遞迴字元文字分割器、嵌入（OpenAI）以及向量資料庫（Chroma、FAISS、Pinecone）。
langchain-ai/langchain-rag 是一個專為開發檢索增強生成（RAG）系統而設計的 AI 代理技能。它能協助處理 RAG 流程的核心元件：從多種來源載入文檔、使用遞迴字元文字分割器將文檔切成片段、透過 OpenAI 嵌入模型將文字轉換為向量表示，並將結果儲存於高效的向量資料庫（如 Chroma、FAISS 或 Pinecone）中。此技能支援 Claude Code、Cursor 和 Codex 等平台，讓開發者能快速整合 LangChain 的 RAG 功能，無需從頭構建。其使用方式包含載入文檔、分割文字、生成嵌入、建立向量儲存庫以及查詢相似片段等步驟，大幅簡化 RAG 系統的實作流程。
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langchain-ragInstalled? Explore more 程式設計與開發 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
建立任何檢索增強生成（RAG）系統時請使用此技能。涵蓋文檔載入器、遞迴字元文字分割器、嵌入（OpenAI）以及向量資料庫（Chroma、FAISS、Pinecone）。
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.