Langgraph Fundamentals

langchain-ai/langchain-skills/config/skills/langgraph-fundamentals

Çoklu dosya

codingResmi

Resmi Sağlayıcı Skill'iView repo

INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.

Dosyalar3 dosya

SKILL.md165 satır

Loading editor…

Kurulum

Önerilen

Tek komut — ajanınız otomatik olarak devreye alır.

AI aracını seç

Kurulum komutunu görmek için yukarıdan bir AI aracı seçin.

veya

Manuel Kurulum

Daha fazla adım

Arşivi indirin ve dosyaları projenize manuel olarak ekleyin.

Skill detayları

Versiyonv1.0.0

YazarLangChain AI

Kategoricoding

Skill IDlangchain-ai/langchain-skills/config/skills/langgraph-fundamentals

Dosyalar3 dosya

İlgili skill'ler

Deep Agents CoreINVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.Deep Agents MemoryINVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.Deep Agents OrchestrationINVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.Deepagents Python QuickstartScaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.Deepagents Typescript QuickstartScaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.Ecosystem PrimerINVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.