langchain-ai

langchain-ai/langgraphjs

Agent

LangGraph supports two types of memory essential for building conversational agents.

langchain-ai/langgraphjs

Agent

This page describes how to configure the chat model used by an agent.

langchain-ai/langgraphjs

Agent

A single agent might struggle if it needs to specialize in multiple domains or manage many tools. To tackle this, you can break your agent into smaller, independent agents and composing them into a multi-agent system.

langchain-ai/langgraphjs

Agent

LangGraph provides both low-level primitives and high-level prebuilt components for building agent-based applications. This section focuses on the prebuilt, reusable components designed to help you construct agentic systems quickly and reliably—without the need to implement orchestration, memory, or human feedback…

langchain-ai/langgraphjs

Agent

To share your project, simply open a Pull Request adding an entry for your package in our packages.yml file.

langchain-ai/langgraphjs

Agent

Agents support execution using either .invoke() for full responses, or .stream() for incremental streaming of the output. This section explains how to provide input, interpret output, enable streaming, and control execution limits.

langchain-ai/langgraphjs

Agent

Streaming is key to building responsive applications. There are a few types of data you’ll want to stream.

langchain-ai/langgraphjs

Agent

Tools are a way to encapsulate a function and its input schema in a way that can be passed to a chat model that supports tool calling. This allows the model to request the execution of this function with specific inputs.

langchain-ai/langgraphjs

Agent

You can use a prebuilt chat UI for interacting with any LangGraph agent through the Agent Chat UI. Using the deployed version is the quickest way to get started, and allows you to interact with both local and deployed graphs.

langchain-ai/langchain-skills

Plugin Claude Code

Plugin marketplace listing 1 plugin: langchain-skills.

langchain-ai/langchain-skills

Plugin Claude Code

Agent skills for building agents with LangChain, LangGraph, and Deep Agents.

langchain-ai/langchain-skills

Skill Claude CodeCodex

INVOKE THIS SKILL when building ANY Deep Agents application. Covers createdeepagent(), harness architecture, SKILL.md format, and configuration options.

langchain-ai/langchain-skills

Skill Claude CodeCodex

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

langchain-ai/langchain-skills

Skill Claude CodeCodex

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

langchain-ai/langchain-skills

Skill Claude CodeCodex

Scaffold 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.

langchain-ai/langchain-skills

Skill Claude CodeCodex

Scaffold 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.

langchain-ai/langchain-skills

Skill Claude CodeCodex

INVOKE 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…

langchain-ai/langchain-skills

Skill Claude CodeCodex

Inspect an agent repository and optional traces, interview the user, write reviewed Task Specs, build and audit Harbor tasks, and bootstrap reusable project World Knowledge Skills. Use for agent evals, benchmark design, Task generation, controlled Environments, synthetic data, Verifiers, Harbor runs, calibration, or…

langchain-ai/langchain-skills

Skill Claude CodeCodex

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…

langchain-ai/langchain-skills

Skill Claude CodeCodex

Create LangChain agents with createagent, define tools, and use middleware for human-in-the-loop and error handling.

langchain-ai/langchain-skills

Skill Claude CodeCodex

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.

langchain-ai/langchain-skills

Skill Claude CodeCodex

Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.

langchain-ai/langchain-skills

Skill Claude CodeCodex

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

langchain-ai/langchain-skills

Skill Claude CodeCodex

Scaffold a minimal local LangChain agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.