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LangChain + Deep Agents Development Guide

This project uses skills that contain up-to-date patterns and working reference scripts.

CRITICAL: Invoke Skills BEFORE Writing Code

ALWAYS invoke the relevant skill first - skills have the correct imports, patterns, and scripts that prevent common mistakes.

Getting Started

  • framework-selection - Invoke when choosing between LangChain, LangGraph, and Deep Agents
  • langchain-dependencies - Invoke before installing packages or when resolving version issues (Python + TypeScript)

LangChain Skills

  • langchain-fundamentals - Invoke for create_agent, @tool decorator, middleware patterns
  • langchain-rag - Invoke for RAG pipelines, vector stores, embeddings
  • langchain-middleware - Invoke for structured output with Pydantic

LangGraph Skills

  • langgraph-fundamentals - Invoke for StateGraph, state schemas, edges, Command, Send, invoke, streaming, error handling
  • langgraph-persistence - Invoke for checkpointers, thread_id, time travel, memory, subgraph scoping
  • langgraph-human-in-the-loop - Invoke for interrupts, human review, error handling, approval workflows

Deep Agents Skills

  • deep-agents-core - Invoke for Deep Agents harness architecture
  • deep-agents-memory - Invoke for long-term memory with StoreBackend
  • deep-agents-orchestration - Invoke for multi-agent coordination

Environment Setup

Required environment variables:

OPENAI_API_KEY=<your-key>  # For OpenAI models
ANTHROPIC_API_KEY=<your-key>  # For Anthropic models