Pause a LangGraph trip planner to collect traveler preferences
At a glance
A LangChain sample demonstrates parallel trip-input preparation, a join barrier, weather research, a human interrupt for preferences, and itinerary assembly using the same graph locally and when deployed. This workflow is listed under builder, langgraph, langsmith, human-in-the-loop, travel-planning.
LangChain's enrichment template searches and reads the web, extracts facts into a supplied schema, and checks completeness, with configurable models and tools in LangGraph Studio.
Open Deep Research provides a public LangGraph implementation with separate research, summarization, compression, and report roles, configurable search providers, MCP support, and an evaluation workflow.
Google's multimodal tutorial uses a LangGraph orchestrator to send files to specialist Gemini agents, gather their modality-specific findings, and synthesize whether a requested object is present.
Anthropic’s Building Effective Agents appendix highlights two proven patterns—support agents that pull data and take actions like refunds, and coding agents that iterate against tests—with clear success metrics and human review.