Prompt for human feedback in LangGraph HITL sample#324
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The graph_api human-in-the-loop sample previously auto-approved the draft and used a hardcoded placeholder response, so running it didn't actually involve a human. Now the draft is generated by an LLM, the runner prompts interactively at the terminal for approval or revision feedback, and the review node revises the draft with the LLM based on that feedback. Tests mock the chat model so they stay deterministic and offline.
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Summary
The
graph_apihuman-in-the-loop chatbot sample didn't actually involve a human when you ran it — it auto-approved the draft via signal and returned a hardcoded placeholder response. This change makes the sample live up to its name:generate_draftnow calls an LLM (claude-sonnet-4-6) instead of returning a canned string.run_workflow.pyprompts at the terminal forapproveor revision feedback, then signals the workflow.human_reviewregenerates the draft with the LLM incorporating the reviewer's notes.Test plan
uv run --group langgraph pytest tests/langgraph_plugin/human_in_the_loop_test.pypassesruff check --select Iandruff format --checkpassmypypasses on changed files