human-in-the-loop-interrupt-resume/README.md

LangGraph Human-in-the-loop Demo

This project demonstrates how to create a LangGraph that pauses execution to ask the user for confirmation via a custom interrupt. The user is prompted in the console using questionary, and the graph resumes once the user provides an answer.

Features

• Custom interrupt node: Triggers a pause and sends a structured payload (type, question, options).
• Human-in-the-loop: The graph waits for user input before continuing.
• State persistence: Uses an in-memory checkpoint to resume execution after the interrupt.
• Simple console UI: Uses questionary for interactive prompts.

Requirements

• Python 3.10 or newer
• langgraph
• questionary

Install the dependencies with:

pip install -r requirements.txt

Running the Demo

python src/main.py

You will see a prompt:

Уверены, что хотите продолжить?
  ❯ approve
  ❯ reject

Select an option. After you choose, the script will print the final state, which includes the user's answer.

Project Structure

├── src/
│   └── main.py          # Main script with graph definition and run loop
├── requirements.txt    # Python dependencies
└── README.md            # This file

How It Works

1. Graph Definition
   The graph has a single node ask_user.

   • On first run, it triggers an interrupt with a payload containing a question and options.
   • After the user responds, the node receives the answer via the resume parameter and stores it in the state.

2. Interrupt Handling
   The main loop listens for chunks from graph.stream().

   • When an interrupt chunk is detected ("__interrupt__" key), it displays the question using questionary.select.
   • The chosen answer is sent back to the graph via Command(resume=answer).

3. Resuming Execution
   The graph resumes from the same node, now with the answer available in the state.
   The final state is printed to the console.

Feel free to extend the graph with more nodes or integrate it with other LangChain components.

Enjoy experimenting with LangGraph and human-in-the-loop workflows!