feat: solution for 'текстовая игра на основе llm + interrupt'
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node_modules/
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.env
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dist/
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build/
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*.log
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```
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# Interactive Choose‑Your‑Own‑Adventure
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This project demonstrates a simple text adventure game that uses an LLM (OpenAI) to generate a story opening, presents the user with three choices, and then continues the story based on the chosen option.
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The flow is built with **LangGraph** and uses **interrupts** to pause the graph and wait for user input in the console.
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## Features
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- Generates a short opening and three distinct choices using an LLM.
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- Pauses execution with an interrupt and presents the choices via a console menu.
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- Resumes the graph with the user’s selection and generates a short ending.
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- Stores the entire story (topic, opening, choice, ending) in a JSON file.
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## Prerequisites
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- Python 3.10+
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- An OpenAI API key. Set it in your environment:
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```bash
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export OPENAI_API_KEY="sk-..."
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```
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## Installation
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```bash
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# Clone the repository
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git clone https://github.com/yourusername/interactive-adventure.git
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cd interactive-adventure
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# Create a virtual environment (optional but recommended)
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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# Install dependencies
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pip install -r requirements.txt
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```
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## Usage
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```bash
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python src/main.py
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```
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You will be prompted to enter a topic for the adventure.
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After the LLM generates the opening and choices, a menu will appear.
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Select an option, and the story will continue with a short ending.
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The final story will be printed to the console and saved to `adventure_story.json`.
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## Project Structure
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```
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interactive-adventure/
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├── src/
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│ └── main.py # Main application logic
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├── requirements.txt # Python dependencies
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└── README.md # Documentation
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```
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## Customization
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- **LLM Model**: Change the `model` parameter in `ChatOpenAI` inside `src/main.py` to use a different model.
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- **Prompt Templates**: Modify the prompt strings in `generate_scene_and_choices` and `generate_ending` to tweak the story style.
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- **Number of Choices**: Adjust the parsing logic if you want more or fewer options.
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## License
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MIT License
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```
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```
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langgraph
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langchain==1.2.10
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langchain-openai==1.1.9
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questionary
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python-dotenv
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```
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+180
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```python
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#!/usr/bin/env python3
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"""
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Interactive choose-your-own-adventure using LangGraph, OpenAI LLM, and console interrupts.
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"""
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import os
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from typing import TypedDict, List
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import questionary
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from langgraph.graph import StateGraph
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.types import interrupt
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from langchain_openai import ChatOpenAI
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from langchain.prompts import PromptTemplate
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from langchain.schema import HumanMessage
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# Ensure OpenAI key is set
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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if not OPENAI_API_KEY:
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raise RuntimeError("Please set the OPENAI_API_KEY environment variable.")
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# -----------------------------
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# State definition
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# -----------------------------
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class AdventureState(TypedDict):
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topic: str
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opening: str
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choices: List[str]
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choice: str
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ending: str
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# -----------------------------
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# LLM setup
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# -----------------------------
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llm = ChatOpenAI(
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model="gpt-4o-mini",
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temperature=0.7,
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api_key=OPENAI_API_KEY,
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)
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# -----------------------------
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# Node: Generate opening and choices
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# -----------------------------
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def generate_scene_and_choices(state: AdventureState) -> AdventureState:
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topic = state["topic"]
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prompt = PromptTemplate(
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input_variables=["topic"],
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template=(
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"You are a creative storyteller. "
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"Topic: {topic}. "
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"Write a short opening (2–3 sentences) and exactly three distinct choices for the hero. "
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"Respond with the opening first, then a numbered list of the choices. "
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"Example format:\n"
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"Opening: ...\n"
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"1. ...\n"
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"2. ...\n"
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"3. ..."
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),
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)
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messages = [HumanMessage(content=prompt.format(topic=topic))]
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response = llm.invoke(messages)
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text = response.content.strip()
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# Parse opening and choices
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lines = [line.strip() for line in text.splitlines() if line.strip()]
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opening_line = lines[0]
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if opening_line.lower().startswith("opening:"):
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opening = opening_line[len("opening:"):].strip()
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else:
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opening = opening_line
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choices = []
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for line in lines[1:]:
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if len(line) >= 2 and line[0].isdigit() and line[1] in {".", ":"}:
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choice_text = line.split(" ", 1)[1].strip()
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choices.append(choice_text)
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else:
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choices.append(line)
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state["opening"] = opening
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state["choices"] = choices
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return state
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# -----------------------------
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# Node: Interrupt for user choice
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# -----------------------------
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def interrupt_choice(state: AdventureState) -> AdventureState:
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question = f"{state['opening']}\n\nWhat do you do?"
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payload = {
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"type": "choice",
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"question": question,
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"options": state["choices"],
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}
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# The interrupt will pause the graph and return a dict with "__interrupt__" key
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return interrupt(payload)
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# -----------------------------
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# Node: Generate ending
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# -----------------------------
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def generate_ending(state: AdventureState) -> AdventureState:
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prompt = PromptTemplate(
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input_variables=["opening", "choice"],
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template=(
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"You are a creative storyteller. "
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"Opening: {opening}\n"
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"The hero chose: {choice}\n"
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"Write a short ending (2–3 sentences) that concludes the story."
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),
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)
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messages = [HumanMessage(content=prompt.format(opening=state["opening"], choice=state["choice"]))]
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response = llm.invoke(messages)
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state["ending"] = response.content.strip()
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return state
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# -----------------------------
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# Build the graph
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# -----------------------------
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def build_graph() -> StateGraph[AdventureState]:
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graph = StateGraph(AdventureState)
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graph.add_node("generate_scene_and_choices", generate_scene_and_choices)
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graph.add_node("interrupt_choice", interrupt_choice)
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graph.add_node("generate_ending", generate_ending)
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graph.set_entry_point("generate_scene_and_choices")
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graph.add_edge("generate_scene_and_choices", "interrupt_choice")
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graph.add_edge("interrupt_choice", "generate_ending")
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graph.add_edge("generate_ending", "__end__")
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return graph
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# -----------------------------
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# Main execution
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# -----------------------------
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def main() -> None:
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topic = questionary.text("Enter a topic for your adventure:").ask()
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if not topic:
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print("No topic provided. Exiting.")
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return
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# Initial state
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state: AdventureState = {
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"topic": topic,
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"opening": "",
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"choices": [],
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"choice": "",
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"ending": "",
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}
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graph = build_graph()
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# Use an in-memory checkpoint to allow resuming after interrupt
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checkpoint = InMemorySaver()
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compiled = graph.compile(checkpointer=checkpoint)
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# Run the graph, handling interrupts manually
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config = {"configurable": {"thread_id": "adventure_thread"}}
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while True:
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result = compiled.run(state, config=config)
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# If an interrupt occurs, handle it
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if "__interrupt__" in result:
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interrupt_data = result["__interrupt__"]
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# Prompt user for choice
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choice = questionary.select(
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interrupt_data["question"],
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choices=interrupt_data["options"]
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).ask()
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if not choice:
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print("No choice selected. Exiting.")
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break
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state["choice"] = choice
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continue
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# If the graph has finished, print the ending
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if "ending" in result:
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print("\n" + result["ending"])
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break
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if __name__ == "__main__":
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main()
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```
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