# Text Adventure Game with LLM and Interrupt

## Overview
This repository implements a **text‑based choose‑your‑story** game that demonstrates how to combine LangGraph, LangChain and the BroJS LLM for interactive storytelling.

The key concepts showcased are:
- A stateful graph that pauses for user input via `interrupt()`.
- Two LLM calls: one generates an opening paragraph with three actions; the second writes a short ending based on the chosen action.
- Human‑in‑the‑loop (HITL) using `questionary` to present a menu and capture the user's choice.

The game is intentionally lightweight so you can run it locally with minimal setup.

## File Structure
| Path | Purpose |
|------|---------|
| `main.py` | Entry point – defines state, nodes, graph and runs the game. |
| `requirements.txt` | Exact dependencies with pinned versions. |
| `README.md` | Project description, installation and usage instructions. |

## Installation
```bash
# Create a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate   # On Windows use `.venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt
```

**Important:** The BroJS LLM requires an API key. Export it as:
```bash
export JOURNAL_MCP_PAT=your_api_key_here
```
or set it in your IDE’s environment variables.

## Running the Game
```bash
python main.py
```
You will be prompted to enter a theme for the adventure (e.g., "a lonely astronaut on a deserted moon"). The game proceeds as follows:
1. **Intro generation** – The LLM writes a short opening paragraph and three numbered actions.
2. **Interrupt** – The graph pauses, displaying the intro and asking you to choose an action via a console menu.
3. **Ending generation** – After you select an option, the LLM produces a concluding paragraph that reflects your choice.
4. **Final output** – The complete story (intro, chosen action, ending) is printed to the console.

## Customization
- **Change the theme**: Edit `main.py` or provide a different prompt when running.
- **Adjust LLM temperature**: Modify the `temperature` parameter in the `ChatOpenAI` initialization.
- **Add more options**: Update the prompt to request more than three actions and adjust parsing logic accordingly.

## Troubleshooting
| Symptom | Likely Cause | Fix |
|---------|--------------|-----|
| No output after running | API key missing or invalid | Ensure `JOURNAL_MCP_PAT` is set correctly. |
| LLM returns unexpected format | Prompt not strict enough | Tighten the prompt to enforce a predictable response structure. |
| Errors in parsing options | Options list contains extra text | Verify that each option line starts with "1)" / "2)" / "3)".

## License & Credits
This project is released under the MIT license. The LLM model used is provided by BroJS and is subject to their terms of service.