https://github.com/hmasdev/langchain_werewolf
A CUI-based simple werewolf game with `langchain` and `langgraph`
https://github.com/hmasdev/langchain_werewolf
game langchain langgraph llm werewolf
Last synced: 4 months ago
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A CUI-based simple werewolf game with `langchain` and `langgraph`
- Host: GitHub
- URL: https://github.com/hmasdev/langchain_werewolf
- Owner: hmasdev
- License: mit
- Created: 2024-09-29T15:37:30.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-10-15T15:18:20.000Z (6 months ago)
- Last Synced: 2024-10-20T10:51:41.479Z (6 months ago)
- Topics: game, langchain, langgraph, llm, werewolf
- Language: Python
- Homepage:
- Size: 8.01 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# :chains: :wolf: :chains: `langchain_werewolf` :chains: :wolf: :chains:
A CUI-based simple werewolf game with `langchain` and `langgraph`
## Requirements
- LLM service API keys
- OpenAI API Key
- [https://platform.openai.com/api-keys](https://platform.openai.com/api-keys)
- Groq API Key
- [https://console.groq.com/keys](https://console.groq.com/keys)
- Gemini API Key
- [https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey)
- Python >= 3.10
- Graphviz
## How to Use
### How to Install
```bash
git clone https://github.com/hmasdev/langchain_werewolf.git
cd langchain_werewolf
python -m pip install .
```
If you have `uv`, `uv sync` is also available to install `langchain_werewolf` instead of `python -m pip install .`.
You can also install `langchain_werewolf` directly from the repository.
```bash
python -m pip install git+https://github.com/hmasdev/langchain_werewolf.git
```
### Preparation
1. Create `.env` file
2. Set `OPENAI_API_KEY`, `GROQ_API_KEY` or `GOOGLE_API_KEY` in the `.env` file as follows:
```text
OPENAI_API_KEY=HERE_IS_YOUR_API_KEY
GROQ_API_KEY=HERE_IS_YOUR_API_KEY
GOOGLE_API_KEY=HERE_IS_YOUR_API_KEY
```
### How to Run
In your command line interface like `bash`,
```bash
python -m langchain_werewolf {HERE_IS_YOUR_FAVORITE_OPTIONS}
```
On the other hand, you can also enjoy `langchain_werewolf` in python environment
```bash
$ python
Python 3.10.11 (main, Sep 20 2024, 18:41:54) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from langchain_werewolf.main import main
>>> main(**HERE_IS_YOUR_FAVORITE_OPTIONS)
```
## Document
### Available Options
```bash
$ python -m langchain_werewolf --help
Usage: python -m langchain_werewolf [OPTIONS]
Options:
-n, --n-players INTEGER The number of players. Default is 4.
-w, --n-werewolves INTEGER The number of werewolves. Default is 1.
-k, --n-knights INTEGER The number of knights. Default is 1.
-f, --n-fortune-tellers INTEGER
The number of fortune tellers. Default is 1.
-o, --output TEXT The output file. Defaults to "".
-l, --system-output-level TEXT The output type of the CLI. ['all',
'public', 'off'] and player names are valid.
Default is All.
--system-output-interface TEXT The system interface. Default is
EInputOutputType.standard.
--system-input-interface TEXT The system interface. Default is
EInputOutputType.standard.
--system-formatter TEXT The system formatter. The format should not
include anything other than "{name}",
"{timestamp}", "{message}",
"{participants}", "{template}".
-c, --config TEXT The configuration file. Defaults to "". Note
that you can specify CLI arguments in this
config file but the config file overwrite
the CLI arguments.
--seed INTEGER The random seed. Defaults to -1.
--model TEXT The model to use. Default is gpt-4o-mini.
--recursion-limit INTEGER The recursion limit. Default is 1000.
--debug Enable debug mode.
--verbose Enable verbose mode.
--help Show this message and exit.
```
You can also another options in the configuration json file like the followings:
```json
{
"general": {
"n_players": 4
},
"game": {
"daytime_chat_kwargs": {
"n_turns_per_day": 2,
"select_speaker": "round_robin"
},
"nighttime_chat_kwargs": {
"n_turns_per_day": 2,
"select_speaker": "random"
}
}
}
```
Then, the configuration file can be specified by `-c` or `--config` option.
See [config.py](https://github.com/hmasdev/langchain_werewolf/blob/main/langchain_werewolf/models/config.py) for more details like the schema of the configuration json file.
### Game Structure
You can see a more detailed grpah in [.pics/langchain_werewolf_game_graph.png](./pics/langchain_werewolf_game_graph.png).
How to Generate the Drawing of the Graphs
```python
Python 3.10.11 (main, Sep 20 2024, 18:41:54) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from dotenv import load_dotenv
>>> load_dotenv()
True
>>> from langchain_werewolf.game.main import create_game_graph
>>> from langchain_werewolf.main import DEFAULT_CONFIG
>>> from langchain_werewolf.setup import generate_players
>>> players = generate_players(DEFAULT_CONFIG.general.n_players, DEFAULT_CONFIG.general.n_werewolves, DEFAULT_CONFIG.general.n_knights, DEFAULT_CONFIG.general.n_fortune_tellers, seed=DEFAULT_CONFIG.general.seed, custom_players=DEFAULT_CONFIG.players)
>>> graph = create_game_graph(players)
>>> graph.get_graph(xray=False).draw_png('pics/langchain_werewolf_game_graph_simple.png')
>>> graph.get_graph(xray=True).draw_png('pics/langchain_werewolf_game_graph.png')
```
## Examples
TBD
## Contribution
### How to Develop
1. Fork the repository: [https://github.com/hmasdev/langchain_werewolf](https://github.com/hmasdev/langchain_werewolf)
2. Clone the repository
```bash
git clone https://github.com/{YOURE_NAME}/langchain_werewolf
cd langchain_werewolf
```
3. Create a virtual environment and install the required packages
```bash
python -m venv venv
source venv/bin/activate
python -m pip install -e .[dev]
```
or
```bash
uv sync --extra dev
```
if you uses `uv`.
4. Checkout your working branch
```bash
git checkout -b your-working-branch
```
5. Make your changes
6. Test your changes
```bash
pytest
flake8 langchain_werewolf tests
mypy langchain_werewolf tests
```
or
```bash
uv run pytest
uv run flake8 langchain_werewolf tests
uv run mypy langchain_werewolf tests
```
Note that the above commands run only unit tests.
It is recommended to run integration tests with `uv run pytest -m integration`.
7. Commit your changes
```bash
git add .
git commit -m "Your commit message"
```
8. Push your changes
```bash
git push origin your-working-branch
```
9. Create a pull request: [https://github.com/hmasdev/langchain_werewolf/compare](https://github.com/hmasdev/langchain_werewolf/compare)
## LICENSE
[MIT](https://github.com/hmasdev/langchain_werewolf/tree/main/LICENSE)
## Authors
- [hmasdev](https://github.com/hmasdev)