mirror of
https://github.com/NousResearch/atropos.git
synced 2026-04-25 17:10:42 +00:00
Add DynastAI game environment with FastAPI backend and web frontend
- Introduced `dynastai_local_server.py` for local development and testing. - Implemented `dynastai_server.py` as the main server entry point. - Created FastAPI endpoints for game state management, card generation, and player choices. - Developed a web interface with HTML, CSS, and JavaScript for user interaction. - Added game logic for managing metrics and decision effects. - Included configuration management and utility functions. - Established a testing framework for API and environment functionality. - Updated README.md with project overview and setup instructions.
This commit is contained in:
parent
c189fc3351
commit
e0dabe1225
18 changed files with 3143 additions and 0 deletions
201
environments/dynastai/README.md
Normal file
201
environments/dynastai/README.md
Normal file
|
|
@ -0,0 +1,201 @@
|
|||
# DynastAI
|
||||
|
||||
A medieval kingdom management game with an adaptive reinforcement learning environment.
|
||||
|
||||
## Overview
|
||||
|
||||
DynastAI is an Atropos-compatible Python RL environment integrated with a web frontend. The game challenges players to rule a medieval kingdom by balancing four key metrics:
|
||||
|
||||
- **Power** - Royal authority
|
||||
- **Stability** - Population happiness
|
||||
- **Piety** - Religious influence
|
||||
- **Wealth** - Kingdom finances
|
||||
|
||||
Each turn, players are presented with scenario cards generated using Qwen 1.7B via OpenRouter. Every decision affects metrics and contributes to an adaptive reward system that evolves gameplay based on previous reigns.
|
||||
|
||||
## Key Features
|
||||
|
||||
- **Atropos-Compatible Environment**: Implements the BaseEnv interface for training with Atropos
|
||||
- **FastAPI Backend**: REST endpoints for game state management
|
||||
- **HTML/CSS/JS Frontend**: Modern, responsive web interface
|
||||
- **Adaptive Rewards**: Reward calculation that adapts to player choices and outcomes
|
||||
- **OpenRouter Integration**: Dynamic card generation using Qwen 1.7B language model
|
||||
|
||||
## Project Structure
|
||||
|
||||
```
|
||||
dynastai/
|
||||
│
|
||||
├── src/
|
||||
│ ├── __init__.py
|
||||
│ ├── dynastai_env.py # Atropos environment class
|
||||
│ ├── config.py # Configuration management
|
||||
│ ├── game_logic.py # Core game mechanics
|
||||
│ ├── util.py # Utility functions
|
||||
│ ├── data/ # Game data storage
|
||||
│ └── web/ # Web interface
|
||||
│ ├── __init__.py
|
||||
│ ├── api.py # FastAPI endpoints
|
||||
│ ├── server.py # Server initialization
|
||||
│ └── static/ # Frontend assets
|
||||
│ ├── css/
|
||||
│ ├── js/
|
||||
│ └── index.html
|
||||
│
|
||||
├── dynastai_server.py # Main server entry point
|
||||
├── dynastai_local_server.py # Local development server
|
||||
├── requirements.txt # Dependencies
|
||||
└── README.md # Documentation
|
||||
```
|
||||
|
||||
## Adaptive Reward Mechanism
|
||||
|
||||
DynastAI implements a novel adaptive reward mechanism that evolves based on gameplay:
|
||||
|
||||
```
|
||||
R = power_final * P + stability_final * S + piety_final * Pi + wealth_final * W
|
||||
```
|
||||
|
||||
Where:
|
||||
- `power_final`, `stability_final`, `piety_final`, `wealth_final` are the final metric values
|
||||
- `P`, `S`, `Pi`, `W` are the counts of cards played in each category
|
||||
|
||||
This creates a dynamic reward system that adapts to each player's style and decisions.
|
||||
|
||||
## Getting Started
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- Python 3.8+
|
||||
- OpenRouter API key (set in `.env` file)
|
||||
|
||||
### Installation
|
||||
|
||||
1. Clone the repository:
|
||||
```bash
|
||||
git clone https://github.com/yourusername/dynastai.git
|
||||
cd dynastai
|
||||
```
|
||||
|
||||
2. Install dependencies:
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
3. Create a `.env` file with your OpenRouter API key:
|
||||
```
|
||||
OPENROUTER_API_KEY=your_api_key_here
|
||||
```
|
||||
|
||||
### Running the Server
|
||||
|
||||
To run the full server with API endpoints:
|
||||
|
||||
```bash
|
||||
python dynastai_server.py
|
||||
```
|
||||
|
||||
For local development with both API and web server:
|
||||
|
||||
```bash
|
||||
python dynastai_local_server.py
|
||||
```
|
||||
|
||||
Then access the web interface at http://localhost:3000
|
||||
|
||||
## API Endpoints
|
||||
|
||||
The game exposes the following REST API endpoints:
|
||||
|
||||
- `GET /api/`: Root endpoint with API status
|
||||
- `POST /api/new_game`: Create a new game session
|
||||
- `GET /api/state/{session_id}`: Get the current game state
|
||||
- `POST /api/generate_card`: Generate a new scenario card
|
||||
- `POST /api/card_choice`: Submit a player decision
|
||||
- `POST /api/end_reign`: End a reign and calculate final rewards
|
||||
|
||||
## Integration with Atropos
|
||||
|
||||
The `DynastAIEnv` class implements Atropos's `BaseEnv` interface, making it compatible with Atropos reinforcement learning workflows:
|
||||
|
||||
```python
|
||||
from atroposlib.envs.base import BaseEnv
|
||||
from src.dynastai_env import DynastAIEnv
|
||||
|
||||
# Create and configure environment
|
||||
env = DynastAIEnv(config, server_configs)
|
||||
|
||||
# Use with Atropos training
|
||||
observation = await env.reset()
|
||||
observation, reward, done, info = await env.step(action)
|
||||
```
|
||||
|
||||
## License
|
||||
|
||||
This project is licensed under the MIT License - see the LICENSE file for details.
|
||||
|
||||
## Acknowledgments
|
||||
|
||||
- Based on the legacy command-line DynastAI game
|
||||
- Uses Qwen 1.7B from OpenRouter for card generation
|
||||
- Built with FastAPI, Uvicorn, and modern web technologies
|
||||
## Using with Atropos
|
||||
|
||||
To use DynastAI with Atropos for training RL models:
|
||||
|
||||
```python
|
||||
from atroposlib.envs.base import BaseEnv
|
||||
from atroposlib.envs.server_handling.server_baseline import ServerBaseline
|
||||
from src.dynastai_env import DynastAIEnv, DynastAIEnvConfig
|
||||
|
||||
# Create and configure environment
|
||||
config = DynastAIEnvConfig(
|
||||
api_host="localhost",
|
||||
api_port=9001,
|
||||
web_ui=True,
|
||||
web_port=3000,
|
||||
openrouter_api_key="your_api_key"
|
||||
)
|
||||
server_configs = ServerBaseline()
|
||||
env = DynastAIEnv(config, server_configs)
|
||||
|
||||
# Use with Atropos training
|
||||
observation = await env.reset()
|
||||
action = {"session_id": observation["session_id"], "choice": "yes"}
|
||||
observation, reward, done, info = await env.step(action)
|
||||
```
|
||||
|
||||
## Testing
|
||||
|
||||
To run the local development server and test the game:
|
||||
|
||||
1. Install dependencies:
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
2. Ensure your OpenRouter API key is set in the `.env` file or environment:
|
||||
```bash
|
||||
export OPENROUTER_API_KEY=your_api_key_here
|
||||
```
|
||||
|
||||
3. Run the local development server:
|
||||
```bash
|
||||
python dynastai_local_server.py
|
||||
```
|
||||
|
||||
4. Open your browser and navigate to `http://localhost:3000` to play the game
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
Potential improvements for future versions:
|
||||
|
||||
- Enhanced card generation with more varied scenarios
|
||||
- Multi-agent gameplay for competitive kingdom management
|
||||
- Persistent game state and user accounts
|
||||
- More complex game mechanics (resource management, diplomacy)
|
||||
- Improved UI with animations and visual history
|
||||
|
||||
## Contributing
|
||||
|
||||
Contributions are welcome! Please feel free to submit a Pull Request.
|
||||
Loading…
Add table
Add a link
Reference in a new issue