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https://github.com/NousResearch/atropos.git
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e0dabe1225
- 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.
115 lines
3.4 KiB
Python
Executable file
115 lines
3.4 KiB
Python
Executable file
#!/usr/bin/env python3
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"""
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DynastAI Test Script
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This script tests the basic functionality of the DynastAI environment:
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- Game state initialization
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- Card generation
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- Choice processing
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- Game over conditions
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- Reward calculation
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"""
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import os
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import sys
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import asyncio
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import json
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import random
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from dotenv import load_dotenv
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# Ensure the src directory is in path
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sys.path.insert(0, os.path.abspath(os.path.dirname(__file__)))
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from src.dynastai_env import DynastAIEnv, DynastAIEnvConfig
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from atroposlib.envs.server_handling.server_baseline import ServerBaseline
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# Load environment variables
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load_dotenv()
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async def test_environment():
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"""Test the DynastAI environment"""
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print("Initializing DynastAI environment...")
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# Create config and environment
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config = DynastAIEnvConfig()
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server_config = ServerBaseline()
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env = DynastAIEnv(config, server_config)
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# Reset the environment
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print("Resetting environment...")
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state = await env.reset()
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session_id = state["session_id"]
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print(f"Session ID: {session_id}")
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print(f"Initial metrics: {state['metrics']}")
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# Run a simulated game
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done = False
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total_reward = 0
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steps = 0
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print("\nStarting simulated game...")
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while not done and steps < 20: # Cap at 20 steps to avoid infinite loop
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# Generate a card (direct method call for testing)
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state["current_card"] = env.game_states[session_id].current_card = env._generate_card_internal(
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env.game_states[session_id].get_metrics(),
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env.category_weights
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)
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# Choose a random action
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choice = random.choice(["yes", "no"])
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action = {"session_id": session_id, "choice": choice}
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print(f"\nStep {steps+1}:")
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print(f"Card: {state['current_card']['text']}")
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print(f"Choice: {choice}")
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# Take the action
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state, reward, done, info = await env.step(action)
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# Print the results
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print(f"New metrics: {state['metrics']}")
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print(f"Reward: {reward}")
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print(f"Done: {done}")
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total_reward += reward
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steps += 1
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if done:
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print("\nGame Over!")
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print(f"Final metrics: {state['metrics']}")
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print(f"Total reward: {total_reward}")
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print(f"Steps: {steps}")
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break
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print("\nTesting complete!")
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return True
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def _generate_card_internal(self, metrics, category_weights):
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"""Internal method for card generation during testing"""
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from src.game_logic import generate_mock_card
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# Select a category based on weights
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categories = list(category_weights.keys())
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weights = [category_weights[cat] for cat in categories]
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total_weight = sum(weights)
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# Normalize weights
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if total_weight > 0:
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normalized_weights = [w/total_weight for w in weights]
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else:
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normalized_weights = [1/len(categories)] * len(categories)
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category = random.choices(categories, weights=normalized_weights, k=1)[0]
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# Use the mock generator for testing
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return generate_mock_card(metrics, category)
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# Add the test method to the environment class
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DynastAIEnv._generate_card_internal = _generate_card_internal
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if __name__ == "__main__":
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print("DynastAI Environment Test")
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print("=========================")
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# Run the test
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asyncio.run(test_environment())
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