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Enhance DynastAI scenario generation with structured point system and history tracking
- Updated point system guidelines to restrict values for Piety, Stability, Power, and Wealth to a range of -20 to 20. - Introduced a category field for scenario classification. - Added examples for scenario generation to improve clarity. - Implemented choice history tracking to maintain a record of player decisions and their effects on the kingdom's state. - Enhanced prompt formatting to include current kingdom state and recent choices for better context in scenario generation.
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Earl Potters
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1 changed files with 188 additions and 45 deletions
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@ -30,20 +30,79 @@ You are playing a game called DynastAI where you generate scenarios for a kingdo
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Each scenario should include a character presenting a dilemma to the ruler, with two choices that affect
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the four key resources of the kingdom: Piety, Stability, Power, and Wealth.
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**Point System Guidelines:**
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- The point values for Piety, Stability, Power, and Wealth for each choice should be integers ranging from -20 to 20.
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- These values should be logically consistent with the scenario and the choice described. A choice that is clearly beneficial should have a net positive sum of points, while a detrimental choice should have a net negative sum.
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- Strive for a variety of point distributions; not all resources need to be affected by every choice.
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Your response must be a valid JSON object with the following structure:
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{
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"Character": "Name/Title of the character",
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"Prompt": "The scenario description",
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"Left_Choice": "The first choice option",
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"Left_Piety": integer value between -30 and 30,
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"Left_Stability": integer value between -30 and 30,
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"Left_Power": integer value between -30 and 30,
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"Left_Wealth": integer value between -30 and 30,
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"Left_Piety": integer value between -20 and 20,
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"Left_Stability": integer value between -20 and 20,
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"Left_Power": integer value between -20 and 20,
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"Left_Wealth": integer value between -20 and 20,
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"Right_Choice": "The second choice option",
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"Right_Piety": integer value between -30 and 30,
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"Right_Stability": integer value between -30 and 30,
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"Right_Power": integer value between -30 and 30,
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"Right_Wealth": integer value between -30 and 30
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"Right_Piety": integer value between -20 and 20,
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"Right_Stability": integer value between -20 and 20,
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"Right_Power": integer value between -20 and 20,
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"Right_Wealth": integer value between -20 and 20,
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"category": "piety/stability/power/wealth"
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}
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Here are some examples:
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Example 1:
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{
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"Character": "Diplomat",
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"Prompt": "With a sly smile, the diplomat gestures broadly: \"Sire, the lords quarrel like children. Shall we mediate disputes between lords?\"",
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"Left_Choice": "We cannot risk the kingdom's future; dismiss them with a royal wave.",
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"Left_Piety": 10,
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"Left_Stability": -10,
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"Left_Power": 0,
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"Left_Wealth": 0,
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"Right_Choice": "Make it so; our enemies shall kneel in terror!",
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"Right_Piety": -10,
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"Right_Stability": 10,
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"Right_Power": 0,
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"Right_Wealth": 0,
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"category": "stability"
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}
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Example 2:
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{
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"Character": "Merchant",
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"Prompt": "The merchant nervously fidgets with coins: \"My king, the markets groan under heavy tariffs. Shall we reduce tariffs?\"",
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"Left_Choice": "Absurd! Unthinkable; it's madness that courts disaster.",
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"Left_Piety": 0,
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"Left_Stability": -15,
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"Left_Power": 0,
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"Left_Wealth": 10,
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"Right_Choice": "Brilliant! Most ingenious; begin before the sun sets!",
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"Right_Piety": 0,
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"Right_Stability": 15,
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"Right_Power": 0,
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"Right_Wealth": -10,
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"category": "wealth"
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}
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Example 3:
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{
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"Character": "Farmer",
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"Prompt": "Mud-stained and weary, the farmer removes his cap: \"Your Grace, our villages yearn for markets. Shall we hold local markets?\"",
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"Left_Choice": "Silence! Such talk borders on treason; it whispers of rebellion and ruin.",
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"Left_Piety": 0,
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"Left_Stability": -15,
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"Left_Power": 0,
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"Left_Wealth": 10,
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"Right_Choice": "Indeed! We shall usher wealth and fortune to the land!",
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"Right_Piety": 0,
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"Right_Stability": 15,
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"Right_Power": 0,
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"Right_Wealth": -10,
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"category": "stability"
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}
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Be creative and make each scenario interesting!"""
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@ -51,7 +110,8 @@ Be creative and make each scenario interesting!"""
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class DynastAIRow(TypedDict):
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scenario_prompt: str
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card: Optional[Dict] = None
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kingdom_current_state: Optional[Dict] = None
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choice_history: Optional[List] = None
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class DynastAIEnv(BaseEnv):
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@ -129,42 +189,58 @@ class DynastAIEnv(BaseEnv):
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self.train = cards[test_size:]
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self.test = cards[:test_size]
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# Keep scenario prompts for generating new scenarios
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self.scenario_prompts = [
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"Create a dilemma involving the Church and Treasury",
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"Create a dilemma involving the Military and People",
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"Create a scenario where a foreign diplomat visits",
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"Create a scenario about a natural disaster",
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"Create a scenario about a rebellious noble",
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"Create a scenario about a religious conflict",
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"Create a scenario about a military campaign",
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"Create a scenario about a royal marriage proposal",
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"Create a scenario about a trade agreement",
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"Create a scenario about a mysterious artifact",
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"Create a scenario about peasant unrest",
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"Create a scenario about a spy in the court",
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"Create a scenario about a disputed succession",
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"Create a scenario about a diplomatic incident",
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"Create a scenario about a technological innovation",
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]
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self.iter = 0
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# Initialize default kingdom state
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self.current_kingdom_state = {
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"Piety": 50,
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"Stability": 50,
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"Power": 50,
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"Wealth": 50
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}
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self.choice_history = []
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def save_checkpoint(self, step, data=None):
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if data is None:
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data = {}
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data["iter"] = self.iter
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data["current_kingdom_state"] = self.current_kingdom_state
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data["choice_history"] = self.choice_history
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super().save_checkpoint(step, data)
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async def evaluate(self, *args, **kwargs):
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# For evaluation, we'll use the test set cards
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eval_tasks = []
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for card in self.test:
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eval_tasks.append(self.rollout_and_score_eval(f"Create a scenario similar to: {card['Prompt']}"))
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input_data = card.get("input", {})
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kingdom_state = input_data.get("kingdom_current_state", self.current_kingdom_state)
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choice_history = input_data.get("choice_history", [])
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prompt = self.format_prompt(kingdom_state, choice_history)
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eval_tasks.append(self.rollout_and_score_eval(prompt))
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scores = await tqdm_asyncio.gather(*eval_tasks)
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self.eval_metrics.append(("eval/percent_correct", sum(scores) / len(scores)))
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def format_prompt(self, kingdom_state, choice_history):
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prompt = "Generate a new scenario for the kingdom with the following current state:\n"
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prompt += f"Piety: {kingdom_state.get('Piety', 50)}, "
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prompt += f"Stability: {kingdom_state.get('Stability', 50)}, "
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prompt += f"Power: {kingdom_state.get('Power', 50)}, "
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prompt += f"Wealth: {kingdom_state.get('Wealth', 50)}\n\n"
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if choice_history:
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prompt += "Previous choices made:\n"
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for i, choice in enumerate(choice_history[-3:]): # Show last 3 choices at most
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prompt += f"{i+1}. {choice.get('Character', 'Unknown')} presented: \"{choice.get('Prompt', 'Unknown')}\"\n"
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prompt += f" Decision: {choice.get('choice_made', 'Unknown')}\n"
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prompt += f" Effects: Piety {choice.get('effects', {}).get('Piety', 0)}, "
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prompt += f"Stability {choice.get('effects', {}).get('Stability', 0)}, "
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prompt += f"Power {choice.get('effects', {}).get('Power', 0)}, "
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prompt += f"Wealth {choice.get('effects', {}).get('Wealth', 0)}\n\n"
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prompt += "Based on this context, generate a new challenging scenario for the ruler."
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return prompt
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async def rollout_and_score_eval(self, scenario_prompt: str) -> number:
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completion = await self.server.chat_completion(
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messages=[
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@ -201,7 +277,8 @@ class DynastAIEnv(BaseEnv):
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required_fields = [
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"Character", "Prompt",
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"Left_Choice", "Left_Piety", "Left_Stability", "Left_Power", "Left_Wealth",
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"Right_Choice", "Right_Piety", "Right_Stability", "Right_Power", "Right_Wealth"
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"Right_Choice", "Right_Piety", "Right_Stability", "Right_Power", "Right_Wealth",
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"category"
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]
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if not all(field in data for field in required_fields):
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@ -216,9 +293,13 @@ class DynastAIEnv(BaseEnv):
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for field in numeric_fields:
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if not isinstance(data[field], int):
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return 0
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if data[field] < -30 or data[field] > 30:
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if data[field] < -20 or data[field] > 20:
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return 0
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# Check category field
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if data["category"] not in ["piety", "stability", "power", "wealth"]:
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return 0
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# If we made it here, the JSON is valid
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return 1
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@ -236,8 +317,8 @@ class DynastAIEnv(BaseEnv):
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max_tokens=self.config.max_token_length,
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)
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to_score = list()
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to_backlog = list()
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to_score = []
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to_backlog = []
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for i, chat_completion in enumerate(chat_completions.choices):
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messages = (
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@ -251,6 +332,39 @@ class DynastAIEnv(BaseEnv):
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})
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to_postprocess = await self.score(to_score)
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# Update choice history with the highest scoring scenario
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if to_postprocess and to_postprocess["scores"]:
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best_idx = to_postprocess["scores"].index(max(to_postprocess["scores"]))
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best_content = to_score[best_idx]["messages"][-1]["content"]
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try:
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# Extract JSON from content
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if "</think>" in best_content:
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best_content = best_content.split("</think>")[-1].strip()
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json_match = re.search(r'\{.*\}', best_content, re.DOTALL)
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if json_match:
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json_str = json_match.group(0)
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data = json.loads(json_str)
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# Store the generated scenario in choice history
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self.choice_history.append({
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"Character": data.get("Character", "Unknown"),
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"Prompt": data.get("Prompt", "Unknown"),
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"choice_made": "Unknown", # Will be set when player makes a choice
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"effects": {
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"Piety": 0,
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"Stability": 0,
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"Power": 0,
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"Wealth": 0
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},
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"category": data.get("category", "unknown"),
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# Store the full scenario data for later use
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"scenario_data": data
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})
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except Exception as e:
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print(f"Error processing scenario: {e}")
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return to_postprocess, to_backlog
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async def score(
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@ -293,19 +407,48 @@ class DynastAIEnv(BaseEnv):
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return scores
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async def get_next_item(self) -> DynastAIRow:
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# Alternate between using saved cards and generating new scenarios
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if self.iter % 2 == 0 and self.train:
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# Use a card from the training set
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card_index = (self.iter // 2) % len(self.train)
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card = self.train[card_index]
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prompt = f"Create a scenario similar to: {card['Prompt']}"
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self.iter += 1
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return {"scenario_prompt": prompt, "card": card}
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# Increment counter
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self.iter += 1
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# Occasionally sample from training data, otherwise use current state
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if self.train and random.random() < 0.3:
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card = random.choice(self.train)
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input_data = card.get("input", {})
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kingdom_state = input_data.get("kingdom_current_state", self.current_kingdom_state)
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choice_history = input_data.get("choice_history", [])
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else:
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# Generate a completely new scenario
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prompt = random.choice(self.scenario_prompts)
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self.iter += 1
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return {"scenario_prompt": prompt}
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kingdom_state = self.current_kingdom_state
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choice_history = self.choice_history
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# Generate prompt based on kingdom state and choice history
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prompt = self.format_prompt(kingdom_state, choice_history)
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return {
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"scenario_prompt": prompt,
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"kingdom_current_state": kingdom_state,
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"choice_history": choice_history
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}
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# Helper method to update kingdom state based on a choice
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def update_kingdom_state(self, choice, is_left_choice=True):
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choice_prefix = "Left_" if is_left_choice else "Right_"
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# Update the most recent choice in the history with the player's decision
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if self.choice_history:
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most_recent = self.choice_history[-1]
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most_recent["choice_made"] = choice.get(f"{choice_prefix}Choice", "Unknown")
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# Update effects based on the choice
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effects = {}
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for resource in ["Piety", "Stability", "Power", "Wealth"]:
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value = choice.get(f"{choice_prefix}{resource}", 0)
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effects[resource] = value
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# Apply effect to current kingdom state
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current_value = self.current_kingdom_state.get(resource, 50)
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self.current_kingdom_state[resource] = max(0, min(100, current_value + value))
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most_recent["effects"] = effects
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if __name__ == "__main__":
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