adaptive_world_controller.py

import json


class AdaptiveWorldController:

    def __init__(self, llm):

        self.llm = llm
        self.target_difficulty = 0.5  # sweet spot

    # ---------------------------------
    # COMPUTE WORLD HEALTH
    # ---------------------------------
    def analyze(self, metrics, world_state):

        avg_reward = metrics.get("avg_reward", 0.5)

        player_health = world_state["player"]["health"]
        popped = world_state["player"]["popped"]

        return {
            "difficulty_signal": avg_reward,
            "player_stability": player_health / 100,
            "progress_rate": popped
        }

    # ---------------------------------
    # BUILD ADAPTATION PROMPT
    # ---------------------------------
    def build_prompt(self, analysis, world):

        return f"""
You are a living game ecosystem controller.

Your job is BALANCE:
- If player is struggling → reduce difficulty
- If player is dominating → increase complexity

TARGET: maintain engagement near {self.target_difficulty}

ANALYSIS:
{json.dumps(analysis)}

WORLD STATE:
{json.dumps(world)}

YOU MAY MODIFY:
- nodes (zones)
- entities (balloons/enemies)
- rules (damage, spawn rates)
- difficulty

OUTPUT ONLY VALID JSON:
{{
  "adjustments": {{
    "difficulty": 0.0
  }},
  "nodes": [],
  "entities": [],
  "rules": {{}}
}}
"""

    # ---------------------------------
    # RUN ONE ADAPTIVE STEP
    # ---------------------------------
    def step(self, metrics, world):

        analysis = self.analyze(metrics, world)

        prompt = self.build_prompt(analysis, world)

        raw = self.llm.generate(prompt)

        try:
            import re
            match = re.search(r"\{.*\}", raw, re.DOTALL)
            if not match:
                return {}

            return json.loads(match.group(0))

        except:
            return {}