AI Dungeon：LLM文字冒险游戏架构

from dataclasses import dataclass, fieldfrom typing import Optional  @dataclassclass SceneTemplate:    """场景模板：封装不同冒险类型的背景设定"""    name: str    world_setting: str    starting_situation: str    character_config: dict    narrative_style: str = "second_person"  # 奇幻冒险场景模板fantasy_template = SceneTemplate(    name="奇幻冒险",    world_setting="一个充满魔法、巨龙和古老遗迹的奇幻大陆",    starting_situation="你醒来时发现自己躺在一片陌生的森林中，远处传来狼嚎声",    character_config={"class": "冒险者", "inventory": ["生锈的短剑", "面包", "水壶"]},    narrative_style="second_person")  def build_system_prompt(template: SceneTemplate, world_state: dict) -> str:    """构建System Prompt，注入世界观和状态约束"""    prompt = f"""你是一个文字冒险游戏的叙事引擎。 ## 世界设定{template.world_setting} ## 当前世界状态- 玩家位置: {world_state.get('location', '未知')}- 玩家生命值: {world_state.get('health', 100)}/100- 已学技能: {', '.join(world_state.get('skills', ['基础攻击']))}- 持有物品: {', '.join(world_state.get('inventory', []))} ## 叙事规则1. 用第二人称描述玩家行为和周围环境2. 参考世界状态确保物理逻辑一致3. 玩家不能使用未学习的技能或到达未探索的区域4. 保持叙事风格与世界设定一致"""    return prompt

import refrom dataclasses import dataclass, fieldfrom typing import Optionalfrom collections import deque  @dataclassclass WorldState:    """世界状态变量：跟踪玩家位置、物品和NPC关系"""    location: str = "森林入口"    health: int = 100    skills: list = field(default_factory=lambda: ["基础攻击", "侦查"])    inventory: list = field(default_factory=lambda: ["短剑", "面包"])    npc_relations: dict = field(default_factory=lambda: {"酒馆老板": "中立"})    explored_areas: list = field(default_factory=lambda: ["森林入口"])  @dataclassclass ParsedAction:    """解析后的结构化动作"""    action_type: str  # attack/talk/explore/move/use    target: str = ""    skill: str = ""    detail: str = ""  class ActionClassifier:    """动作分类器：将自然语言输入解析为结构化动作"""     def parse(self, user_input: str) -> list:        actions = []        text = user_input.strip()         if re.search(r'攻击|打|杀|砍|射', text):            target = self._extract_target(text, r'攻击|打|杀|砍|射')            skill = self._extract_skill(text)            actions.append(ParsedAction(                action_type="attack",                target=target,                skill=skill,                detail=text            ))         if re.search(r'去|走|跑|逃跑|前往|进入', text):            target = self._extract_location(text)            actions.append(ParsedAction(                action_type="move",                target=target,                detail=text            ))         if re.search(r'说话|聊天|问|告诉|交谈', text):            target = self._extract_target(text, r'说话|聊天|问|告诉|交谈')            actions.append(ParsedAction(                action_type="talk",                target=target,                detail=text            ))         if not actions:            actions.append(ParsedAction(                action_type="explore",                detail=text            ))         return actions     def _extract_target(self, text, pattern):        match = re.search(f'{pattern}(.+?)(?:的|并|，|。|$)', text)        return match.group(1).strip() if match else "未知目标"     def _extract_skill(self, text):        skills = ["火球术", "冰冻术", "治愈术", "隐身术", "闪电链"]        for skill in skills:            if skill in text:                return skill        return "基础攻击"     def _extract_location(self, text):        locations = ["森林", "酒馆", "洞穴", "城堡", "村庄", "山顶"]        for loc in locations:            if loc in text:                return loc        return "未知地点"  class StateValidator:    """状态验证器：检查动作可行性"""     def validate(self, action: ParsedAction, state: WorldState) -> dict:        result = {"valid": True, "reason": ""}         if action.action_type == "attack":            if action.skill and action.skill not in state.skills:                result["valid"] = False                result["reason"] = f"玩家未学习{action.skill}，无法使用"         elif action.action_type == "move":            if action.target and action.target not in state.explored_areas:                if state.location not in action.target:                    result["valid"] = False                    result["reason"] = f"无法直接前往{action.target}，需要先探索路径"         elif action.action_type == "talk":            if action.target and action.target not in state.npc_relations:                result["valid"] = False                result["reason"] = f"附近没有{action.target}"         return result  class ContextManager:    """上下文管理器：滑动窗口 + 关键事件摘要"""     def __init__(self, window_size=10):        self.window = deque(maxlen=window_size)        self.summaries = []     def add_interaction(self, user_input, ai_response):        self.window.append({"user": user_input, "ai": ai_response})     def compress_oldest(self):        if len(self.window) >= self.window.maxlen:            oldest = self.window[0]            summary = f"玩家{oldest['user'][:20]}... -> {oldest['ai'][:30]}..."            self.summaries.append(summary)     def build_context(self):        summary_text = "\n".join(self.summaries[-5:])        window_text = "\n".join(            f"玩家: {m['user']}\n叙事: {m['ai']}"            for m in self.window        )        return f"## 历史摘要\n{summary_text}\n\n## 最近交互\n{window_text}"  class AIDungeonEngine:    """AI Dungeon核心引擎：整合动作解析、状态验证和上下文管理"""     def __init__(self):        self.state = WorldState()        self.classifier = ActionClassifier()        self.validator = StateValidator()        self.context = ContextManager(window_size=10)        self.turn_count = 0     def process_input(self, user_input: str) -> dict:        self.turn_count += 1        actions = self.classifier.parse(user_input)         results = []        for action in actions:            validation = self.validator.validate(action, self.state)            if not validation["valid"]:                results.append({                    "action": action.action_type,                    "valid": False,                    "narrative": validation["reason"]                })            else:                self._update_state(action)                results.append({                    "action": action.action_type,                    "valid": True,                    "narrative": f"动作验证通过，交由LLM生成叙事"                })         context_prompt = self.context.build_context()        return {            "turn": self.turn_count,            "parsed_actions": [                {"type": a.action_type, "target": a.target, "skill": a.skill}                for a in actions            ],            "results": results,            "context_length": len(context_prompt),            "world_state": {                "location": self.state.location,                "health": self.state.health,                "skills": self.state.skills,                "inventory": self.state.inventory            }        }     def _update_state(self, action: ParsedAction):        if action.action_type == "move" and action.target:            self.state.location = action.target            if action.target not in self.state.explored_areas:                self.state.explored_areas.append(action.target)        elif action.action_type == "attack" and action.skill:            if action.skill not in self.state.skills:                pass  if __name__ == '__main__':    engine = AIDungeonEngine()     test_inputs = [        "我用火球术攻击巨龙的左手",        "我去酒馆和酒馆老板聊天",        "我用隐身术潜入城堡"    ]     for user_input in test_inputs:        print(f"\n{'='*60}")        print(f"玩家输入: {user_input}")        result = engine.process_input(user_input)        print(f"解析动作: {result['parsed_actions']}")        for r in result['results']:            status = '✓' if r['valid'] else '✗'            print(f"  {status} {r['action']}: {r['narrative']}")        print(f"世界状态: 位置={result['world_state']['location']}, 技能={result['world_state']['skills']}")