feat: 添加角色事件评论系统
- 新增 Opinion 模型，记录角色对事件的观点 - 新增 opinions.py，基于规则生成观点（支持5种事件×3种情绪） - 同一事件生命周期内每个 agent 只生成一次观点 - 观点同时记录到 agent.memory - 新增 3 个测试用例 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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@@ -5,6 +5,7 @@ from .models import (
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GlobalEventResult, GlobalEventInfo
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)
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from .global_events import GLOBAL_EVENT_POOL, GlobalEvent
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from .opinions import generate_opinions
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MAX_EVENTS = 20
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MAX_MEMORY_PER_AGENT = 3
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@@ -82,6 +83,9 @@ def process_events(state: WorldState, events: List[Event]) -> WorldState:
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# 更新所有 agent 的 emotion
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update_emotions(state)
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# 生成角色对事件的观点
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generate_opinions(state)
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return state
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@@ -112,6 +116,9 @@ def check_and_trigger_global_event(
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# 更新 emotion
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update_emotions(state)
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# 生成角色对新事件的观点
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generate_opinions(state)
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result = GlobalEventResult(
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triggered=True,
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event=global_event.to_info()
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@@ -31,10 +31,20 @@ class WorldEffect(BaseModel):
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mood_modifier: int = 0
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class Opinion(BaseModel):
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"""角色对事件的观点"""
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about: str # 事件类型 (effect_type)
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text: str # 观点内容
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tick: int # 生成时的 tick
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class AgentState(BaseModel):
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emotion: Emotion = Emotion.CALM
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goal: str = ""
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memory: List[str] = Field(default_factory=list)
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opinion: Optional[Opinion] = None
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# 记录已评论过的事件，防止重复生成
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commented_effects: List[str] = Field(default_factory=list)
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class WorldState(BaseModel):
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163
engine-python/app/opinions.py
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163
engine-python/app/opinions.py
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@@ -0,0 +1,163 @@
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"""角色事件评论系统 - 基于规则生成观点"""
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from typing import Dict, List, Optional
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from .models import WorldState, AgentState, Opinion, Emotion, WorldEffect
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# 观点模板：effect_type -> emotion -> 观点列表
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OPINION_TEMPLATES: Dict[str, Dict[str, List[str]]] = {
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"festival": {
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"happy": [
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"这真是个让人开心的日子！",
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"节日的气氛太棒了！",
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"大家都在庆祝，真好！",
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],
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"calm": [
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"节日挺热闹的。",
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"看来大家都很高兴。",
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"难得的庆典活动。",
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],
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"anxious": [
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"我不太确定这是不是好事...",
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"人太多了，有点不安。",
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"希望一切顺利吧。",
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],
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},
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"storm": {
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"happy": [
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"暴风雨也有它的美！",
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"待在室内也挺好的。",
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"雨声其实很治愈。",
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],
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"calm": [
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"暴风雨来了，注意安全。",
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"等雨停了再出门吧。",
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"天气变化无常啊。",
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],
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"anxious": [
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"这暴风雨让我很担心...",
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"情况看起来不太妙。",
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"希望大家都平安。",
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],
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},
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"scandal": {
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"happy": [
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"不管怎样，生活还要继续！",
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"真相总会大白的。",
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"保持乐观吧。",
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],
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"calm": [
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"这件事确实令人意外。",
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"让我们静观其变。",
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"事情总会解决的。",
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],
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"anxious": [
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"这消息太令人震惊了...",
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"不知道接下来会怎样。",
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"小镇的未来让人担忧。",
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],
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},
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"miracle": {
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"happy": [
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"太神奇了！这是奇迹！",
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"彩虹真的太美了！",
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"今天是幸运的一天！",
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],
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"calm": [
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"难得一见的景象。",
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"大自然真是神奇。",
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"值得记住的时刻。",
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],
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"anxious": [
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"希望这是好兆头...",
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"美丽的景象，但愿能持续。",
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"也许事情会好转吧。",
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],
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},
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"fire": {
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"happy": [
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"消防队很快就会控制住的！",
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"大家齐心协力，一定没问题！",
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"相信我们能度过难关！",
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],
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"calm": [
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"火灾很危险，大家要小心。",
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"希望没有人受伤。",
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"消防队正在处理。",
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],
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"anxious": [
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"情况变得不妙，我得小心...",
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"火灾太可怕了...",
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"希望大家都能平安。",
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],
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},
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}
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# 默认观点（未知事件类型）
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DEFAULT_OPINIONS: Dict[str, List[str]] = {
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"happy": ["不管发生什么，保持乐观！"],
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"calm": ["让我们看看会怎样。"],
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"anxious": ["不知道这意味着什么..."],
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}
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def get_opinion_text(
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effect_type: str,
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emotion: Emotion,
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agent_id: str,
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tick: int
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) -> str:
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"""根据事件类型和情绪生成观点文本"""
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emotion_key = emotion.value
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# 获取对应模板
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if effect_type in OPINION_TEMPLATES:
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templates = OPINION_TEMPLATES[effect_type].get(
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emotion_key,
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DEFAULT_OPINIONS[emotion_key]
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)
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else:
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templates = DEFAULT_OPINIONS[emotion_key]
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# 基于 agent_id 和 tick 选择模板（确保可复现）
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index = (hash(agent_id) + tick) % len(templates)
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return templates[index]
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def generate_opinions(state: WorldState) -> None:
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"""为所有 agent 生成对当前活跃事件的观点"""
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# 无活跃效果时，清空 opinion
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if not state.world_effects:
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for agent in state.agents.values():
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agent.opinion = None
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return
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# 取第一个活跃效果（优先级最高）
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active_effect = state.world_effects[0]
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effect_key = f"{active_effect.type}_{active_effect.name}"
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for agent_id, agent in state.agents.items():
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# 检查是否已对此事件发表过观点
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if effect_key in agent.commented_effects:
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continue
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# 生成观点
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text = get_opinion_text(
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active_effect.type,
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agent.emotion,
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agent_id,
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state.tick
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)
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# 更新 agent.opinion
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agent.opinion = Opinion(
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about=active_effect.type,
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text=text,
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tick=state.tick
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)
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# 记录到 memory
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memory_entry = f"[{agent_id}对{active_effect.name}的看法] {text}"
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agent.memory.append(memory_entry)
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# 标记已评论
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agent.commented_effects.append(effect_key)
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@@ -171,3 +171,61 @@ def test_global_event_cooldown(client):
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assert data["global_event"]["triggered"] is False
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# 冷却递减
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assert data["world_state"]["global_meter"]["cooldown"] == 4
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def test_opinion_generated_on_world_effect(client):
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"""测试世界事件触发时生成观点"""
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# 触发世界事件
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events = [
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{"type": "chaos", "text": f"chaos{i}", "user": "test", "ts": i}
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for i in range(20)
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]
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resp = client.post("/step", json={"events": events})
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data = resp.json()
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# 验证事件触发
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assert data["global_event"]["triggered"] is True
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assert len(data["world_state"]["world_effects"]) > 0
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# 验证每个 agent 都有 opinion
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for agent_id, agent in data["world_state"]["agents"].items():
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assert agent["opinion"] is not None
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assert "about" in agent["opinion"]
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assert "text" in agent["opinion"]
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assert "tick" in agent["opinion"]
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def test_opinion_only_once_per_effect(client):
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"""测试同一事件只生成一次观点"""
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# 触发世界事件
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events = [
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{"type": "chaos", "text": f"chaos{i}", "user": "test", "ts": i}
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for i in range(20)
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]
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resp = client.post("/step", json={"events": events})
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data = resp.json()
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# 记录第一次的观点
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first_opinions = {
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aid: agent["opinion"]["text"]
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for aid, agent in data["world_state"]["agents"].items()
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}
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# 再次调用 step（事件仍在持续）
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resp2 = client.post("/step", json={"events": []})
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data2 = resp2.json()
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# 观点应该保持不变（不重新生成）
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for aid, agent in data2["world_state"]["agents"].items():
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if agent["opinion"]:
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assert agent["opinion"]["text"] == first_opinions[aid]
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def test_opinion_cleared_when_no_effect(client):
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"""测试无活跃事件时观点为空"""
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resp = client.post("/step", json={"events": []})
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data = resp.json()
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# 无世界事件时，opinion 应为 None
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for agent_id, agent in data["world_state"]["agents"].items():
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assert agent["opinion"] is None
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