5ae63d9df9
- 扩展 AgentState 添加 action_points, max_action_points, last_action_tick 字段 - 新增 ActionFeedback 模型用于返回行动执行结果 - 创建 action_points.py 模块实现行动点消耗与恢复逻辑 - 行动消耗表: vote=1, trigger_skill=2, influence=2, comment/support/chaos=0 - 每 tick 恢复 1 点行动点（不超过 max） - 行动点不足时拒绝执行并返回失败反馈 - 新增 7 个测试用例，全部 37 个测试通过 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
from fastapi import FastAPI
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from .models import StepRequest, StepResponse
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from .state import load_state, save_state
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from .engine import process_events, generate_actions, check_and_trigger_global_event
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from .factions import check_and_trigger_faction_event
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from .story_arcs import update_story_progress, check_and_trigger_story_event
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app = FastAPI(title="AI Town Engine", version="0.1.0")
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@app.post("/step", response_model=StepResponse)
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def step(request: StepRequest) -> StepResponse:
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"""执行一个模拟步骤"""
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# 加载当前状态
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state = load_state()
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# 处理事件并更新状态，获取行动反馈
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state, action_feedbacks = process_events(state, request.events)
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# 检查并触发世界级事件
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state, global_event_result = check_and_trigger_global_event(state)
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# 检查并触发阵营事件
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faction_event_result = check_and_trigger_faction_event(state)
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# 更新剧情进度
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update_story_progress(state)
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# 检查并触发剧情事件
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story_event_result = check_and_trigger_story_event(state)
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# 生成 agent 行动
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actions = generate_actions(state)
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# 保存状态
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save_state(state)
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return StepResponse(
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world_state=state,
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actions=actions,
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global_event=global_event_result,
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triggered_faction_event=faction_event_result,
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story_event=story_event_result,
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action_feedbacks=action_feedbacks
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)
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@app.get("/health")
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def health():
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"""健康检查"""
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return {"status": "ok"}
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