449 lines
16 KiB
Python
449 lines
16 KiB
Python
#!/usr/bin/env python3
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"""
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main.py — EzVibe AI 桌宠系统主入口
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===================================
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用法:
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python main.py # 完整启动（PySide6 窗口 + 所有模块）
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python main.py --dummy # Dummy 模式（headless，无需 Qt）
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python main.py --server # 仅启动 API 服务器
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依赖:
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pip install -r requirements.txt
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import atexit
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import os
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import signal
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import sys
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import threading
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from pathlib import Path
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# 确保项目根目录在 sys.path
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_ROOT = Path(__file__).parent.resolve()
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sys.path.insert(0, str(_ROOT))
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# Linux: 必须在任何 Qt 模块导入之前设置平台
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if sys.platform.startswith("linux") and os.environ.get("QT_QPA_PLATFORM") is None:
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os.environ["QT_QPA_PLATFORM"] = "xcb"
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# ============================================================================
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# 组件导入
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# ============================================================================
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from agent.emotion import EmotionEngine
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from agent.memory import VectorMemory
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from agent.scheduler import BehaviorScheduler
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from perception import (
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KeyboardMouseMonitor,
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ScreenCapture,
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get_global_monitor,
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stop_global_monitor,
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)
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from ui.pet_window import create_pet_window, DummyPetWindow
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# brain 和 api 延迟导入（避免 dummy 模式下不必要的依赖）
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_brain_module = None
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_api_module = None
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def _get_brain():
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global _brain_module
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if _brain_module is None:
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from agent import brain as _brain_module
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return _brain_module
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def _get_api():
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global _api_module
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if _api_module is None:
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from api import server as _api_module
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return _api_module
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# ============================================================================
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# EzVibeApp — 整合所有模块
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# ============================================================================
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class EzVibeApp:
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"""
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桌宠应用主控制器。
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负责初始化各层组件并协调生命周期：
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1. 初始化情绪引擎（EmotionEngine）
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2. 初始化记忆系统（VectorMemory）
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3. 初始化 LLM 大脑（AgentBrain）
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4. 初始化感知层（KeyboardMouseMonitor）
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5. 初始化行为调度器（BehaviorScheduler）
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6. 初始化桌宠窗口（PetWindow）
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7. 启动 API 服务器（可选）
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8. Qt 事件循环 + asyncio 并行运行
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"""
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def __init__(
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self,
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llm_backend: str = "dummy",
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llm_config: dict | None = None,
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use_dummy_window: bool = False,
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start_api_server: bool = False,
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api_port: int = 8765,
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assets_dir: str | Path | None = None,
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) -> None:
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self._llm_backend = llm_backend
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self._llm_config = llm_config or {}
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self._use_dummy = use_dummy_window
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self._start_api = start_api_server
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self._api_port = api_port
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self._assets_dir = assets_dir
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# ── 核心组件（延迟初始化） ─────────────────────────────────────
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self._emotion: EmotionEngine | None = None
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self._memory: VectorMemory | None = None
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self._brain = None
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self._scheduler: BehaviorScheduler | None = None
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self._monitor: KeyboardMouseMonitor | None = None
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self._screen: ScreenCapture | None = None
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self._window: DummyPetWindow | None = None
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self._api_server = None
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# ── 异步基础设施 ─────────────────────────────────────────────
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self._loop: asyncio.AbstractEventLoop | None = None
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self._api_thread: threading.Thread | None = None
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# 初始化
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self._init_components()
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# ── 初始化 ────────────────────────────────────────────────────────────
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def _init_components(self) -> None:
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"""同步初始化所有组件。"""
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print("[EzVibe] 初始化组件 ...")
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# 1. 情绪引擎
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self._emotion = EmotionEngine()
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print(f" [✓] EmotionEngine: {self._emotion.get_state()}")
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# 2. 记忆系统（embedder_backend="dummy" 避免依赖 Ollama）
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self._memory = VectorMemory(
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storage_path="data/MEMORY.db",
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embedder_backend="dummy",
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vector_mode="numpy",
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)
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# VectorMemory.initialize() 是 async，但也可以同步调用
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# 这里在同步初始化（因为我们还没有事件循环）
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try:
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import asyncio
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asyncio.run(self._memory.initialize())
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except RuntimeError:
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# 如果已经在事件循环中，用 run_in_executor
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pass
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print(" [✓] VectorMemory initialized")
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# 3. LLM 大脑
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brain_mod = _get_brain()
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self._brain = brain_mod.AgentBrain(
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llm_backend=self._llm_backend,
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llm_config=self._llm_config,
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emotion_engine=self._emotion,
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memory=self._memory,
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)
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print(f" [✓] AgentBrain: {self._llm_backend}")
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# 4. 感知层
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self._monitor = get_global_monitor(
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window_seconds=300.0,
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idle_timeout=60.0,
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)
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self._screen = ScreenCapture()
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print(" [✓] KeyboardMouseMonitor started")
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# 5. 行为调度器
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# BehaviorScheduler 内部有自己的 ActivityDetector，
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# 但 perception 层的 KeyboardMouseMonitor 也有一个。
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# 这里让 scheduler 使用 monitor 自己的 _activity，
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# 需要确保接口兼容（perception ActivityDetector 有 activity_level @property）。
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self._scheduler = BehaviorScheduler(
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emotion_engine=self._emotion,
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activity_detector=self._monitor._activity,
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)
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print(" [✓] BehaviorScheduler initialized")
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# 6. 桌宠窗口（延迟创建，见 _run_qt）
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# 注意：PetWindow.__init__ 需要 QApplication，所以不能在这里调用 create_pet_window
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self._window = None
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# 注册退出清理
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atexit.register(self.shutdown)
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# ── API 服务器（可选，后台线程） ──────────────────────────────────────
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def _start_api_server(self) -> None:
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"""在后台线程启动 FastAPI 服务器。"""
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api_mod = _get_api()
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# 注意：APIServer 需要 emotion + brain
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self._api_server = api_mod.APIServer(
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emotion_engine=self._emotion,
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brain=self._brain,
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memory=self._memory,
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scheduler=self._scheduler,
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port=self._api_port,
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)
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self._api_thread = threading.Thread(
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target=self._api_server.run,
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daemon=True,
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name="ezvibe-api",
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)
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self._api_thread.start()
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print(f" [✓] APIServer started on http://127.0.0.1:{self._api_port}")
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# ── 行为调度集成 ──────────────────────────────────────────────────────
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def _run_scheduler_loop(self) -> None:
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"""
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定期调用 scheduler.check_and_trigger()（async）。
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每次触发时：显示提醒、记录到记忆。
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"""
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import time
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while getattr(self, "_running", False):
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try:
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if self._scheduler and self._monitor:
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activity = self._monitor.get_activity()
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# check_and_trigger 是 async
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triggered: list[dict] = asyncio.run(
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self._scheduler.check_and_trigger(user_activity_level=activity)
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)
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for action in triggered:
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# 显示提醒
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self._window.show_reminder(
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action.get("message", ""),
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priority=action.get("priority", 1),
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)
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# 记录到记忆（async add）
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try:
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asyncio.run(
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self._memory.add(
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text=f"[SCHEDULER] {action.get('type')}: {action.get('message', '')}",
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tags=["behavior", action.get("type", "unknown")],
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)
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)
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except Exception:
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pass
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except Exception as e:
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print(f"[EzVibe] Scheduler error: {e}")
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time.sleep(10) # 每 10 秒检查一次
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# ── 主运行循环 ─────────────────────────────────────────────────────────
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def run(self) -> None:
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"""启动应用。Dummy 模式和 Qt 模式共用同一套初始化。"""
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self._running = True
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print(f"\n[EzVibe] 启动中 ... (mode={'dummy' if self._use_dummy else 'full'})\n")
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# API 服务器（可选）
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if self._start_api:
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self._start_api_server()
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# 调度循环（后台线程）
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scheduler_thread = threading.Thread(
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target=self._run_scheduler_loop,
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daemon=True,
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name="ezvibe-scheduler",
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)
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scheduler_thread.start()
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if self._use_dummy:
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self._run_dummy()
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else:
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self._run_qt()
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def _run_dummy(self) -> None:
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"""Dummy 模式：显示状态摘要后退出。"""
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print("\n" + "=" * 50)
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print("EzVibe 桌宠 — Dummy 模式")
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print("=" * 50)
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print(f" 情绪状态 : {self._emotion.get_state()}")
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print(f" 活跃度 : {self._monitor.get_activity():.2f}")
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print(f" 调度器 : ready")
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# 记忆条目数
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try:
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n_mem = self._memory._store.count()
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print(f" [✓] VectorMemory: {n_mem} entries")
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except Exception as e:
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print(f" [!] VectorMemory: {e}")
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print("=" * 50)
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print("\n模拟一次主动行为触发：")
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triggered: list[dict] = asyncio.run(
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self._scheduler.check_and_trigger(user_activity_level=0.05)
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)
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if triggered:
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for action in triggered:
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print(f" → 触发行为: {action.get('type')} — {action.get('message', '')}")
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self._window.show_reminder(action.get("message", ""), priority=action.get("priority", 1))
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else:
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print(" → 无行为触发（正常，取决于情绪和冷却状态）")
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print("\nDummy 模式完成。")
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print("要运行完整 GUI：python main.py")
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self.shutdown()
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def _run_qt(self) -> None:
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"""Qt 模式：启动 PySide6/PyQt6 事件循环。"""
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try:
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from PySide6 import QtWidgets
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except ImportError:
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try:
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from PyQt6 import QtWidgets
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except ImportError:
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print("错误：需要 PySide6 或 PyQt6")
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print("安装：pip install PySide6")
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sys.exit(1)
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# Linux: 强制使用 XCB 平台插件（Wayland 兼容性问题）
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if sys.platform.startswith("linux") and os.environ.get("QT_QPA_PLATFORM") is None:
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os.environ["QT_QPA_PLATFORM"] = "xcb"
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app = QtWidgets.QApplication(sys.argv)
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app.setApplicationName("EzVibe")
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app.setApplicationDisplayName("EzVibe 桌宠")
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print(f"[EzVibe] Qt 平台: {app.platformName()}")
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# ★ 现在 QApplication 已存在，创建桌宠窗口（必须在 QApplication 之后）
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from ui.pet_window import create_pet_window
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self._window = create_pet_window(
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emotion_engine=self._emotion,
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brain=self._brain,
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scheduler=self._scheduler,
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assets_dir=self._assets_dir,
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force_dummy=self._use_dummy,
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)
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if self._use_dummy:
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print(" [✓] PetWindow: DummyPetWindow (headless mode)")
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else:
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from ui.pet_window import _load_qt
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qt_lib = _load_qt()
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print(f" [✓] PetWindow: {type(self._window).__name__} (Qt={qt_lib})")
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# Ctrl-C (SIGINT) → 优雅退出 Qt 事件循环
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def _sigint_handler(signum, frame):
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print("\n[EzVibe] 收到 Ctrl+C，正在关闭 ...")
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app.quit()
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signal.signal(signal.SIGINT, _sigint_handler)
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# 显示窗口
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self._window.show()
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print(f"[EzVibe] 窗口 visible={self._window.isVisible()} geometry={self._window.geometry()}")
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# Qt 事件循环（主线程）
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# 同时嵌入 asyncio
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self._loop = asyncio.new_event_loop()
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asyncio.set_event_loop(self._loop)
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def _run_async():
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"""每个 Qt 事件循环迭代运行一次 asyncio。"""
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try:
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self._loop.run_until_complete(asyncio.sleep(0))
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except Exception:
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pass
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from PySide6.QtCore import QTimer
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timer = QTimer(app)
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timer.timeout.connect(_run_async)
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timer.setInterval(20) # 50 Hz
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timer.start()
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print("[EzVibe] 桌宠已显示。右键点击切换情绪。")
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print("[EzVibe] 按 Ctrl+C 或关闭窗口退出。")
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app.exec()
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self._running = False
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self.shutdown()
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# ── 生命周期 ──────────────────────────────────────────────────────────
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def shutdown(self) -> None:
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"""优雅关闭所有组件。"""
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self._running = False
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print("\n[EzVibe] 正在关闭 ...")
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# 停止 monitor
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stop_global_monitor()
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# 停止窗口
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if self._window:
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try:
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self._window.close()
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except Exception:
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pass
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# 关闭事件循环
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if self._loop and self._loop.is_running():
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self._loop.stop()
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print("[EzVibe] 已关闭。")
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# ============================================================================
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# CLI 入口
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# ============================================================================
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def main():
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parser = argparse.ArgumentParser(
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description="EzVibe AI 桌宠系统",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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示例:
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python main.py # 完整 GUI 模式
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python main.py --dummy # Headless 测试
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python main.py --server --port 8765 # 仅 API 服务器
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python main.py --llm ollama # 使用 Ollama
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""",
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)
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parser.add_argument(
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"--dummy", action="store_true",
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help="使用 DummyPetWindow（无需图形界面）"
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)
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parser.add_argument(
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"--server", action="store_true",
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help="启动 FastAPI REST/WebSocket 服务器"
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)
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parser.add_argument(
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"--port", type=int, default=8765,
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help="API 服务器端口（默认 8765）"
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)
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parser.add_argument(
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"--llm",
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choices=["ollama", "openai", "dummy"],
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default="dummy",
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help="LLM 后端（默认 dummy）"
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)
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parser.add_argument(
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"--assets",
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type=Path,
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default=None,
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help="桌宠图像资源目录"
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)
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args = parser.parse_args()
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app = EzVibeApp(
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llm_backend=args.llm,
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use_dummy_window=args.dummy,
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start_api_server=args.server,
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api_port=args.port,
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assets_dir=args.assets,
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)
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app.run()
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if __name__ == "__main__":
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main()
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