refactor llm config
This commit is contained in:
@@ -210,8 +210,57 @@ def serialize_phenomenon(phenomenon) -> Optional[dict]:
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"effect_desc": effect_desc
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}
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def check_llm_connectivity() -> tuple[bool, str]:
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"""
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检查 LLM 连通性
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Returns:
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(是否成功, 错误信息)
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"""
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try:
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from src.utils.llm.config import LLMMode, LLMConfig
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normal_config = LLMConfig.from_mode(LLMMode.NORMAL)
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fast_config = LLMConfig.from_mode(LLMMode.FAST)
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# 检查配置是否完整
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if not normal_config.api_key or not normal_config.base_url:
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return False, "LLM 配置不完整:请填写 API Key 和 Base URL"
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if not normal_config.model_name:
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return False, "LLM 配置不完整:请填写智能模型名称"
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# 判断是否需要测试两次
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same_model = (normal_config.model_name == fast_config.model_name and
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normal_config.base_url == fast_config.base_url and
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normal_config.api_key == fast_config.api_key)
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if same_model:
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# 只测试一次
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print(f"检测 LLM 连通性(单模型): {normal_config.model_name}")
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success, error = test_connectivity(LLMMode.NORMAL, normal_config)
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if not success:
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return False, f"连接失败:{error}"
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else:
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# 测试两次
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print(f"检测智能模型连通性: {normal_config.model_name}")
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success, error = test_connectivity(LLMMode.NORMAL, normal_config)
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if not success:
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return False, f"智能模型连接失败:{error}"
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print(f"检测快速模型连通性: {fast_config.model_name}")
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success, error = test_connectivity(LLMMode.FAST, fast_config)
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if not success:
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return False, f"快速模型连接失败:{error}"
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return True, ""
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except Exception as e:
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return False, f"连通性检测异常:{str(e)}"
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def init_game():
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"""初始化游戏世界,逻辑复用自 src/run/run.py"""
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print("正在初始化游戏世界...")
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game_map = load_cultivation_world_map()
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world = World(map=game_map, month_stamp=create_month_stamp(Year(100), Month.JANUARY))
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@@ -267,6 +316,24 @@ def init_game():
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game_instance["world"] = world
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game_instance["sim"] = sim
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print("游戏世界初始化完成!")
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# ===== LLM 连通性检测(在 simulator 运行前)=====
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print("正在检测 LLM 连通性...")
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success, error_msg = check_llm_connectivity()
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if not success:
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print(f"[警告] LLM 连通性检测失败: {error_msg}")
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print("[警告] Simulator 已暂停,等待配置 LLM...")
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game_instance["llm_check_failed"] = True
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game_instance["llm_error_message"] = error_msg
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game_instance["is_paused"] = True
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print("等待前端连接并配置 LLM...")
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else:
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print("LLM 连通性检测通过 ✓")
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game_instance["llm_check_failed"] = False
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game_instance["llm_error_message"] = ""
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game_instance["is_paused"] = False
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# ===== LLM 检测结束 =====
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async def game_loop():
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"""后台自动运行游戏循环"""
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@@ -455,6 +522,17 @@ print(f"Web dist path: {WEB_DIST_PATH}")
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@app.websocket("/ws")
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async def websocket_endpoint(websocket: WebSocket):
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await manager.connect(websocket)
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# ===== 检查 LLM 状态并通知前端 =====
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if game_instance.get("llm_check_failed", False):
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error_msg = game_instance.get("llm_error_message", "LLM 连接失败")
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await websocket.send_json({
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"type": "llm_config_required",
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"error": error_msg
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})
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print(f"已向客户端发送 LLM 配置要求: {error_msg}")
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# ===== 检测结束 =====
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try:
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while True:
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# 保持连接活跃,接收客户端指令(目前暂不处理复杂指令)
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@@ -1024,17 +1102,22 @@ def test_llm_connection(req: TestConnectionRequest):
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model_name=req.model_name
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)
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success = test_connectivity(config=config)
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success, error_msg = test_connectivity(config=config)
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if success:
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return {"status": "ok", "message": "连接成功"}
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else:
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raise HTTPException(status_code=400, detail="连接失败")
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# 返回 400 错误并附带详细的错误信息
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raise HTTPException(status_code=400, detail=error_msg)
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except HTTPException:
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# 重新抛出 HTTPException
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raise
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except Exception as e:
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# 其他未预期的错误
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raise HTTPException(status_code=500, detail=f"测试出错: {str(e)}")
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@app.post("/api/config/llm/save")
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def save_llm_config(req: LLMConfigDTO):
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async def save_llm_config(req: LLMConfigDTO):
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"""保存 LLM 配置"""
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try:
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# 1. Update In-Memory Config (Partial update)
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@@ -1075,6 +1158,24 @@ def save_llm_config(req: LLMConfigDTO):
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OmegaConf.save(conf, local_config_path)
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# ===== 如果之前 LLM 连接失败,现在恢复运行 =====
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if game_instance.get("llm_check_failed", False):
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print("检测到之前 LLM 连接失败,正在恢复 Simulator 运行...")
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# 清除失败标志并恢复运行
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game_instance["llm_check_failed"] = False
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game_instance["llm_error_message"] = ""
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game_instance["is_paused"] = False
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print("Simulator 已恢复运行 ✓")
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# 通知所有客户端刷新
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await manager.broadcast({
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"type": "game_reinitialized",
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"message": "LLM 配置成功,游戏已恢复运行"
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})
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# ===== 恢复运行结束 =====
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return {"status": "ok", "message": "配置已保存"}
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except Exception as e:
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import traceback
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@@ -1113,22 +1214,6 @@ def api_save_game(req: SaveGameRequest):
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if not world or not sim:
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raise HTTPException(status_code=503, detail="Game not initialized")
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# 这里的 existed_sects 需要从 world 或者 sim 中获取,目前简单起见,
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# 我们可以遍历地图上的宗门总部,或者如果全局有保存最好。
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# 由于 init_game 只有一次,我们需要从 world 中反推 active sects
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# 但 save_game 签名里的 existed_sects 主要是为了记录 id。
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# 实际上 world.map.regions 中包含了宗门总部信息。
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# 或者更简单的:直接从 sects_by_id 取所有? 不太对。
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# 让我们看看 save_game 实现:它主要是存 id。
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# 我们可以传入空列表,如果在 load 时能容忍的话。
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# 实际上 load_game 里:existed_sects = [sects_by_id[sid] for sid in existed_sect_ids]
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# 所以 save 时如果不传,load 时就拿不到。
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# 临时方案:遍历所有宗门,如果它有领地或者有人,就算存在。
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# 或者更粗暴:CONFIG.game.sect_num 如果没变,可以不管。
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# 最好是 world 对象上能挂载 existed_sects。
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# 暂时方案:传入所有宗门作为 existed_sects (全集),虽然有点浪费,但不丢数据。
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# 更好的方案:修改 init_game,把 existed_sects 挂载到 world 上。
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# 尝试从 world 属性获取(如果以后添加了)
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existed_sects = getattr(world, "existed_sects", [])
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if not existed_sects:
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@@ -1,9 +1,7 @@
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"""
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配置管理模块
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使用OmegaConf读取config.yml和local_config.yml
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local_config.yml的优先级更高
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"""
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from pathlib import Path
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from omegaconf import OmegaConf
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@@ -34,10 +32,11 @@ def load_config():
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config = OmegaConf.merge(base_config, local_config)
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# 把paths下的所有值pathlib化
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for key, value in config.paths.items():
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config.paths[key] = Path(value)
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if hasattr(config, "paths"):
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for key, value in config.paths.items():
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config.paths[key] = Path(value)
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return config
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# 导出配置对象
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CONFIG = load_config()
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CONFIG = load_config()
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@@ -173,7 +173,7 @@ async def call_llm_with_task_name(
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return await call_llm_with_template(template_path, infos, mode, max_retries)
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def test_connectivity(mode: LLMMode = LLMMode.NORMAL, config: Optional[LLMConfig] = None) -> bool:
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def test_connectivity(mode: LLMMode = LLMMode.NORMAL, config: Optional[LLMConfig] = None) -> tuple[bool, str]:
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"""
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测试 LLM 服务连通性 (同步版本)
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@@ -182,7 +182,7 @@ def test_connectivity(mode: LLMMode = LLMMode.NORMAL, config: Optional[LLMConfig
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config: 直接使用该配置进行测试
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Returns:
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bool: 连接成功返回 True,失败返回 False
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tuple[bool, str]: (是否成功, 错误信息),成功时错误信息为空字符串
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"""
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try:
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if config is None:
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@@ -199,7 +199,22 @@ def test_connectivity(mode: LLMMode = LLMMode.NORMAL, config: Optional[LLMConfig
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else:
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# 直接调用 requests 实现
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_call_with_requests(config, "test")
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return True
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return True, ""
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except Exception as e:
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print(f"Connectivity test failed: {e}")
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return False
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error_msg = str(e)
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print(f"Connectivity test failed: {error_msg}")
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# 解析常见错误并提供友好提示
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if "401" in error_msg or "invalid_api_key" in error_msg or "Incorrect API key" in error_msg:
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return False, "API Key 无效,请检查您的密钥是否正确"
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elif "403" in error_msg or "Forbidden" in error_msg:
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return False, "访问被拒绝,请检查您的权限或配额"
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elif "404" in error_msg:
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return False, "服务地址不存在,请检查 Base URL 是否正确"
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elif "timeout" in error_msg.lower():
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return False, "连接超时,请检查网络连接或服务地址"
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elif "Connection" in error_msg or "connect" in error_msg.lower():
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return False, "无法连接到服务器,请检查 Base URL 和网络"
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else:
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# 返回原始错误信息
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return False, error_msg
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@@ -2,13 +2,13 @@
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from enum import Enum
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from dataclasses import dataclass
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import os
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from src.utils.config import CONFIG
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class LLMMode(str, Enum):
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"""LLM 调用模式"""
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NORMAL = "normal"
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FAST = "fast"
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DEFAULT = "default"
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@dataclass(frozen=True)
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@@ -21,7 +21,7 @@ class LLMConfig:
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@classmethod
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def from_mode(cls, mode: LLMMode) -> 'LLMConfig':
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"""
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根据模式创建配置
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根据模式创建配置,从 CONFIG 读取
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Args:
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mode: LLM 调用模式
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@@ -29,36 +29,46 @@ class LLMConfig:
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Returns:
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LLMConfig: 配置对象
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"""
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from src.utils.config import CONFIG
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# 从 CONFIG 读取配置
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api_key = getattr(CONFIG.llm, "key", "")
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base_url = getattr(CONFIG.llm, "base_url", "")
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# 根据模式选择模型
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model_name = (
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CONFIG.llm.model_name if mode == LLMMode.NORMAL
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else CONFIG.llm.fast_model_name
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)
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# API Key 优先从环境变量读取
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api_key = CONFIG.llm.key
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model_name = ""
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if mode == LLMMode.FAST:
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model_name = getattr(CONFIG.llm, "fast_model_name", "")
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else:
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# NORMAL or DEFAULT fallback
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model_name = getattr(CONFIG.llm, "model_name", "")
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return cls(
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model_name=model_name,
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api_key=api_key,
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base_url=CONFIG.llm.base_url
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base_url=base_url
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)
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def get_task_mode(task_name: str) -> LLMMode:
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"""
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获取指定任务的 LLM 调用模式
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Args:
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task_name: 任务名称 (配置在 llm.default_modes 下的 key)
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Returns:
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LLMMode: 对应的模式,如果未配置则默认返回 NORMAL
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根据任务名称获取 LLM 模式
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"""
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from src.utils.config import CONFIG
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# 从 CONFIG 读取全局模式
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global_mode = getattr(CONFIG.llm, "mode", "default").lower()
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# 获取配置的模式字符串,默认 normal
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mode_str = getattr(CONFIG.llm.default_modes, task_name, "normal")
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return LLMMode(mode_str)
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if global_mode == "normal":
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return LLMMode.NORMAL
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elif global_mode == "fast":
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return LLMMode.FAST
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# Default 模式:根据 task_name 从细粒度配置中获取
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# 如果配置了 default_modes,则根据任务名称返回对应模式
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default_modes = getattr(CONFIG.llm, "default_modes", {})
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if default_modes and task_name in default_modes:
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task_mode = default_modes[task_name].lower()
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if task_mode == "fast":
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return LLMMode.FAST
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else:
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return LLMMode.NORMAL
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# 如果没有配置,默认返回 NORMAL
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return LLMMode.NORMAL
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