225 lines
8.4 KiB
Python
225 lines
8.4 KiB
Python
import json
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import os
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from pathlib import Path
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import yaml
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from src.utils.logging_config import logger
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class SimpleConfig(dict):
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def __key(self, key):
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return "" if key is None else key # 目前忘记了这里为什么要 lower 了，只能说配置项最好不要有大写的
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def __str__(self):
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return json.dumps(self)
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def __setattr__(self, key, value):
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self[self.__key(key)] = value
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def __getattr__(self, key):
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return self.get(self.__key(key))
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def __getitem__(self, key):
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return self.get(self.__key(key))
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def __setitem__(self, key, value):
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return super().__setitem__(self.__key(key), value)
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def __dict__(self):
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return {k: v for k, v in self.items()}
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def update(self, other):
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for key, value in other.items():
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self[key] = value
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class Config(SimpleConfig):
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def __init__(self):
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super().__init__()
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self._config_items = {}
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self.save_dir = os.getenv("SAVE_DIR", "saves")
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self.filename = str(Path(f"{self.save_dir}/config/base.yaml"))
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os.makedirs(os.path.dirname(self.filename), exist_ok=True)
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self._models_config_path: Path | None = os.getenv("OVERRIDE_DEFAULT_MODELS_CONFIG_WITH")
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self._update_models_from_file()
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### >>> 默认配置
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# 功能选项
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self.add_item("enable_reranker", default=False, des="是否开启重排序")
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self.add_item("enable_content_guard", default=False, des="是否启用内容审查")
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self.add_item("enable_content_guard_llm", default=False, des="是否启用LLM内容审查")
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self.add_item(
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"content_guard_llm_model", default="siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507", des="内容审查LLM模型"
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)
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# 默认智能体配置
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self.add_item("default_agent_id", default="", des="默认智能体ID")
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# 模型配置
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## 注意这里是模型名，而不是具体的模型路径，默认使用 HuggingFace 的路径
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## 如果需要自定义本地模型路径，则在 .env 中配置 MODEL_DIR
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self.add_item("model_provider", default="siliconflow", des="模型提供商", choices=list(self.model_names.keys()))
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self.add_item("model_name", default="zai-org/GLM-4.5", des="模型名称")
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self.add_item(
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"fast_model",
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default="siliconflow/THUDM/GLM-4-9B-0414",
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des="快速响应模型",
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)
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self.add_item(
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"embed_model",
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default="siliconflow/BAAI/bge-m3",
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des="Embedding 模型",
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choices=list(self.embed_model_names.keys()),
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)
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self.add_item(
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"reranker",
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default="siliconflow/BAAI/bge-reranker-v2-m3",
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des="Re-Ranker 模型",
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choices=list(self.reranker_names.keys()),
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) # noqa: E501
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### <<< 默认配置结束
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self.load()
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self.handle_self()
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def add_item(self, key, default, des=None, choices=None):
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self.__setattr__(key, default)
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self._config_items[key] = {"default": default, "des": des, "choices": choices}
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def __dict__(self):
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blocklist = [
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"_config_items",
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"model_names",
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"model_provider_status",
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"embed_model_names",
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"reranker_names",
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"_models_config_path",
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]
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return {k: v for k, v in self.items() if k not in blocklist}
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def _update_models_from_file(self):
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"""
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从 models.yaml 或覆盖配置文件中更新 MODEL_NAMES
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"""
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# 检查是否设置了覆盖配置文件的环境变量
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override_config_path = os.getenv("OVERRIDE_DEFAULT_MODELS_CONFIG_WITH")
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if override_config_path and os.path.exists(override_config_path):
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config_file = Path(override_config_path)
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logger.info(f"Using override models config from: {override_config_path}")
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else:
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config_file = Path("src/config/static/models.yaml")
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logger.info("Using default models config")
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self._models_config_path = str(config_file)
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with open(self._models_config_path, encoding="utf-8") as f:
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_models = yaml.safe_load(f)
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self.model_names = _models["MODEL_NAMES"]
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self.embed_model_names = _models["EMBED_MODEL_INFO"]
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self.reranker_names = _models["RERANKER_LIST"]
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def _save_models_to_file(self):
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"""
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将当前模型配置写回模型配置文件
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"""
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if self._models_config_path is None:
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self._models_config_path = str(Path("src/config/static/models.yaml"))
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models_payload = {
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"MODEL_NAMES": self.model_names,
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"EMBED_MODEL_INFO": self.embed_model_names,
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"RERANKER_LIST": self.reranker_names,
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}
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with open(self._models_config_path, "w", encoding="utf-8") as f:
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yaml.safe_dump(models_payload, f, indent=2, allow_unicode=True, sort_keys=False)
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def handle_self(self):
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"""
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处理配置
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"""
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self.model_dir = os.environ.get("MODEL_DIR", "")
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if self.model_dir:
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if os.path.exists(self.model_dir):
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logger.debug(
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f"The model directory （{self.model_dir}） "
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f"contains the following folders: {os.listdir(self.model_dir)}"
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)
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else:
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logger.warning(
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f"Warning: The model directory （{self.model_dir}） does not exist. "
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"If not configured, please ignore it. "
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"If configured, please check if the configuration is correct; "
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"For example, the mapping in the docker-compose file"
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)
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# 检查模型提供商的环境变量
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self.model_provider_status = {}
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for provider in self.model_names:
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env_var = self.model_names[provider]["env"]
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# 如果环境变量名为 NO_API_KEY，则认为总是可用
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if env_var == "NO_API_KEY":
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self.model_provider_status[provider] = True
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else:
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self.model_provider_status[provider] = bool(os.getenv(env_var))
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if os.getenv("TAVILY_API_KEY"):
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self.enable_web_search = True
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self.valuable_model_provider = [k for k, v in self.model_provider_status.items() if v]
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assert len(self.valuable_model_provider) > 0, "No model provider available, please check your `.env` file."
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def load(self):
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"""根据传入的文件覆盖掉默认配置"""
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logger.info(f"Loading config from {self.filename}")
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if self.filename is not None and os.path.exists(self.filename):
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if self.filename.endswith(".json"):
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with open(self.filename) as f:
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content = f.read()
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if content:
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local_config = json.loads(content)
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self.update(local_config)
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else:
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print(f"{self.filename} is empty.")
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elif self.filename.endswith(".yaml"):
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with open(self.filename) as f:
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content = f.read()
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if content:
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local_config = yaml.safe_load(content)
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self.update(local_config)
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else:
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print(f"{self.filename} is empty.")
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else:
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logger.warning(f"Unknown config file type {self.filename}")
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def save(self):
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logger.info(f"Saving config to {self.filename}")
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if self.filename is None:
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logger.warning("Config file is not specified, save to default config/base.yaml")
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self.filename = os.path.join(self.save_dir, "config", "base.yaml")
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os.makedirs(os.path.dirname(self.filename), exist_ok=True)
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if self.filename.endswith(".json"):
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with open(self.filename, "w+") as f:
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json.dump(self.__dict__(), f, indent=4, ensure_ascii=False)
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elif self.filename.endswith(".yaml"):
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with open(self.filename, "w+") as f:
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yaml.dump(self.__dict__(), f, indent=2, allow_unicode=True)
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else:
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logger.warning(f"Unknown config file type {self.filename}, save as json")
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with open(self.filename, "w+") as f:
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json.dump(self, f, indent=4)
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logger.info(f"Config file {self.filename} saved")
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def dump_config(self):
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return json.loads(str(self))
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config = Config()
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