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# -*- coding: utf-8 -*-
"""
微舆配置文件
此模块使用 pydantic-settings 管理全局配置,支持从环境变量和 .env 文件自动加载。
数据模型定义位置:
- 本文件 - 配置模型定义
"""
from pathlib import Path
from pydantic_settings import BaseSettings
from pydantic import Field, ConfigDict
from typing import Optional
from loguru import logger
# 计算 .env 优先级:优先当前工作目录,其次项目根目录
PROJECT_ROOT: Path = Path(__file__).resolve().parent
CWD_ENV: Path = Path.cwd() / ".env"
ENV_FILE: str = str(CWD_ENV if CWD_ENV.exists() else (PROJECT_ROOT / ".env"))
class Settings(BaseSettings):
"""
全局配置;支持 .env 和环境变量自动加载。
变量名与原 config.py 大写一致,便于平滑过渡。
"""
# ================== Flask 服务器配置 ====================
HOST: str = Field("0.0.0.0", description="Flask服务器主机地址,默认0.0.0.0(允许外部访问)")
PORT: int = Field(5000, description="Flask服务器端口号,默认5000")
# ====================== 数据库配置 ======================
DB_DIALECT: str = Field("mysql", description="数据库类型,例如 'mysql' 或 'postgresql'。用于支持多种数据库后端(如 SQLAlchemy,请与连接信息共同配置)")
DB_HOST: str = Field("your_db_host", description="数据库主机,例如localhost 或 127.0.0.1。我们也提供云数据库资源便捷配置,日均10w+数据,可免费申请,联系我们:670939375@qq.com NOTE:为进行数据合规性审查与服务升级,云数据库自2025年10月1日起暂停接收新的使用申请")
DB_PORT: int = Field(3306, description="数据库端口号,默认为3306")
DB_USER: str = Field("your_db_user", description="数据库用户名")
DB_PASSWORD: str = Field("your_db_password", description="数据库密码")
DB_NAME: str = Field("your_db_name", description="数据库名称")
DB_CHARSET: str = Field("utf8mb4", description="数据库字符集,推荐utf8mb4,兼容emoji")
# ======================= LLM 相关 =======================
# 我们的LLM模型API赞助商有:https://share.302.ai/P66Qe3、https://aihubmix.com/?aff=8Ds9,提供了非常全面的模型api
# Insight Agent(推荐Kimi,申请地址:https://platform.moonshot.cn/)
INSIGHT_ENGINE_API_KEY: Optional[str] = Field(None, description="Insight Agent(推荐Kimi,https://platform.moonshot.cn/)API密钥,用于主LLM。您可以更改每个部分LLM使用的API,🚩只要兼容OpenAI请求格式都可以,定义好KEY、BASE_URL与MODEL_NAME即可正常使用。重要提醒:我们强烈推荐您先使用推荐的配置申请API,先跑通再进行您的更改!")
INSIGHT_ENGINE_BASE_URL: Optional[str] = Field("https://api.moonshot.cn/v1", description="Insight Agent LLM接口BaseUrl,可自定义厂商API")
INSIGHT_ENGINE_MODEL_NAME: str = Field("kimi-k2-0711-preview", description="Insight Agent LLM模型名称,如kimi-k2-0711-preview")
# Media Agent(推荐Gemini,推荐中转厂商:https://aihubmix.com/?aff=8Ds9)
MEDIA_ENGINE_API_KEY: Optional[str] = Field(None, description="Media Agent(推荐Gemini,推荐中转api厂商:https://aihubmix.com/?aff=8Ds9")
MEDIA_ENGINE_BASE_URL: Optional[str] = Field("https://aihubmix.com/v1", description="Media Agent LLM接口BaseUrl")
MEDIA_ENGINE_MODEL_NAME: str = Field("gemini-2.5-pro", description="Media Agent LLM模型名称,如gemini-2.5-pro")
# Query Agent(推荐DeepSeek,申请地址:https://www.deepseek.com/)
QUERY_ENGINE_API_KEY: Optional[str] = Field(None, description="Query Agent(推荐DeepSeek,https://www.deepseek.com/)API密钥")
QUERY_ENGINE_BASE_URL: Optional[str] = Field("https://api.deepseek.com", description="Query Agent LLM接口BaseUrl")
QUERY_ENGINE_MODEL_NAME: str = Field("deepseek-reasoner", description="Query Agent LLM模型,如deepseek-reasoner")
# Report Agent(推荐Gemini,推荐中转厂商:https://aihubmix.com/?aff=8Ds9)
REPORT_ENGINE_API_KEY: Optional[str] = Field(None, description="Report Agent(推荐Gemini,推荐中转api厂商:https://aihubmix.com/?aff=8Ds9")
REPORT_ENGINE_BASE_URL: Optional[str] = Field("https://aihubmix.com/v1", description="Report Agent LLM接口BaseUrl")
REPORT_ENGINE_MODEL_NAME: str = Field("gemini-2.5-pro", description="Report Agent LLM模型,如gemini-2.5-pro")
# Forum Host(Qwen3最新模型,这里我使用了硅基流动这个平台,申请地址:https://cloud.siliconflow.cn/)
FORUM_HOST_API_KEY: Optional[str] = Field(None, description="Forum Host(Qwen3最新模型,这里我使用了硅基流动这个平台,申请地址:https://cloud.siliconflow.cn/)API密钥")
FORUM_HOST_BASE_URL: Optional[str] = Field("https://api.siliconflow.cn/v1", description="Forum Host LLM BaseUrl")
FORUM_HOST_MODEL_NAME: str = Field("Qwen/Qwen3-235B-A22B-Instruct-2507", description="Forum Host LLM模型名,如Qwen/Qwen3-235B-A22B-Instruct-2507")
# SQL keyword Optimizer(小参数Qwen3模型,这里我使用了硅基流动这个平台,申请地址:https://cloud.siliconflow.cn/)
KEYWORD_OPTIMIZER_API_KEY: Optional[str] = Field(None, description="SQL keyword Optimizer(小参数Qwen3模型,这里我使用了硅基流动这个平台,申请地址:https://cloud.siliconflow.cn/)API密钥")
KEYWORD_OPTIMIZER_BASE_URL: Optional[str] = Field("https://api.siliconflow.cn/v1", description="Keyword Optimizer BaseUrl")
KEYWORD_OPTIMIZER_MODEL_NAME: str = Field("Qwen/Qwen3-30B-A3B-Instruct-2507", description="Keyword Optimizer LLM模型名称,如Qwen/Qwen3-30B-A3B-Instruct-2507")
# ================== 网络工具配置 ====================
# Tavily API(申请地址:https://www.tavily.com/)
TAVILY_API_KEY: Optional[str] = Field(None, description="Tavily API(申请地址:https://www.tavily.com/)API密钥,用于Tavily网络搜索")
BOCHA_BASE_URL: Optional[str] = Field("https://api.bochaai.com/v1/ai-search", description="Bocha AI 搜索BaseUrl或博查网页搜索BaseUrl")
# Bocha API(申请地址:https://open.bochaai.com/)
BOCHA_WEB_SEARCH_API_KEY: Optional[str] = Field(None, description="Bocha API(申请地址:https://open.bochaai.com/)API密钥,用于Bocha搜索")
# ================== Insight Engine 搜索配置 ====================
DEFAULT_SEARCH_HOT_CONTENT_LIMIT: int = Field(100, description="热榜内容默认最大数")
DEFAULT_SEARCH_TOPIC_GLOBALLY_LIMIT_PER_TABLE: int = Field(50, description="按表全局话题最大数")
DEFAULT_SEARCH_TOPIC_BY_DATE_LIMIT_PER_TABLE: int = Field(100, description="按日期话题最大数")
DEFAULT_GET_COMMENTS_FOR_TOPIC_LIMIT: int = Field(500, description="单话题评论最大数")
DEFAULT_SEARCH_TOPIC_ON_PLATFORM_LIMIT: int = Field(200, description="平台搜索话题最大数")
MAX_SEARCH_RESULTS_FOR_LLM: int = Field(0, description="供LLM用搜索结果最大数")
MAX_HIGH_CONFIDENCE_SENTIMENT_RESULTS: int = Field(0, description="高置信度情感分析最大数")
MAX_REFLECTIONS: int = Field(3, description="最大反思次数")
MAX_PARAGRAPHS: int = Field(6, description="最大段落数")
SEARCH_TIMEOUT: int = Field(240, description="单次搜索请求超时")
MAX_CONTENT_LENGTH: int = Field(500000, description="搜索最大内容长度")
model_config = ConfigDict(
env_file=ENV_FILE,
env_prefix="",
case_sensitive=False,
extra="allow"
)
# 创建全局配置实例
settings = Settings()
def reload_settings() -> Settings:
"""
重新加载配置
从 .env 文件和环境变量重新加载配置,更新全局 settings 实例。
用于在运行时动态更新配置。
Returns:
Settings: 新创建的配置实例
"""
global settings
settings = Settings()
return settings