f395309207
- Add providers.py with 5 provider presets (OpenAI, DeepSeek, Xiaomi MiMo, Alibaba DashScope, MiniMax) - Add LLM_PROVIDER env var for one-line provider switching - Improve <think> tag stripping for reasoning models - Add .env.example with documented configuration - Update README with provider configuration section
134 lines
4.7 KiB
Python
134 lines
4.7 KiB
Python
"""
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配置管理
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统一从项目根目录的 .env 文件加载配置
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"""
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import os
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from dotenv import load_dotenv
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# 加载项目根目录的 .env 文件
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# 路径: MiroFish/.env (相对于 backend/app/config.py)
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project_root_env = os.path.join(os.path.dirname(__file__), '../../.env')
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if os.path.exists(project_root_env):
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load_dotenv(project_root_env, override=True)
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else:
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# 如果根目录没有 .env，尝试加载环境变量（用于生产环境）
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load_dotenv(override=True)
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def _resolve_llm_config() -> tuple[str, str, str | None]:
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"""
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解析LLM配置。
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优先级：
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1. 如果设置了 LLM_PROVIDER，使用提供商预设填充 base_url 和 model（但可被显式值覆盖）
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2. 否则使用 LLM_BASE_URL / LLM_MODEL_NAME（兼容原有行为）
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Returns:
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(base_url, model_name, provider_name_or_none)
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"""
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from .providers import get_provider
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provider_name = os.environ.get('LLM_PROVIDER', '').strip()
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explicit_base_url = os.environ.get('LLM_BASE_URL', '').strip()
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explicit_model = os.environ.get('LLM_MODEL_NAME', '').strip()
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if provider_name:
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preset = get_provider(provider_name)
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if preset is None:
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provider_names = ["openai", "deepseek", "xiaomi_mimo", "alibaba_dashscope", "minimax"]
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available = ", ".join(provider_names)
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raise ValueError(
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f"未知的 LLM_PROVIDER: '{provider_name}'. "
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f"可用值: {available}"
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)
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# 显式值优先于预设默认值
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base_url = explicit_base_url or preset.base_url
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model = explicit_model or preset.default_model
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return base_url, model, provider_name
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else:
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# 兼容原有行为：无 LLM_PROVIDER 时直接使用显式值
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base_url = explicit_base_url or 'https://api.openai.com/v1'
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model = explicit_model or 'gpt-4o-mini'
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return base_url, model, None
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# 在模块加载时解析配置（避免重复计算）
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_llm_base_url, _llm_model_name, _llm_provider = _resolve_llm_config()
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class Config:
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"""Flask配置类"""
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# Flask配置
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SECRET_KEY = os.environ.get('SECRET_KEY', 'mirofish-secret-key')
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DEBUG = os.environ.get('FLASK_DEBUG', 'True').lower() == 'true'
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# JSON配置 - 禁用ASCII转义，让中文直接显示（而不是 \uXXXX 格式）
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JSON_AS_ASCII = False
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# LLM配置（统一使用OpenAI格式）
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LLM_API_KEY = os.environ.get('LLM_API_KEY')
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LLM_PROVIDER = _llm_provider # e.g. "deepseek" or None
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LLM_BASE_URL = _llm_base_url
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LLM_MODEL_NAME = _llm_model_name
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# Zep配置
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ZEP_API_KEY = os.environ.get('ZEP_API_KEY')
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# 文件上传配置
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MAX_CONTENT_LENGTH = 50 * 1024 * 1024 # 50MB
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UPLOAD_FOLDER = os.path.join(os.path.dirname(__file__), '../uploads')
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ALLOWED_EXTENSIONS = {'pdf', 'md', 'txt', 'markdown'}
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# 文本处理配置
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DEFAULT_CHUNK_SIZE = 500 # 默认切块大小
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DEFAULT_CHUNK_OVERLAP = 50 # 默认重叠大小
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# OASIS模拟配置
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OASIS_DEFAULT_MAX_ROUNDS = int(os.environ.get('OASIS_DEFAULT_MAX_ROUNDS', '10'))
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OASIS_SIMULATION_DATA_DIR = os.path.join(os.path.dirname(__file__), '../uploads/simulations')
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# OASIS平台可用动作配置
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OASIS_TWITTER_ACTIONS = [
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'CREATE_POST', 'LIKE_POST', 'REPOST', 'FOLLOW', 'DO_NOTHING', 'QUOTE_POST'
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]
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OASIS_REDDIT_ACTIONS = [
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'LIKE_POST', 'DISLIKE_POST', 'CREATE_POST', 'CREATE_COMMENT',
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'LIKE_COMMENT', 'DISLIKE_COMMENT', 'SEARCH_POSTS', 'SEARCH_USER',
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'TREND', 'REFRESH', 'DO_NOTHING', 'FOLLOW', 'MUTE'
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]
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# Report Agent配置
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REPORT_AGENT_MAX_TOOL_CALLS = int(os.environ.get('REPORT_AGENT_MAX_TOOL_CALLS', '5'))
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REPORT_AGENT_MAX_REFLECTION_ROUNDS = int(os.environ.get('REPORT_AGENT_MAX_REFLECTION_ROUNDS', '2'))
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REPORT_AGENT_TEMPERATURE = float(os.environ.get('REPORT_AGENT_TEMPERATURE', '0.5'))
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@classmethod
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def validate(cls) -> list[str]:
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"""验证必要配置"""
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errors: list[str] = []
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if not cls.LLM_API_KEY:
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errors.append("LLM_API_KEY 未配置")
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if not cls.ZEP_API_KEY:
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errors.append("ZEP_API_KEY 未配置")
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return errors
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@classmethod
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def get_active_provider_info(cls) -> dict:
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"""返回当前活跃的LLM提供商信息（用于日志/API展示）"""
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from .providers import get_provider
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info = {
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"provider": cls.LLM_PROVIDER or "custom",
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"base_url": cls.LLM_BASE_URL,
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"model": cls.LLM_MODEL_NAME,
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}
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if cls.LLM_PROVIDER:
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preset = get_provider(cls.LLM_PROVIDER)
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if preset:
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info["display_name"] = preset.display_name
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info["notes"] = preset.notes
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return info
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