dazhuang
04f7d372ea
- Add HF_ENDPOINT configuration option - Set HuggingFace mirror to https://hf-mirror.com - Fix 'cannot connect to huggingface.co' error - Update .env.example with HF_ENDPOINT setting Problem: - RAG engine uses sentence-transformers model - Model download requires connection to huggingface.co - China network cannot access huggingface.co - Error: 'We couldn't connect to https://huggingface.co' Solution: - Add HF_ENDPOINT environment variable support - Use hf-mirror.com as HuggingFace mirror - Set mirror before loading sentence-transformers - Document in .env.example Files: - backend/app/config.py: add HF_ENDPOINT config - backend/app/core/rag_engine.py: set HF_ENDPOINT before model load - backend/setup_hf_mirror.sh: setup script - backend/.env: configure mirror (not tracked)
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
from pydantic_settings import BaseSettings
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from pydantic import ConfigDict, field_validator
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from functools import lru_cache
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from urllib.parse import quote_plus
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class Settings(BaseSettings):
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# Application
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APP_NAME: str = "ERP AI Assistant"
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APP_ENV: str = "development"
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DEBUG: bool = True
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SECRET_KEY: str
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# Database
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DB_DRIVER: str
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DB_SERVER: str
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DB_PORT: int = 1433
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DB_NAME: str
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DB_USER: str
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DB_PASSWORD: str
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# Claude API
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ANTHROPIC_API_KEY: str
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ANTHROPIC_BASE_URL: str | None = None # Optional custom base URL for proxy/self-hosted
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CLAUDE_MODEL: str = "claude-sonnet-4-6"
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CLAUDE_MAX_TOKENS: int = 8192
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CLAUDE_TEMPERATURE: float = 0.7
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# Knowledge Base
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KNOWLEDGE_BASE_PATH: str = "./knowledge_base"
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CHROMA_DB_PATH: str = "./knowledge_base/chroma_db"
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EMBEDDING_MODEL: str = "all-MiniLM-L6-v2"
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CHUNK_SIZE: int = 500
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CHUNK_OVERLAP: int = 50
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# HuggingFace
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HF_ENDPOINT: str | None = None # Optional: HuggingFace mirror endpoint
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@property
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def DATABASE_URL(self) -> str:
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"""构建数据库连接 URL（密码安全编码）"""
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password = quote_plus(self.DB_PASSWORD)
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return (
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f"mssql+pyodbc://{self.DB_USER}:{password}"
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f"@{self.DB_SERVER}:{self.DB_PORT}/{self.DB_NAME}"
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f"?driver={quote_plus(self.DB_DRIVER)}"
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)
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@field_validator('CLAUDE_TEMPERATURE')
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@classmethod
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def validate_temperature(cls, v):
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if not 0 <= v <= 2:
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raise ValueError('CLAUDE_TEMPERATURE must be between 0 and 2')
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return v
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@field_validator('CHUNK_OVERLAP')
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@classmethod
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def validate_chunk_overlap(cls, v, info):
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chunk_size = info.data.get('CHUNK_SIZE', 500)
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if v >= chunk_size:
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raise ValueError('CHUNK_OVERLAP must be less than CHUNK_SIZE')
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return v
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model_config = ConfigDict(env_file=".env", case_sensitive=True)
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@lru_cache()
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def get_settings() -> Settings:
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"""获取配置单例"""
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return Settings()
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