68 lines
1.7 KiB
Python
68 lines
1.7 KiB
Python
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"""Configuration centralisée via Pydantic Settings."""
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from functools import lru_cache
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from pydantic_settings import BaseSettings
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from pydantic import field_validator
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from typing import List
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class Settings(BaseSettings):
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# Serveur
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backend_host: str = "127.0.0.1"
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backend_port: int = 8000
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debug: bool = True
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secret_key: str = "changeme"
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# Base de données
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database_url: str = "sqlite:///./data/hsbg_ai.db"
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# LLM
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llm_provider: str = "ollama"
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llm_base_url: str = "http://localhost:11434"
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llm_model: str = "llama3.2"
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llm_fallback_model: str = "mistral"
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llm_timeout: int = 30
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llm_max_tokens: int = 2048
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llm_temperature: float = 0.1
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# Vision
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vision_enabled: bool = True
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screenshot_interval: float = 2.0
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tesseract_path: str = "/usr/bin/tesseract"
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# Apprentissage
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learning_enabled: bool = True
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learning_rate: float = 0.001
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learning_batch_size: int = 32
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learning_auto_save: bool = True
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learning_save_interval: int = 300
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# Frontend
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frontend_host: str = "127.0.0.1"
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frontend_port: int = 3000
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cors_origins: List[str] = ["http://localhost:3000", "http://127.0.0.1:3000"]
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# Logs
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log_level: str = "INFO"
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log_file: str = "./logs/hsbg_ai.log"
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# Data
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hsbg_data_path: str = "./data/hsbg"
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current_patch: str = "30.2"
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@field_validator("cors_origins", mode="before")
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@classmethod
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def parse_cors(cls, v):
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if isinstance(v, str):
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return [x.strip() for x in v.split(",")]
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return v
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class Config:
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env_file = ".env"
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env_file_encoding = "utf-8"
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case_sensitive = False
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@lru_cache()
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def get_settings() -> Settings:
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return Settings()
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