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87 lines
2.7 KiB
Python
87 lines
2.7 KiB
Python
from pydantic import field_validator
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(
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env_file=".env",
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extra="ignore",
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)
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google_project_id: str
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google_location: str = "us-central1"
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vertex_model_name: str = "gemini-2.5-pro"
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# Tools database (MySQL)
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db_host: str = "127.0.0.1"
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db_port: int = 3306
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db_user: str = "root"
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db_password: str = ""
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db_name: str = "orquestrador_mock"
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db_cloud_sql_connection_name: str | None = None
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# Mock database (MySQL) for fictitious business data
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mock_db_host: str = "127.0.0.1"
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mock_db_port: int = 3306
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mock_db_user: str = "root"
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mock_db_password: str = ""
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mock_db_name: str = "orquestrador_mock"
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mock_db_cloud_sql_connection_name: str | None = None
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mock_seed_enabled: bool = True
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auto_seed_tools: bool = True
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auto_seed_mock: bool = True
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environment: str = "production"
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debug: bool = False
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# Cloud SQL (legacy Postgres var kept only for backward compatibility in deploy scripts)
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cloud_sql_connection_name: str | None = None
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# Parametros de rede legados (mantidos por compatibilidade)
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run_vpc_connector: str | None = None
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run_vpc_egress: str = "private-ranges-only"
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# Telegram satellite
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telegram_bot_token: str | None = None
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telegram_polling_timeout: int = 30
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telegram_request_timeout: int = 45
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# Conversation state backend
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conversation_state_backend: str = "memory"
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conversation_state_ttl_minutes: int = 60
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# Redis conversation state
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redis_url: str = "redis://127.0.0.1:6379/0"
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redis_key_prefix: str = "orquestrador"
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redis_socket_timeout_seconds: int = 5
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# External integrations
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integrations_enabled: bool = False
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integration_sync_delivery_enabled: bool = True
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brevo_api_key: str | None = None
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brevo_base_url: str = "https://api.brevo.com/v3"
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brevo_sender_email: str | None = None
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brevo_sender_name: str = "Orquestrador"
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brevo_request_timeout_seconds: int = 10
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@field_validator("debug", mode="before")
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@classmethod
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def parse_debug_aliases(cls, value):
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if isinstance(value, str):
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normalized = value.strip().lower()
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if normalized in {"debug", "development", "dev"}:
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return True
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if normalized in {"release", "production", "prod"}:
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return False
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return value
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@field_validator("environment", "conversation_state_backend", mode="before")
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@classmethod
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def normalize_text_settings(cls, value):
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if isinstance(value, str):
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return value.strip().lower()
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return value
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settings = Settings()
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