130 lines
3.8 KiB
Python
Executable File
130 lines
3.8 KiB
Python
Executable File
# #region ConfigModels [C:3] [TYPE Module] [SEMANTICS pydantic, model, schedule]
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# @BRIEF Defines the data models for application configuration using Pydantic.
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# @LAYER: Core
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# @RELATION IMPLEMENTS -> [CoreContracts]
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# @RELATION IMPLEMENTS -> [ConnectionContracts]
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from pydantic import BaseModel, Field
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from typing import List, Optional
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from ..models.storage import StorageConfig
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from ..services.llm_prompt_templates import (
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DEFAULT_LLM_ASSISTANT_SETTINGS,
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DEFAULT_LLM_PROMPTS,
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DEFAULT_LLM_PROVIDER_BINDINGS,
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)
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# #region Schedule [TYPE DataClass]
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# @BRIEF Represents a backup schedule configuration.
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class Schedule(BaseModel):
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enabled: bool = False
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cron_expression: str = "0 0 * * *" # Default: daily at midnight
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# #endregion Schedule
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# #region Environment [TYPE DataClass]
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# @BRIEF Represents a Superset environment configuration.
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class Environment(BaseModel):
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id: str
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name: str
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url: str
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username: str
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password: str # Will be masked in UI
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stage: str = Field(default="DEV", pattern="^(DEV|PREPROD|PROD)$")
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verify_ssl: bool = True
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timeout: int = 30
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is_default: bool = False
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is_production: bool = False
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backup_schedule: Schedule = Field(default_factory=Schedule)
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# #endregion Environment
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# #region LoggingConfig [TYPE DataClass]
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# @BRIEF Defines the configuration for the application's logging system.
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class LoggingConfig(BaseModel):
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level: str = "INFO"
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task_log_level: str = (
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"INFO" # Minimum level for task-specific logs (DEBUG, INFO, WARNING, ERROR)
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)
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file_path: Optional[str] = None
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max_bytes: int = 10 * 1024 * 1024
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backup_count: int = 5
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enable_belief_state: bool = True
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# #endregion LoggingConfig
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# #region CleanReleaseConfig [TYPE DataClass]
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# @BRIEF Configuration for clean release compliance subsystem.
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class CleanReleaseConfig(BaseModel):
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active_policy_id: Optional[str] = None
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active_registry_id: Optional[str] = None
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# #endregion CleanReleaseConfig
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# #region FeaturesConfig [C:1] [TYPE DataClass]
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# @BRIEF Top-level feature flags that toggle entire project features on/off.
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# @RATIONALE: Features are read from environment variables on bootstrap and persisted in DB.
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# DB is source of truth after initial bootstrap; env vars only seed defaults.
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class FeaturesConfig(BaseModel):
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dataset_review: bool = True
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health_monitor: bool = True
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# #endregion FeaturesConfig
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# #region GlobalSettings [TYPE DataClass]
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# @BRIEF Represents global application settings.
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class GlobalSettings(BaseModel):
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storage: StorageConfig = Field(default_factory=StorageConfig)
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clean_release: CleanReleaseConfig = Field(default_factory=CleanReleaseConfig)
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default_environment_id: Optional[str] = None
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logging: LoggingConfig = Field(default_factory=LoggingConfig)
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features: FeaturesConfig = Field(default_factory=FeaturesConfig)
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connections: List[dict] = []
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llm: dict = Field(
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default_factory=lambda: {
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"providers": [],
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"default_provider": "",
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"prompts": dict(DEFAULT_LLM_PROMPTS),
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"provider_bindings": dict(DEFAULT_LLM_PROVIDER_BINDINGS),
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**dict(DEFAULT_LLM_ASSISTANT_SETTINGS),
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}
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)
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# Task retention settings
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task_retention_days: int = 30
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task_retention_limit: int = 100
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pagination_limit: int = 10
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# Migration sync settings
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migration_sync_cron: str = "0 2 * * *"
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# Dataset Review Feature Flags
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ff_dataset_auto_review: bool = True
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ff_dataset_clarification: bool = True
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ff_dataset_execution: bool = True
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# #endregion GlobalSettings
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# #region AppConfig [TYPE DataClass]
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# @BRIEF The root configuration model containing all application settings.
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class AppConfig(BaseModel):
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environments: List[Environment] = []
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settings: GlobalSettings
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# #endregion AppConfig
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# #endregion ConfigModels
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