"""
Training schemas
"""

from pydantic import BaseModel, Field, validator
from typing import Optional, Dict, Any, List
from datetime import datetime
from enum import Enum

class TrainingJobStatus(str, Enum):
    """Training job status enum"""
    QUEUED = "queued"
    RUNNING = "running"
    COMPLETED = "completed"
    FAILED = "failed"
    CANCELLED = "cancelled"

class TrainingRequest(BaseModel):
    """Training request schema"""
    tenant_id: Optional[str] = None  # Will be set from auth
    force_retrain: bool = Field(default=False, description="Force retrain even if recent models exist")
    products: Optional[List[str]] = Field(default=None, description="Specific products to train, or None for all")
    training_days: Optional[int] = Field(default=730, ge=30, le=1095, description="Number of days of historical data to use")
    
    @validator('training_days')
    def validate_training_days(cls, v):
        if v < 30:
            raise ValueError('Minimum training days is 30')
        if v > 1095:
            raise ValueError('Maximum training days is 1095 (3 years)')
        return v

class TrainingJobResponse(BaseModel):
    """Training job response schema"""
    id: str
    tenant_id: str
    status: TrainingJobStatus
    progress: int
    current_step: Optional[str]
    started_at: datetime
    completed_at: Optional[datetime]
    duration_seconds: Optional[int]
    models_trained: Optional[Dict[str, Any]]
    metrics: Optional[Dict[str, Any]]
    error_message: Optional[str]
    
    class Config:
        from_attributes = True

class TrainedModelResponse(BaseModel):
    """Trained model response schema"""
    id: str
    product_name: str
    model_type: str
    model_version: str
    mape: Optional[float]
    rmse: Optional[float]
    mae: Optional[float]
    r2_score: Optional[float]
    training_samples: Optional[int]
    features_used: Optional[List[str]]
    is_active: bool
    created_at: datetime
    last_used_at: Optional[datetime]
    
    class Config:
        from_attributes = True

class TrainingProgress(BaseModel):
    """Training progress update schema"""
    job_id: str
    progress: int
    current_step: str
    estimated_completion: Optional[datetime]
    
class TrainingMetrics(BaseModel):
    """Training metrics schema"""
    total_jobs: int
    successful_jobs: int
    failed_jobs: int
    average_duration: float
    models_trained: int
    active_models: int

class ModelValidationResult(BaseModel):
    """Model validation result schema"""
    product_name: str
    is_valid: bool
    accuracy_score: float
    validation_error: Optional[str]
    recommendations: List[str]