"""Pydantic schemas for adaptive learning path endpoints."""

from pydantic import BaseModel, ConfigDict, Field


class LearningPathStep(BaseModel):
    """A single step in a learning path."""
    
    step_number: int = Field(..., ge=1, description="Step order in the path")
    lo_id: str = Field(..., description="Learning outcome ID")
    title: str = Field(..., description="Learning outcome title")
    grade: int = Field(..., ge=6, le=8, description="Grade level")
    subject: str = Field(..., description="Subject name")
    chapter: str = Field(..., description="Chapter name")
    difficulty: str = Field(..., description="Difficulty level")
    bloom_level: str = Field(..., description="Bloom taxonomy level")
    
    # Student-specific context
    current_mastery: float = Field(..., ge=0.0, le=1.0, description="Student's current mastery score")
    mastery_label: str = Field(..., description="Student's mastery label")
    is_prerequisite: bool = Field(..., description="Whether this is a prerequisite for the target")
    estimated_study_time: int = Field(..., ge=0, description="Estimated study time in minutes")
    
    # Reasoning
    reason: str = Field(..., description="Why this step is recommended")


class LearningPathRequest(BaseModel):
    """Request for adaptive learning path generation."""
    
    model_config = ConfigDict(extra="forbid")
    
    student_id: str = Field(..., description="Student ID")
    target_lo_id: str = Field(..., description="Target learning outcome ID")
    max_steps: int = Field(default=10, ge=1, le=20, description="Maximum number of steps in path")
    include_mastered: bool = Field(default=False, description="Include already mastered LOs for review")
    difficulty_preference: str = Field(default="adaptive", description="Difficulty preference: easy, medium, hard, adaptive")


class LearningPathResponse(BaseModel):
    """Response for adaptive learning path generation."""
    
    model_config = ConfigDict(extra="forbid")
    
    student_id: str = Field(..., description="Student ID")
    target_lo_id: str = Field(..., description="Target learning outcome ID")
    model_version: str = Field(default="adaptive_path_v2_baseline_001", description="Service version")
    source: str = Field(default="knowledge_graph_traversal", description="Path generation method")
    timestamp: str = Field(..., description="Response timestamp")
    
    # Path details
    learning_path: list[LearningPathStep] = Field(..., description="Ordered learning steps")
    total_steps: int = Field(..., ge=0, description="Total number of steps")
    estimated_total_time: int = Field(..., ge=0, description="Total estimated study time in minutes")
    
    # Student context
    current_overall_mastery: float = Field(..., ge=0.0, le=1.0, description="Student's overall mastery")
    weak_prerequisites: list[str] = Field(default_factory=list, description="Weak prerequisite LO IDs")
    
    # Path metadata
    path_difficulty: str = Field(..., description="Overall path difficulty")
    completion_probability: float = Field(..., ge=0.0, le=1.0, description="Estimated completion probability")
    
    # Recommendations
    next_action: str = Field(..., description="Immediate next action for student")
    teacher_notes: str = Field(..., description="Notes for teacher intervention")