app/schemas/learning_engine.py

from __future__ import annotations

from typing import Any

from pydantic import BaseModel, Field


class CoursePlanRequest(BaseModel):
    raw_request: str
    source_ids: list[str] | None = None
    source_context: str | None = None
    playlist_metadata: dict[str, Any] | None = None
    current_level: str | None = None
    weak_topics: list[str] | None = None
    class_level: str | None = None
    syllabus: str | None = None
    board: str | None = None
    semester: str | None = None
    degree: str | None = None
    goal: str | None = None
    time_available: str | None = None
    daily_study_time: str | None = None
    subject: str | None = None
    chapter: str | None = None
    topic: str | None = None
    exam_date: str | None = None


class LessonOutput(BaseModel):
    title: str
    duration_minutes: int
    task: str
    reason_type: str
    source_basis: str
    expected_output: str = ""
    prerequisite_check: str = ""


class ModuleOutput(BaseModel):
    title: str
    lessons: list[LessonOutput] = Field(default_factory=list)
    estimated_minutes: int = 0
    source_basis: str = "catalog_seed"


class QuizOutput(BaseModel):
    title: str
    question_count: int
    focus_areas: list[str] = Field(default_factory=list)


class PracticeTaskOutput(BaseModel):
    title: str
    task_type: str
    description: str = ""
    source_basis: str = "generic"


class RevisionCheckpointOutput(BaseModel):
    title: str
    focus_areas: list[str] = Field(default_factory=list)
    estimated_minutes: int = 15


class StudentContextOutput(BaseModel):
    class_level: str = ""
    syllabus: str = ""
    subject: str = ""
    chapter: str = ""
    exam_date: str = ""
    daily_study_time: str = ""
    goal: str = ""


class ConceptExplanationOutput(BaseModel):
    title: str
    explanation: str
    board_exam_focus: str = ""


class DerivationProblemStepOutput(BaseModel):
    title: str
    steps: list[str] = Field(default_factory=list)
    common_mistake: str = ""
    source_basis: str = "catalog_seed"


class PracticeQuestionOutput(BaseModel):
    question: str
    marks: int = 2
    answer_hint: str = ""
    question_type: str = "short_answer"


class WeakTopicRepairOutput(BaseModel):
    topic: str
    symptom: str = ""
    repair_task: str = ""


class RevisionPlanItemOutput(BaseModel):
    timing: str
    task: str
    purpose: str = ""
    estimated_minutes: int = 10


class CoursePlanResult(BaseModel):
    title: str
    learner_level: str
    subject_area: str
    source_basis: str
    modules: list[ModuleOutput] = Field(default_factory=list)
    lessons_total: int = 0
    estimated_total_minutes: int = 0
    prerequisites: list[str] = Field(default_factory=list)
    key_concepts: list[str] = Field(default_factory=list)
    practice_tasks: list[PracticeTaskOutput] = Field(default_factory=list)
    quizzes: list[QuizOutput] = Field(default_factory=list)
    revision_checkpoints: list[RevisionCheckpointOutput] = Field(default_factory=list)
    final_outcome: str = ""
    next_action: str = ""
    data_source_label: str = "Starter seed"
    confidence: float = 0.0
    trust_notes: list[str] = Field(default_factory=list)
    student_context: StudentContextOutput = Field(default_factory=StudentContextOutput)
    lesson_outline: list[str] = Field(default_factory=list)
    prerequisite_check: list[str] = Field(default_factory=list)
    concept_explanation: ConceptExplanationOutput | None = None
    derivation_or_problem_steps: list[DerivationProblemStepOutput] = Field(default_factory=list)
    practice_questions: list[PracticeQuestionOutput] = Field(default_factory=list)
    pyq_style_questions: list[PracticeQuestionOutput] = Field(default_factory=list)
    weak_topic_repairs: list[WeakTopicRepairOutput] = Field(default_factory=list)
    revision_plan: list[RevisionPlanItemOutput] = Field(default_factory=list)
    estimated_study_time: str = ""


class ExamCoachSessionRequest(BaseModel):
    class_level: str | None = None
    board: str | None = None
    university: str | None = None
    subject: str | None = None
    chapter: str | None = None
    topic: str | None = None
    exam_date: str | None = None
    daily_time: str = "1 hour"
    goal: str | None = None
    weak_topics: list[str] | None = None
    pyq_data: list[dict[str, Any]] | None = None
    source_ids: list[str] | None = None
    source_context: str | None = None


class StudyBlockOutput(BaseModel):
    duration_label: str
    duration_minutes: int
    title: str
    tasks: list[str] = Field(default_factory=list)
    reason: str = ""


class ExamCoachSessionResult(BaseModel):
    session_title: str
    exam_countdown: str
    time_budget: str
    today_mission: str
    study_blocks: list[StudyBlockOutput] = Field(default_factory=list)
    concept_teaching_task: dict[str, Any] = Field(default_factory=dict)
    visual_lesson_task: dict[str, Any] = Field(default_factory=dict)
    derivation_or_numerical_task: dict[str, Any] = Field(default_factory=dict)
    pyq_task: dict[str, Any] = Field(default_factory=dict)
    answer_writing_task: dict[str, Any] = Field(default_factory=dict)
    revision_task: dict[str, Any] = Field(default_factory=dict)
    quick_test: dict[str, Any] = Field(default_factory=dict)
    next_day_plan: dict[str, Any] = Field(default_factory=dict)
    data_source_label: str = "Starter seed"
    trust_notes: list[str] = Field(default_factory=list)