from __future__ import annotations

from typing import Any

from pydantic import BaseModel, Field


class StudyPathRequest(BaseModel):
    raw_text: str | None = None
    syllabus_text: str | None = None
    source_id: str | None = None
    source_ids: list[str] | None = None
    study_profile_id: str | None = None
    use_my_profile: bool = True
    topic: str | None = None
    subject: str | None = None
    exam: str | None = None
    goal: str | None = None
    time_left: str | None = None
    level: str | None = None
    language_preference: str | None = None


class TimelineItem(BaseModel):
    order: int
    title: str
    duration_minutes: int
    reason: str
    reason_type: str
    task: str
    expected_output: str
    actions: list[str] = Field(default_factory=list)
    source_basis: str
    day_block: str | None = None


class StudyPathResult(BaseModel):
    title: str
    exam: str | None
    subject: str | None
    topic: str | None
    goal: str | None
    time_left: str | None
    level: str | None
    plan_type: str = "standard"
    plan_label: str = "Study plan"
    plan_tip: str | None = None
    readiness_score: float
    next_best_action: str
    study_timeline: list[TimelineItem] = Field(default_factory=list)
    weak_areas: list[str] = Field(default_factory=list)
    easy_marks: list[str] = Field(default_factory=list)
    danger_areas: list[str] = Field(default_factory=list)
    revision_keywords: list[str] = Field(default_factory=list)
    source_basis: str = "generic_topic_template"
    trust_notes: list[str] = Field(default_factory=list)
    evidence_label: str | None = None
    analysis: dict[str, Any] = Field(default_factory=dict)