LockInBroAPI/app/models.py

from datetime import datetime
from uuid import UUID

from pydantic import BaseModel, EmailStr, Field


# ── Auth ──


class RegisterRequest(BaseModel):
    email: EmailStr
    password: str = Field(min_length=8)
    display_name: str | None = None
    timezone: str = "America/Chicago"


class LoginRequest(BaseModel):
    email: EmailStr
    password: str


class AppleAuthRequest(BaseModel):
    identity_token: str
    authorization_code: str
    full_name: str | None = None


class RefreshRequest(BaseModel):
    refresh_token: str


class AuthResponse(BaseModel):
    access_token: str
    refresh_token: str
    expires_in: int
    user: "UserOut"


class UserOut(BaseModel):
    id: UUID
    email: str | None
    display_name: str | None
    timezone: str
    created_at: datetime


# ── Tasks ──


class TaskCreate(BaseModel):
    title: str
    description: str | None = None
    priority: int = Field(0, ge=0, le=4)
    deadline: datetime | None = None
    estimated_minutes: int | None = None
    tags: list[str] = []


class TaskUpdate(BaseModel):
    title: str | None = None
    description: str | None = None
    priority: int | None = Field(None, ge=0, le=4)
    status: str | None = None
    deadline: datetime | None = None
    estimated_minutes: int | None = None
    tags: list[str] | None = None


class TaskOut(BaseModel):
    id: UUID
    user_id: UUID
    title: str
    description: str | None
    priority: int
    status: str
    deadline: datetime | None
    estimated_minutes: int | None
    source: str
    tags: list[str]
    plan_type: str | None
    brain_dump_raw: str | None
    created_at: datetime
    updated_at: datetime


class BrainDumpRequest(BaseModel):
    raw_text: str
    source: str = "manual"
    timezone: str = "America/Chicago"


class ParsedSubtask(BaseModel):
    title: str
    description: str | None = None
    deadline: datetime | None = None
    estimated_minutes: int | None = None
    suggested: bool = False


class ParsedTask(BaseModel):
    task_id: str | None = None
    title: str
    description: str | None = None
    priority: int = 0
    deadline: datetime | None = None
    estimated_minutes: int | None = None
    tags: list[str] = []
    subtasks: list[ParsedSubtask] = []

class BrainDumpResponse(BaseModel):
    parsed_tasks: list[ParsedTask]
    unparseable_fragments: list[str] = []
    ask_for_plans: bool = True


class PlanRequest(BaseModel):
    plan_type: str = "llm_generated"


# ── Steps ──


class StepOut(BaseModel):
    id: UUID
    task_id: UUID
    sort_order: int
    title: str
    description: str | None
    estimated_minutes: int | None
    status: str
    checkpoint_note: str | None
    last_checked_at: datetime | None
    completed_at: datetime | None
    created_at: datetime


class StepUpdate(BaseModel):
    title: str | None = None
    description: str | None = None
    estimated_minutes: int | None = None
    sort_order: int | None = None
    status: str | None = None
    checkpoint_note: str | None = None


class PlanResponse(BaseModel):
    task_id: UUID
    plan_type: str
    steps: list[StepOut]


# ── Sessions ──


class SessionStartRequest(BaseModel):
    task_id: UUID | None = None
    platform: str = "mac"
    work_app_bundle_ids: list[str] | None = None


class SessionCheckpointRequest(BaseModel):
    current_step_id: UUID | None = None
    last_action_summary: str | None = None
    next_up: str | None = None
    goal: str | None = None
    active_app: str | None = None
    last_screenshot_analysis: str | None = None
    attention_score: int | None = None
    distraction_count: int | None = None


class SessionEndRequest(BaseModel):
    status: str = "completed"


class OpenSessionOut(BaseModel):
    id: UUID
    task_id: UUID | None
    task: dict | None
    status: str
    platform: str
    started_at: datetime
    ended_at: datetime | None
    checkpoint: dict


class SessionJoinRequest(BaseModel):
    platform: str = "ipad"
    work_app_bundle_ids: list[str] | None = None


class SessionJoinResponse(BaseModel):
    session_id: UUID
    joined: bool
    task: dict | None
    current_step: dict | None
    all_steps: list[StepOut]
    suggested_app_scheme: str | None
    suggested_app_name: str | None


class SessionOut(BaseModel):
    id: UUID
    user_id: UUID
    task_id: UUID | None
    platform: str
    started_at: datetime
    ended_at: datetime | None
    status: str
    checkpoint: dict
    created_at: datetime


class ResumeCard(BaseModel):
    welcome_back: str
    you_were_doing: str
    next_step: str
    motivation: str


class SessionResumeResponse(BaseModel):
    session_id: UUID
    task: dict | None
    current_step: dict | None
    progress: dict
    resume_card: ResumeCard


# ── Distractions ──


class ScreenshotAnalysisResponse(BaseModel):
    on_task: bool
    current_step_id: UUID | None
    checkpoint_note_update: str | None
    steps_completed: list[UUID] = []
    distraction_type: str | None
    app_name: str | None
    confidence: float
    gentle_nudge: str | None
    vlm_summary: str | None


class AppActivityRequest(BaseModel):
    session_id: UUID
    app_bundle_id: str
    app_name: str
    duration_seconds: int
    returned_to_task: bool = False


class AppActivityResponse(BaseModel):
    distraction_logged: bool
    session_distraction_count: int
    gentle_nudge: str | None


class AppCheckRequest(BaseModel):
    app_bundle_id: str


class AppCheckResponse(BaseModel):
    is_distraction_app: bool
    pending_task_count: int
    most_urgent_task: dict | None
    nudge: str | None


# ── Analyze Result (Device-Side VLM) ──


class ProposedAction(BaseModel):
    label: str
    action_type: str
    details: str | None = None


class FrictionDetection(BaseModel):
    type: str = "none"
    confidence: float = 0.0
    description: str | None = None
    proposed_actions: list[ProposedAction] = []
    source_context: str | None = None
    target_context: str | None = None


class SessionAction(BaseModel):
    type: str = "none"  # resume | switch | complete | start_new | none
    session_id: UUID | None = None
    reason: str | None = None


class AnalyzeResultRequest(BaseModel):
    session_id: UUID | None = None  # optional — VLM can run without an active session
    on_task: bool
    current_step_id: UUID | None = None
    inferred_task: str | None = None
    checkpoint_note_update: str | None = None
    steps_completed: list[UUID] = []
    friction: FrictionDetection = FrictionDetection()
    session_action: SessionAction = SessionAction()
    intent: str | None = None
    distraction_type: str | None = None
    app_name: str | None = None
    confidence: float = 0.0
    gentle_nudge: str | None = None
    vlm_summary: str | None = None


class AnalyzeResultResponse(BaseModel):
    side_effects_applied: bool
    steps_updated: int
    distraction_logged: bool
    proactive_action_id: UUID | None = None


# ── Proactive Actions ──


class ProactiveRespondRequest(BaseModel):
    proactive_action_id: UUID
    user_choice: str  # accepted | declined | alternative_chosen
    chosen_action: str | None = None


class ProactiveRespondResponse(BaseModel):
    logged: bool
    should_execute: bool


class ProactiveExecuteRequest(BaseModel):
    proactive_action_id: UUID
    action_type: str
    execution_params: dict = {}


class ProactiveExecuteResponse(BaseModel):
    executed: bool
    result: str | None = None


class ProactivePreference(BaseModel):
    preferred_action: str | None
    total_choices: int
    acceptance_rate: float


class ProactivePreferencesResponse(BaseModel):
    preferences: dict[str, ProactivePreference]


# ── Device Token ──


class DeviceTokenRequest(BaseModel):
    platform: str
    token: str


# ── Analytics ──


class AnalyticsSummary(BaseModel):
    total_focus_minutes: float
    sessions_completed: int
    tasks_completed: int
    top_distractors: list[dict]
    avg_attention_score: float | None